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dict | prediction
null | prediction_agent
null | annotation
list | annotation_agent
null | multi_label
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{
"abstract": " We derive the uniqueness of weak solutions to the Shigesada-Kawasaki-Teramoto\n(SKT) systems using the adjoint problem argument. Combining with [PT17] we then\nderive the well-posedness for the SKT systems in space dimension $d\\le 4$\n",
"title": "A Result of Uniqueness of Solutions of the Shigesada-Kawasaki-Teramoto Equations"
}
| null | null | null | null | true | null |
1601
| null |
Default
| null | null |
null |
{
"abstract": " The main task in oil and gas exploration is to gain an understanding of the\ndistribution and nature of rocks and fluids in the subsurface. Well logs are\nrecords of petro-physical data acquired along a borehole, providing direct\ninformation about what is in the subsurface. The data collected by logging\nwells can have significant economic consequences, due to the costs inherent to\ndrilling wells, and the potential return of oil deposits. In this paper, we\ndescribe preliminary work aimed at building a general framework for well log\nprediction.\nFirst, we perform a descriptive and exploratory analysis of the gaps in the\nneutron porosity logs of more than a thousand wells in the North Sea. Then, we\ngenerate artificial gaps in the neutron logs that reflect the statistics\ncollected before. Finally, we compare Artificial Neural Networks, Random\nForests, and three algorithms of Linear Regression in the prediction of missing\ngaps on a well-by-well basis.\n",
"title": "Mind the Gap: A Well Log Data Analysis"
}
| null | null | null | null | true | null |
1602
| null |
Default
| null | null |
null |
{
"abstract": " We tackle the problem of template estimation when data have been randomly\ntransformed under an isometric group action in the presence of noise. In order\nto estimate the template, one often minimizes the variance when the influence\nof the transformations have been removed (computation of the Fr{é}chet mean\nin quotient space). The consistency bias is defined as the distance (possibly\nzero) between the orbit of the template and the orbit of one element which\nminimizes the variance. In this article we establish an asymptotic behavior of\nthe consistency bias with respect to the noise level. This behavior is linear\nwith respect to the noise level. As a result the inconsistency is unavoidable\nas soon as the noise is large enough. In practice, the template estimation with\na finite sample is often done with an algorithm called max-max. We show the\nconvergence of this algorithm to an empirical Karcher mean. Finally, our\nnumerical experiments show that the bias observed in practice cannot be\nattributed to the small sample size or to a convergence problem but is indeed\ndue to the previously studied inconsistency.\n",
"title": "Inconsistency of Template Estimation with the Fr{é}chet mean in Quotient Space"
}
| null | null | null | null | true | null |
1603
| null |
Default
| null | null |
null |
{
"abstract": " High-index dielectric nanoparticles have become a powerful platform for\nmodern light science, enabling various fascinating applications, especially in\nnonlinear nanophotonics for which they enable special types of optical\nnonlinearity, such as electron-hole plasma photoexcitation, which are not\ninherent to plasmonic nanostructures. Here, we propose a novel geometry for\nhighly tunable all-dielectric nanoantennas, consisting of a chain of silicon\nnanoparticles excited by an electric dipole source, which allows tuning their\nradiation properties via electron-hole plasma photoexcitation. We show that the\nslowly guided modes determining the Van Hove singularity of the nanoantenna are\nvery sensitive to the nanoparticle permittivity, opening up the ability to\nutilize this effect for efficient all-optical modulation. We show that by\npumping several boundary nanoparticles with relatively low intensities may\ncause dramatic variations in the nanoantenna radiation power patterns and\nPurcell factor. We also demonstrate that ultrafast pumping of the designed\nnanoantenna allows unidirectional launching of surface plasmon-polaritons, with\ninteresting implications for modern nonlinear nanophotonics.\n",
"title": "All-optical switching and unidirectional plasmon launching with electron-hole plasma driven silicon nanoantennas"
}
| null | null |
[
"Physics"
] | null | true | null |
1604
| null |
Validated
| null | null |
null |
{
"abstract": " We propose a bio-inspired, agent-based approach to describe the natural\nphenomenon of group chasing in both two and three dimensions. Using a set of\nlocal interaction rules we created a continuous-space and discrete-time model\nwith time delay, external noise and limited acceleration. We implemented a\nunique collective chasing strategy, optimized its parameters and studied its\nproperties when chasing a much faster, erratic escaper. We show that collective\nchasing strategies can significantly enhance the chasers' success rate. Our\nrealistic approach handles group chasing within closed, soft boundaries -\ncontrasting most of those published in the literature with periodic ones -- and\nresembles several properties of pursuits observed in nature, such as the\nemergent encircling or the escaper's zigzag motion.\n",
"title": "Group chasing tactics: how to catch a faster prey?"
}
| null | null | null | null | true | null |
1605
| null |
Default
| null | null |
null |
{
"abstract": " Consider the linear congruence equation $x_1+\\ldots+x_k \\equiv b\\,(\\text{mod\n} n)$ for $b,n\\in\\mathbb{Z}$. By $(a,b)_s$, we mean the largest\n$l^s\\in\\mathbb{N}$ which divides $a$ and $b$ simultaneously. For each $d_j|n$,\ndefine $\\mathcal{C}_{j,s} = \\{1\\leq x\\leq n^s | (x,n^s)_s = d^s_j\\}$. Bibak et\nal. gave a formula using Ramanujan sums for the number of solutions of the\nabove congruence equation with some gcd restrictions on $x_i$. We generalize\ntheir result with generalized gcd restrictions on $x_i$ by proving that for the\nabove linear congruence, the number of solutions is\n$$\\frac{1}{n^s}\\sum\\limits_{d|n}c_{d,s}(b)\\prod\\limits_{j=1}^{\\tau(n)}\\left(c_{\\frac{n}{d_j},s}(\\frac{n^s}{d^s})\\right)^{g_j}$$\nwhere $g_j = |\\{x_1,\\ldots, x_k\\}\\cap \\mathcal{C}_{j,s}|$ for $j=1,\\ldots\n\\tau(n)$ and $c_{d,s}$ denote the generalized ramanujan sum defined by E.\nCohen.\n",
"title": "On solving a restricted linear congruence using generalized Ramanujan sums"
}
| null | null |
[
"Mathematics"
] | null | true | null |
1606
| null |
Validated
| null | null |
null |
{
"abstract": " Bismuth substituted lutetium iron garnet (BLIG) films exhibit larger Faraday\nrotation, and have a higher Curie temperature than yttrium iron garnet. We have\nobserved magnetic stripe domains and measured domain widths of 1.4 {\\mu}{\\mu}m\nusing Fourier domain polarization microscopy, Faraday rotation experiments\nyield a coercive field of 5 Oe. These characterizations form the basis of\nmicromagnetic simulations that allow us to estimate and compare spin wave\nexcitations in BLIG films. We observed that these films support thermal magnons\nwith a precessional frequency of 7 GHz with a line width of 400 MHz. Further,\nwe studied the dependence of precessional frequency on the externally applied\nmagnetic field. Brillouin light scattering experiments and precession\nfrequencies predicted by simulations show similar trend with increasing field.\n",
"title": "Magnetization spin dynamics in a (LuBi)3Fe5O12 (BLIG) epitaxial film"
}
| null | null | null | null | true | null |
1607
| null |
Default
| null | null |
null |
{
"abstract": " We present a new variable selection method based on model-based gradient\nboosting and randomly permuted variables. Model-based boosting is a tool to fit\na statistical model while performing variable selection at the same time. A\ndrawback of the fitting lies in the need of multiple model fits on slightly\naltered data (e.g. cross-validation or bootstrap) to find the optimal number of\nboosting iterations and prevent overfitting. In our proposed approach, we\naugment the data set with randomly permuted versions of the true variables, so\ncalled shadow variables, and stop the step-wise fitting as soon as such a\nvariable would be added to the model. This allows variable selection in a\nsingle fit of the model without requiring further parameter tuning. We show\nthat our probing approach can compete with state-of-the-art selection methods\nlike stability selection in a high-dimensional classification benchmark and\napply it on gene expression data for the estimation of riboflavin production of\nBacillus subtilis.\n",
"title": "Probing for sparse and fast variable selection with model-based boosting"
}
| null | null | null | null | true | null |
1608
| null |
Default
| null | null |
null |
{
"abstract": " A semicalssical method based on surface-hopping techniques is developed to\nmodel the dynamics of radiative association with electronic transitions in\narbitrary polyatomic systems. It can be proven that our method is an extension\nof the established semiclassical formula used in the characterization of\ndiatomic molecule- formation. Our model is tested for diatomic molecules. It\ngives the same cross sections as the former semiclassical formula, but contrary\nto the former method it allows us to follow the fate of the trajectories after\nthe emission of a photon. This means that we can characterize the rovibrational\nstates of the stabilized molecules: using semiclassial quantization we can\nobtain quantum state resolved cross sections or emission spectra for the\nradiative association process. The calculated semiclassical state resolved\nspectra show good agreement with the result of quantum mechanical perturbation\ntheory. Furthermore our surface-hopping model is not only applicable for the\ndescription of radiative association but it can be use for semiclassical\ncharacterization of any molecular process where spontaneous emission occurs.\n",
"title": "A surface-hopping method for semiclassical calculations of cross sections for radiative association with electronic transitions"
}
| null | null | null | null | true | null |
1609
| null |
Default
| null | null |
null |
{
"abstract": " Random tensor networks provide useful models that incorporate various\nimportant features of holographic duality. A tensor network is usually defined\nfor a fixed graph geometry specified by the connection of tensors. In this\npaper, we generalize the random tensor network approach to allow quantum\nsuperposition of different spatial geometries. We set up a framework in which\nall possible bulk spatial geometries, characterized by weighted adjacent\nmatrices of all possible graphs, are mapped to the boundary Hilbert space and\nform an overcomplete basis of the boundary. We name such an overcomplete basis\nas holographic coherent states. A generic boundary state can be expanded on\nthis basis, which describes the state as a superposition of different spatial\ngeometries in the bulk. We discuss how to define distinct classical geometries\nand small fluctuations around them. We show that small fluctuations around\nclassical geometries define \"code subspaces\" which are mapped to the boundary\nHilbert space isometrically with quantum error correction properties. In\naddition, we also show that the overlap between different geometries is\nsuppressed exponentially as a function of the geometrical difference between\nthe two geometries. The geometrical difference is measured in an area law\nfashion, which is a manifestation of the holographic nature of the states\nconsidered.\n",
"title": "Holographic coherent states from random tensor networks"
}
| null | null | null | null | true | null |
1610
| null |
Default
| null | null |
null |
{
"abstract": " Persistent spread measurement is to count the number of distinct elements\nthat persist in each network flow for predefined time periods. It has many\npractical applications, including detecting long-term stealthy network\nactivities in the background of normal-user activities, such as stealthy DDoS\nattack, stealthy network scan, or faked network trend, which cannot be detected\nby traditional flow cardinality measurement. With big network data, one\nchallenge is to measure the persistent spreads of a massive number of flows\nwithout incurring too much memory overhead as such measurement may be performed\nat the line speed by network processors with fast but small on-chip memory. We\npropose a highly compact Virtual Intersection HyperLogLog (VI-HLL) architecture\nfor this purpose. It achieves far better memory efficiency than the best prior\nwork of V-Bitmap, and in the meantime drastically extends the measurement\nrange. Theoretical analysis and extensive experiments demonstrate that VI-HLL\nprovides good measurement accuracy even in very tight memory space of less than\n1 bit per flow.\n",
"title": "Persistent Spread Measurement for Big Network Data Based on Register Intersection"
}
| null | null |
[
"Computer Science"
] | null | true | null |
1611
| null |
Validated
| null | null |
null |
{
"abstract": " In the last few years, an extensive literature has been focused on the\n$\\ell_1$ penalized least squares (Lasso) estimators of high dimensional linear\nregression when the number of covariates $p$ is considerably larger than the\nsample size $n$. However, there is limited attention paid to the properties of\nthe estimators when the errors or/and the covariates are serially dependent. In\nthis study, we investigate the theoretical properties of the Lasso estimators\nfor linear regression with random design under serially dependent and/or\nnon-sub-Gaussian errors and covariates. In contrast to the traditional case in\nwhich the errors are i.i.d and have finite exponential moments, we show that\n$p$ can at most be a power of $n$ if the errors have only polynomial moments.\nIn addition, the rate of convergence becomes slower due to the serial\ndependencies in errors and the covariates. We also consider sign consistency\nfor model selection via Lasso when there are serial correlations in the errors\nor the covariates or both. Adopting the framework of functional dependence\nmeasure, we provide a detailed description on how the rates of convergence and\nthe selection consistencies of the estimators depend on the dependence measures\nand moment conditions of the errors and the covariates. Simulation results show\nthat Lasso regression can be substantially more powerful than the mixed\nfrequency data sampling regression (MIDAS) in the presence of irrelevant\nvariables. We apply the results obtained for the Lasso method to nowcasting\nmixing frequency data in which serially correlated errors and a large number of\ncovariates are common. In real examples, the Lasso procedure outperforms the\nMIDAS in both forecasting and nowcasting.\n",
"title": "High-dimensional Linear Regression for Dependent Observations with Application to Nowcasting"
}
| null | null | null | null | true | null |
1612
| null |
Default
| null | null |
null |
{
"abstract": " The optical emission of InGaN quantum dots embedded in GaN nanowires is\ndynamically controlled by a surface acoustic wave (SAW). The emission energy of\nboth the exciton and biexciton lines is modulated over a 1.5 meV range at ~330\nMHz. A small but systematic difference in the exciton and biexciton spectral\nmodulation reveals a linear change of the biexciton binding energy with the SAW\namplitude. The present results are relevant for the dynamic control of\nindividual single photon emitters based on nitride semiconductors.\n",
"title": "Dynamic control of the optical emission from GaN/InGaN nanowire quantum dots by surface acoustic waves"
}
| null | null | null | null | true | null |
1613
| null |
Default
| null | null |
null |
{
"abstract": " We propose a novel computational method to extract information about\ninteractions among individuals with different behavioral states in a biological\ncollective from ordinary video recordings. Assuming that individuals are acting\nas finite state machines, our method first detects discrete behavioral states\nof those individuals and then constructs a model of their state transitions,\ntaking into account the positions and states of other individuals in the\nvicinity. We have tested the proposed method through applications to two\nreal-world biological collectives: termites in an experimental setting and\nhuman pedestrians in a university campus. For each application, a robust\ntracking system was developed in-house, utilizing interactive human\nintervention (for termite tracking) or online agent-based simulation (for\npedestrian tracking). In both cases, significant interactions were detected\nbetween nearby individuals with different states, demonstrating the\neffectiveness of the proposed method.\n",
"title": "Robust Tracking and Behavioral Modeling of Movements of Biological Collectives from Ordinary Video Recordings"
}
| null | null | null | null | true | null |
1614
| null |
Default
| null | null |
null |
{
"abstract": " Membership Inference Attack (MIA) determines the presence of a record in a\nmachine learning model's training data by querying the model. Prior work has\nshown that the attack is feasible when the model is overfitted to its training\ndata or when the adversary controls the training algorithm. However, when the\nmodel is not overfitted and the adversary does not control the training\nalgorithm, the threat is not well understood. In this paper, we report a study\nthat discovers overfitting to be a sufficient but not a necessary condition for\nan MIA to succeed. More specifically, we demonstrate that even a\nwell-generalized model contains vulnerable instances subject to a new\ngeneralized MIA (GMIA). In GMIA, we use novel techniques for selecting\nvulnerable instances and detecting their subtle influences ignored by\noverfitting metrics. Specifically, we successfully identify individual records\nwith high precision in real-world datasets by querying black-box machine\nlearning models. Further we show that a vulnerable record can even be\nindirectly attacked by querying other related records and existing\ngeneralization techniques are found to be less effective in protecting the\nvulnerable instances. Our findings sharpen the understanding of the fundamental\ncause of the problem: the unique influences the training instance may have on\nthe model.\n",
"title": "Understanding Membership Inferences on Well-Generalized Learning Models"
}
| null | null | null | null | true | null |
1615
| null |
Default
| null | null |
null |
{
"abstract": " We identify [Se III] 1.0994 micron in the planetary nebula (PN) NGC 5315 and\n[Kr VI] 1.2330 micron in three PNe, from spectra obtained with the FIRE\nspectrometer on the 6.5-m Baade Telescope. Se and Kr are the two most\nwidely-detected neutron-capture elements in astrophysical nebulae, and can be\nenriched by s-process nucleosynthesis in PN progenitor stars. The detection of\n[Se III] 1.0994 micron is particularly valuable when paired with observations\nof [Se IV] 2.2858 micron, as it can be used to improve the accuracy of nebular\nSe abundance determinations, and allows Se ionization correction factor (ICF)\nschemes to be empirically tested for the first time. We present new effective\ncollision strength calculations for Se^{2+} and Kr^{5+}, which we use to\ncompute ionic abundances. In NGC 5315, we find that the Se abundance computed\nfrom Se^{3+}/H^+ is lower than that determined with ICFs that incorporate\nSe^{2+}/H^+. We compute new Kr ICFs that take Kr^{5+}/H^+ into account, by\nfitting correlations found in grids of Cloudy models between Kr ionic fractions\nand those of more abundant elements, and use these to derive Kr abundances in\nfour PNe. Observations of [Se III] and [Kr VI] in a larger sample of PNe, with\na range of excitation levels, are needed to rigorously test the ICF\nprescriptions for Se and our new Kr ICFs.\n",
"title": "Identification of Near-Infrared [Se III] and [Kr VI] Emission Lines in Planetary Nebulae"
}
| null | null | null | null | true | null |
1616
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, locally Lipschitz regular functions are utilized to identify\nand remove infeasible directions from differential inclusions. The resulting\nreduced differential inclusion is point-wise smaller (in the sense of set\ncontainment) than the original differential inclusion. The reduced inclusion is\nutilized to develop a generalized notion of a derivative in the direction(s) of\na set-valued map for locally Lipschitz candidate Lyapunov functions. The\ndeveloped generalized derivative yields less conservative statements of\nLyapunov stability results, invariance-like results, and Matrosov results for\ndifferential inclusions. Illustrative examples are included to demonstrate the\nutility of the developed stability theorems.\n",
"title": "On reduction of differential inclusions and Lyapunov stability"
}
| null | null | null | null | true | null |
1617
| null |
Default
| null | null |
null |
{
"abstract": " This thesis investigates unsupervised time series representation learning for\nsequence prediction problems, i.e. generating nice-looking input samples given\na previous history, for high dimensional input sequences by decoupling the\nstatic input representation from the recurrent sequence representation. We\nintroduce three models based on Generative Stochastic Networks (GSN) for\nunsupervised sequence learning and prediction. Experimental results for these\nthree models are presented on pixels of sequential handwritten digit (MNIST)\ndata, videos of low-resolution bouncing balls, and motion capture data. The\nmain contribution of this thesis is to provide evidence that GSNs are a viable\nframework to learn useful representations of complex sequential input data, and\nto suggest a new framework for deep generative models to learn complex\nsequences by decoupling static input representations from dynamic time\ndependency representations.\n",
"title": "Deep Generative Networks For Sequence Prediction"
}
| null | null | null | null | true | null |
1618
| null |
Default
| null | null |
null |
{
"abstract": " In this work, we aim at building a bridge from poor behavioral data to an\neffective, quick-response, and robust behavior model for online identity theft\ndetection. We concentrate on this issue in online social networks (OSNs) where\nusers usually have composite behavioral records, consisting of\nmulti-dimensional low-quality data, e.g., offline check-ins and online user\ngenerated content (UGC). As an insightful result, we find that there is a\ncomplementary effect among different dimensions of records for modeling users'\nbehavioral patterns. To deeply exploit such a complementary effect, we propose\na joint model to capture both online and offline features of a user's composite\nbehavior. We evaluate the proposed joint model by comparing with some typical\nmodels on two real-world datasets: Foursquare and Yelp. In the widely-used\nsetting of theft simulation (simulating thefts via behavioral replacement), the\nexperimental results show that our model outperforms the existing ones, with\nthe AUC values $0.956$ in Foursquare and $0.947$ in Yelp, respectively.\nParticularly, the recall (True Positive Rate) can reach up to $65.3\\%$ in\nFoursquare and $72.2\\%$ in Yelp with the corresponding disturbance rate (False\nPositive Rate) below $1\\%$. It is worth mentioning that these performances can\nbe achieved by examining only one composite behavior (visiting a place and\nposting a tip online simultaneously) per authentication, which guarantees the\nlow response latency of our method. This study would give the cybersecurity\ncommunity new insights into whether and how a real-time online identity\nauthentication can be improved via modeling users' composite behavioral\npatterns.\n",
"title": "Composite Behavioral Modeling for Identity Theft Detection in Online Social Networks"
}
| null | null | null | null | true | null |
1619
| null |
Default
| null | null |
null |
{
"abstract": " The purpose this article is to try to understand the mysterious coincidence\nbetween the asymptotic behavior of the volumes of the Moduli Space of closed\nhyperbolic surfaces of genus $g$ with respect to the Weil-Petersson metric and\nthe asymptotic behavior of the number of arithmetic closed hyperbolic surfaces\nof genus $g$. If the set of arithmetic surfaces is well distributed then its\nimage for any interesting function should be well distributed too. We\ninvestigate the distribution of the function systole. We give several results\nindicating that the systoles of arithmetic surfaces can not be concentrated,\nconsequently the same holds for the set of arithmetic surfaces. The proofs are\nbased in different techniques: combinatorics (obtaining regular graphs with any\ngirth from results of B. Bollobas and constructions with cages and Ramanujan\ngraphs), group theory (constructing finite index subgroups of surface groups\nfrom finite index subgroups of free groups using results of G. Baumslag) and\ngeometric group theory (linking the geometry of graphs with the geometry of\ncoverings of a surface).\n",
"title": "Asymptotic properties of the set of systoles of arithmetic Riemann surfaces"
}
| null | null | null | null | true | null |
1620
| null |
Default
| null | null |
null |
{
"abstract": " This article concerns a class of elliptic equations on Carnot groups\ndepending on one real positive parameter and involving a subcritical\nnonlinearity (for the critical case we refer to G. Molica Bisci and D.\nRepovš, Yamabe-type equations on Carnot groups, Potential Anal. 46:2\n(2017), 369-383; arXiv:1705.10100 [math.AP]). As a special case of our results\nwe prove the existence of at least one nontrivial solution for a subelliptic\nequation defined on a smooth and bounded domain $D$ of the Heisenberg group\n$\\mathbb{H}^n=\\mathbb{C}^n\\times \\mathbb{R}$. The main approach is based on\nvariational methods.\n",
"title": "Nonlinear elliptic equations on Carnot groups"
}
| null | null | null | null | true | null |
1621
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we represent Raptor codes as multi-edge type low-density\nparity-check (MET-LDPC) codes, which gives a general framework to design them\nfor higher-order modulation using MET density evolution. We then propose an\nefficient Raptor code design method for higher-order modulation, where we\ndesign distinct degree distributions for distinct bit levels. We consider a\njoint decoding scheme based on belief propagation for Raptor codes and also\nderive an exact expression for the stability condition. In several examples, we\ndemonstrate that the higher-order modulated Raptor codes designed using the\nmulti-edge framework outperform previously reported higher-order modulation\ncodes in literature.\n",
"title": "Raptor Codes for Higher-Order Modulation Using a Multi-Edge Framework"
}
| null | null | null | null | true | null |
1622
| null |
Default
| null | null |
null |
{
"abstract": " The package cleanNLP provides a set of fast tools for converting a textual\ncorpus into a set of normalized tables. The underlying natural language\nprocessing pipeline utilizes Stanford's CoreNLP library, exposing a number of\nannotation tasks for text written in English, French, German, and Spanish.\nAnnotators include tokenization, part of speech tagging, named entity\nrecognition, entity linking, sentiment analysis, dependency parsing,\ncoreference resolution, and information extraction.\n",
"title": "A Tidy Data Model for Natural Language Processing using cleanNLP"
}
| null | null | null | null | true | null |
1623
| null |
Default
| null | null |
null |
{
"abstract": " We propose a modified expectation-maximization algorithm by introducing the\nconcept of quantum annealing, which we call the deterministic quantum annealing\nexpectation-maximization (DQAEM) algorithm. The expectation-maximization (EM)\nalgorithm is an established algorithm to compute maximum likelihood estimates\nand applied to many practical applications. However, it is known that EM\nheavily depends on initial values and its estimates are sometimes trapped by\nlocal optima. To solve such a problem, quantum annealing (QA) was proposed as a\nnovel optimization approach motivated by quantum mechanics. By employing QA, we\nthen formulate DQAEM and present a theorem that supports its stability.\nFinally, we demonstrate numerical simulations to confirm its efficiency.\n",
"title": "Relaxation of the EM Algorithm via Quantum Annealing for Gaussian Mixture Models"
}
| null | null |
[
"Physics",
"Statistics"
] | null | true | null |
1624
| null |
Validated
| null | null |
null |
{
"abstract": " We report point contact Andreev Reflection (PCAR) measurements on a\nhigh-quality single crystal of the non-centrosymmetric superconductor Re6Zr. We\nobserve that the PCAR spectra can be fitted by taking two isotropic\nsuperconducting gaps with Delta_1 ~ 0.79 meV and Delta_2 ~ 0.22 meV\nrespectively, suggesting that there are at least two bands which contribute to\nsuperconductivity. Combined with the observation of time reversal symmetry\nbreaking at the superconducting transition from muon spin relaxation\nmeasurements (Phys. Rev. Lett. 112, 107002 (2014)), our results imply an\nunconventional superconducting order in this compound: A multiband singlet\nstate that breaks time reversal symmetry or a triplet state dominated by\ninterband pairing.\n",
"title": "Multiband Superconductivity in the time reversal symmetry broken superconductor Re6Zr"
}
| null | null | null | null | true | null |
1625
| null |
Default
| null | null |
null |
{
"abstract": " Doubly occupied configuration interaction (DOCI), the exact diagonalization\nof the Hamiltonian in the paired (seniority zero) sector of the Hilbert space,\nis a combinatorial cost wave function that can be very efficiently approximated\nby pair coupled cluster doubles (pCCD) at mean-field computational cost. As\nsuch, it is a very interesting candidate as a starting point for building the\nfull configuration interaction (FCI) ground state eigenfunction belonging to\nall (not just paired) seniority sectors. The true seniority zero sector of FCI\n(referred to here as FCI${}_0$) includes the effect of coupling between all\nseniority sectors rather than just seniority zero, and is, in principle,\ndifferent from DOCI. We here study the accuracy with which DOCI approximates\nFCI${}_0$. Using a set of small Hubbard lattices, where FCI is possible, we\nshow that DOCI $\\sim$ FCI${}_0$ under weak correlation. However, in the strong\ncorrelation regime, the nature of the FCI${}_0$ wavefunction can change\nsignificantly, rendering DOCI and pCCD a less than ideal starting point for\napproximating FCI.\n",
"title": "Influence of broken-pair excitations on the exact pair wavefunction"
}
| null | null | null | null | true | null |
1626
| null |
Default
| null | null |
null |
{
"abstract": " We first investigate the evolution of opening and closing auctions volumes of\nUS equities along the years. We then report dynamical properties of pre-auction\nperiods: the indicative match price is strongly mean-reverting because the\nimbalance is; the final auction price reacts to a single auction order\nplacement or cancellation in markedly different ways in the opening and closing\nauctions when computed conditionally on imbalance improving or worsening\nevents; the indicative price reverts towards the mid price of the regular limit\norder book but is not especially bound to the spread.\n",
"title": "Dynamical regularities of US equities opening and closing auctions"
}
| null | null | null | null | true | null |
1627
| null |
Default
| null | null |
null |
{
"abstract": " We present measurements of the hyperfine splitting in the Yb-173\n$6s6p~^1P_1^{\\rm o} (F^{\\prime}=3/2,7/2)$ states that disagree significantly\nwith those measured previously by Das and Natarajan [Phys. Rev. A 76, 062505\n(2007)]. We point out inconsistencies in their measurements and suggest that\ntheir error is due to optical pumping and improper determination of the atomic\nline center. Our measurements are made using an optical frequency comb. We use\nan optical pumping scheme to improve the signal-to-background ratio for the\n$F^{\\prime}=3/2$ component.\n",
"title": "Comment on \"Laser cooling of $^{173}$Yb for isotope separation and precision hyperfine spectroscopy\""
}
| null | null | null | null | true | null |
1628
| null |
Default
| null | null |
null |
{
"abstract": " We address the issue of limit cycling behavior in training Generative\nAdversarial Networks and propose the use of Optimistic Mirror Decent (OMD) for\ntraining Wasserstein GANs. Recent theoretical results have shown that\noptimistic mirror decent (OMD) can enjoy faster regret rates in the context of\nzero-sum games. WGANs is exactly a context of solving a zero-sum game with\nsimultaneous no-regret dynamics. Moreover, we show that optimistic mirror\ndecent addresses the limit cycling problem in training WGANs. We formally show\nthat in the case of bi-linear zero-sum games the last iterate of OMD dynamics\nconverges to an equilibrium, in contrast to GD dynamics which are bound to\ncycle. We also portray the huge qualitative difference between GD and OMD\ndynamics with toy examples, even when GD is modified with many adaptations\nproposed in the recent literature, such as gradient penalty or momentum. We\napply OMD WGAN training to a bioinformatics problem of generating DNA\nsequences. We observe that models trained with OMD achieve consistently smaller\nKL divergence with respect to the true underlying distribution, than models\ntrained with GD variants. Finally, we introduce a new algorithm, Optimistic\nAdam, which is an optimistic variant of Adam. We apply it to WGAN training on\nCIFAR10 and observe improved performance in terms of inception score as\ncompared to Adam.\n",
"title": "Training GANs with Optimism"
}
| null | null | null | null | true | null |
1629
| null |
Default
| null | null |
null |
{
"abstract": " In the field of cold atom inertial sensors, we present and analyze innovative\nconfigurations for improving their measurement range and sensitivity,\nespecially attracting for onboard applications. These configurations rely on\nmulti-species atom interferometry, involving the simultaneous manipulation of\ndifferent atomic species in a unique instrument to deduce inertial\nmeasurements. Using a dual-species atom accelerometer manipulating\nsimultaneously both isotopes of rubidium, we report a preliminary experimental\nrealization of original concepts involving the implementation of two atom\ninterferometers first with different interrogation times and secondly in phase\nquadrature. These results open the door to a new generation of atomic sensors\nrelying on high performance multi-species atom interferometric measurements.\n",
"title": "New concepts of inertial measurements with multi-species atom interferometry"
}
| null | null | null | null | true | null |
1630
| null |
Default
| null | null |
null |
{
"abstract": " We study statistical models for one-dimensional diffusions which are\nrecurrent null. A first parameter in the drift is the principal one, and\ndetermines regular varying rates of convergence for the score and the\ninformation process. A finite number of other parameters, of secondary\nimportance, introduces additional flexibility for the modelization of the\ndrift, and does not perturb the null recurrent behaviour. Under time-continuous\nobservation we obtain local asymptotic mixed normality (LAMN), state a local\nasymptotic minimax bound, and specify asymptotically optimal estimators.\n",
"title": "LAMN in a class of parametric models for null recurrent diffusion"
}
| null | null | null | null | true | null |
1631
| null |
Default
| null | null |
null |
{
"abstract": " Meaningful topological invariants for mixed quantum states are challenging to\nidentify as there is no unique way to define them, and most choices do not\ndirectly relate to physical observables. Here, we propose a simple pragmatic\napproach to construct topological invariants of mixed states while preserving a\nconnection to physical observables, by continuously deforming known topological\ninvariants for pure (ground) states. Our approach relies on expectation values\nof many-body operators, with no reference to single-particle (e.g., Bloch)\nwavefunctions. To illustrate it, we examine extensions to mixed states of\n$U(1)$ geometric (Berry) phases and their corresponding topological invariant\n(winding or Chern number). We discuss measurement schemes, and provide a\ndetailed construction of invariants for thermal or more general mixed states of\nquantum systems with (at least) $U(1)$ charge-conservation symmetry, such as\nquantum Hall insulators.\n",
"title": "A recipe for topological observables of density matrices"
}
| null | null |
[
"Physics"
] | null | true | null |
1632
| null |
Validated
| null | null |
null |
{
"abstract": " Deep learning (DL) advances state-of-the-art reinforcement learning (RL), by\nincorporating deep neural networks in learning representations from the input\nto RL. However, the conventional deep neural network architecture is limited in\nlearning representations for multi-task RL (MT-RL), as multiple tasks can refer\nto different kinds of representations. In this paper, we thus propose a novel\ndeep neural network architecture, namely generalization tower network (GTN),\nwhich can achieve MT-RL within a single learned model. Specifically, the\narchitecture of GTN is composed of both horizontal and vertical streams. In our\nGTN architecture, horizontal streams are used to learn representation shared in\nsimilar tasks. In contrast, the vertical streams are introduced to be more\nsuitable for handling diverse tasks, which encodes hierarchical shared\nknowledge of these tasks. The effectiveness of the introduced vertical stream\nis validated by experimental results. Experimental results further verify that\nour GTN architecture is able to advance the state-of-the-art MT-RL, via being\ntested on 51 Atari games.\n",
"title": "Generalization Tower Network: A Novel Deep Neural Network Architecture for Multi-Task Learning"
}
| null | null | null | null | true | null |
1633
| null |
Default
| null | null |
null |
{
"abstract": " A space $G(M, \\varPhi)$ of infinitely differentiable functions in ${\\mathbb\nR}^n$ constructed with a help of a family\n$\\varPhi=\\{\\varphi_m\\}_{m=1}^{\\infty}$ of real-valued functions $\\varphi_m\n\\in~C({\\mathbb R}^n)$ and a logarithmically convex sequence $M$ of positive\nnumbers is considered in the article. In view of conditions on $M$ each\nfunction of $G(M, \\varPhi)$ can be extended to an entire function in ${\\mathbb\nC}^n$. Imposed conditions on $M$ and $\\varPhi$ allow to describe the space of\nsuch extensions.\n",
"title": "On a class of infinitely differentiable functions in ${\\mathbb R}^n$ admitting holomorphic extension in ${\\mathbb C}^n$"
}
| null | null | null | null | true | null |
1634
| null |
Default
| null | null |
null |
{
"abstract": " An accurate description of spatial variations in the energy levels of\npatterned semiconductor substrates on the micron and sub-micron scale as a\nfunction of local doping is an important technological challenge for the\nmicroelectronics industry. Spatially resolved surface analysis by photoelectron\nspectromicroscopy can provide an invaluable contribution thanks to the\nrelatively non-destructive, quantitative analysis. We present results on highly\ndoped n and p type patterns on, respectively, p and n type silicon substrates.\nUsing synchrotron radiation and spherical aberration-corrected energy\nfiltering, we have obtained a spectroscopic image series at the Si 2p core\nlevel and across the valence band. Local band alignments are extracted,\naccounting for doping, band bending and surface photovoltage.\n",
"title": "Spatially resolved, energy-filtered imaging of core level and valence band photoemission of highly p and n doped silicon patterns"
}
| null | null |
[
"Physics"
] | null | true | null |
1635
| null |
Validated
| null | null |
null |
{
"abstract": " We study the influence of degree correlations or network mixing in\ninterdependent security. We model the interdependence in security among agents\nusing a dependence graph and employ a population game model to capture the\ninteraction among many agents when they are strategic and have various security\nmeasures they can choose to defend themselves. The overall network security is\nmeasured by what we call the average risk exposure (ARE) from neighbors, which\nis proportional to the total (expected) number of attacks in the network.\nWe first show that there exists a unique pure-strategy Nash equilibrium of a\npopulation game. Then, we prove that as the agents with larger degrees in the\ndependence graph see higher risks than those with smaller degrees, the overall\nnetwork security deteriorates in that the ARE experienced by agents increases\nand there are more attacks in the network. Finally, using this finding, we\ndemonstrate that the effects of network mixing on ARE depend on the (cost)\neffectiveness of security measures available to agents; if the security\nmeasures are not effective, increasing assortativity of dependence graph\nresults in higher ARE. On the other hand, if the security measures are\neffective at fending off the damages and losses from attacks, increasing\nassortativity reduces the ARE experienced by agents.\n",
"title": "Effects of Degree Correlations in Interdependent Security: Good or Bad?"
}
| null | null | null | null | true | null |
1636
| null |
Default
| null | null |
null |
{
"abstract": " Multi-source transfer learning has been proven effective when within-target\nlabeled data is scarce. Previous work focuses primarily on exploiting domain\nsimilarities and assumes that source domains are richly or at least comparably\nlabeled. While this strong assumption is never true in practice, this paper\nrelaxes it and addresses challenges related to sources with diverse labeling\nvolume and diverse reliability. The first challenge is combining domain\nsimilarity and source reliability by proposing a new transfer learning method\nthat utilizes both source-target similarities and inter-source relationships.\nThe second challenge involves pool-based active learning where the oracle is\nonly available in source domains, resulting in an integrated active transfer\nlearning framework that incorporates distribution matching and uncertainty\nsampling. Extensive experiments on synthetic and two real-world datasets\nclearly demonstrate the superiority of our proposed methods over several\nbaselines including state-of-the-art transfer learning methods.\n",
"title": "Towards more Reliable Transfer Learning"
}
| null | null | null | null | true | null |
1637
| null |
Default
| null | null |
null |
{
"abstract": " We show that black-hole High-Mass X-ray Binaries (HMXBs) with O- or B-type\ndonor stars and relatively short orbital periods, of order one week to several\nmonths may survive spiral in, to then form Wolf-Rayet (WR) X-ray binaries with\norbital periods of order a day to a few days; while in systems where the\ncompact star is a neutron star, HMXBs with these orbital periods never survive\nspiral-in. We therefore predict that WR X-ray binaries can only harbor black\nholes. The reason why black-hole HMXBs with these orbital periods may survive\nspiral in is: the combination of a radiative envelope of the donor star, and a\nhigh mass of the compact star. In this case, when the donor begins to overflow\nits Roche lobe, the systems are able to spiral in slowly with stable Roche-lobe\noverflow, as is shown by the system SS433. In this case the transferred mass is\nejected from the vicinity of the compact star (so-called \"isotropic\nre-emission\" mass loss mode, or \"SS433-like mass loss\"), leading to gradual\nspiral-in. If the mass ratio of donor and black hole is $>3.5$, these systems\nwill go into CE evolution and are less likely to survive. If they survive, they\nproduce WR X-ray binaries with orbital periods of a few hours to one day.\nSeveral of the well-known WR+O binaries in our Galaxy and the Magellanic\nClouds, with orbital periods in the range between a week and several months,\nare expected to evolve into close WR-Black-Hole binaries,which may later\nproduce close double black holes. The galactic formation rate of double black\nholes resulting from such systems is still uncertain, as it depends on several\npoorly known factors in this evolutionary picture. It might possibly be as high\nas $\\sim 10^{-5}$ per year.\n",
"title": "Forming short-period Wolf-Rayet X-ray binaries and double black holes through stable mass transfer"
}
| null | null | null | null | true | null |
1638
| null |
Default
| null | null |
null |
{
"abstract": " We study syzygies of (maximal) Cohen-Macaulay modules over one dimensional\nCohen-Macaulay local rings. We compare these modules to Cohen-Macaulay modules\nover the endomorphism ring of the maximal ideal. After this comparison, we give\nseveral characterizations of almost Gorenstein rings in terms of syzygies of\nCohen-Macaulay modules.\n",
"title": "Syzygies of Cohen-Macaulay modules over one dimensional Cohen-Macaulay local rings"
}
| null | null | null | null | true | null |
1639
| null |
Default
| null | null |
null |
{
"abstract": " Chirality in shape and motility can evolve rapidly in microbes and cancer\ncells. To determine how chirality affects cell fitness, we developed a model of\nchiral growth in compact aggregates such as microbial colonies and solid\ntumors. Our model recapitulates previous experimental findings and shows that\nmutant cells can invade by increasing their chirality or switching their\nhandedness. The invasion results either in a takeover or stable coexistence\nbetween the mutant and the ancestor depending on their relative chirality. For\nlarge chiralities, the coexistence is accompanied by strong intermixing between\nthe cells, while spatial segregation occurs otherwise. We show that the\ncompetition within the aggregate is mediated by bulges in regions where the\ncells with different chiralities meet. The two-way coupling between aggregate\nshape and natural selection is described by the chiral Kardar-Parisi-Zhang\nequation coupled to the Burgers' equation with multiplicative noise. We solve\nfor the key features of this theory to explain the origin of selection on\nchirality. Overall, our work suggests that chirality could be an important\necological trait that mediates competition, invasion, and spatial structure in\ncellular populations.\n",
"title": "Chirality provides a direct fitness advantage and facilitates intermixing in cellular aggregates"
}
| null | null |
[
"Physics"
] | null | true | null |
1640
| null |
Validated
| null | null |
null |
{
"abstract": " We propose a simple algorithm to train stochastic neural networks to draw\nsamples from given target distributions for probabilistic inference. Our method\nis based on iteratively adjusting the neural network parameters so that the\noutput changes along a Stein variational gradient direction (Liu & Wang, 2016)\nthat maximally decreases the KL divergence with the target distribution. Our\nmethod works for any target distribution specified by their unnormalized\ndensity function, and can train any black-box architectures that are\ndifferentiable in terms of the parameters we want to adapt. We demonstrate our\nmethod with a number of applications, including variational autoencoder (VAE)\nwith expressive encoders to model complex latent space structures, and\nhyper-parameter learning of MCMC samplers that allows Bayesian inference to\nadaptively improve itself when seeing more data.\n",
"title": "Learning to Draw Samples with Amortized Stein Variational Gradient Descent"
}
| null | null | null | null | true | null |
1641
| null |
Default
| null | null |
null |
{
"abstract": " This note proposes a simple and general framework of dynamic mode\ndecomposition (DMD) and a mode selection for large datasets. The proposed\nframework explicitly introduces a preconditioning step using an incremental\nproper orthogonal decomposition to DMD and mode selection algorithms. By\nperforming the preconditioning step, the DMD and the mode selection can be\nperformed with low memory consumption and small computational complexity and\ncan be applied to large datasets. In addition, a simple mode selection\nalgorithm based on a greedy method is proposed. The proposed framework is\napplied to the analysis of a three-dimensional flows around a circular\ncylinder.\n",
"title": "Preconditioned dynamic mode decomposition and mode selection algorithms for large datasets using incremental proper orthogonal decomposition"
}
| null | null |
[
"Physics"
] | null | true | null |
1642
| null |
Validated
| null | null |
null |
{
"abstract": " We investigate the emergence of ${\\cal N}=1$ supersymmetry in the long-range\nbehavior of three-dimensional parity-symmetric Yukawa systems. We discuss a\nrenormalization approach that manifestly preserves supersymmetry whenever such\nsymmetry is realized, and use it to prove that supersymmetry-breaking operators\nare irrelevant, thus proving that such operators are suppressed in the\ninfrared. All our findings are illustrated with the aid of the\n$\\epsilon$-expansion and a functional variant of perturbation theory, but we\nprovide numerical estimates of critical exponents that are based on the\nnon-perturbative functional renormalization group.\n",
"title": "A functional perspective on emergent supersymmetry"
}
| null | null | null | null | true | null |
1643
| null |
Default
| null | null |
null |
{
"abstract": " Adaptive gradient methods have become recently very popular, in particular as\nthey have been shown to be useful in the training of deep neural networks. In\nthis paper we have analyzed RMSProp, originally proposed for the training of\ndeep neural networks, in the context of online convex optimization and show\n$\\sqrt{T}$-type regret bounds. Moreover, we propose two variants SC-Adagrad and\nSC-RMSProp for which we show logarithmic regret bounds for strongly convex\nfunctions. Finally, we demonstrate in the experiments that these new variants\noutperform other adaptive gradient techniques or stochastic gradient descent in\nthe optimization of strongly convex functions as well as in training of deep\nneural networks.\n",
"title": "Variants of RMSProp and Adagrad with Logarithmic Regret Bounds"
}
| null | null | null | null | true | null |
1644
| null |
Default
| null | null |
null |
{
"abstract": " We study connections between Dykstra's algorithm for projecting onto an\nintersection of convex sets, the augmented Lagrangian method of multipliers or\nADMM, and block coordinate descent. We prove that coordinate descent for a\nregularized regression problem, in which the (separable) penalty functions are\nseminorms, is exactly equivalent to Dykstra's algorithm applied to the dual\nproblem. ADMM on the dual problem is also seen to be equivalent, in the special\ncase of two sets, with one being a linear subspace. These connections, aside\nfrom being interesting in their own right, suggest new ways of analyzing and\nextending coordinate descent. For example, from existing convergence theory on\nDykstra's algorithm over polyhedra, we discern that coordinate descent for the\nlasso problem converges at an (asymptotically) linear rate. We also develop two\nparallel versions of coordinate descent, based on the Dykstra and ADMM\nconnections.\n",
"title": "Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions"
}
| null | null | null | null | true | null |
1645
| null |
Default
| null | null |
null |
{
"abstract": " Techniques from higher categories and higher-dimensional rewriting are\nbecoming increasingly important for understanding the finer, computational\nproperties of higher algebraic theories that arise, among other fields, in\nquantum computation. These theories have often the property of containing\nsimpler sub-theories, whose interaction is regulated in a limited number of\nways, which reveals a topological substrate when pictured by string diagrams.\nBy exploring the double nature of computads as presentations of higher\nalgebraic theories, and combinatorial descriptions of \"directed spaces\", we\ndevelop a basic language of directed topology for the compositional study of\nalgebraic theories. We present constructions of computads, all with clear\nanalogues in standard topology, that capture in great generality such notions\nas homomorphisms and actions, and the interactions of monoids and comonoids\nthat lead to the theory of Frobenius algebras and of bialgebras. After a number\nof examples, we describe how a fragment of the ZX calculus can be reconstructed\nin this framework.\n",
"title": "A Topological Perspective on Interacting Algebraic Theories"
}
| null | null | null | null | true | null |
1646
| null |
Default
| null | null |
null |
{
"abstract": " We introduce dynamic nested sampling: a generalisation of the nested sampling\nalgorithm in which the number of \"live points\" varies to allocate samples more\nefficiently. In empirical tests the new method significantly improves\ncalculation accuracy compared to standard nested sampling with the same number\nof samples; this increase in accuracy is equivalent to speeding up the\ncomputation by factors of up to ~72 for parameter estimation and ~7 for\nevidence calculations. We also show that the accuracy of both parameter\nestimation and evidence calculations can be improved simultaneously. In\naddition, unlike in standard nested sampling, more accurate results can be\nobtained by continuing the calculation for longer. Popular standard nested\nsampling implementations can be easily adapted to perform dynamic nested\nsampling, and several dynamic nested sampling software packages are now\npublicly available.\n",
"title": "Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation"
}
| null | null |
[
"Physics",
"Statistics"
] | null | true | null |
1647
| null |
Validated
| null | null |
null |
{
"abstract": " Multistage design has been used in a wide range of scientific fields. By\nallocating sensing resources adaptively, one can effectively eliminate null\nlocations and localize signals with a smaller study budget. We formulate a\ndecision-theoretic framework for simultaneous multi- stage adaptive testing and\nstudy how to minimize the total number of measurements while meeting\npre-specified constraints on both the false positive rate (FPR) and missed\ndiscovery rate (MDR). The new procedure, which effectively pools information\nacross individual tests using a simultaneous multistage adaptive ranking and\nthresholding (SMART) approach, can achieve precise error rates control and lead\nto great savings in total study costs. Numerical studies confirm the\neffectiveness of SMART for FPR and MDR control and show that it achieves\nsubstantial power gain over existing methods. The SMART procedure is\ndemonstrated through the analysis of high-throughput screening data and spatial\nimaging data.\n",
"title": "Multistage Adaptive Testing of Sparse Signals"
}
| null | null | null | null | true | null |
1648
| null |
Default
| null | null |
null |
{
"abstract": " We investigate powerspace constructions on topological spaces, with a\nparticular focus on the category of quasi-Polish spaces. We show that the upper\nand lower powerspaces commute on all quasi-Polish spaces, and show more\ngenerally that this commutativity is equivalent to the topological property of\nconsonance. We then investigate powerspace constructions on the open set\nlattices of quasi-Polish spaces, and provide a complete characterization of how\nthe upper and lower powerspaces distribute over the open set lattice\nconstruction.\n",
"title": "On the commutativity of the powerspace constructions"
}
| null | null | null | null | true | null |
1649
| null |
Default
| null | null |
null |
{
"abstract": " A numerical method is presented which conveniently computes upper bounds on\nheat transport and poloidal energy in plane layer convection for infinite and\nfinite Prandtl numbers. The bounds obtained for the heat transport coincide\nwith earlier results. These bounds imply upper bounds for the poloidal energy\nwhich follow directly from the definitions of dissipation and energy. The same\nconstraints used for computing upper bounds on the heat transport lead to\nimproved bounds for the poloidal energy.\n",
"title": "Bounds on poloidal kinetic energy in plane layer convection"
}
| null | null | null | null | true | null |
1650
| null |
Default
| null | null |
null |
{
"abstract": " We prove near-tight concentration of measure for polynomial functions of the\nIsing model under high temperature. For any degree $d$, we show that a\ndegree-$d$ polynomial of a $n$-spin Ising model exhibits exponential tails that\nscale as $\\exp(-r^{2/d})$ at radius $r=\\tilde{\\Omega}_d(n^{d/2})$. Our\nconcentration radius is optimal up to logarithmic factors for constant $d$,\nimproving known results by polynomial factors in the number of spins. We\ndemonstrate the efficacy of polynomial functions as statistics for testing the\nstrength of interactions in social networks in both synthetic and real world\ndata.\n",
"title": "Concentration of Multilinear Functions of the Ising Model with Applications to Network Data"
}
| null | null | null | null | true | null |
1651
| null |
Default
| null | null |
null |
{
"abstract": " This paper proposes an exploration method for deep reinforcement learning\nbased on parameter space noise. Recent studies have experimentally shown that\nparameter space noise results in better exploration than the commonly used\naction space noise. Previous methods devised a way to update the diagonal\ncovariance matrix of a noise distribution and did not consider the direction of\nthe noise vector and its correlation. In addition, fast updates of the noise\ndistribution are required to facilitate policy learning. We propose a method\nthat deforms the noise distribution according to the accumulated returns and\nthe noises that have led to the returns. Moreover, this method switches\nisotropic exploration and directional exploration in parameter space with\nregard to obtained rewards. We validate our exploration strategy in the OpenAI\nGym continuous environments and modified environments with sparse rewards. The\nproposed method achieves results that are competitive with a previous method at\nbaseline tasks. Moreover, our approach exhibits better performance in sparse\nreward environments by exploration with the switching strategy.\n",
"title": "Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning"
}
| null | null | null | null | true | null |
1652
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, based on the framework of traditional spectrophotometry, we\nput forward a novel fast and high-accuracy technique for measuring\ntransmittance spectrum in VIS-NIR wave range, its key feature is that during\nthe measurement procedure, the output wavelength of the grating monochromator\nis kept increasing continuously and at the same time, the photoelectric\ndetectors execute a concurrently continuous data acquisition routine. Initial\nexperiment result shows that the newly proposed technique could shorten the\ntime consumed for measuring the transmittance spectrum down to 50% that of the\nconventional spectrophotometric method, a relative error of 0.070% and a\nrepeatability error of 0.042% are generated. Compared with the current mostly\nused techniques (spectrophotometry, methods based on multi-channel spectrometer\nand strategy using Fourier transform spectrometer) for obtaining transmittance\nspectrum in VIS-NIR, the new strategy has at all once the following advantages,\nfirstly the measuring speed could be greatly quicken, fast measurement of\ntransmittance spectrum in VIS-NIR is therefore promising, which would find wide\napplication in dynamic environment, secondly high measuring accuracy\n(0.1%-0.3%) is available, and finally the measuring system has high mechanical\nstability because the motor of the grating monochromator is rotating\ncontinuously during the measurement.\n",
"title": "Fast and high-accuracy measuring technique for transmittance spectrum in VIS-NIR"
}
| null | null | null | null | true | null |
1653
| null |
Default
| null | null |
null |
{
"abstract": " We propose a method to solve the initial value problem for the ultradiscrete\nSomos-4 and Somos-5 equations by expressing terms in the equations as convex\npolygons and regarding max-plus algebras as those on polygons.\n",
"title": "The solution to the initial value problem for the ultradiscrete Somos-4 and 5 equations"
}
| null | null | null | null | true | null |
1654
| null |
Default
| null | null |
null |
{
"abstract": " Quantum confinement and interference often generate exotic properties in\nnanostructures. One recent highlight is the experimental indication of a\nmagnetic phase transition in zigzag-edged graphene nanoribbons at the critical\nribbon width of about 7 nm [G. Z. Magda et al., Nature \\textbf{514}, 608\n(2014)]. Here we show theoretically that with further increase in the ribbon\nwidth, the magnetic correlation of the two edges can exhibit an intriguing\noscillatory behavior between antiferromagnetic and ferromagnetic, driven by\nacquiring the positive coherence between the two edges to lower the free\nenergy. The oscillation effect is readily tunable in applied magnetic fields.\nThese novel properties suggest new experimental manifestation of the edge\nmagnetic orders in graphene nanoribbons, and enhance the hopes of graphene-like\nspintronic nanodevices functioning at room temperature.\n",
"title": "Width-tuned magnetic order oscillation on zigzag edges of honeycomb nanoribbons"
}
| null | null | null | null | true | null |
1655
| null |
Default
| null | null |
null |
{
"abstract": " The gamma distribution arises frequently in Bayesian models, but there is not\nan easy-to-use conjugate prior for the shape parameter of a gamma. This\ninconvenience is usually dealt with by using either Metropolis-Hastings moves,\nrejection sampling methods, or numerical integration. However, in models with a\nlarge number of shape parameters, these existing methods are slower or more\ncomplicated than one would like, making them burdensome in practice. It turns\nout that the full conditional distribution of the gamma shape parameter is well\napproximated by a gamma distribution, even for small sample sizes, when the\nprior on the shape parameter is also a gamma distribution. This article\nintroduces a quick and easy algorithm for finding a gamma distribution that\napproximates the full conditional distribution of the shape parameter. We\nempirically demonstrate the speed and accuracy of the approximation across a\nwide range of conditions. If exactness is required, the approximation can be\nused as a proposal distribution for Metropolis-Hastings.\n",
"title": "Fast and accurate approximation of the full conditional for gamma shape parameters"
}
| null | null | null | null | true | null |
1656
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we present two algorithms based on the Froidure-Pin Algorithm\nfor computing the structure of a finite semigroup from a generating set. As was\nthe case with the original algorithm of Froidure and Pin, the algorithms\npresented here produce the left and right Cayley graphs, a confluent\nterminating rewriting system, and a reduced word of the rewriting system for\nevery element of the semigroup.\nIf $U$ is any semigroup, and $A$ is a subset of $U$, then we denote by\n$\\langle A\\rangle$ the least subsemigroup of $U$ containing $A$. If $B$ is any\nother subset of $U$, then, roughly speaking, the first algorithm we present\ndescribes how to use any information about $\\langle A\\rangle$, that has been\nfound using the Froidure-Pin Algorithm, to compute the semigroup $\\langle A\\cup\nB\\rangle$. More precisely, we describe the data structure for a finite\nsemigroup $S$ given by Froidure and Pin, and how to obtain such a data\nstructure for $\\langle A\\cup B\\rangle$ from that for $\\langle A\\rangle$. The\nsecond algorithm is a lock-free concurrent version of the Froidure-Pin\nAlgorithm.\n",
"title": "Two variants of the Froiduire-Pin Algorithm for finite semigroups"
}
| null | null | null | null | true | null |
1657
| null |
Default
| null | null |
null |
{
"abstract": " We address the problem of a lightly doped spin-liquid through a large-scale\ndensity-matrix renormalization group (DMRG) study of the $t$-$J$ model on a\nKagome lattice with a small but non-zero concentration, $\\delta$, of doped\nholes. It is now widely accepted that the undoped ($\\delta=0$) spin 1/2\nHeisenberg antiferromagnet has a spin-liquid groundstate. Theoretical arguments\nhave been presented that light doping of such a spin-liquid could give rise to\na high temperature superconductor or an exotic topological Fermi liquid metal\n(FL$^\\ast$). Instead, we infer that the doped holes form an insulating\ncharge-density wave state with one doped-hole per unit cell - i.e. a Wigner\ncrystal (WC). Spin correlations remain short-ranged, as in the spin-liquid\nparent state, from which we infer that the state is a crystal of spinless\nholons (WC$^\\ast$), rather than of holes. Our results may be relevant to Kagome\nlattice Herbertsmithite $\\rm ZnCu_3(OH)_6Cl_2$ upon doping.\n",
"title": "Holon Wigner Crystal in a Lightly Doped Kagome Quantum Spin Liquid"
}
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1658
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| null | null |
null |
{
"abstract": " Nonconvex optimization problems arise in different research fields and arouse\nlots of attention in signal processing, statistics and machine learning. In\nthis work, we explore the accelerated proximal gradient method and some of its\nvariants which have been shown to converge under nonconvex context recently. We\nshow that a novel variant proposed here, which exploits adaptive momentum and\nblock coordinate update with specific update rules, further improves the\nperformance of a broad class of nonconvex problems. In applications to sparse\nlinear regression with regularizations like Lasso, grouped Lasso, capped\n$\\ell_1$ and SCAP, the proposed scheme enjoys provable local linear\nconvergence, with experimental justification.\n",
"title": "Accelerated Block Coordinate Proximal Gradients with Applications in High Dimensional Statistics"
}
| null | null | null | null | true | null |
1659
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null |
{
"abstract": " This paper considers the problem of phase retrieval, where the goal is to\nrecover a signal $z\\in C^n$ from the observations $y_i=|a_i^* z|$,\n$i=1,2,\\cdots,m$. While many algorithms have been proposed, the alternating\nminimization algorithm has been one of the most commonly used methods, and it\nis very simple to implement. Current work has proved that when the observation\nvectors $\\{a_i\\}_{i=1}^m$ are sampled from a complex Gaussian distribution\n$N(0, I)$, it recovers the underlying signal with a good initialization when\n$m=O(n)$, or with random initialization when $m=O(n^2)$, and it conjectured\nthat random initialization succeeds with $m=O(n)$. This work proposes a\nmodified alternating minimization method in a batch setting, and proves that\nwhen $m=O(n\\log^{3}n)$, the proposed algorithm with random initialization\nrecovers the underlying signal with high probability. The proof is based on the\nobservation that after each iteration of alternating minimization, with high\nprobability, the angle between the estimated signal and the underlying signal\nis reduced.\n",
"title": "Phase retrieval using alternating minimization in a batch setting"
}
| null | null | null | null | true | null |
1660
| null |
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| null | null |
null |
{
"abstract": " Inverse problems in statistical physics are motivated by the challenges of\n`big data' in different fields, in particular high-throughput experiments in\nbiology. In inverse problems, the usual procedure of statistical physics needs\nto be reversed: Instead of calculating observables on the basis of model\nparameters, we seek to infer parameters of a model based on observations. In\nthis review, we focus on the inverse Ising problem and closely related\nproblems, namely how to infer the coupling strengths between spins given\nobserved spin correlations, magnetisations, or other data. We review\napplications of the inverse Ising problem, including the reconstruction of\nneural connections, protein structure determination, and the inference of gene\nregulatory networks. For the inverse Ising problem in equilibrium, a number of\ncontrolled and uncontrolled approximate solutions have been developed in the\nstatistical mechanics community. A particularly strong method,\npseudolikelihood, stems from statistics. We also review the inverse Ising\nproblem in the non-equilibrium case, where the model parameters must be\nreconstructed based on non-equilibrium statistics.\n",
"title": "Inverse statistical problems: from the inverse Ising problem to data science"
}
| null | null | null | null | true | null |
1661
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null |
{
"abstract": " We propose a novel mechanism which explains cored dark matter density profile\nin recently observed dark matter rich dwarf spheroidal galaxies. In our\nscenario, dark matter particle mass decreases gradually as function of distance\ntowards the center of a dwarf galaxy due to its interaction with a chameleon\nscalar. At closer distance towards galactic center the strength of attractive\nscalar fifth force becomes much stronger than gravity and is balanced by the\nFermi pressure of dark matter cloud, thus an equilibrium static configuration\nof dark matter halo is obtained. Like the case of soliton star or fermion\nQ-star, the stability of the dark matter halo is obtained as the scalar\nachieves a static profile and reaches an asymptotic value away from the\ngalactic center. For simple scalar-dark matter interaction and quadratic scalar\nself interaction potential, we show that dark matter behaves exactly like cold\ndark matter (CDM) beyond few $\\rm{kpc}$ away from galactic center but at closer\ndistance it becomes lighter and fermi pressure cannot be ignored anymore. Using\nThomas-Fermi approximation, we numerically solve the radial static profile of\nthe scalar field, fermion mass and dark matter energy density as a function of\ndistance. We find that for fifth force mediated by an ultra light scalar, it is\npossible to obtain a flattened dark matter density profile towards galactic\ncenter. In our scenario, the fifth force can be neglected at distance $ r \\geq\n1\\, \\rm{kpc}$ from galactic center and dark matter can be simply treated as\nheavy non-relativistic particles beyond this distance, thus reproducing the\nsuccess of CDM at large scales.\n",
"title": "Static structure of chameleon dark Matter as an explanation of dwarf spheroidal galactic core"
}
| null | null | null | null | true | null |
1662
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null |
{
"abstract": " Recommender systems have been successfully applied to assist decision making\nby producing a list of item recommendations tailored to user preferences.\nTraditional recommender systems only focus on optimizing the utility of the end\nusers who are the receiver of the recommendations. By contrast,\nmulti-stakeholder recommendation attempts to generate recommendations that\nsatisfy the needs of both the end users and other parties or stakeholders. This\npaper provides an overview and discussion about the multi-stakeholder\nrecommendations from the perspective of practical applications, available data\nsets, corresponding research challenges and potential solutions.\n",
"title": "Multi-Stakeholder Recommendation: Applications and Challenges"
}
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1663
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null |
{
"abstract": " We prove a lower bound of $\\Omega(n^2/\\log^2 n)$ on the size of any\nsyntactically multilinear arithmetic circuit computing some explicit\nmultilinear polynomial $f(x_1, \\ldots, x_n)$. Our approach expands and improves\nupon a result of Raz, Shpilka and Yehudayoff ([RSY08]), who proved a lower\nbound of $\\Omega(n^{4/3}/\\log^2 n)$ for the same polynomial. Our improvement\nfollows from an asymptotically optimal lower bound for a generalized version of\nGalvin's problem in extremal set theory.\n",
"title": "Unbalancing Sets and an Almost Quadratic Lower Bound for Syntactically Multilinear Arithmetic Circuits"
}
| null | null |
[
"Computer Science"
] | null | true | null |
1664
| null |
Validated
| null | null |
null |
{
"abstract": " We introduce the concept of saturated absorption competition (SAC) microscopy\nas a means of providing sub-diffraction spatial resolution in fluorescence\nimaging. Unlike the post-competition process between stimulated and spontaneous\nemission that is used in stimulated emission depletion (STED) microscopy, SAC\nmicroscopy breaks the diffraction limit by emphasizing a pre-competition\nprocess that occurs in the fluorescence absorption stage in a manner that\nshares similarities with ground-state depletion (GSD) microscopy. Moreover,\nunlike both STED and GSD microscopy, SAC microscopy offers a reduction in\ncomplexity and cost by utilizing only a single continuous-wave laser diode and\nan illumination intensity that is ~ 20x smaller than that used in STED. Our\napproach can be physically implemented in a confocal microscope by dividing the\ninput laser source into a time-modulated primary excitation beam and a\ndoughnut-shaped saturation beam, and subsequently employing a homodyne\ndetection scheme to select the modulated fluorescence signal. Herein, we\nprovide both a physico-chemical model of SAC and experimentally demonstrate by\nway of a proof-of-concept experiment a transverse spatial resolution of\n~lambda/6.\n",
"title": "Saturated absorption competition microscopy"
}
| null | null | null | null | true | null |
1665
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| null | null |
null |
{
"abstract": " In this work, we investigate the combined influence of the nontrivial\ntopology introduced by a disclination and non inertial effects due to rotation,\nin the energy levels and the wave functions of a noninteracting electron gas\nconfined to a two-dimensional pseudoharmonic quantum dot, under the influence\nof an external uniform magnetic field. The exact solutions for energy\neigenvalues and wave functions are computed as functions of the applied\nmagnetic field strength, the disclination topological charge, magnetic quantum\nnumber and the rotation speed of the sample. We investigate the modifications\non the light interband absorption coefficient and absorption threshold\nfrequency. We observe novel features in the system, including a range of\nmagnetic field without corresponding absorption phenomena, which is due to a\ntripartite term of the Hamiltonian, involving magnetic field, the topological\ncharge of the defect and the rotation frequency.\n",
"title": "Topological and non inertial effects on the interbank light absorption"
}
| null | null | null | null | true | null |
1666
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| null | null |
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{
"abstract": " We report the observation of magnetic domains in the exotic,\nantiferromagnetically ordered all-in-all-out state of Nd$_2$Zr$_2$O$_7$,\ninduced by spin canting. The all-in-all-out state can be realized by Ising-like\nspins on a pyrochlore lattice and is established in Nd$_2$Zr$_2$O$_7$ below\n0.31 K for external magnetic fields up to 0.14 T. Two different spin\narrangements can fulfill this configuration which leads to the possibility of\nmagnetic domains. The all-in-all-out domain structure can be controlled by an\nexternal magnetic field applied parallel to the [111] direction. This is a\nresult of different spin canting mechanism for the two all-in-all-out\nconfigurations for such a direction of the magnetic field. The change of the\ndomain structure is observed through a hysteresis in the magnetic\nsusceptibility. No hysteresis occurs, however, in case the external magnetic\nfield is applied along [100].\n",
"title": "Evolution of antiferromagnetic domains in the all-in-all-out ordered pyrochlore Nd$_2$Zr$_2$O$_7$"
}
| null | null | null | null | true | null |
1667
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| null | null |
null |
{
"abstract": " Phylogenetic networks are becoming of increasing interest to evolutionary\nbiologists due to their ability to capture complex non-treelike evolutionary\nprocesses. From a combinatorial point of view, such networks are certain types\nof rooted directed acyclic graphs whose leaves are labelled by, for example,\nspecies. A number of mathematically interesting classes of phylogenetic\nnetworks are known. These include the biologically relevant class of stable\nphylogenetic networks whose members are defined via certain fold-up and un-fold\noperations that link them with concepts arising within the theory of, for\nexample, graph fibrations. Despite this exciting link, the structural\ncomplexity of stable phylogenetic networks is still relatively poorly\nunderstood. Employing the popular tree-based, reticulation-visible, and\ntree-child properties which allow one to gauge this complexity in one way or\nanother, we provide novel characterizations for when a stable phylogenetic\nnetwork satisfies either one of these three properties.\n",
"title": "Phylogenetic networks that are their own fold-ups"
}
| null | null | null | null | true | null |
1668
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| null | null |
null |
{
"abstract": " In this paper, we prove the short-time existence of hyperbolic inverse (mean)\ncurvature flow (with or without the specified forcing term) under the\nassumption that the initial compact smooth hypersurface of $\\mathbb{R}^{n+1}$\n($n\\geqslant2$) is mean convex and star-shaped. Several interesting examples\nand some hyperbolic evolution equations for geometric quantities of the\nevolving hypersurfaces have been shown. Besides, under different assumptions\nfor the initial velocity, we can get the expansion and the convergence results\nof a hyperbolic inverse mean curvature flow in the plane $\\mathbb{R}^2$, whose\nevolving curves move normally.\n",
"title": "Hyperbolic inverse mean curvature flow"
}
| null | null | null | null | true | null |
1669
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| null | null |
null |
{
"abstract": " We identify a trade-off between robustness and accuracy that serves as a\nguiding principle in the design of defenses against adversarial examples.\nAlthough the problem has been widely studied empirically, much remains unknown\nconcerning the theory underlying this trade-off. In this work, we quantify the\ntrade-off in terms of the gap between the risk for adversarial examples and the\nrisk for non-adversarial examples. The challenge is to provide tight bounds on\nthis quantity in terms of a surrogate loss. We give an optimal upper bound on\nthis quantity in terms of classification-calibrated loss, which matches the\nlower bound in the worst case. Inspired by our theoretical analysis, we also\ndesign a new defense method, TRADES, to trade adversarial robustness off\nagainst accuracy. Our proposed algorithm performs well experimentally in\nreal-world datasets. The methodology is the foundation of our entry to the\nNeurIPS 2018 Adversarial Vision Challenge in which we won the 1st place out of\n1,995 submissions in the robust model track, surpassing the runner-up approach\nby $11.41\\%$ in terms of mean $\\ell_2$ perturbation distance.\n",
"title": "Theoretically Principled Trade-off between Robustness and Accuracy"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
1670
| null |
Validated
| null | null |
null |
{
"abstract": " The DArk Matter Particle Explorer (DAMPE) is one of the four satellites\nwithin the Strategic Pioneer Research Program in Space Science of the Chinese\nAcademy of Science (CAS). The Silicon-Tungsten Tracker (STK), which is composed\nof 768 singled-sided silicon microstrip detectors, is one of the four\nsubdetectors in DAMPE, providing track reconstruction and charge identification\nfor relativistic charged particles. The charge response of DAMPE silicon\nmicrostrip detectors is complicated, depending on the incident angle and impact\nposition. A new charge reconstruction algorithm for the DAMPE silicon\nmicrostrip detector is introduced in this paper. This algorithm can correct the\ncomplicated charge response, and was proved applicable by the ion test beam.\n",
"title": "A new charge reconstruction algorithm for the DAMPE silicon microstrip detector"
}
| null | null | null | null | true | null |
1671
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| null | null |
null |
{
"abstract": " Representation learning is a fundamental but challenging problem, especially\nwhen the distribution of data is unknown. We propose a new representation\nlearning method, termed Structure Transfer Machine (STM), which enables feature\nlearning process to converge at the representation expectation in a\nprobabilistic way. We theoretically show that such an expected value of the\nrepresentation (mean) is achievable if the manifold structure can be\ntransferred from the data space to the feature space. The resulting structure\nregularization term, named manifold loss, is incorporated into the loss\nfunction of the typical deep learning pipeline. The STM architecture is\nconstructed to enforce the learned deep representation to satisfy the intrinsic\nmanifold structure from the data, which results in robust features that suit\nvarious application scenarios, such as digit recognition, image classification\nand object tracking. Compared to state-of-the-art CNN architectures, we achieve\nthe better results on several commonly used benchmarks\\footnote{The source code\nis available. this https URL }.\n",
"title": "The Structure Transfer Machine Theory and Applications"
}
| null | null | null | null | true | null |
1672
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| null | null |
null |
{
"abstract": " We address in this paper the problem of modifying both profits and costs of a\nfractional knapsack problem optimally such that a prespecified solution becomes\nan optimal solution with prespect to new parameters. This problem is called the\ninverse fractional knapsack problem. Concerning the $l_1$-norm, we first prove\nthat the problem is NP-hard. The problem can be however solved in quadratic\ntime if we only modify profit parameters. Additionally, we develop a\nquadratic-time algorithm that solves the inverse fractional knapsack problem\nunder $l_\\infty$-norm.\n",
"title": "Inverse Fractional Knapsack Problem with Profits and Costs Modification"
}
| null | null | null | null | true | null |
1673
| null |
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| null | null |
null |
{
"abstract": " Margin-based classifiers have been popular in both machine learning and\nstatistics for classification problems. Since a large number of classifiers are\navailable, one natural question is which type of classifiers should be used\ngiven a particular classification task. We aim to answering this question by\ninvestigating the asymptotic performance of a family of large-margin\nclassifiers in situations where the data dimension $p$ and the sample $n$ are\nboth large. This family covers a broad range of classifiers including support\nvector machine, distance weighted discrimination, penalized logistic\nregression, and large-margin unified machine as special cases. The asymptotic\nresults are described by a set of nonlinear equations and we observe a close\nmatch of them with Monte Carlo simulation on finite data samples. Our\nanalytical studies shed new light on how to select the best classifier among\nvarious classification methods as well as on how to choose the optimal tuning\nparameters for a given method.\n",
"title": "Large dimensional analysis of general margin based classification methods"
}
| null | null | null | null | true | null |
1674
| null |
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| null | null |
null |
{
"abstract": " Let $k$ be a nonperfect separably closed field. Let $G$ be a connected\nreductive algebraic group defined over $k$. We study rationality problems for\nSerre's notion of complete reducibility of subgroups of $G$. In particular, we\npresent a new example of subgroup $H$ of $G$ of type $D_4$ in characteristic\n$2$ such that $H$ is $G$-completely reducible but not $G$-completely reducible\nover $k$ (or vice versa). This is new: all known such examples are for $G$ of\nexceptional type. We also find a new counterexample for Külshammer's question\non representations of finite groups for $G$ of type $D_4$. A problem concerning\nthe number of conjugacy classes is also considered. The notion of nonseparable\nsubgroups plays a crucial role in all our constructions.\n",
"title": "Complete reducibility, Kulshammer's question, conjugacy classes: a D_4 example"
}
| null | null | null | null | true | null |
1675
| null |
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| null | null |
null |
{
"abstract": " In a general linear model, this paper derives a necessary and sufficient\ncondition under which two general ridge estimators coincide with each other.\nThe condition is given as a structure of the dispersion matrix of the error\nterm. Since the class of estimators considered here contains linear unbiased\nestimators such as the ordinary least squares estimator and the best linear\nunbiased estimator, our result can be viewed as a generalization of the\nwell-known theorems on the equality between these two estimators, which have\nbeen fully studied in the literature. Two related problems are also considered:\nequality between two residual sums of squares, and classification of dispersion\nmatrices by a perturbation approach.\n",
"title": "Covariance structure associated with an equality between two general ridge estimators"
}
| null | null | null | null | true | null |
1676
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| null | null |
null |
{
"abstract": " In this article we construct three explicit natural subgroups of the\nBrauer-Picard group of the category of representations of a finite-dimensional\nHopf algebra. In examples the Brauer Picard group decomposes into an ordered\nproduct of these subgroups, somewhat similar to a Bruhat decomposition.\nOur construction returns for any Hopf algebra three types of braided\nautoequivalences and correspondingly three families of invertible bimodule\ncategories. This gives examples of so-called (2-)Morita equivalences and\ndefects in topological field theories. We have a closer look at the case of\nquantum groups and Nichols algebras and give interesting applications. Finally,\nwe briefly discuss the three families of group-theoretic extensions.\n",
"title": "Three natural subgroups of the Brauer-Picard group of a Hopf algebra with applications"
}
| null | null | null | null | true | null |
1677
| null |
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| null | null |
null |
{
"abstract": " We demonstrate the use of semantic object detections as robust features for\nVisual Teach and Repeat (VTR). Recent CNN-based object detectors are able to\nreliably detect objects of tens or hundreds of categories in a video at frame\nrates. We show that such detections are repeatable enough to use as landmarks\nfor VTR, without any low-level image features. Since object detections are\nhighly invariant to lighting and surface appearance changes, our VTR can cope\nwith global lighting changes and local movements of the landmark objects. In\nthe teaching phase, we build a series of compact scene descriptors: a list of\ndetected object labels and their image-plane locations. In the repeating phase,\nwe use Seq-SLAM-like relocalization to identify the most similar learned scene,\nthen use a motion control algorithm based on the funnel lane theory to navigate\nthe robot along the previously piloted trajectory. We evaluate the method on a\ncommodity UAV, examining the robustness of the algorithm to new viewpoints,\nlighting conditions, and movements of landmark objects. The results suggest\nthat semantic object features could be useful due to their invariance to\nsuperficial appearance changes compared to low-level image features.\n",
"title": "UAV Visual Teach and Repeat Using Only Semantic Object Features"
}
| null | null | null | null | true | null |
1678
| null |
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| null | null |
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{
"abstract": " There have been numerous breakthroughs with reinforcement learning in the\nrecent years, perhaps most notably on Deep Reinforcement Learning successfully\nplaying and winning relatively advanced computer games. There is undoubtedly an\nanticipation that Deep Reinforcement Learning will play a major role when the\nfirst AI masters the complicated game plays needed to beat a professional\nReal-Time Strategy game player. For this to be possible, there needs to be a\ngame environment that targets and fosters AI research, and specifically Deep\nReinforcement Learning. Some game environments already exist, however, these\nare either overly simplistic such as Atari 2600 or complex such as Starcraft II\nfrom Blizzard Entertainment. We propose a game environment in between Atari\n2600 and Starcraft II, particularly targeting Deep Reinforcement Learning\nalgorithm research. The environment is a variant of Tower Line Wars from\nWarcraft III, Blizzard Entertainment. Further, as a proof of concept that the\nenvironment can harbor Deep Reinforcement algorithms, we propose and apply a\nDeep Q-Reinforcement architecture. The architecture simplifies the state space\nso that it is applicable to Q-learning, and in turn improves performance\ncompared to current state-of-the-art methods. Our experiments show that the\nproposed architecture can learn to play the environment well, and score 33%\nbetter than standard Deep Q-learning which in turn proves the usefulness of the\ngame environment.\n",
"title": "Towards a Deep Reinforcement Learning Approach for Tower Line Wars"
}
| null | null | null | null | true | null |
1679
| null |
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| null | null |
null |
{
"abstract": " One of the primary questions when characterizing Earth-sized and\nsuper-Earth-sized exoplanets is whether they have a substantial atmosphere like\nEarth and Venus or a bare-rock surface like Mercury. Phase curves of the\nplanets in thermal emission provide clues to this question, because a\nsubstantial atmosphere would transport heat more efficiently than a bare-rock\nsurface. Analyzing phase curve photometric data around secondary eclipse has\npreviously been used to study energy transport in the atmospheres of hot\nJupiters. Here we use phase curve, Spitzer time-series photometry to study the\nthermal emission properties of the super-Earth exoplanet 55 Cancri e. We\nutilize a semi-analytical framework to fit a physical model to the infrared\nphotometric data at 4.5 micron. The model uses parameters of planetary\nproperties including Bond albedo, heat redistribution efficiency (i.e., ratio\nbetween radiative timescale and advective timescale of the atmosphere), and\natmospheric greenhouse factor. The phase curve of 55 Cancri e is dominated by\nthermal emission with an eastward-shifted hot spot. We determine the heat\nredistribution efficiency to be ~1.47, which implies that the advective\ntimescale is on the same order as the radiative timescale. This requirement\ncannot be met by the bare-rock planet scenario because heat transport by\ncurrents of molten lava would be too slow. The phase curve thus favors the\nscenario with a substantial atmosphere. Our constraints on the heat\nredistribution efficiency translate to an atmospheric pressure of ~1.4 bar. The\nSpitzer 4.5-micron band is thus a window into the deep atmosphere of the planet\n55 Cancri e.\n",
"title": "A Case for an Atmosphere on Super-Earth 55 Cancri e"
}
| null | null | null | null | true | null |
1680
| null |
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| null | null |
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{
"abstract": " With ever-increasing productivity targets in mining operations, there is a\ngrowing interest in mining automation. The PIMM project addresses the\nfundamental challenge of network communication by constructing a pilot 5G\nnetwork in the underground mine Kankberg. In this report, we discuss how such a\n5G network could constitute the essential infrastructure to organize existing\nsystems in Kankberg into a system-of-systems (SoS). In this report, we analyze\na scenario in which LiDAR equipped vehicles operating in the mine are connected\nto existing mine mapping and positioning solutions. The approach is motivated\nby the approaching era of remote controlled, or even autonomous, vehicles in\nmining operations. The proposed SoS could ensure continuously updated maps of\nKankberg, rendered in unprecedented detail, supporting both productivity and\nsafety in the underground mine. We present four different SoS solutions from an\norganizational point of view, discussing how development and operations of the\nconstituent systems could be distributed among Boliden and external\nstakeholders, e.g., the vehicle suppliers, the hauling company, and the\ndevelopers of the mapping software. The four scenarios are compared from both\ntechnical and business perspectives, and based on trade-off discussions and\nSWOT analyses. We conclude our report by recommending continued research along\ntwo future paths, namely a closer cooperation with the vehicle suppliers, and\nfurther feasibility studies regarding establishing a Kankberg software\necosystem.\n",
"title": "From LiDAR to Underground Maps via 5G - Business Models Enabling a System-of-Systems Approach to Mapping the Kankberg Mine"
}
| null | null | null | null | true | null |
1681
| null |
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| null | null |
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{
"abstract": " Laman graphs model planar frameworks that are rigid for a general choice of\ndistances between the vertices. There are finitely many ways, up to isometries,\nto realize a Laman graph in the plane. Such realizations can be seen as\nsolutions of systems of quadratic equations prescribing the distances between\npairs of points. Using ideas from algebraic and tropical geometry, we provide a\nrecursive formula for the number of complex solutions of such systems.\n",
"title": "The number of realizations of a Laman graph"
}
| null | null | null | null | true | null |
1682
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| null | null |
null |
{
"abstract": " We demonstrate an InAlN/GaN-on-Si HEMT based UV detector with photo to dark\ncurrent ratio > 107. Ti/Al/Ni/Au metal stack was evaporated and rapid thermal\nannealed for Ohmic contacts to the 2D electron gas (2DEG) at the InAlN/GaN\ninterface while the channel + barrier was recess etched to a depth of 20 nm to\npinch-off the 2DEG between Source-Drain pads. Spectral responsivity (SR) of 34\nA/W at 367 nm was measured at 5 V in conjunction with very high photo to dark\ncurrent ratio of > 10^7. The photo to dark current ratio at a fixed bias was\nfound to be decreasing with increase in recess length of the PD. The fabricated\ndevices were found to exhibit a UV-to-visible rejection ratio of >103 with a\nlow dark current < 32 pA at 5 V. Transient measurements showed rise and fall\ntimes in the range of 3-4 ms. The gain mechanism was investigated and carrier\nlifetimes were estimated which matched well with those reported elsewhere.\n",
"title": "UV Detector based on InAlN/GaN-on-Si HEMT Stack with Photo-to-Dark Current Ratio > 107"
}
| null | null | null | null | true | null |
1683
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{
"abstract": " This paper is the first attempt to learn the policy of an inquiry dialog\nsystem (IDS) by using deep reinforcement learning (DRL). Most IDS frameworks\nrepresent dialog states and dialog acts with logical formulae. In order to make\nlearning inquiry dialog policies more effective, we introduce a logical formula\nembedding framework based on a recursive neural network. The results of\nexperiments to evaluate the effect of 1) the DRL and 2) the logical formula\nembedding framework show that the combination of the two are as effective or\neven better than existing rule-based methods for inquiry dialog policies.\n",
"title": "Deep Reinforcement Learning for Inquiry Dialog Policies with Logical Formula Embeddings"
}
| null | null | null | null | true | null |
1684
| null |
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| null | null |
null |
{
"abstract": " The problem of Time's Arrow is rigorously solved in a certain microscopic\nsystem associated with a Hamiltonian using only information about the\nmicroscopic system. This microscopic system obeys an equation with time\nreversal symmetry. In detail, we prove that a symplectic map with time reversal\nsymmetry is an Anosov diffeomorphism. This result guarantees that any initial\ndensity function defined except for a zero volume set converges to the unique\ninvariant density (uniform distribution) in the sense of mixing. In addition,\nwe discover that there is a mathematical structure which connects Time's Arrow\n(Anosov diffeomorphism) with superdiffusion in our system. In particular, the\nmechanism of this superdiffusion in our system is different from those\npreviously found.\n",
"title": "Proof of Time's Arrow with Perfectly Chaotic Superdiffusion"
}
| null | null | null | null | true | null |
1685
| null |
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| null | null |
null |
{
"abstract": " Phone sensors could be useful in assessing changes in gait that occur with\nalcohol consumption. This study determined (1) feasibility of collecting\ngait-related data during drinking occasions in the natural environment, and (2)\nhow gait-related features measured by phone sensors relate to estimated blood\nalcohol concentration (eBAC). Ten young adult heavy drinkers were prompted to\ncomplete a 5-step gait task every hour from 8pm to 12am over four consecutive\nweekends. We collected 3-xis accelerometer, gyroscope, and magnetometer data\nfrom phone sensors, and computed 24 gait-related features using a sliding\nwindow technique. eBAC levels were calculated at each time point based on\nEcological Momentary Assessment (EMA) of alcohol use. We used an artificial\nneural network model to analyze associations between sensor features and eBACs\nin training (70% of the data) and validation and test (30% of the data)\ndatasets. We analyzed 128 data points where both eBAC and gait-related sensor\ndata was captured, either when not drinking (n=60), while eBAC was ascending\n(n=55) or eBAC was descending (n=13). 21 data points were captured at times\nwhen the eBAC was greater than the legal limit (0.08 mg/dl). Using a Bayesian\nregularized neural network, gait-related phone sensor features showed a high\ncorrelation with eBAC (Pearson's r > 0.9), and >95% of estimated eBAC would\nfall between -0.012 and +0.012 of actual eBAC. It is feasible to collect\ngait-related data from smartphone sensors during drinking occasions in the\nnatural environment. Sensor-based features can be used to infer gait changes\nassociated with elevated blood alcohol content.\n",
"title": "Using Phone Sensors and an Artificial Neural Network to Detect Gait Changes During Drinking Episodes in the Natural Environment"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
1686
| null |
Validated
| null | null |
null |
{
"abstract": " In view of recent intense experimental and theoretical interests in the\nbiophysics of liquid-liquid phase separation (LLPS) of intrinsically disordered\nproteins (IDPs), heteropolymer models with chain molecules configured as\nself-avoiding walks on the simple cubic lattice are constructed to study how\nphase behaviors depend on the sequence of monomers along the chains. To address\npertinent general principles, we focus primarily on two fully charged\n50-monomer sequences with significantly different charge patterns. Each monomer\nin our models occupies a single lattice site and all monomers interact via a\nscreened pairwise Coulomb potential. Phase diagrams are obtained by extensive\nMonte Carlo sampling performed at multiple temperatures on ensembles of 300\nchains in boxes of sizes ranging from $52\\times 52\\times 52$ to $246\\times\n246\\times 246$ to simulate a large number of different systems with the overall\npolymer volume fraction $\\phi$ in each system varying from $0.001$ to $0.1$.\nPhase separation in the model systems is characterized by the emergence of a\nlarge cluster connected by inter-monomer nearest-neighbor lattice contacts and\nby large fluctuations in local polymer density. The simulated critical\ntemperatures, $T_{\\rm cr}$, of phase separation for the two sequences differ\nsignificantly, whereby the sequence with a more \"blocky\" charge pattern\nexhibits a substantially higher propensity to phase separate. The trend is\nconsistent with our sequence-specific random-phase-approximation (RPA) polymer\ntheory, but the variation of the simulated $T_{\\rm cr}$ with a previously\nproposed \"sequence charge decoration\" pattern parameter is milder than that\npredicted by RPA. Ramifications of our findings for the development of\nanalytical theory and simulation protocols of IDP LLPS are discussed.\n",
"title": "A Lattice Model of Charge-Pattern-Dependent Polyampholyte Phase Separation"
}
| null | null | null | null | true | null |
1687
| null |
Default
| null | null |
null |
{
"abstract": " When measuring quadratic values representative of random fluctuations, such\nas the thermal noise of Atomic Force Microscopy (AFM) cantilevers, the\nbackground measurement noise cannot be averaged to zero. We present a signal\nprocessing method that allows to get rid of this limitation using the\nubiquitous optical beam deflection sensor of standard AFMs. We demonstrate a\ntwo orders of magnitude enhancement of the signal to noise ratio in our\nexperiment, allowing the calibration of stiff cantilevers or easy\nidentification of higher order modes from thermal noise measurements.\n",
"title": "\"Noiseless\" thermal noise measurement of atomic force microscopy cantilevers"
}
| null | null | null | null | true | null |
1688
| null |
Default
| null | null |
null |
{
"abstract": " How does our motor system solve the problem of anticipatory control in spite\nof a wide spectrum of response dynamics from different musculo-skeletal\nsystems, transport delays as well as response latencies throughout the central\nnervous system? To a great extent, our highly-skilled motor responses are a\nresult of a reactive feedback system, originating in the brain-stem and spinal\ncord, combined with a feed-forward anticipatory system, that is adaptively\nfine-tuned by sensory experience and originates in the cerebellum. Based on\nthat interaction we design the counterfactual predictive control (CFPC)\narchitecture, an anticipatory adaptive motor control scheme in which a\nfeed-forward module, based on the cerebellum, steers an error feedback\ncontroller with counterfactual error signals. Those are signals that trigger\nreactions as actual errors would, but that do not code for any current or\nforthcoming errors. In order to determine the optimal learning strategy, we\nderive a novel learning rule for the feed-forward module that involves an\neligibility trace and operates at the synaptic level. In particular, our\neligibility trace provides a mechanism beyond co-incidence detection in that it\nconvolves a history of prior synaptic inputs with error signals. In the context\nof cerebellar physiology, this solution implies that Purkinje cell synapses\nshould generate eligibility traces using a forward model of the system being\ncontrolled. From an engineering perspective, CFPC provides a general-purpose\nanticipatory control architecture equipped with a learning rule that exploits\nthe full dynamics of the closed-loop system.\n",
"title": "A Forward Model at Purkinje Cell Synapses Facilitates Cerebellar Anticipatory Control"
}
| null | null | null | null | true | null |
1689
| null |
Default
| null | null |
null |
{
"abstract": " Oeljeklaus-Toma (OT) manifolds are complex non-Kähler manifolds whose\nconstruction arises from specific number fields. In this note, we compute their\nde Rham cohomology in terms of invariants associated to the background number\nfield. This is done by two distinct approaches, one using invariant cohomology\nand the other one using the Leray-Serre spectral sequence. In addition, we\ncompute also their Morse-Novikov cohomology. As an application, we show that\nthe low degree Chern classes of any complex vector bundle on an OT manifold\nvanish in the real cohomology. Other applications concern the OT manifolds\nadmitting locally conformally Kähler (LCK) metrics: we show that there is\nonly one possible Lee class of an LCK metric, and we determine all the possible\nMorse-Novikov classes of an LCK metric, which implies the nondegeneracy of\ncertain Lefschetz maps in cohomology.\n",
"title": "De Rham and twisted cohomology of Oeljeklaus-Toma manifolds"
}
| null | null | null | null | true | null |
1690
| null |
Default
| null | null |
null |
{
"abstract": " We investigate different strategies for active learning with Bayesian deep\nneural networks. We focus our analysis on scenarios where new, unlabeled data\nis obtained episodically, such as commonly encountered in mobile robotics\napplications. An evaluation of different strategies for acquisition, updating,\nand final training on the CIFAR-10 dataset shows that incremental network\nupdates with final training on the accumulated acquisition set are essential\nfor best performance, while limiting the amount of required human labeling\nlabor.\n",
"title": "Episode-Based Active Learning with Bayesian Neural Networks"
}
| null | null | null | null | true | null |
1691
| null |
Default
| null | null |
null |
{
"abstract": " We study a possible connection between different non-thermal emissions from\nthe inner few parsecs of the Galaxy. We analyze the origin of the gamma-ray\nsource 2FGL J1745.6-2858 (or 3FGL J1745.6-2859c) in the Galactic Center and the\ndiffuse hard X-ray component recently found by NuSTAR, as well as the radio\nemission and processes of hydrogen ionization from this area. We assume that a\nsource in the GC injected energetic particles with power-law spectrum into the\nsurrounding medium in the past or continues to inject until now. The energetic\nparticles may be protons, electrons or a combination of both. These particles\ndiffuse to the surrounding medium and interact with gas, magnetic field and\nbackground photons to produce non-thermal emissions. We study the spectral and\nspatial features of the hard X-ray emission and gamma-ray emission by the\nparticles from the central source. Our goal is to examine whether the hard\nX-ray and gamma-ray emissions have a common origin. Our estimations show that\nin the case of pure hadronic models the expected flux of hard X-ray emission is\ntoo low. Despite protons can produce a non-zero contribution in gamma-ray\nemission, it is unlikely that they and their secondary electrons can make a\nsignificant contribution in hard X-ray flux. In the case of pure leptonic\nmodels it is possible to reproduce both X-ray and gamma-ray emissions for both\ntransient and continuous supply models. However, in the case of continuous\nsupply model the ionization rate of molecular hydrogen may significantly exceed\nthe observed value.\n",
"title": "Origin of X-ray and gamma-ray emission from the Galactic central region"
}
| null | null |
[
"Physics"
] | null | true | null |
1692
| null |
Validated
| null | null |
null |
{
"abstract": " We show that the partial transposes of complex Wishart random matrices are\nasymptotically free. We also investigate regimes where the number of blocks is\nfixed but the size of the blocks increases. This gives a example where the\npartial transpose produces freeness at the operator level. Finally we\ninvestigate the case of real Wishart matrices.\n",
"title": "Freeness and The Partial Transposes of Wishart Random Matrices"
}
| null | null | null | null | true | null |
1693
| null |
Default
| null | null |
null |
{
"abstract": " The technique for constructing conformally invariant theories within the\ncoset space construction is developed. It reproduces all consequences of the\nconformal invariance and Lagrangians of widely-known conformal field theories.\nThe method of induced representations, which plays the key role in the\nconstruction, allows to reveal a special role of the \"Nambu-Goldstone fields\"\nfor special conformal transformations. Namely, their dependence on the\ncoordinates turns out to be fixed by the symmetries. This results in the\nappearance of the constraints on possible forms of Lagrangians, which ensure\nthat discrete symmetries are indeed symmetries of the theory.\n",
"title": "Coset space construction for the conformal group. I. Unbroken phase"
}
| null | null | null | null | true | null |
1694
| null |
Default
| null | null |
null |
{
"abstract": " A well-known result says that the Euclidean unit ball is the unique fixed\npoint of the polarity operator. This result implies that if, in $\\mathbb{R}^n$,\nthe unit ball of some norm is equal to the unit ball of the dual norm, then the\nnorm must be Euclidean. Motivated by these results and by relatively recent\nresults in convex analysis and convex geometry regarding various properties of\norder reversing operators, we consider, in a real Hilbert space setting, a more\ngeneral fixed point equation in which the polarity operator is composed with a\ncontinuous invertible linear operator. We show that if the linear operator is\npositive definite, then the considered equation is uniquely solvable by an\nellipsoid. Otherwise, the equation can have several (possibly infinitely many)\nsolutions or no solution at all. Our analysis yields a few by-products of\npossible independent interest, among them results related to coercive bilinear\nforms (essentially a quantitative convex analytic converse to the celebrated\nLax-Milgram theorem from partial differential equations) and a characterization\nof real Hilbertian spaces.\n",
"title": "Fixed points of polarity type operators"
}
| null | null | null | null | true | null |
1695
| null |
Default
| null | null |
null |
{
"abstract": " Multiple imputation (MI) inference handles missing data by first properly\nimputing the missing values $m$ times, and then combining the $m$ analysis\nresults from applying a complete-data procedure to each of the completed\ndatasets. However, the existing method for combining likelihood ratio tests has\nmultiple defects: (i) the combined test statistic can be negative in practice\nwhen the reference null distribution is a standard $F$ distribution; (ii) it is\nnot invariant to re-parametrization; (iii) it fails to ensure monotonic power\ndue to its use of an inconsistent estimator of the fraction of missing\ninformation (FMI) under the alternative hypothesis; and (iv) it requires\nnon-trivial access to the likelihood ratio test statistic as a function of\nestimated parameters instead of datasets. This paper shows, via both\ntheoretical derivations and empirical investigations, that essentially all of\nthese problems can be straightforwardly addressed if we are willing to perform\nan additional likelihood ratio test by stacking the $m$ completed datasets as\none big completed dataset. A particularly intriguing finding is that the FMI\nitself can be estimated consistently by a likelihood ratio statistic for\ntesting whether the $m$ completed datasets produced by MI can be regarded\neffectively as samples coming from a common model. Practical guidelines are\nprovided based on an extensive comparison of existing MI tests.\n",
"title": "Multiple Improvements of Multiple Imputation Likelihood Ratio Tests"
}
| null | null | null | null | true | null |
1696
| null |
Default
| null | null |
null |
{
"abstract": " Given samples from a distribution, how many new elements should we expect to\nfind if we continue sampling this distribution? This is an important and\nactively studied problem, with many applications ranging from unseen species\nestimation to genomics. We generalize this extrapolation and related unseen\nestimation problems to the multiple population setting, where population $j$\nhas an unknown distribution $D_j$ from which we observe $n_j$ samples. We\nderive an optimal estimator for the total number of elements we expect to find\namong new samples across the populations. Surprisingly, we prove that our\nestimator's accuracy is independent of the number of populations. We also\ndevelop an efficient optimization algorithm to solve the more general problem\nof estimating multi-population frequency distributions. We validate our methods\nand theory through extensive experiments. Finally, on a real dataset of human\ngenomes across multiple ancestries, we demonstrate how our approach for unseen\nestimation can enable cohort designs that can discover interesting mutations\nwith greater efficiency.\n",
"title": "Estimating the unseen from multiple populations"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
1697
| null |
Validated
| null | null |
null |
{
"abstract": " We construct new continued fraction expansions of Jacobi-type J-fractions in\n$z$ whose power series expansions generate the ratio of the $q$-Pochhamer\nsymbols, $(a; q)_n / (b; q)_n$, for all integers $n \\geq 0$ and where $a,b,q\n\\in \\mathbb{C}$ are non-zero and defined such that $|q| < 1$ and $|b/a| < |z| <\n1$. If we set the parameters $(a, b) := (q, q^2)$ in these generalized series\nexpansions, then we have a corresponding J-fraction enumerating the sequence of\nterms $(1-q) / (1-q^{n+1})$ over all integers $n \\geq 0$. Thus we are able to\ndefine new $q$-series expansions which correspond to the Lambert series\ngenerating the divisor function, $d(n)$, when we set $z \\mapsto q$ in our new\nJ-fraction expansions. By repeated differentiation with respect to $z$, we also\nuse these generating functions to formulate new $q$-series expansions of the\ngenerating functions for the sums-of-divisors functions, $\\sigma_{\\alpha}(n)$,\nwhen $\\alpha \\in \\mathbb{Z}^{+}$. To expand the new $q$-series generating\nfunctions for these special arithmetic functions we define a generalized\nclasses of so-termed Stirling-number-like \"$q$-coefficients\", or Stirling\n$q$-coefficients, whose properties, relations to elementary symmetric\npolynomials, and relations to the convergents to our infinite J-fractions are\nalso explored within the results proved in the article.\n",
"title": "Continued Fractions and $q$-Series Generating Functions for the Generalized Sum-of-Divisors Functions"
}
| null | null |
[
"Mathematics"
] | null | true | null |
1698
| null |
Validated
| null | null |
null |
{
"abstract": " The convolution of galaxy images by the point-spread function (PSF) is the\ndominant source of bias for weak gravitational lensing studies, and an accurate\nestimate of the PSF is required to obtain unbiased shape measurements. The PSF\nestimate for a galaxy depends on its spectral energy distribution (SED),\nbecause the instrumental PSF is generally a function of the wavelength. In this\npaper we explore various approaches to determine the resulting `effective' PSF\nusing broad-band data. Considering the Euclid mission as a reference, we find\nthat standard SED template fitting methods result in biases that depend on\nsource redshift, although this may be remedied if the algorithms can be\noptimised for this purpose. Using a machine-learning algorithm we show that, at\nleast in principle, the required accuracy can be achieved with the current\nsurvey parameters. It is also possible to account for the correlations between\nphotometric redshift and PSF estimates that arise from the use of the same\nphotometry. We explore the impact of errors in photometric calibration, errors\nin the assumed wavelength dependence of the PSF model and limitations of the\nadopted template libraries. Our results indicate that the required accuracy for\nEuclid can be achieved using the data that are planned to determine photometric\nredshifts.\n",
"title": "Implications of a wavelength dependent PSF for weak lensing measurements"
}
| null | null | null | null | true | null |
1699
| null |
Default
| null | null |
null |
{
"abstract": " Given a traveling salesman problem (TSP) tour $H$ in graph $G$ a $k$-move is\nan operation which removes $k$ edges from $H$, and adds $k$ edges of $G$ so\nthat a new tour $H'$ is formed. The popular $k$-OPT heuristics for TSP finds a\nlocal optimum by starting from an arbitrary tour $H$ and then improving it by a\nsequence of $k$-moves.\nUntil 2016, the only known algorithm to find an improving $k$-move for a\ngiven tour was the naive solution in time $O(n^k)$. At ICALP'16 de Berg,\nBuchin, Jansen and Woeginger showed an $O(n^{\\lfloor 2/3k \\rfloor+1})$-time\nalgorithm.\nWe show an algorithm which runs in $O(n^{(1/4+\\epsilon_k)k})$ time, where\n$\\lim \\epsilon_k = 0$. We are able to show that it improves over the state of\nthe art for every $k=5,\\ldots,10$. For the most practically relevant case $k=5$\nwe provide a slightly refined algorithm running in $O(n^{3.4})$ time. We also\nshow that for the $k=4$ case, improving over the $O(n^3)$-time algorithm of de\nBerg et al. would be a major breakthrough: an $O(n^{3-\\epsilon})$-time\nalgorithm for any $\\epsilon>0$ would imply an $O(n^{3-\\delta})$-time algorithm\nfor the ALL PAIRS SHORTEST PATHS problem, for some $\\delta>0$.\n",
"title": "Improving TSP tours using dynamic programming over tree decomposition"
}
| null | null | null | null | true | null |
1700
| null |
Default
| null | null |
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