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We consider the statistical deconvolution problem where one observes $n$ replications from the model $Y=X+\epsilon$, where $X$ is the unobserved random signal of interest and $\epsilon$ is an independent random error with distribution $\phi$. Under weak assumptions on the decay of the Fourier transform of $\phi,$ we derive upper bounds for the finite-sample sup-norm risk of wavelet deconvolution density estimators $f_n$ for the density $f$ of $X$, where $f:\mathbb{R}\to \mathbb{R}$ is assumed to be bounded. We then derive lower bounds for the minimax sup-norm risk over Besov balls in this estimation problem and show that wavelet deconvolution density estimators attain these bounds. We further show that linear estimators adapt to the unknown smoothness of $f$ if the Fourier transform of $\phi$ decays exponentially and that a corresponding result holds true for the hard thresholding wavelet estimator if $\phi$ decays polynomially. We also analyze the case where $f$ is a "supersmooth"/analytic density. We finally show how our results and recent techniques from Rademacher processes can be applied to construct global confidence bands for the density $f$. | Global uniform risk bounds for wavelet deconvolution estimators |
With the sphere $\mathbb{S}^2 \subset \mathbb{R}^3$ as a conductor holding a unit charge with logarithmic interactions, we consider the problem of determining the support of the equilibrium measure in the presence of an external field consisting of finitely many point charges on the surface of the sphere. We determine that for any such configuration, the complement of the equilibrium support is the stereographic preimage from the plane of a union of classical quadrature domains, whose orders sum to the number of point charges. | Logarithmic Equilibrium on the Sphere in the Presence of Multiple Point Charges |
In this paper we developed approach based on the BFKL evolution in $\ln\Lb Q^2\Rb$. We show that the simplest diffusion approximation with running QCD coupling is able to describe the HERA experimental data on the deep inelastic structure function with good $\chi^2/d.o.f. \approx 1.3$. From our description of the experimental data we learned several lessons; (i) the non-perturbative physics at long distances started to show up at $Q^2 = 0.25\,GeV^2$; (ii) the scattering amplitude at $Q^2 = 0.25\,GeV^2$ cannot be written as sum of soft Pomeron and the secondary Reggeon but the Pomeron interactions should be taken into account; (iii) the Pomeron interactions can be reduced to the enhanced diagrams and, therefore, we do not see any needs for the shadowing corrections at HERA energies; and (iv) we demonstrated that the shadowing correction could be sizable at higher than HERA energies without any contradiction with our initial conditions. | BFKL equation with running QCD coupling and HERA data |
We have used Simple Denoising Algorithm using Wavelet Transform on the daily Forbush decrease data from the year 1967 to 2003. For this data we observe periodicity around 5-6, 11, 13, 15 and 24 years. For all the obtained peaks corresponding confidence levels are higher than 95%. We observe that the periodicity of around 5-6 years is common to solar flare data, major proton event data and solar neutrino flux data. Because of that common periodicity, it is suggested that Forbush decrease with the solar flare data and major solar proton event data together with solar neutrino flux variations, behave similarly and may have a common origin. | Time Variations of the Forbush Decrease Data |
We introduce the biharmonic Steklov problem on differential forms by considering suitable boundary conditions. We characterize its smallest eigenvalue and prove elementary properties of the spectrum. We obtain various estimates for the first eigenvalue, some of which involve eigenvalues of other problems such as the Dirichlet, Neumann, Robin and Steklov ones. Independently, new inequalities relating the eigenvalues of the latter problems are proved. | Biharmonic Steklov operator on differential forms |
Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been -- so far -- no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies. Specifications of PEtab, the PEtab Python library, as well as links to examples, and all supporting software tools are available at https://github.com/PEtab-dev/PEtab, a snapshot is available at https://doi.org/10.5281/zenodo.3732958. All original content is available under permissive licenses. | PEtab -- interoperable specification of parameter estimation problems in systems biology |
We extensively develop an algorithm of implementing the Hartree-Fock-Bogolyubov calculations, in which the Gaussian expansion method is employed. This algorithm is advantageous in describing the energy-dependent exponential and oscillatory asymptotics of the quasiparticle wave functions at large $r$, and in handling various effective interactions including those with finite ranges. We apply the present method to the oxygen isotopes with the Gogny interaction, keeping the spherical symmetry. In respect to the new magic numbers, effects of the pair correlation on the N=16 and 32 nuclei are investigated. | Hartree-Fock-Bogolyubov calculations with Gaussian expansion method |
We study relativistic corrections in exclusive $S$-wave charmonium decays into proton-antiproton final state. We calculate the NRQCD corrections to the dominant decay amplitude, which depend on the nucleon twist-3 light-cone distribution amplitudes only. It is shown that in this case the collinear factorisation is also valid beyond the leading-order approximation. Our numerical estimates show that relativistic correction of relative order $v^2$ provides large numerical impact. | A study of relativistic corrections to $ J/\psi\rightarrow p\bar{p}$ decay |
(abridged) As the favoured progenitors of long-duration gamma-ray bursts, massive stars may represent our best signposts of individual objects in the early Universe, but special conditions seem required to make these bursters, which might originate from the progenitor's rapid rotation and associated asymmetry. To obtain empirical constraints on the interplay between stellar rotation and wind asymmetry, we perform linear Halpha spectropolarimetry on a sample of 18 spectroscopically peculiar massive O stars, including OVz, Of?p, Oe, and Onfp stars, supplemented by an earlier sample of 20 O supergiants. Despite their rapid rotation (with vsin(i) up to 400 km/s) most O-type stars are found to be spherically symmetric, but with notable exceptions amongst specific object classes. We divide the peculiar O stars into four distinct categories: Groups III and IV include the Oe stars and Onfp stars, which are on the high-end tail of the O star rotation distribution and have in the past been claimed to be embedded in disks. Here we report the detection of a classical depolarization ``line effect'' in the Oe star HD 45314, but the overall incidence of line effects amongst Oe stars is significantly lower (1 out of 6) than amongst Be stars. The chance that the Oe and Be datasets are drawn from the same parent population is negligible (with 95% confidence). This implies there is as yet no evidence for a disk hypothesis in Oe stars, providing relevant constraints on the physical mechanism that is responsible for the Be phenomenon. Finally, we find that 3 out of 4 of the group IV Onfp stars show evidence for complex polarization effects, which are likely related to rapid rotation, and we speculate on the evolutionary links to B[e] stars. | On the presence and absence of disks around O-type stars |
Various soliton-obstruction systems have been studied from analytical perspective. We have used collective coordinate to approach the dynamics of solitons as they meet a potential obstruction in a form of square barriers and holes for three models in (1+1) dimensions, namely: $\lambda\phi^{4}$ model, deformed Sine-Gordon model, and a model that give rise to Q-ball solution. We have shown that our approximated field solution is valid enough to describe the behaviour of solitons scattering off a potential obstruction. | Collective Coordinate Approach to the Dynamics of Various Soliton-Obstruction Systems |
Cosmic microwave background (CMB) experiments that constrain the tensor-to-scalar ratio $r$ are now approaching the sensitivity at which delensing---removing the $B$ modes induced by the gravitational lensing of large-scale structure---is necessary. We consider the improvement in delensing that maps of large-scale structure from tomographic line intensity mapping (IM) experiments targeting $2 < z < 10$ could provide. Compared to a nominal baseline of cosmic infrared background and internal delensing at CMB-S4 sensitivity, we find that the addition of high-redshift IM data could improve delensing performance by ~11%. Achieving the requisite sensitivity in the IM data is feasible with next-generation experiments that are now being planned. However, these results are contingent on the ability to measure low-$k$ modes along the line of sight. Without these modes, IM datasets are unable to to correlate with the lensing kernel and do not aid in delensing. | Delensing Degree-Scale $B$-Mode Polarization with High-Redshift Line Intensity Mapping |
We present a novel AI approach for high-resolution high-dynamic range synthesis imaging by radio interferometry (RI) in astronomy. R2D2, standing for "{R}esidual-to-{R}esidual {D}NN series for high-{D}ynamic range imaging", is a model-based data-driven approach relying on hybrid deep neural networks (DNNs) and data-consistency updates. Its reconstruction is built as a series of residual images estimated as the outputs of DNNs, each taking the residual dirty image of the previous iteration as an input. The approach can be interpreted as a learned version of a matching pursuit approach, whereby model components are iteratively identified from residual dirty images, and of which CLEAN is a well-known example. We propose two variants of the R2D2 model, built upon two distinctive DNN architectures: a standard U-Net, and a novel unrolled architecture. We demonstrate their use for monochromatic intensity imaging on highly-sensitive observations of the radio galaxy Cygnus~A at S band, from the Very Large Array (VLA). R2D2 is validated against CLEAN and the recent RI algorithms AIRI and uSARA, which respectively inject a learned implicit regularization and an advanced handcrafted sparsity-based regularization into the RI data. With only few terms in its series, the R2D2 model is able to deliver high-precision imaging, significantly superior to CLEAN and matching the precision of AIRI and uSARA. In terms of computational efficiency, R2D2 runs at a fraction of the cost of AIRI and uSARA, and is also faster than CLEAN, opening the door to real-time precision imaging in RI. | R2D2: Deep neural network series for near real-time high-dynamic range imaging in radio astronomy |
We report in this paper spectroscopic and photometric analysis of eight massive stars observed during Campaign 8 of the Kepler/K2 mission from January to March 2016. Spectroscopic data were obtained on these stars at OPD/LNA, Brazil, and their stellar parameters determined using SME. Periodic analyses of the light curves were performed through CLEANEST and PERIOD04 algorithms. Mass, luminosity, and radius of our stars were estimated employing CESAM+POSC grids. Three of our stars show significant periodicity. K2 ID 220679442 and K2 ID 220532854 have periods linked to the stellar rotation. K2 ID 220532854 has prominent silicon lines (Si II 4128-4131), a characteristic presented in the peculiar class of Ap magnetic main sequence stars. However, in our spectral analysis, this object was found to be an evolved, luminous giant star. K2 ID 220466722 was revealed to be a $\delta$ Scuti variable, and 40 individual frequencies were determined for this star. No significant periodicity was found in the light curves for the remaining stars analyzed in this work, besides the instrumental one. | Photometry and spectroscopy of massive stars observed during K2 Campaign 8 |
Video relevance prediction is one of the most important tasks for online streaming service. Given the relevance of videos and viewer feedbacks, the system can provide personalized recommendations, which will help the user discover more content of interest. In most online service, the computation of video relevance table is based on users' implicit feedback, e.g. watch and search history. However, this kind of method performs poorly for "cold-start" problems - when a new video is added to the library, the recommendation system needs to bootstrap the video relevance score with very little user behavior known. One promising approach to solve it is analyzing video content itself, i.e. predicting video relevance by video frame, audio, subtitle and metadata. In this paper, we describe a challenge on Content-based Video Relevance Prediction (CBVRP) that is hosted by Hulu in the ACM Multimedia Conference 2018. In this challenge, Hulu drives the study on an open problem of exploiting content characteristics directly from original video for video relevance prediction. We provide massive video assets and ground truth relevance derived from our really system, to build up a common platform for algorithm development and performance evaluation. | Content-based Video Relevance Prediction Challenge: Data, Protocol, and Baseline |
Bovine tuberculosis, a disease that affects cattle and badgers in Ireland, was studied via stochastic epidemic modeling using incidence data from the Four Area Project (Griffin et al., 2005). The Four Area Project was a large scale field trial conducted in four diverse farming regions of Ireland over a five-year period (1997-2002) to evaluate the impact of badger culling on bovine tuberculosis incidence in cattle herds. Based on the comparison of several models, the model with no between-herd transmission and badger-to-herd transmission proportional to the total number of infected badgers culled was best supported by the data. Detailed model validation was conducted via model prediction, identifiability checks and sensitivity analysis. The results suggest that badger-to-cattle transmission is of more importance than between-herd transmission and that if there was no badger-to-herd transmission, levels of bovine tuberculosis in cattle herds in Ireland could decrease considerably. | Epidemic modelling of bovine tuberculosis in cattle herds and badgers in Ireland |
Topological insulators display unusual light-matter interactions due to the helical nature of surface electronic states. We study the near-field interaction of light propagating in an optical fiber with crystals of Sb2Te3, a 3D topological insulator (TI), and observe a large apparent Faraday rotation. The origin of this unexpected polarization rotation in the optical fiber is attributed to a magneto-optical Kerr effect at the TI-fiber interface. We show that the combined effects of time-reversal symmetry breaking, which arises from Zeeman coupling of the electromagnetic field with the surface electrons of the TI, and inversion symmetry breaking of optical excitations, which arises from the exponential decay of the evanescent light across the TI crystal, are central to realizing this giant polarization rotation. Our work demonstrates a facile approach for realizing large magneto-optical effects without any magnetic fields by exploiting the unique physics of light-matter interactions at TI surfaces. | Realizing Giant Magneto-Optical Effects in 3D Topological Insulators Without Magnetic Fields |
The study of substructure in the stellar halo of the Milky Way has made a lot of progress in recent years, especially with the advent of surveys like the Sloan Digital Sky Survey. Here, we study the newly discovered tidal tails of the Galactic globular cluster NGC 5466. By means of numerical simulations, we reproduce the shape, direction and surface density of the tidal tails, as well as the structural and kinematical properties of the present-day NGC 5466. Although its tails are very extended in SDSS data (> 45 degrees), NGC 5466 is only losing mass slowly at the present epoch and so can survive for probably a further Hubble time. The effects of tides at perigalacticon and disc crossing are the dominant causes of the slow dissolution of NGC 5466, accounting for about 60 % of the mass loss over the course of its evolution. The morphology of the tails provides a constraint on the proper motion -- the observationally determined proper motion has to be refined (within the stated error margins) to match the location of the tidal tails. | The Tidal Tails of NGC 5466 |
We illustrate in terms familiar to modern day science students that: (i) an uncertainty slope mechanism underlies the usefulness of temperature via its reciprocal, which is incidentally around 42 [nats/eV] at the freezing point of water; (ii) energy over kT and differential heat capacity are ``multiplicity exponents'', i.e. the bits of state information lost to the environment outside a system per 2-fold increase in energy and temperature respectively; (iii) even awaiting description of ``the dice'', gambling theory gives form to the laws of thermodynamics, availability minimization, and net surprisals for measuring finite distances from equilibrium, information content differences, and complexity; (iv) heat and information engine properties underlie the biological distinction between autotrophs and heterotrophs, and life's ongoing symbioses between steady-state excitations and replicable codes; and (v) mutual information resources (i.e. correlations between structures e.g. a phenomenon and its explanation, or an organism and its niche) within and across six boundary types (ranging from the edges of molecules to the gap between cultures) are delocalized physical structures whose development is a big part of the natural history of invention. These tools might offer a physical framework to students of the code-based sciences when considering such disparate (and sometimes competing) issues as conservation of available work and the nurturing of genetic or memetic diversity. | Information physics: From energy to codes |
We analyzed the spectroscopic data from the PN and the MOS cameras in the 0.4-10 keV band. We also used an archival BeppoSAX 1-50 keV observation of IRAS 09104+4109 to investigate possible variations of the quasar emission. The X-ray emission in the EPIC band is dominated by the intra-cluster medium thermal emission. We found that the quasar contributes ~35% of the total flux in the 2-10 keV band. Both a transmission- (through a Compton-thin absorber with a Compton optical depth of \tau_C~0.3, i.e. Nh~5 x 10^{23} cm^-2) and a reflection-dominated (\tau_C>1) model provide an excellent fit to the quasar continuum emission. However, the value measured for the EW of Fe Kalpha emission line is only marginally consistent with the presence of a Compton-thick absorber in a reflection-dominated scenario, which had been suggested by a previous, marginal (i.e. 2.5\sigma) detection with the hard X-ray (15-50 keV), non-imaging BeppoSAX/PDS instrument. Moreover, the value of luminosity in the 2-10 keV band measured by the transmission-dominated model is fully consistent with that expected on the basis of the bolometric luminosity of IRAS 09104+4109. From the analysis of the XMM-Newton data we therefore suggest the possibility that the absorber along the line of sight to the nucleus of IRAS 09104+4109 is Compton-thin. Alternatively, the absorber column density could have changed from Compton-thick to -thin in the five years elapsed between the observations. If this is the case, then IRAS 09104+4109 is the first 'changing-look' quasar ever detected. | The XMM-Newton view of IRAS 09104+4109: evidence for a changing-look Type 2 quasar? |
We present a method of forming and controlling large arrays of gate-defined quantum devices. The method uses a novel, on-chip, multiplexed charge-locking system and helps to overcome the restraints imposed by the number of wires available in cryostat measurement systems. Two device innovations are introduced. Firstly, a multiplexer design which utilises split gates to allow the multiplexer to divide three or more ways at each branch. Secondly we describe a device architecture that utilises a multiplexer-type scheme to lock charge onto gate electrodes. The design allows access to and control of gates whose total number exceeds that of the available electrical contacts and enables the formation, modulation and measurement of large arrays of quantum devices. We fabricate devices utilising these innovations on n-type GaAs/AlGaAs substrates and investigate the stability of the charge locked on to the gates. Proof-of-concept is shown by measurement of the Coulomb blockade peaks of a single quantum dot formed by a floating gate in the device. The floating gate is seen to drift by approximately one Coulomb oscillation per hour. | Multiplexed Charge-locking Device for Large Arrays of Quantum Devices |
In this paper, we address the issue of automatic tracking areas (TAs) planning in fifth generation (5G) ultra-dense networks (UDNs). By invoking handover (HO) attempts and measurement reports (MRs) statistics of a 4G live network, we first introduce a new kernel function mapping HO attempts, MRs and inter-site distances (ISDs) into the so-called similarity weight. The corresponding matrix is then fed to a self-tuning spectral clustering (STSC) algorithm to automatically define the TAs number and borders. After evaluating its performance in terms of the $Q$-metric as well as the silhouette score for various kernel parameters, we show that the clustering scheme yields a significant reduction of tracking area updates and average paging requests per TA; optimizing thereby network resources. | Self-Tuning Spectral Clustering for Adaptive Tracking Areas Design in 5G Ultra-Dense Networks |
We explore the possible formation of ordered phases in neutron star matter. In the framework of a quantum hadrodynamics model where neutrons, protons and Lambda hyperons interact via the exchange of mesons, we compare the energy of the usually assumed uniform, liquid phase, to that of a configuration in which di-lambda pairs immersed in an uniform nucleon fluid are localized on the nodes of a regular lattice. The confining potential is calculated self-consistently as resulting from the combined action of the nucleon fluid and the other hyperons, under the condition of beta equilibrium. We are able to obtain stable ordered phases for some reasonable sets of values of the model parameters. This could have important consequences on the structure and cooling of neutron stars. | Hyperon ordering in neutron star matter |
We present a simulation protocol that allows for efficient sampling of the degrees of freedom of a solute in explicit solvent. The protocol involves using a non-equilibrium umbrella sampling method, in this case the recently developed adaptively biased molecular dynamics method, to compute an approximate free energy for the slow modes of the solute in explicit solvent. This approximate free energy is then used to set up a Hamiltonian replica exchange scheme that samples both from biased and unbiased distributions. The final accurate free energy is recovered via the WHAM technique applied to all the replicas, and equilibrium properties of the solute are computed from the unbiased trajectory. We illustrate the approach by applying it to the study of the puckering landscapes of the methyl glycosides of $\alpha$-L-iduronic acid and its C5 epimer $\beta$-D-glucuronic acid in water. Big savings in computational resources are gained in comparison to the standard parallel tempering method. | Conformational free energies of methyl-$\alpha$-L-iduronic and methyl-$\beta$-D-glucuronic acids in water |
This paper reviews a recent non-Landau-Ginzburg-Wilson (LGW) approach to superfluid to Mott insulator transitions in two dimensional bosonic lattice systems, using a dual vortex field theory (cond-mat/0408329). The physical interpretation of conventional LGW theory of quantum criticality is re-examined and similarities and differences with the vortex picture are discussed. The ``unification'' of various competing (insulating) orders, and the coincidence of these orders with the Mott transition are readily understood in this formulation. Some aspects of the recent theory of ``deconfined'' quantum criticality, which are to an extent subsumed in this approach, are discussed. A pedagogical presentation of the ``nuts and bolts'' of boson-vortex duality at the hamiltonian level is included, tailored to a condensed matter audience. | Competing Orders and non-Landau-Ginzburg-Wilson Criticality in (Bose) Mott transitions |
Predicting the trajectory of stochastic dynamical systems (SDSs) is an intriguing problem in numerous fields, where characterizing the predictability of SDSs is of fundamental importance. Prior works have tackled this issue by indirectly investigating the uncertainty of distribution in each prediction. How accurately the trajectory of SDSs can be directly predicted still remains open. This paper proposes a new metric, namely predictability exponent, to characterize the decaying rate of probability that the prediction error never exceeds arbitrary $\epsilon$. To evaluate predictability exponent, we begin with providing a complete framework for model-known cases. Then, we bring to light the explicit relationship between predictability exponent and entropy by discrete approximation techniques. The definition and evaluation on predictability exponent are further extended to model-unknown cases by optimizing over model spaces, which build a bridge between the accuracy of trajectory predictions and popular entropy-based uncertainty measures. Examples of unpredictable trajectory design are presented to elaborate the applicability of the proposed predictability metric. Simulations are conducted to illustrate the efficiency of the obtained results. | Predictability of Stochastic Dynamical Systems: Metric, Optimality and Application |
Exact solution of Dirac equation for a particle whose potential energy and mass are inversely proportional to the distance from the force centre has been found. The bound states exist provided the length scale $a$ which appears in the expression for the mass is smaller than the classical electron radius $e^2/mc^2$. Furthermore, bound states also exist for negative values of $a$ even in the absence of the Coulomb interaction. Quasirelativistic expansion of the energy has been carried out, and a modified expression for the fine structure of energy levels has been obtained. The problem of kinetic energy operator in the Schr\"odinger equation is discussed for the case of position-dependent mass. In particular, we have found that for highly excited states the mutual ordering of the inverse mass and momentum operator in the non-relativistic theory is not important. | Kepler problem in Dirac theory for a particle with position-dependent mass |
Clearing functions (CFs), which express a mathematical relationship between the expected throughput of a production facility in a planning period and its workload (or work-in-progress, WIP) in that period have shown considerable promise for modeling WIP-dependent cycle times in production planning. While steady-state queueing models are commonly used to derive analytic expressions for CFs, the finite length of planning periods calls their validity into question. We apply a different approach to propose a mechanistic model for one-resource, one-product factory shop based on the analogy between the operation of machine and enzyme molecule. The model is reduced to a singularly perturbed system of two differential equations for slow (WIP) and fast (busy machines) variables, respectively. The analysis of this slow-fast system finds that CF is nothing but a result of the asymptotic expansion of the slow invariant manifold. The validity of CF is ultimately determined by how small is the parameter multiplying the derivative of the fast variable. It is shown that sufficiently small characteristic ratio 'working machines : WIP' guarantees the applicability of CF approximation in unsteady-state operation. | Clearing function in the context of the invariant manifold method |
We study analytically, via the Newman-Penrose formalism, the late time decay of scalar, electromagnetic, and gravitational perturbations outside a realistic rotating (Kerr) black hole. We find a power-law decay at timelike infinity, as well as at null infinity and along the event horizon (EH). For generic initial data we derive the power-law indices for all radiating modes of the various fields. We also give an exact analytic expression (accurate to leading order in 1/t) for the r-dependence of the late time tail at any r. Some of our main conclusions are: (i) For generic initial data, the late time behavior of the fields is dominated by the mode l=|s| (with s being the spin parameter), which dies off at fixed $r$ as $t^{-2|s|-3}$ --- as in the Schwarzschild background. (ii) However, other modes admit decay rates slower than in the Schwarzschild case. (iii) For s>0 fields, non-axially symmetric modes dominate the late time behavior along the EH. These modes oscillate along the null generators of the EH. | Late time decay of scalar, electromagnetic, and gravitational perturbations outside rotating black holes |
We describe an implementation of a semi-automated review system for the astrophysics literature. Registered users identify names under which they publish, and provide scores for individual papers of their choosing. Scores are held confidentially, and combined in a weighted average grade for each paper. The grade is divided among the co-authors as assigned credit. The credit accumulated by each user (their ``mass'') provides the weight by which their score is averaged into papers' grades. Thus, papers' grades and users' masses are mutually dependent and evolve in time as scores are added. Likewise, a user's influence on the grade of a paper is determined from the perceived original scientific contribution of all the user's previous papers. The implementation, called RefSponse -- currently hosted at http://bororo.physics.mcgill.ca -- includes papers in astro-ph, the ApJ, AJ, A&A, MNRAS, PASP, PASJ, New Astronomy, Nature, ARA&A, Phys. Rev. Letters, Phys. Rev. D. and Acta Astronomica from 1965 to the present, making extensive use of the NASA/ADS abstract server. We describe some of the possible utilities of this system in enabling progress in the field. | RefSponse: A Literature Evaluation System for the Professional Astrophysics Community |
Mn1-xZnxCr2O4 (0<x<1) single crystals have been grown by the chemical vapor transport (CVT) method. The crystallographic, magnetic, and thermal transport properties of the single crystals were investigated by the room-temperature X-ray diffraction, magnetization M(T) and specific heat CP(T) measurements. Mn1-xZnxCr2O4 crystals show a cubic structure, the lattice constant a decreases with the increasing content x of the doped Zn2+ ions and follows the Vegard law. Based on the magnetization and heat capacity measurements, the magnetic evolution of Mn1-xZnxCr2O4 crystals has been discussed. For 0<x<0.3, the magnetic ground state is the coexistence of the collinear ferrimagnetic order (CFIM) and spiral ferrimagnetic one (SFIM), which is similar to that of the parent MnCr2O4. When x changes from 0.3 to 0.8, the SFIM is progressively suppressed and spin glass-like behavior is observed. When x is above 0.8, an antiferromagnetic (AFM) order presents. At the same time, the magnetic specific heat (Cmag.) was also investigated and the results are coincident with the magnetic measurements. The possible reasons based on the disorder effect and the reduced molecular field effect induced by the substitution of Mn2+ ions by nonmagnetic Zn2+ ones in Mn1-xZnxCr2O4 crystals have been discussed. | Magnetic evolution of Spinel Mn1-xZnxCr2O4 single crystals |
We study the quantum localization phenomena for a random matrix model belonging to the Gaussian orthogonal ensemble (GOE). An oscillating external field is applied on the system. After the transient time evolution, energy is saturated to various values depending on the frequencies. We investigate the frequency dependence of the saturated energy. This dependence cannot be explained by a naive picture of successive independent Landau-Zener transitions at avoided level crossing points. The effect of quantum interference is essential. We define the number of Floquet states which have large overlap with the initial state, and calculate its frequency dependence. The number of Floquet states shows approximately linear dependence on the frequency, when the frequency is small. Comparing the localization length in Floquet states and that in energy states from the viewpoint of the Anderson localization, we conclude that the Landau-Zener picture works for the local transition processes between levels. | Frequency Dependence of Quantum Localization in a Periodically Driven System |
By observing their environment as well as other traffic participants, humans are enabled to drive road vehicles safely. Vehicle passengers, however, perceive a notable difference between non-experienced and experienced drivers. In particular, they may get the impression that the latter ones anticipate what will happen in the next few moments and consider these foresights in their driving behavior. To make the driving style of automated vehicles comparable to the one of human drivers with respect to comfort and perceived safety, the aforementioned anticipation skills need to become a built-in feature of self-driving vehicles. This article provides a systematic comparison of methods and strategies to generate this intention for self-driving cars using machine learning techniques. To implement and test these algorithms we use a large data set collected over more than 30000 km of highway driving and containing approximately 40000 real-world driving situations. We further show that it is possible to classify driving maneuvers upcoming within the next 5 s with an Area Under the ROC Curve (AUC) above 0.92 for all defined maneuver classes. This enables us to predict the lateral position with a prediction horizon of 5 s with a median lateral error of less than 0.21 m. | Teaching Vehicles to Anticipate: A Systematic Study on Probabilistic Behavior Prediction Using Large Data Sets |
We propose a method to reconstruct the vibrational quantum state of molecules excited by a general excitation laser pulse. Unlike existing methods, we do not require the molecules before excitation to be in a pure state, allowing us to treat the important case of initially thermally excited molecules. Even if only a single initial level is appreciably populated, initial levels with small populations can still give major contributions to the unknown vibrational state, making it essential to take them into account. In addition to the excitation pulse, the method uses two incident, short laser pulses in a non-co-linear geometry to create four-wave mixing in the molecules. The measurements used in the reconstruction are spectra of the outgoing four-wave mixing pulse at different time delays of the excitation laser pulse. An important point is that the method does not require detailed knowledge of molecular transition moments between excited states nor of any of the incoming laser pulses, but circumvents this requirement by using one or more calibration laser pulses in a separate experiment either before or after the main data are recorded. The only requirements for the calibration laser pulses are that the constant parts of their spectrums should together cover the spectral range of the excitation laser pulse, and the constant part of each should have sufficient spectral overlap with one other calibration pulse to populate two of the same levels. Finally, we discuss the extension of the reconstruction method in this paper to more general situations, hereby presenting the new idea of quantum state reconstruction through perturbations with calibration. | Reconstructing vibrational states in warm molecules using four-wave mixing with femtosecond laser pulses |
The goal of this note is to extend the result bounding from bellow the minimal possible growth of frequently oscillating subharmonic functions to a larger class of functions that carry similar properties. We refine and find further applications for the technique presented by Jones and Makarov in their celebrated paper, Density properties of harmonic measure. | Frequently oscillating families related to subharmonic functions |
We study phonon emission in a GaAs/AlGaAs double quantum dot by monitoring the tunneling of a single electron between the two dots. We prepare the system such that a known amount of energy is emitted in the transition process. The energy is converted into lattice vibrations and the resulting tunneling rate depends strongly on the phonon scattering and its effective phonon spectral density. We are able to fit the measured transition rates and see imprints of interference of phonons with themselves causing oscillations in the transition rates. | Phonon spectral density in a GaAs/AlGaAs double quantum dot |
We advocate an effective field theory approach to anomalous couplings. The effective field theory approach is the natural way to extend the standard model such that the gauge symmetries are respected. It is general enough to capture any physics beyond the standard model, yet also provides guidance as to the most likely place to see the effects of new physics. The effective field theory approach also clarifies that one need not be concerned with the violation of unitarity in scattering processes at high energy. We apply these ideas to pair production of electroweak vector bosons. | Effective Field Theory: A Modern Approach to Anomalous Couplings |
We compute the two-loop $\beta$-function of scalar and spinorial quantum electrodynamics as well as pure Yang-Mills and quantum chromodynamics using the background field method in a fully quadridimensional setup using Implicit Regularization (IREG). Moreover, a thorough comparison with dimensional approaches such as conventional dimensional regularization (CDR) and dimensional reduction (DRED) is presented. Subtleties related to Lorentz algebra contractions/symmetric integrations inside divergent integrals as well as renormalisation schemes are carefully discussed within IREG where the renormalisation constants are fully defined as basic divergent integrals to arbitrary loop order. Moreover, we confirm the hypothesis that momentum routing invariance in the loops of Feynman diagrams implemented via setting well-defined surface terms to zero deliver non-abelian gauge invariant amplitudes within IREG just as it has been proven for abelian theories. | Two-loop renormalisation of gauge theories in $4D$ Implicit Regularisation and connections to dimensional methods |
The symmetries of the DNA double helix require a new term in its linear response to stress: the coupling between twist and stretch. Recent experiments with torsionally-constrained single molecules give the first direct measurement of this new material parameter. We extract its value from a recent experiment. We also present a very simple microscopic theory predicting a value comparable to the one observed. Finally we sketch the effect of constrained twist on entropic elasticity of DNA arising from the connection between Link, Twist, and Writhe. | New Measurements of DNA Twist Elasticity |
Let G be a locally compact group acting properly by type-preserving automorphisms on a locally finite thick Euclidean building $\Delta$ and K be the stabilizer of a special vertex in $\Delta$. It is known that (G, K) is a Gelfand pair as soon as G acts strongly transitively on $\Delta$; this is in particular the case when G is a semi-simple algebraic group over a local field. We show a converse to this statement, namely: if (G, K) is a Gelfand pair and G acts cocompactly on $\Delta$, then the action is strongly transitive. The proof uses the existence of strongly regular hyperbolic elements in G and their peculiar dynamics on the spherical building at infinity. Other equivalent formulations are also obtained, including the fact that G is strongly transitive on $\Delta$ if and only if it is strongly transitive on the spherical building at infinity. | Gelfand pairs and strong transitivity for Euclidean buildings |
Crowdsourcing is a mechanism by means of which groups of people are able to execute a task by sharing ideas, efforts and resources. Thanks to the online technologies, crowdsourcing has become in the last decade an even more utilized process in different and diverse fields. An instance of such process is the so-called "label aggregation problem": in practice, it is the evaluation of an item by groups of agents, where each agent gives its own judgment of it. Starting from the individual evaluations of their members, how can the groups give their global assessment? In this work, by means of a game-theoretical, evolutionary approach, we show that in most cases the majority rule (the group evaluation is the evaluation of the majority of its members) is still the best way to get a reliable group evaluation, even when the agents are not the best experts of the topic at stake; on the other hand, we also show that noise (i.e., fortuitous errors, misunderstanding, or every possible source of non-deterministic outcomes) can undermine the efficiency of the procedure in non-trivial situations. Therefore, in order to make the process as reliable as possible, the presence of noise and its effects should be carefully taken into account. | Noise and fluctuations can undermine the efficiency of Majority Rule in Group Evaluation problems |
Recent years have seen great advancements in the development of deep learning models for histopathology image analysis in digital pathology applications, evidenced by the increasingly common deployment of these models in both research and clinical settings. Although such models have shown unprecedented performance in solving fundamental computational tasks in DP applications, they suffer from catastrophic forgetting when adapted to unseen data with transfer learning. With an increasing need for deep learning models to handle ever changing data distributions, including evolving patient population and new diagnosis assays, continual learning models that alleviate model forgetting need to be introduced in DP based analysis. However, to our best knowledge, there is no systematic study of such models for DP-specific applications. Here, we propose CL scenarios in DP settings, where histopathology image data from different sources/distributions arrive sequentially, the knowledge of which is integrated into a single model without training all the data from scratch. We then established an augmented dataset for colorectal cancer H&E classification to simulate shifts of image appearance and evaluated CL model performance in the proposed CL scenarios. We leveraged a breast tumor H&E dataset along with the colorectal cancer to evaluate CL from different tumor types. In addition, we evaluated CL methods in an online few-shot setting under the constraints of annotation and computational resources. We revealed promising results of CL in DP applications, potentially paving the way for application of these methods in clinical practice. | Continual Learning for Tumor Classification in Histopathology Images |
Accurately and rapidly classifying exoplanet candidates from transit surveys is a goal of growing importance as the data rates from space-based survey missions increases. This is especially true for NASA's TESS mission which generates thousands of new candidates each month. Here we created the first deep learning model capable of classifying TESS planet candidates. We adapted the neural network model of Ansdell et al. (2018) to TESS data. We then trained and tested this updated model on 4 sectors of high-fidelity, pixel-level simulations data created using the Lilith simulator and processed using the full TESS SPOC pipeline. We find our model performs very well on our simulated data, with 97% average precision and 92% accuracy on planets in the 2-class model. This accuracy is also boosted by another ~4% if planets found at the wrong periods are included. We also performed 3- and 4-class classification of planets, blended & target eclipsing binaries, and non-astrophysical false positives, which have slightly lower average precision and planet accuracies, but are useful for follow-up decisions. When applied to real TESS data, 61% of TCEs coincident with currently published TOIs are recovered as planets, 4% more are suggested to be EBs, and we propose a further 200 TCEs as planet candidates. | Rapid Classification of TESS Planet Candidates with Convolutional Neural Networks |
We investigate spherical accretion to a rotating magnetized star in the "propeller" regime using axisymmetric resistive magnetohydrodynamic simulations. The regime is predicted to occur if the magnetospheric radius is larger than the corotation radius and smaller than the light cylinder radius. The simulations show that accreting matter is expelled from the equatorial region of the magnetosphere and that it moves away from the star in a supersonic, disk-shaped outflow. At larger radial distances the outflow slows down and becomes subsonic. The equatorial matter outflow is initially driven by the centrifugal force, but at larger distances the pressure gradient force becomes significant. We find the fraction of the Bondi accretion rate which accretes to the surface of the star. | Accretion to a Magnetized Neutron Star in the "Propeller" Regime |
A classical statistical inequality is used to show that the distance covariance of two bounded random vectors is bounded from above by a simple function of the dimensionality and the bounds of the random vectors. Two special cases that further simplify the result are considered: one in which both random vectors have the same number of components, each component taking values in an interval of unit length, and the other in which both random vectors have one component. | Upper bounding the distance covariance of bounded random vectors |
We numerically investigate the influence of high-order dispersion on both temporal and spectral characterizations of microresonator-based optical frequency combs. The moment method is utilized to study the temporal dynamics of intracavity solitons. The theoretical and numerical results indicate the temporal shifts are induced by high-odd-order dispersion rather than high-even-order dispersion. The role of high-order dispersion on the frequency comb envelopes is carefully elucidated through analyzing the intracavity Cherenkov radiations. We further demonstrate that the spectra envelope of an ultrabroadband optical frequency comb can be engineered by using dispersion profiles with multiple zero dispersion wavelengths. | Analysis of high-order dispersion on ultrabroadband microresonator-based frequency combs |
The (1+1)-dimensional gauge model of two complex self-interacting scalar fields that interact with each other through an Abelian gauge field and a quartic scalar interaction is considered. It is shown that the model has nontopological soliton solutions describing soliton systems consisting of two Q-ball components possessing opposite electric charges. The two Q-ball components interact with each other through the Abelian gauge field and the quartic scalar interaction. The interplay between the attractive electromagnetic interaction and the repulsive quartic interaction leads to the existence of symmetric and nonsymmetric soliton systems. Properties of these systems are investigated by analytical and numerical methods. The symmetric soliton system exists in the whole allowable interval of the phase frequency, whereas the nonsymmetric soliton system exists only in some interior subinterval. Despite the fact that these soliton systems are electrically neutral, they nevertheless possess nonzero electric fields in their interiors. It is found that the nonsymmetric soliton system is more preferable from the viewpoint of energy than the symmetric one. Both symmetric and nonsymmetric soliton systems are stable to the decay into massive scalar bosons. | A one-dimensional soliton system of gauged Q-ball and anti-Q-ball |
The transverse momentum of a colour-singlet massive particle in a hadronic collision is built up by two components, the perturbative effect of parton branchings and the nonperturbative effect of primordial kT. In previous studies of transverse momentum spectra for Z0 production at the Tevatron, the best fit to the experimental data are given when the primordial kT is set to a much higher value than what is expected considering the confinement of partons in the proton. We here investigate the possibility that the reason for this is that too few branchings are generated in showers, compared to the evolution used in the tuning of parton densities. This could then be compensated by increasing the value of Lambda_QCD. The study is done using the regular Pythia showering routines and a new algorithm where the branchings are ordered in transverse momentum pT^2 instead of virtuality Q^2. | Perturbative and Nonperturbative Effects in Transverse Momentum Generation |
We carry out a systematic investigation for the minimal Dirac neutrino mass models emerging from generic one-loop and two-loop topologies that arise from $d=5$ effective operator with a singlet scalar, $\sigma$. To ensure that the tree-level Dirac mass, as well as Majorana mass terms at all orders, are absent for the neutrinos, we work in the framework where the Standard Model is supplemented by the well-motivated $U(1)_{B-L}$ gauge symmetry. At the one-loop level, we analyze six possible topologies, out of which two of them have the potential to generate desired Dirac neutrino mass. Adopting a systematic approach to select minimal models, we construct seventeen viable one-loop Dirac neutrino mass models. By embracing a similar methodical approach at the two-loop, we work out twenty-three minimal candidates. Among the forty selected economical models, the majority of the models proposed in this work are new. In our search, we also include the scenarios where the particles in the loop carry charges under the color group. Furthermore, we discuss the possible dark matter candidates within a given model, if any, without extending the minimal particle content. | Minimal Realizations of Dirac Neutrino Mass from Generic One-loop and Two-loop Topologies at $d=5$ |
This study introduces the Tempotron, a powerful classifier based on a third-generation neural network model, for pulse shape discrimination. By eliminating the need for manual feature extraction, the Tempotron model can process pulse signals directly, generating discrimination results based on learned prior knowledge. The study performed experiments using GPU acceleration, resulting in over a 500 times speedup compared to the CPU-based model, and investigated the impact of noise augmentation on the Tempotron's performance. Experimental results showed that the Tempotron is a potent classifier capable of achieving high discrimination accuracy. Furthermore, analyzing the neural activity of Tempotron during training shed light on its learning characteristics and aided in selecting the Tempotron's hyperparameters. The dataset used in this study and the source code of the GPU-based Tempotron are publicly available on GitHub at https://github.com/HaoranLiu507/TempotronGPU. | Pulse shape discrimination based on the Tempotron: a powerful classifier on GPU |
Let $X$ and $Y$ be separable Banach spaces and $T:X\to Y$ be a bounded linear operator. We characterize the non-separability of $T^*(Y^*)$ by means of fixing properties of the operator $T$. | Operators whose dual has non-separable range |
Multi-time wave functions are wave functions for multi-particle quantum systems that involve several time variables (one per particle). In this paper we contrast them with solutions of wave equations on a space-time with multiple timelike dimensions, i.e., on a pseudo-Riemannian manifold whose metric has signature such as ${+}{+}{-}{-}$ or ${+}{+}{-}{-}{-}{-}{-}{-}$, instead of ${+}{-}{-}{-}$. Despite the superficial similarity, the two behave very differently: Whereas wave equations in multiple timelike dimensions are typically mathematically ill-posed and presumably unphysical, relevant Schr\"odinger equations for multi-time wave functions possess for every initial datum a unique solution on the spacelike configurations and form a natural covariant representation of quantum states. | Multi-Time Wave Functions versus Multiple Timelike Dimensions |
We explore a distance-3 homological CSS quantum code, namely the small stellated dodecahedron code, for dense storage of quantum information and we compare its performance with the distance-3 surface code. The data and ancilla qubits of the small stellated dodecahedron code can be located on the edges resp. vertices of a small stellated dodecahedron, making this code suitable for 3D connectivity. This code encodes 8 logical qubits into 30 physical qubits (plus 22 ancilla qubits for parity check measurements) as compared to 1 logical qubit into 9 physical qubits (plus 8 ancilla qubits) for the surface code. We develop fault-tolerant parity check circuits and a decoder for this code, allowing us to numerically assess the circuit-based pseudo-threshold. | The Small Stellated Dodecahedron Code and Friends |
In this paper we show that a complete characterization of the controllability property for linear control system on three-dimensional solvable nonnilpotent Lie groups is possible by the LARC and the knowledge of the eigenvalues of the derivation associated with the drift of the system. | On the characterization of the controllability property for linear control systems on nonnilpotent, solvable three-dimensional Lie groups |
In this paper, previous works on the Model Predictive Control (MPC) and the Divergent Component of Motion (DCM) for bipedal walking control are extended. To this end, we employ a single MPC which uses a combination of Center of Pressure (CoP) manipulation, step adjustment, and Centroidal Moment Pivot (CMP) modulation to design a robust walking controller. Furthermore, we exploit the concept of time-varying DCM to generalize our walking controller for walking in uneven surfaces. Using our scheme, a general and robust walking controller is designed which can be implemented on robots with different control authorities, for walking on various environments, e.g. uneven terrains or surfaces with a very limited feasible area for stepping. The effectiveness of the proposed approach is verified through simulations on different scenarios and comparison to the state of the art. | Robust Bipedal Locomotion Control Based on Model Predictive Control and Divergent Component of Motion |
A graph is called normal if its vertex set can be covered by cliques and also by stable sets, such that every such clique and stable set have non-empty intersection. This notion is due to Korner, who introduced the class of normal graphs as an extension of the class of perfect graphs. Normality has also relevance in information theory. Here we prove, that the line graphs of cubic graphs are normal. | Line-graphs of cubic graphs are normal |
We examine the modular structure of the metabolic network when combined with the regulatory network representing direct regulation of enzymes by small metabolites in E.coli. In order to identify the modular structure we introduce clustering algorithm based on a novel vertex similarity measure for bipartite graphs. We also apply a standard module identification method based on simulated annealing. Both methods identify the same modular core each of them with different resolution. We observe slight but still statistically significant increase of modularity after regulatory interactions addition. Enrichment of the metabolic network with the regulatory information leads to identification of new functional modules, which cannot be detected in the metabolic network only. Regulatory loops in the modules are the source of their self-control, i.e. autonomy, and allow to make hypothesis about module function. This study demonstrates that incorporation of regulatory information is important component in defining functional units of the metabolic network. | Modules in the metabolic network of E.coli with regulatory interactions |
This paper presents an efficient method for texture retrieval using multiscale feature extraction and embedding based on the local extrema keypoints. The idea is to first represent each texture image by its local maximum and local minimum pixels. The image is then divided into regular overlapping blocks and each one is characterized by a feature vector constructed from the radiometric, geometric and structural information of its local extrema. All feature vectors are finally embedded into a covariance matrix which will be exploited for dissimilarity measurement within retrieval task. Thanks to the method's simplicity, multiscale scheme can be easily implemented to improve its scale-space representation capacity. We argue that our handcrafted features are easy to implement, fast to run but can provide very competitive performance compared to handcrafted and CNN-based learned descriptors from the literature. In particular, the proposed framework provides highly competitive retrieval rate for several texture databases including 94.95% for MIT Vistex, 79.87% for Stex, 76.15% for Outex TC-00013 and 89.74% for USPtex. | Efficient texture retrieval using multiscale local extrema descriptors and covariance embedding |
A sound stimulus entering the inner ear excites a deformation of the basilar membrane which travels along the cochlea towards the apex. It is well established that this wave-like disturbance is amplified by an active system. Recently, it has been proposed that the active system consists of a set of self-tuned critical oscillators which automatically operate at an oscillatory instability. Here, we show how the concepts of a traveling wave and of self-tuned critical oscillators can be combined to describe the nonlinear wave in the cochlea. | The Active Traveling Wave in the Cochlea |
It is possible to eliminate exactly all the auxiliary fields (einbein fields) appearing in the rotating string Hamiltonian to obtain the classical equations of motion of the relativistic flux tube model. A clear interpretation can then be done for the characteristic variables of the rotating string model. | Auxiliary fields and the flux tube model |
Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference. While optimizations have been proposed for inference latency, memory footprint, and energy consumption, prior hardware-aware neural architecture search (NAS) methods have omitted resource utilization, preventing DNNs to take full advantage of the target inference platforms. Modeling resource utilization efficiently and accurately is challenging, especially for widely-used array-based inference accelerators such as Google TPU. In this work, we propose a novel hardware-aware NAS framework that does not only optimize for task accuracy and inference latency, but also for resource utilization. We also propose and validate a new computational model for resource utilization in inference accelerators. By using the proposed NAS framework and the proposed resource utilization model, we achieve 2.8 - 4x speedup for DNN inference compared to prior hardware-aware NAS methods while attaining similar or improved accuracy in image classification on CIFAR-10 and Imagenet-100 datasets. | U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search |
Recently Deyo et al. [\prb {\bf 106}, 104502 (2022)] suggested that the surface resistance $R_s(H_0)$ of a superconductor under strong electromagnetic field can be affected by field-induced quasiparticle bound states at the surface. This Comment shows that the existence of such bound states and their contribution to $R_s$ are not substantiated and the phenomenological models of Ref. \cite{corn} give incorrect field and temperature dependencies of $R_s(T,H_0)$. | On the effect of localized and delocalized quasiparticles on a nonlinear conductivity of superconductors |
We describe the singularities in the averaged density of states and the corresponding statistics of the energy levels in two- (2D) and three-dimensional (3D) chiral symmetric and time-reversal invariant disordered systems, realized in bipartite lattices with real off-diagonal disorder. For off-diagonal disorder of zero mean we obtain a singular density of states in 2D which becomes much less pronounced in 3D, while the level-statistics can be described by semi-Poisson distribution with mostly critical fractal states in 2D and Wigner surmise with mostly delocalized states in 3D. For logarithmic off-diagonal disorder of large strength we find indistinguishable behavior from ordinary disorder with strong localization in any dimension but in addition one-dimensional $1/|E|$ Dyson-like asymptotic spectral singularities. The off-diagonal disorder is also shown to enhance the propagation of two interacting particles similarly to systems with diagonal disorder. Although disordered models with chiral symmetry differ from non-chiral ones due to the presence of spectral singularities, both share the same qualitative localization properties except at the chiral symmetry point E=0 which is critical. | Spectral Statistics in Chiral-Orthogonal Disordered Systems |
The magneto-optical properties of Ga$_{1-x}$Mn$_{x}$As including their most common defects were investigated with precise first--principles density-functional FLAPW calculations in order to: {\em i}) elucidate the origin of the features in the Kerr spectra in terms of the underlying electronic structure; {\em ii}) perform an accurate comparison with experiments; and {\em iii}) understand the role of the Mn concentration and occupied sites in shaping the spectra. In the substitutional case, our results show that most of the features have an interband origin and are only slightly affected by Drude--like contributions, even at low photon energies. While not strongly affected by the Mn concentration for the intermediately diluted range ($x\sim$ 10%), the Kerr factor shows a marked minimum (up to 1.5$^o$) occurring at a photon energy of $\sim$ 0.5 eV. For interstitial Mn, the calculated results bear a striking resemblance to the experimental spectra, pointing to the comparison between simulated and experimental Kerr angles as a valid tool to distinguish different defects in the diluted magnetic semiconductors framework. | Magneto-optics in pure and defective Ga_{1-x}Mn_xAs from first-principles |
In recent years, considerable work has been done to tackle the issue of designing control laws based on observations to allow unknown dynamical systems to perform pre-specified tasks. At least as important for autonomy, however, is the issue of learning which tasks can be performed in the first place. This is particularly critical in situations where multiple (possibly conflicting) tasks and requirements are demanded from the agent, resulting in infeasible specifications. Such situations arise due to over-specification or dynamic operating conditions and are only aggravated when the dynamical system model is learned through simulations. Often, these issues are tackled using regularization and penalties tuned based on application-specific expert knowledge. Nevertheless, this solution becomes impractical for large-scale systems, unknown operating conditions, and/or in online settings where expert input would be needed during the system operation. Instead, this work enables agents to autonomously pose, tune, and solve optimal control problems by compromising between performance and specification costs. Leveraging duality theory, it puts forward a counterfactual optimization algorithm that directly determines the specification trade-off while solving the optimal control problem. | Counterfactual Programming for Optimal Control |
Superconductivity and its underlying mechanisms are one of the most active research fields in condensed-matter physics. An important question is how to enhance the transition temperature $T_{\rm c}$ of a superconductor. In this respect, the possibly positive role of valence-skipping elements in the pairing mechanism has been attracting considerable interest. Here we follow this pathway and successfully enhance $T_{\rm c}$ up to almost 6 K in the simple chalcogenide SnTe known as topological crystalline insulator by doping the valence-skipping element In and codoping Se. A high-pressure synthesis method enabled us to form single-phase solid solutions Sn$_{1-x}$In$_{x}$Te$_{1-y}$Se$_{y}$ over a wide composition range while keeping the cubic structure necessary for the superconductivity. Our experimental results are supported by density-functional theory calculations which suggest that even higher $T_{\rm c}$ values would be possible if the required doping range were experimentally accessible. | Tailoring band-structure and band-filling in a simple cubic (IV, III) - VI superconductor |
Mobile agents research is clearly aiming towards imposing agent based development as the next generation of tools for writing software. This paper comes with its own contribution to this global goal by introducing a novel unifying framework meant to bring simplicity and interoperability to and among agent platforms as we know them today. In addition to this, we also introduce a set of agent behaviors which, although tailored for and from the area of virtual learning environments, are none the less generic enough to be used for rapid, simple, useful and reliable agent deployment. The paper also presents an illustrative case study brought forward to prove the feasibility of our design. | A framework of reusable structures for mobile agent development |
We consider the local bifurcation and global dynamics of a predator-prey model with cooperative hunting and Allee effect. For the model with weak cooperation, we prove the existence of limit cycle, heteroclinic cycle at a threshold of conversion rate $p=p^{\#}$. When $p>p^{\#}$, both species go extinct, and when $p<p^{\#}$, there is a separatrix. The species with initial population above the separatrix finally become extinct; otherwise, they coexist or oscillate sustainably. In the case with strong cooperation, we exhibit the complex dynamics of system in three different cases, including limit cycle, loop of heteroclinic orbits among three equilibria, and homoclinic cycle. Moreover, we find diffusion may induce Turing instability and Turing-Hopf bifurcation, leaving the system with spatially inhomogeneous distribution of the species, coexistence of two different spatial-temporal oscillations. Finally, we investigate Hopf and double Hopf bifurcations of the diffusive system induced by two delays. | Global dynamics in a predator-prey model with cooperative hunting and Allee effect and bifurcation induced by diffusion and delays |
We study finite quantum wires and rings in the presence of a charge density wave gap induced by a periodic modulation of the chemical potential. We show that the Tamm-Shockley bound states emerging at the ends of the wire are stable against weak disorder and interactions, for discrete open chains and for continuum systems. The low-energy physics can be mapped onto the Jackiw-Rebbi equations describing massive Dirac fermions and bound end states. We treat interactions via the continuum model and show that they increase the charge gap and further localize the end states. In an Aharonov-Bohm ring with weak link, the bound states give rise to an unusual $4\pi$-peridodicity in the spectrum and persistent current as function of an external flux. The electrons placed in the two localized states on the opposite ends of the wire can interact via exchange interactions and this setup can be used as a double quantum dot hosting spin-qubits. | Localized end states in density modulated quantum wires and rings |
This paper presents a deep-learning based traffic classification method for identifying multiple streaming video sources at the same time within an encrypted tunnel. The work defines a novel feature inspired by Natural Language Processing (NLP) that allows existing NLP techniques to help the traffic classification. The feature extraction method is described, and a large dataset containing video streaming and web traffic is created to verify its effectiveness. Results are obtained by applying several NLP methods to show that the proposed method performs well on both binary and multilabel traffic classification problems. We also show the ability to achieve zero-shot learning with the proposed method. | A Natural Language-Inspired Multi-label Video Streaming Traffic Classification Method Based on Deep Neural Networks |
There exists a canonical functor from the category of fibrant objects of a model category modulo cylinder homotopy to its homotopy category. We show that this functor is faithful under certain conditions, but not in general. | Faithfulness of a functor of Quillen |
We demonstrate an all-optical four-channel wavelength multicasting in a coupled Silicon microring resonator system. The scheme is based on two-photon absorption induced free carrier dispersion in Silicon. The coupled cavity facilitates resonance splitting that is utilized as individual channels for multicasting. Using the split resonances, we achieve an aggregate multicasted data rate of 48 Gbps (4X12 Gbps). Moreover, we also present a detailed analysis and performance of the multicasting architecture. | All-optical wavelength multicasting in quadruple resonance-split coupled Silicon microring cavity |
In the past two decades high-harmonic generation (HHG) has become a key process in ultra-fast science due to the extremely short time-structure of the underlying electron dynamics being imprinted in the emitted harmonic light bursts. After discussing the fundamental physical picture of HHG including continuum--continuum transitions, we describe the experimental progress rendering HHG to the unique source of attosecond pulses. The development of bright photon sources with zeptosecond pulse duration and keV photon energy is underway. In this article we describe several approaches pointed toward this aim and beyond. As the main barriers for multi-keV HHG, phase-matching and relativistic drift are discussed. Routes to overcome these problems are pointed out as well as schemes to control the HHG process via alterations of the driving fields. Finally, we report on how the investigation of fundamental physical processes benefits from the continuous development of HHG sources. | Frontiers of atomic high-harmonic generation |
The adaptation of biological species to their environment depends on their traits. When various biological processes occur (survival, reproduction, migration, etc.), the trait distribution may change with respect to time and space. In the context of invasions, when considering the evolution of a heritable trait that encodes the dispersive ability of individuals, the trait distribution develops a particular spatial structure that leads to the acceleration of the front propagation. That phenomenon is known as spatial sorting. Many biological examples can be cited like the bush cricket in Britain, the cane toad invasion in Australia or the common myna one in South Africa. Adopting this framework, recent mathematical studies have led to highlight the influence of the reproductive mode on the front propagation. Asexual populations have been shown to spread with an asymptotic rate of t 3/2 in a minimal reactiondiffusion model, whereas the analogous rate for sexual populations is of t 5/4 (where t denotes the time). However, the precise description of the behaviour of the front propagation in the sexual case is still an open question. The aim of this paper is to give precise approximations for large times of its position, as well as some features of the local trait distribution at the front. To do so, we solve explicitly the asymptotic problem derived formally. Numerical simulations are shown to confirm these calculations. | Front propagation of a sexual population with evolution of dispersion: a formal analysis |
We study the band structures and the associated contact points for a phosphorene superlattice made up of two periodic areas. We use the boundary conditions to extract an equation describing the dispersion relation after obtaining the eigen-wavefunctions. We show that energy transforms into linear behavior near contact points, and fermions move at different speeds along $x$- and $y$- directions. It was discovered that the periodic potential caused additional Dirac points, which we located in $k$-space by establishing their positions. We demonstrate that the barrier height and width can be used to adjust the energy gap and modify the contact points. It might be that our findings will be useful in the development of phosphorene-based electronic devices. | Band structures and contact points in phosphorene superlattice |
We present a mark correlation analysis of the galaxies in the Sloan Digital Sky Survey using weights provided by MOPED. The large size of the sample permits statistically significant statements about how galaxies with different metallicities and star formation histories are spatially correlated. Massive objects formed a larger fraction of their stars at higher redshifts and over shorter timescales than did less massive objects (sometimes called down-sizing). We find that those galaxies which dominated the cosmic star formation at z~3 are predominantly in clusters today, whereas galaxies which dominate the star formation at z~0 inhabit substantially lower mass objects in less dense regions today. Hence, our results indicate that star formation and chemical enrichment occured first in the denser regions of the Universe, and moved to less dense regions at later times. | Environment and the cosmic evolution of star formation |
By the use of phase perturbation theory we show that if a single realization of a one-dimensional randomly rough interface between two dielectric media is illuminated at normal incidence from either medium by a broadband Gaussian beam, it produces a scattered field whose differential reflection coefficient closely matches the result produced by averaging the differential reflection coefficient produced by a monochromatic incident beam over the ensemble of realizations of the interface profile function. | Replacement of ensemble averaging by the use of a broadband source in scattering of light from a one-dimensional randomly rough interface between two dielectric media |
The main objective of this paper is to propose K-Nearest-Neighbor (KNN) algorithm for predicting NOx emissions from natural gas electrical generation turbines. The process of producing electricity is dynamic and rapidly changing due to many factors such as weather and electrical grid requirements. Gas turbine equipment are also a dynamic part of the electricity generation since the equipment characteristics and thermodynamics behavior change as the turbines age. Regular maintenance of turbines are also another dynamic part of the electrical generation process, affecting the performance of equipment. This analysis discovered using KNN, trained on relatively small dataset produces the most accurate prediction rates. This statement can be logically explained as KNN finds the K nearest neighbor to the current input parameters and estimates a rated average of historically similar observations as prediction. This paper incorporates ambient weather conditions, electrical output as well as turbine performance factors to build a machine learning model to predict NOx emissions. The model can be used to optimize the operational processes for reduction in harmful emissions and increasing overall operational efficiency. Latent algorithms such as Principle Component Algorithms (PCA) have been used for monitoring the equipment performance behavior change which deeply influences process paraments and consequently determines NOx emissions. Typical statistical methods of machine learning performance evaluations such as multivariate analysis, clustering and residual analysis have been used throughout the paper. | Environmental Pollution Prediction of NOx by Process Analysis and Predictive Modelling in Natural Gas Turbine Power Plants |
Specific antiferromagnetic (AF) spin configurations generate large anomalous Hall effects (AHEs) even at zero magnetic field through nonvanishing Berry curvature in momentum space. In addition to restrictions on AF structures, suitable control of AF domains is essential to observe this effect without cancellations among its domains; therefore, compatible materials remain limited. Here we show that an orthorhombic noncollinear AF material, NbMnP, acquired AF structure-based AHE and controllability of the AF domains. Theoretical calculations indicated that a large Hall conductivity of $\sim230$ $\Omega^{-1}$cm$^{-1}$ originated from the AF structure of NbMnP. Symmetry considerations explained the production of a small net magnetization, whose anisotropy enabled the generation and cancellation of the Hall responses using magnetic fields in different directions. Finally, asymmetric hysteresis in NbMnP shows potential for development of controllability of responses in AF materials. | Large anomalous Hall effect and unusual domain switching in an orthorhombic antiferromagnetic material NbMnP |
Taobao, as the largest online retail platform in the world, provides billions of online display advertising impressions for millions of advertisers every day. For commercial purposes, the advertisers bid for specific spots and target crowds to compete for business traffic. The platform chooses the most suitable ads to display in tens of milliseconds. Common pricing methods include cost per mille (CPM) and cost per click (CPC). Traditional advertising systems target certain traits of users and ad placements with fixed bids, essentially regarded as coarse-grained matching of bid and traffic quality. However, the fixed bids set by the advertisers competing for different quality requests cannot fully optimize the advertisers' key requirements. Moreover, the platform has to be responsible for the business revenue and user experience. Thus, we proposed a bid optimizing strategy called optimized cost per click (OCPC) which automatically adjusts the bid to achieve finer matching of bid and traffic quality of page view (PV) request granularity. Our approach optimizes advertisers' demands, platform business revenue and user experience and as a whole improves traffic allocation efficiency. We have validated our approach in Taobao display advertising system in production. The online A/B test shows our algorithm yields substantially better results than previous fixed bid manner. | Optimized Cost per Click in Taobao Display Advertising |
Spatially flat loitering universe models have recently been shown to arise in the context of brane world scenarios. Such models allow more time for structure formation to take place at high redshifts, easing, e.g., the tension between the observed and predicted evolution of the quasar population with redshift. While having the desirable effect of boosting the growth of structures, we show that in such models the position of the first peak in the power spectrum of the cosmic microwave background anisotropies severely constrains the amount of loitering at high redshifts. | Loitering universe models in light of the CMB |
We prove the existence and some properties of the limiting gap distribution functions for the directions of orbits of some infinite covolume subgroups of $Isom(\mathbb{H}^2)$ in the Poincar\'e disk. | The gap distribution of directions in some Schottky groups |
We explain that the set of new integrable systems generalizing the Calogero family and implied by the study of WLZZ models, which was described in arXiv:2303.05273, is only the tip of the iceberg. We provide its wide generalization and explain that it is related to commutative subalgebras (Hamiltonians) of the $W_{1+\infty}$ algebra. We construct many such subalgebras and explain how they look in various representations. We start from the even simpler $w_\infty$ contraction, then proceed to the one-body representation in terms of differential operators on a circle, further generalizing to matrices and in their eigenvalues, in finally to the bosonic representation in terms of time-variables. Moreover, we explain that some of the subalgebras survive the $\beta$-deformation, an intermediate step from $W_{1+\infty}$ to the affine Yangian. The very explicit formulas for the corresponding Hamiltonians in these cases are provided. Integrable many-body systems generalizing the rational Calogero model arise in the representation in terms of eigenvalues. Each element of $W_{1+\infty}$ algebra gives rise to KP/Toda $\tau$-functions. The hidden symmetry given by the families of commuting Hamiltonians is in charge of the special, (skew) hypergeometric $\tau$-functions among these. | Commutative families in $W_\infty$, integrable many-body systems and hypergeometric $\tau$-functions |
We prove that for recurrent, reversible graphs, the following conditions are equivalent: (a) existence and uniqueness of the potential kernel, (b) existence and uniqueness of harmonic measure from infinity, (c) a new anchored Harnack inequality, and (d) one-endedness of the wired Uniform Spanning Tree. In particular this gives a proof of the anchored (and in fact also elliptic) Harnack inequality on the UIPT. This also complements and strengthens some results of Benjamini, Lyons, Peres and Schramm. Furthermore, we make progress towards a conjecture of Aldous and Lyons by proving that these conditions are fulfilled for strictly subdiffusive recurrent unimodular graphs. Finally, we discuss the behaviour of the random walk conditioned to never return to the origin, which is well defined as a consequence of our results | Harnack inequality and one-endedness of UST on reversible random graphs |
Differential privacy (DP) has emerged as a de facto standard privacy notion for a wide range of applications. Since the meaning of data utility in different applications may vastly differ, a key challenge is to find the optimal randomization mechanism, i.e., the distribution and its parameters, for a given utility metric. Existing works have identified the optimal distributions in some special cases, while leaving all other utility metrics (e.g., usefulness and graph distance) as open problems. Since existing works mostly rely on manual analysis to examine the search space of all distributions, it would be an expensive process to repeat such efforts for each utility metric. To address such deficiency, we propose a novel approach that can automatically optimize different utility metrics found in diverse applications under a common framework. Our key idea that, by regarding the variance of the injected noise itself as a random variable, a two-fold distribution may approximately cover the search space of all distributions. Therefore, we can automatically find distributions in this search space to optimize different utility metrics in a similar manner, simply by optimizing the parameters of the two-fold distribution. Specifically, we define a universal framework, namely, randomizing the randomization mechanism of differential privacy (R$^2$DP), and we formally analyze its privacy and utility. Our experiments show that R$^2$DP can provide better results than the baseline distribution (Laplace) for several utility metrics with no known optimal distributions, whereas our results asymptotically approach to the optimality for utility metrics having known optimal distributions. As a side benefit, the added degree of freedom introduced by the two-fold distribution allows R$^2$DP to accommodate the preferences of both data owners and recipients. | R$^2$DP: A Universal and Automated Approach to Optimizing the Randomization Mechanisms of Differential Privacy for Utility Metrics with No Known Optimal Distributions |
We show experimentally that both single and multiple mechanical memories can be encoded in an amorphous bubble raft, a prototypical soft glass, subject to an oscillatory strain. In line with recent numerical results, we find that multiple memories can be formed sans external noise. By systematically investigating memory formation for a range of training strain amplitudes spanning yield, we find clear signatures of memory even beyond yielding. Most strikingly, the extent to which the system recollects memory is largest for training amplitudes near the yield strain and is a direct consequence of the spatial extent over which the system reorganizes during the encoding process. Our study further suggests that the evolution of force networks on training plays a decisive role in memory formation in jammed packings. | Strength of Mechanical Memories is Maximal at the Yield Point of a Soft Glass |
Residual networks (ResNets) represent a powerful type of convolutional neural network (CNN) architecture, widely adopted and used in various tasks. In this work we propose an improved version of ResNets. Our proposed improvements address all three main components of a ResNet: the flow of information through the network layers, the residual building block, and the projection shortcut. We are able to show consistent improvements in accuracy and learning convergence over the baseline. For instance, on ImageNet dataset, using the ResNet with 50 layers, for top-1 accuracy we can report a 1.19% improvement over the baseline in one setting and around 2% boost in another. Importantly, these improvements are obtained without increasing the model complexity. Our proposed approach allows us to train extremely deep networks, while the baseline shows severe optimization issues. We report results on three tasks over six datasets: image classification (ImageNet, CIFAR-10 and CIFAR-100), object detection (COCO) and video action recognition (Kinetics-400 and Something-Something-v2). In the deep learning era, we establish a new milestone for the depth of a CNN. We successfully train a 404-layer deep CNN on the ImageNet dataset and a 3002-layer network on CIFAR-10 and CIFAR-100, while the baseline is not able to converge at such extreme depths. Code is available at: https://github.com/iduta/iresnet | Improved Residual Networks for Image and Video Recognition |
Active stabilization in systems with zero or negative stiffness is an essential element of a wide variety of biological processes. We study a prototypical example of this phenomenon at a micro-scale and show how active rigidity, interpreted as a formation of a pseudo-well in the effective energy landscape, can be generated in an overdamped ratchet-type stochastic system. We link the transition from negative to positive rigidity with correlations in the noise and show that subtle differences in out-of-equilibrium driving may compromise the emergence of a pseudo-well. | Pseudo energy wells in active systems |
For the first time, a small dual-phase (liquid/gas) xenon time projection chamber was equipped with a top array of silicon photomultipliers for light and charge readout. Here we describe the instrument in detail, as well as the data processing and the event position reconstruction algorithms. We obtain a spatial resolution of ~1.5 mm in the horizontal plane. To characterise the detector performance, we show calibration data with internal $^{83\text{m}}$Kr and $^{37}$Ar sources, and we detail the production of the latter as well as its introduction into the system. We finally compare the observed light and charge yields down to electronic recoil energies of 2.82 keV to predictions based on NEST v2.0. | The first dual-phase xenon TPC equipped with silicon photomultipliers and characterisation with $^{37}$Ar |
The purpose of this paper is to model mathematically mechanical aspects of cardiac tissues. The latter constitute an elastic domain whose total volume remains constant. The time deformation of the heart tissue is modeled with the elastodynamics equations dealing with the displacement field as main unknown. These equations are coupled with a pressure whose variations characterize the heart beat. This pressure variable corresponds to a Lagrange multiplier associated with the so-called global injectivity condition. We derive the corresponding coupled system with nonhomogeneous boundary conditions where the pressure variable appears. For mathematical convenience a damping term is added, and for a given class of strain energies we prove the existence of local-in-time solutions in the context of the $L^p$-parabolic maximal regularity. | A damped elastodynamics system under the global injectivity condition: Local wellposedness in $L^p$-spaces |
Strong deviations in the finite temperature atomic structure of halide perovskites from their average geometry can have profound impacts on optoelectronic and other device-relevant properties. Detailed mechanistic understandings of these structural fluctuations and their consequences remain, however, limited by the experimental and theoretical challenges involved in characterizing strongly anharmonic vibrational characteristics and their impact on other properties. We overcome some of these challenges by a theoretical characterization of the vibrational interactions that occur among the atoms in the prototypical cubic CsPbBr$_3$. Our investigation based on first-principles molecular dynamics calculations finds that the motions of neighboring Cs-Br atoms interlock, which appears as the most likely Cs-Br distance being significantly shorter than what is inferred from an ideal cubic structure. This form of dynamic Cs-Br coupling coincides with very shallow dynamic potential wells for Br motions that occur across a locally and dynamically disordered energy landscape. We reveal an interesting dynamic coupling mechanism among the atoms within the nominal unit cell of cubic CsPbBr$_3$ and quantify the important local structural fluctuations on an atomic scale. | Probing the Disorder inside the Cubic Unit Cell of Halide Perovskites from First-Principles |
Factor models have been widely used in economics and finance. However, the heavy-tailed nature of macroeconomic and financial data is often neglected in the existing literature. To address this issue and achieve robustness, we propose an approach to estimate factor loadings and scores by minimizing the Huber loss function, which is motivated by the equivalence of conventional Principal Component Analysis (PCA) and the constrained least squares method in the factor model. We provide two algorithms that use different penalty forms. The first algorithm, which we refer to as Huber PCA, minimizes the $\ell_2$-norm-type Huber loss and performs PCA on the weighted sample covariance matrix. The second algorithm involves an element-wise type Huber loss minimization, which can be solved by an iterative Huber regression algorithm. Our study examines the theoretical minimizer of the element-wise Huber loss function and demonstrates that it has the same convergence rate as conventional PCA when the idiosyncratic errors have bounded second moments. We also derive their asymptotic distributions under mild conditions. Moreover, we suggest a consistent model selection criterion that relies on rank minimization to estimate the number of factors robustly. We showcase the benefits of Huber PCA through extensive numerical experiments and a real financial portfolio selection example. An R package named ``HDRFA" has been developed to implement the proposed robust factor analysis. | Huber Principal Component Analysis for Large-dimensional Factor Models |
We discuss the usefulness of quantum cloning and present examples of quantum computation tasks for which cloning offers an advantage which cannot be matched by any approach that does not resort to it. In these quantum computations, we need to distribute quantum information contained in states about which we have some partial information. To perform quantum computations, we use state-dependent probabilistic quantum cloning procedure to distribute quantum information in the middle of a quantum computation. | Probabilistically Cloning and Quantum Computation |
As is well known, both Weyl and Weitzenb\"ock spacetimes were initially used as attempts to geometrize the electromagnetic field. In this letter, we prove that this field can also be regarded as a geometrical quantity in an extended version of the Weitzenb\"ock spacetime. The new geometry encompasses features of both Weyl and Weitzenb\"ock spacetimes. In addition, we obtain Einstein's field equations coupled to the Maxwell energy-momentum tensor from a purely geometrical action and, to exemplify the advantage of using this new geometry when dealing with conformal invariance, we construct a model that is equivalent to a known conformal invariant teleparallel model. | An Extension of Teleparallelism and the Geometrization of the Electromagnetic Field |
The World Economic Forum (WEF) publishes annual reports on global risks which have the high impact on the world's economy. Currently, many researchers analyze the modeling and evolution of risks. However, few studies focus on validation of the global risk networks published by the WEF. In this paper, we first create a risk knowledge graph from the annotated risk events crawled from the Wikipedia. Then, we compare the relational dependencies of risks in the WEF and Wikipedia networks, and find that they share over 50% of their edges. Moreover, the edges unique to each network signify the different perspectives of the experts and the public on global risks. To reduce the cost of manual annotation of events triggering risk activation, we build an auto-detection tool which filters out over 80% media reported events unrelated to the global risks. In the process of filtering, our tool also continuously learns keywords relevant to global risks from the event sentences. Using locations of events extracted from the risk knowledge graph, we find characteristics of geographical distributions of the categories of global risks. | Supervised Learning of the Global Risk Network Activation from Media Event Reports |
We present an example of two isotopic but not strongly isotopic commutative semifields. This example shows that a recent result of Coulter and Henderson on semifield of order p^n, n odd, can not be generalized to the case n even. | A Note on the Isotopism of Commutative Semifields |
Manipulation tasks such as preparing a meal or assembling furniture remain highly challenging for robotics and vision. Traditional task and motion planning (TAMP) methods can solve complex tasks but require full state observability and are not adapted to dynamic scene changes. Recent learning methods can operate directly on visual inputs but typically require many demonstrations and/or task-specific reward engineering. In this work we aim to overcome previous limitations and propose a reinforcement learning (RL) approach to task planning that learns to combine primitive skills. First, compared to previous learning methods, our approach requires neither intermediate rewards nor complete task demonstrations during training. Second, we demonstrate the versatility of our vision-based task planning in challenging settings with temporary occlusions and dynamic scene changes. Third, we propose an efficient training of basic skills from few synthetic demonstrations by exploring recent CNN architectures and data augmentation. Notably, while all of our policies are learned on visual inputs in simulated environments, we demonstrate the successful transfer and high success rates when applying such policies to manipulation tasks on a real UR5 robotic arm. | Learning to combine primitive skills: A step towards versatile robotic manipulation |
Knowledge graph (KG) enhanced recommendation has demonstrated improved performance in the recommendation system (RecSys) and attracted considerable research interest. Recently the literature has adopted neural graph networks (GNNs) on the collaborative knowledge graph and built an end-to-end KG-enhanced RecSys. However, the majority of these approaches have three limitations: (1) treat the collaborative knowledge graph as a homogeneous graph and overlook the highly heterogeneous relationships among items, (2) lack of design to explicitly leverage the rich side information, and (3) overlook the rich knowledge in user preference. To fill this gap, in this paper, we explore the rich, heterogeneous relationship among items and propose a new KG-enhanced recommendation model called Collaborative Meta-Knowledge Enhanced Recommender System (MetaKRec). In particular, we focus on modeling the rich, heterogeneous semantic relationships among items and construct several collaborative Meta-KGs to explicitly depict the relatedness of the items under the guidance of meta-knowledge. In addition to the knowledge obtained from KG, we leverage user knowledge that extracts from user preference to construct the Meta-KGs. The constructed Meta-KGs can capture the knowledge from both the knowledge graph and user preference. Furthermore. we utilize a light convolution encoder to recursively integrate the item relationship in each collaborative Meta-KGs. This scheme allows us to explicitly gather the heterogeneous semantic relationships among items and encode them into the representations of items. In addition, we propose channel attention to fuse the item and user representations from different Meta-KGs. Extensive experiments are conducted on four real-world benchmark datasets, demonstrating significant gains over the state-of-the-art baselines on both regular and cold-start recommendation settings. | MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System |
This report presents our submission to the MS COCO Captioning Challenge 2015. The method uses Convolutional Neural Network activations as an embedding to find semantically similar images. From these images, the most typical caption is selected based on unigram frequencies. Although the method received low scores with automated evaluation metrics and in human assessed average correctness, it is competitive in the ratio of captions which pass the Turing test and which are assessed as better or equal to human captions. | Technical Report: Image Captioning with Semantically Similar Images |
Rewards typically express desirabilities or preferences over a set of alternatives. Here we propose that rewards can be defined for any probability distribution based on three desiderata, namely that rewards should be real-valued, additive and order-preserving, where the latter implies that more probable events should also be more desirable. Our main result states that rewards are then uniquely determined by the negative information content. To analyze stochastic processes, we define the utility of a realization as its reward rate. Under this interpretation, we show that the expected utility of a stochastic process is its negative entropy rate. Furthermore, we apply our results to analyze agent-environment interactions. We show that the expected utility that will actually be achieved by the agent is given by the negative cross-entropy from the input-output (I/O) distribution of the coupled interaction system and the agent's I/O distribution. Thus, our results allow for an information-theoretic interpretation of the notion of utility and the characterization of agent-environment interactions in terms of entropy dynamics. | A conversion between utility and information |
This work put forward a comprehensive study of moire pattern in commensurate twisted bilayer graphene (TBG) to determine the connection of moire period with corresponding twist angle. Using the understanding of moire pattern, computational codes are developed to simulate the planar positions of carbon atoms lying in a large specimen of commensurate twisted bilayer graphene (CTBG) with any commensurate twist angle. With the help of simulated moire patterns of CTBG it is demonstrated that for many commensurate twist angles the apparent moire period may be quite different from the actual moire period, and the same moire pattern may have multiple slightly different values of the apparent moire period. These multiple slightly different values of the apparent moire period show that strain and broken rotational symmetry in moire pattern of CTBG are intrinsic. From various values of apparent moire period, the apparent strain in moire pattern of CTBG is calculated for many commensurate twist angles; the calculated values of apparent strain are in good agreement with experimentally reported values. Taking some insight from available experimental data related to twisted bilayer graphene systems and conventional bilayer graphene systems, corrugation in CTBG is modelled and incorporated with the simulated positions of carbon atoms. | Twist Angle, Strain, Broken Rotational Symmetry, Corrugation and Supercell in Twisted Bilayer Graphene |
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