title
stringlengths 7
239
| abstract
stringlengths 7
2.76k
| cs
int64 0
1
| phy
int64 0
1
| math
int64 0
1
| stat
int64 0
1
| quantitative biology
int64 0
1
| quantitative finance
int64 0
1
|
|---|---|---|---|---|---|---|---|
Parallel implementation of the coupled harmonic oscillator | This article presents the parallel implementation of the coupled harmonic
oscillator. From the analytical solution of the coupled harmonic oscillator,
the design parameters are obtained. After that, a numerical integration of the
system with MATLAB, which is used as a tool of benchmark evaluation, is
performed. Next, parallel implementation is performed using a well-known
approach like OpenMP and WinAPI. Taking into account the errors of basic
parameters of the simulated process, the generated oscillations of the proposed
parallel realization are almost identical to the actual solution of the
harmonic oscillator model. Test ways to optimize the parallel architecture of
computing processes for software implementations of the considered application
is carried out. The developed model is used to study a fixed priority
scheduling algorithm for real-time parallel threads execution. The proposed
parallel implementation of the considered dynamic system has an independent
value and can be considered as a test for determining the characteristics of
multi-core systems for time-critical simulation problems. Keywords: Harmonic
oscillator, model, SMP, parallel programming, OpenMP;
| 1 | 0 | 0 | 0 | 0 | 0 |
TiEV: The Tongji Intelligent Electric Vehicle in the Intelligent Vehicle Future Challenge of China | TiEV is an autonomous driving platform implemented by Tongji University of
China. The vehicle is drive-by-wire and is fully powered by electricity. We
devised the software system of TiEV from scratch, which is capable of driving
the vehicle autonomously in urban paths as well as on fast express roads. We
describe our whole system, especially novel modules of probabilistic perception
fusion, incremental mapping, the 1st and the 2nd planning and the overall
safety concern. TiEV finished 2016 and 2017 Intelligent Vehicle Future
Challenge of China held at Changshu. We show our experiences on the development
of autonomous vehicles and future trends.
| 1 | 0 | 0 | 0 | 0 | 0 |
Towards Decoding as Continuous Optimization in Neural Machine Translation | We propose a novel decoding approach for neural machine translation (NMT)
based on continuous optimisation. We convert decoding - basically a discrete
optimization problem - into a continuous optimization problem. The resulting
constrained continuous optimisation problem is then tackled using
gradient-based methods. Our powerful decoding framework enables decoding
intractable models such as the intersection of left-to-right and right-to-left
(bidirectional) as well as source-to-target and target-to-source (bilingual)
NMT models. Our empirical results show that our decoding framework is
effective, and leads to substantial improvements in translations generated from
the intersected models where the typical greedy or beam search is not feasible.
We also compare our framework against reranking, and analyse its advantages and
disadvantages.
| 1 | 0 | 0 | 0 | 0 | 0 |
A tail cone version of the Halpern-Läuchli theorem at a large cardinal | The classical Halpern-Läuchli theorem states that for any finite coloring
of a finite product of finitely branching perfect trees of height $\omega$,
there exist strong subtrees sharing the same level set such that tuples
consisting of elements lying on the same level get the same color. Relative to
large cardinals, we establish the consistency of a tail cone version of the
Halpern-Läuchli theorem at large cardinal, which, roughly speaking, deals
with many colorings simultaneously and diagonally. Among other applications, we
generalize a polarized partition relation on rational numbers due to Laver and
Galvin to one on linear orders of larger saturation.
| 0 | 0 | 1 | 0 | 0 | 0 |
Over the Air Deep Learning Based Radio Signal Classification | We conduct an in depth study on the performance of deep learning based radio
signal classification for radio communications signals. We consider a rigorous
baseline method using higher order moments and strong boosted gradient tree
classification and compare performance between the two approaches across a
range of configurations and channel impairments. We consider the effects of
carrier frequency offset, symbol rate, and multi-path fading in simulation and
conduct over-the-air measurement of radio classification performance in the lab
using software radios and compare performance and training strategies for both.
Finally we conclude with a discussion of remaining problems, and design
considerations for using such techniques.
| 1 | 0 | 0 | 0 | 0 | 0 |
On conditional parity as a notion of non-discrimination in machine learning | We identify conditional parity as a general notion of non-discrimination in
machine learning. In fact, several recently proposed notions of
non-discrimination, including a few counterfactual notions, are instances of
conditional parity. We show that conditional parity is amenable to statistical
analysis by studying randomization as a general mechanism for achieving
conditional parity and a kernel-based test of conditional parity.
| 1 | 0 | 0 | 1 | 0 | 0 |
A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints | We consider caching in cellular networks in which each base station is
equipped with a cache that can store a limited number of files. The popularity
of the files is known and the goal is to place files in the caches such that
the probability that a user at an arbitrary location in the plane will find the
file that she requires in one of the covering caches is maximized.
We develop distributed asynchronous algorithms for deciding which contents to
store in which cache. Such cooperative algorithms require communication only
between caches with overlapping coverage areas and can operate in asynchronous
manner. The development of the algorithms is principally based on an
observation that the problem can be viewed as a potential game. Our basic
algorithm is derived from the best response dynamics. We demonstrate that the
complexity of each best response step is independent of the number of files,
linear in the cache capacity and linear in the maximum number of base stations
that cover a certain area. Then, we show that the overall algorithm complexity
for a discrete cache placement is polynomial in both network size and catalog
size. In practical examples, the algorithm converges in just a few iterations.
Also, in most cases of interest, the basic algorithm finds the best Nash
equilibrium corresponding to the global optimum. We provide two extensions of
our basic algorithm based on stochastic and deterministic simulated annealing
which find the global optimum.
Finally, we demonstrate the hit probability evolution on real and synthetic
networks numerically and show that our distributed caching algorithm performs
significantly better than storing the most popular content, probabilistic
content placement policy and Multi-LRU caching policies.
| 1 | 0 | 0 | 0 | 0 | 0 |
Linear, Second order and Unconditionally Energy Stable schemes for a phase-field moving contact line Model | In this paper, we consider the numerical approximations for solving a
hydrodynamics coupled phase field model consisting of incompressible
Navier-Stokes equations with generalized Navier boundary conditions, and the
Cahn-Hilliard equation with dynamic moving contact line boundary conditions.
The main challenging issue for solving this model numerically is the time
marching problem, i.e., how to develop suitable higher order temporal schemes
while preserving the unconditional energy stability at the discrete level. We
solve this issue by developing two linear, second-order schemes based on the
"Invariant Energy Quadratization" method for the nonlinear terms in the bulk
and on the boundary, the projection method for the Navier-Stokes equations, and
a subtle implicit-explicit treatment for the stress and convective terms.
Rigorous proofs of the well-posedness of the linear system and the
unconditional energy stabilities are provided. A spectral-Galerkin spatial
discretization is implemented and various numerical results are presented to
verify the second order accuracy and the efficiency of the proposed schemes.
| 0 | 0 | 1 | 0 | 0 | 0 |
On Security and Sparsity of Linear Classifiers for Adversarial Settings | Machine-learning techniques are widely used in security-related applications,
like spam and malware detection. However, in such settings, they have been
shown to be vulnerable to adversarial attacks, including the deliberate
manipulation of data at test time to evade detection. In this work, we focus on
the vulnerability of linear classifiers to evasion attacks. This can be
considered a relevant problem, as linear classifiers have been increasingly
used in embedded systems and mobile devices for their low processing time and
memory requirements. We exploit recent findings in robust optimization to
investigate the link between regularization and security of linear classifiers,
depending on the type of attack. We also analyze the relationship between the
sparsity of feature weights, which is desirable for reducing processing cost,
and the security of linear classifiers. We further propose a novel octagonal
regularizer that allows us to achieve a proper trade-off between them. Finally,
we empirically show how this regularizer can improve classifier security and
sparsity in real-world application examples including spam and malware
detection.
| 1 | 0 | 0 | 0 | 0 | 0 |
Sharp-interface limits of a phase-field model with a generalized Navier slip boundary condition for moving contact lines | The sharp-interface limits of a phase-field model with a generalized Navier
slip boundary condition for moving contact line problem are studied by
asymptotic analysis and numerical simulations. The effects of the {mobility}
number as well as a phenomenological relaxation parameter in the boundary
condition are considered. In asymptotic analysis, we focus on the case that the
{mobility} number is the same order of the Cahn number and derive the
sharp-interface limits for several setups of the boundary relaxation parameter.
It is shown that the sharp interface limit of the phase field model is the
standard two-phase incompressible Navier-Stokes equations coupled with several
different slip boundary conditions. Numerical results are consistent with the
analysis results and also illustrate the different convergence rates of the
sharp-interface limits for different scalings of the two parameters.
| 0 | 1 | 0 | 0 | 0 | 0 |
Notes on Discrete Compound Poisson Point Process and Its Concentration Inequalities | The first part of this notes provides a new characterization for discrete
compound Poisson point process (proposed by {Acz{é}l}
[Acta~Math.~Hungar.~3(3)(1952), 219-224.]), which extends the characterization
of Poisson point process given by Copeland and Regan [Ann.~Math.~(1936):
357-362.]. Next, we derive some concentration inequalities for discrete
compound Poisson random variable and discrete compound Poisson point process
(Poisson and negative binomial are the special cases). These concentration
inequalities are potentially useful. In high-dimensional negative binomial
regression with weighted Lasso penalty, we give the application that KKT
conditions of penalized likelihood holds with high probability.
| 0 | 0 | 1 | 1 | 0 | 0 |
Characteristic cycles of highest weight Harish-Chandra modules | Characteristic cycles and leading term cycles of irreducible highest weight
Harish-Chandra modules of regular integral infinitesimal character are
determined. In the simply laced cases they are irreducible, but in the
nonsimply laced cases they are more complicated.
| 0 | 0 | 1 | 0 | 0 | 0 |
Assessing the effect of advertising expenditures upon sales: a Bayesian structural time series model | We propose a robust implementation of the Nerlove--Arrow model using a
Bayesian structural time series model to explain the relationship between
advertising expenditures of a country-wide fast-food franchise network with its
weekly sales. Thanks to the flexibility and modularity of the model, it is well
suited to generalization to other markets or situations. Its Bayesian nature
facilitates incorporating \emph{a priori} information (the manager's views),
which can be updated with relevant data. This aspect of the model will be used
to present a strategy of budget scheduling across time and channels.
| 0 | 0 | 0 | 1 | 0 | 1 |
Anytime Exact Belief Propagation | Statistical Relational Models and, more recently, Probabilistic Programming,
have been making strides towards an integration of logic and probabilistic
reasoning. A natural expectation for this project is that a probabilistic logic
reasoning algorithm reduces to a logic reasoning algorithm when provided a
model that only involves 0-1 probabilities, exhibiting all the advantages of
logic reasoning such as short-circuiting, intelligibility, and the ability to
provide proof trees for a query answer. In fact, we can take this further and
require that these characteristics be present even for probabilistic models
with probabilities \emph{near} 0 and 1, with graceful degradation as the model
becomes more uncertain. We also seek inference that has amortized constant time
complexity on a model's size (even if still exponential in the induced width of
a more directly relevant portion of it) so that it can be applied to huge
knowledge bases of which only a relatively small portion is relevant to typical
queries. We believe that, among the probabilistic reasoning algorithms, Belief
Propagation is the most similar to logic reasoning: messages are propagated
among neighboring variables, and the paths of message-passing are similar to
proof trees. However, Belief Propagation is either only applicable to tree
models, or approximate (and without guarantees) for precision and convergence.
In this paper we present work in progress on an Anytime Exact Belief
Propagation algorithm that is very similar to Belief Propagation but is exact
even for graphical models with cycles, while exhibiting soft short-circuiting,
amortized constant time complexity in the model size, and which can provide
probabilistic proof trees.
| 1 | 0 | 0 | 0 | 0 | 0 |
Appropriate conditions to realize a $p$-wave superfluid state starting from a spin-orbit coupled $s$-wave superfluid Fermi gas | We theoretically investigate a spin-orbit coupled $s$-wave superfluid Fermi
gas, to examine the time evolution of the system, after an $s$-wave pairing
interaction is replaced by a $p$-wave one at $t=0$. In our recent paper, we
proposed that this manipulation may realize a $p$-wave superfluid Fermi gas,
because the $p$-wave pair amplitude that is induced in the $s$-wave superfluid
state by a parity-broken antisymmetric spin-orbit interaction gives a
non-vanishing $p$-wave superfluid order parameter, immediately after the
$p$-wave interaction is turned on. In this paper, using a time-dependent
Bogoliubov-de Gennes theory, we assess this idea under various conditions with
respect to the $s$-wave and $p$-wave interaction strengths, as well as the
spin-orbit coupling strength. From these, we clarify that the momentum
distribution of Fermi atoms in the initial $s$-wave state ($t<0$) is a key to
produce a large $p$-wave superfluid order parameter. Since the realization of a
$p$-wave superfluid state is one of the most exciting and difficult challenges
in cold Fermi gas physics, our results may provide a possible way to accomplish
this.
| 0 | 1 | 0 | 0 | 0 | 0 |
On the vanishing of self extensions over Cohen-Macaulay local rings | The celebrated Auslander-Reiten Conjecture, on the vanishing of self
extensions of a module, is one of the long-standing conjectures in ring theory.
Although it is still open, there are several results in the literature that
establish the conjecture over Gorenstein rings under certain conditions. The
purpose of this article is to obtain extensions of such results over
Cohen-Macaulay local rings that admit canonical modules. In particular, our
main result recovers theorems of Araya, and Ono and Yoshino simultaneously.
| 0 | 0 | 1 | 0 | 0 | 0 |
Finite Temperature Phase Diagrams of a Two-band Model of Superconductivity | We explore the temperature effects in the superconducting phases of a
hybridized two-band system. We show that for zero hybridization between the
bands, there are two different critical temperatures. However, for any finite
hybridization there are only one critical temperature at which the two gaps
vanish simultaneously. We construct the phase diagrams of the critical
temperature versus hybridization parameter $\alpha$ and critical temperature
versus critical chemical potential asymmetry $\delta \mu$ between the bands,
identifying the superconductor and normal phases in the system. We find an
interesting reentrant behavior in the superconducting phase as the parameters
$\alpha$ or $\delta \mu$, which drive the phase transitions, increase. We also
find that for optimal values of both $\alpha$ and $\delta \mu$ there is a
significant enhancement of the critical temperature of the model.
| 0 | 1 | 0 | 0 | 0 | 0 |
Detecting Multiple Change Points Using Adaptive Regression Splines with Application to Neural Recordings | Time series, as frequently the case in neuroscience, are rarely stationary,
but often exhibit abrupt changes due to attractor transitions or bifurcations
in the dynamical systems producing them. A plethora of methods for detecting
such change points in time series statistics have been developed over the
years, in addition to test criteria to evaluate their significance. Issues to
consider when developing change point analysis methods include computational
demands, difficulties arising from either limited amount of data or a large
number of covariates, and arriving at statistical tests with sufficient power
to detect as many changes as contained in potentially high-dimensional time
series. Here, a general method called Paired Adaptive Regressors for Cumulative
Sum is developed for detecting multiple change points in the mean of
multivariate time series. The method's advantages over alternative approaches
are demonstrated through a series of simulation experiments. This is followed
by a real data application to neural recordings from rat medial prefrontal
cortex during learning. Finally, the method's flexibility to incorporate useful
features from state-of-the-art change point detection techniques is discussed,
along with potential drawbacks and suggestions to remedy them.
| 0 | 0 | 0 | 0 | 1 | 0 |
The Automorphism Group of Hall's Universal Group | We study the automorphism group of Hall's universal locally finite group $H$.
We show that in $Aut(H)$ every subgroup of index $< 2^\omega$ lies between the
pointwise and the setwise stabilizer of a unique finite subgroup $A$ of $H$,
and use this to prove that $Aut(H)$ is complete. We further show that $Inn(H)$
is the largest locally finite normal subgroup of $Aut(H)$. Finally, we observe
that from the work of [Sh:312] it follows that for every countable locally
finite $G$ there exists $G \cong G' \leq H$ such that every $f \in Aut(G')$
extends to an $\hat{f} \in Aut(H)$ in such a way that $f \mapsto \hat{f}$
embeds $Aut(G')$ into $Aut(H)$. In particular, we solve the three open
questions of Hickin on $Aut(H)$ from [3], and give a partial answer to Question
VI.5 of Kegel and Wehrfritz from [6].
| 0 | 0 | 1 | 0 | 0 | 0 |
On Atiyah-Singer and Atiyah-Bott for finite abstract simplicial complexes | A linear or multi-linear valuation on a finite abstract simplicial complex
can be expressed as an analytic index dim(ker(D)) -dim(ker(D^*)) of a
differential complex D:E -> F. In the discrete, a complex D can be called
elliptic if a McKean-Singer spectral symmetry applies as this implies
str(exp(-t D^2)) is t-independent. In that case, the analytic index of D is the
sum of (-1)^k b_k(D), where b_k(D) is the k'th Betti number, which by Hodge is
the nullity of the (k+1)'th block of the Hodge operator L=D^2. It can also be
written as a topological index summing K(v) over the set of zero-dimensional
simplices in G and where K is an Euler type curvature defined by G and D. This
can be interpreted as a Atiyah-Singer type correspondence between analytic and
topological index. Examples are the de Rham differential complex for the Euler
characteristic X(G) or the connection differential complex for Wu
characteristic w_k(G). Given an endomorphism T of an elliptic complex, the
Lefschetz number X(T,G,D) is defined as the super trace of T acting on
cohomology defined by E. It is equal to the sum i(v) over V which are contained
in fixed simplices of T, and i is a Brouwer type index. This Atiyah-Bott result
generalizes the Brouwer-Lefschetz fixed point theorem for an endomorphism of
the simplicial complex G. In both the static and dynamic setting, the proof is
done by heat deforming the Koopman operator U(T) to get the cohomological
picture str(exp(-t D^2) U(T)) in the limit t to infinity and then use Hodge,
and then by applying a discrete gradient flow to the simplex data defining the
valuation to push str(U(T)) to V, getting curvature K(v) or the Brouwer type
index i(v).
| 1 | 0 | 1 | 0 | 0 | 0 |
Evolution of macromolecular structure: a 'double tale' of biological accretion | The evolution of structure in biology is driven by accretion and change.
Accretion brings together disparate parts to form bigger wholes. Change
provides opportunities for growth and innovation. Here we review patterns and
processes that are responsible for a 'double tale' of evolutionary accretion at
various levels of complexity, from proteins and nucleic acids to high-rise
building structures in cities. Parts are at first weakly linked and associate
variously. As they diversify, they compete with each other and are selected for
performance. The emerging interactions constrain their structure and
associations. This causes parts to self-organize into modules with tight
linkage. In a second phase, variants of the modules evolve and become new parts
for a new generative cycle of higher-level organization. Evolutionary genomics
and network biology support the 'double tale' of structural module creation and
validate an evolutionary principle of maximum abundance that drives the gain
and loss of modules.
| 0 | 0 | 0 | 0 | 1 | 0 |
An estimate of the root mean square error incurred when approximating an $f \in L^2({\mathbb{R}})$ by a partial sum of its Hermite series | Let $f$ be a band-limited function in $L^2({\mathbb{R}})$. Fix $T >0$ and
suppose $f^{\prime}$ exists and is integrable on $[-T, T]$. This paper gives a
concrete estimate of the error incurred when approximating $f$ in the root mean
square by a partial sum of its Hermite series.
Specifically, we show, for $K=2n, \quad n \in Z_+,$
$$
\left[\frac{1}{2T}\int_{-T}^T[f(t)-(S_Kf)(t)]^2dt\right]^{1/2}\leq
\left(1+\frac 1K\right)\left(\left[ \frac{1}{2T}\int_{|t|>
T}f(t)^2dt\right]^{1/2} +\left[\frac{1}{2T} \int_{|\omega|>N}|\hat
f(\omega)|^2d\omega\right]^{1/2} \right)
+\frac{1}{K}\left[\frac{1}{2T}\int_{|t|\leq T}f_N(t)^2dt\right]^{1/2}
+\frac{1}{\pi}\left(1+\frac{1}{2K}\right)S_a(K,T), $$ in which $S_Kf$ is the
$K$-th partial sum of the Hermite series of $f, \hat f $ is the Fourier
transform of $f$, $\displaystyle{N=\frac{\sqrt{2K+1}+% \sqrt{2K+3}}{2}}$ and
$f_N=(\hat f
\chi_{(-N,N)})^\vee(t)=\frac{1}{\pi}\int_{-\infty}^{\infty}\frac{\sin
(N(t-s))}{t-s}f(s)ds$. An explicit upper bound is obtained for $S_{a}(K,T)$.
| 0 | 0 | 1 | 0 | 0 | 0 |
Learning Topic-Sensitive Word Representations | Distributed word representations are widely used for modeling words in NLP
tasks. Most of the existing models generate one representation per word and do
not consider different meanings of a word. We present two approaches to learn
multiple topic-sensitive representations per word by using Hierarchical
Dirichlet Process. We observe that by modeling topics and integrating topic
distributions for each document we obtain representations that are able to
distinguish between different meanings of a given word. Our models yield
statistically significant improvements for the lexical substitution task
indicating that commonly used single word representations, even when combined
with contextual information, are insufficient for this task.
| 1 | 0 | 0 | 0 | 0 | 0 |
Celestial Walk: A Terminating Oblivious Walk for Convex Subdivisions | We present a new oblivious walking strategy for convex subdivisions. Our walk
is faster than the straight walk and more generally applicable than the
visibility walk. To prove termination of our walk we use a novel monotonically
decreasing distance measure.
| 1 | 0 | 0 | 0 | 0 | 0 |
Kernel k-Groups via Hartigan's Method | Energy statistics was proposed by Székely in the 80's inspired by
Newton's gravitational potential in classical mechanics, and it provides a
model-free hypothesis test for equality of distributions. In its original form,
energy statistics was formulated in Euclidean spaces. More recently, it was
generalized to metric spaces of negative type. In this paper, we consider a
formulation for the clustering problem using a weighted version of energy
statistics in spaces of negative type. We show that this approach leads to a
quadratically constrained quadratic program in the associated kernel space,
establishing connections with graph partitioning problems and kernel methods in
unsupervised machine learning. To find local solutions of such an optimization
problem, we propose an extension of Hartigan's method to kernel spaces. Our
method has the same computational cost as kernel k-means algorithm, which is
based on Lloyd's heuristic, but our numerical results show an improved
performance, especially in high dimensions.
| 1 | 0 | 1 | 1 | 0 | 0 |
Estimators of the correlation coefficient in the bivariate exponential distribution | A finite-support constraint on the parameter space is used to derive a lower
bound on the error of an estimator of the correlation coefficient in the
bivariate exponential distribution. The bound is then exploited to examine
optimality of three estimators, each being a nonlinear function of moments of
exponential or Rayleigh observables. The estimator based on a measure of cosine
similarity is shown to be highly efficient for values of the correlation
coefficient greater than 0.35; for smaller values, however, it is the
transformed Pearson correlation coefficient that exhibits errors closer to the
derived bound.
| 0 | 0 | 0 | 1 | 0 | 0 |
A theoretical framework for retinal computations: insights from textbook knowledge | Neural circuits in the retina divide the incoming visual scene into more than
a dozen distinct representations that are sent on to central brain areas, such
as the lateral geniculate nucleus and the superior colliculus. The retina can
be viewed as a parallel image processor made of a multitude of small
computational devices. Neural circuits of the retina are constituted by various
cell types that separate the incoming visual information in different channels.
Visual information is processed by retinal neural circuits and several
computations are performed extracting distinct features from the visual scene.
The aim of this article is to understand the computational basis involved in
processing visual information which finally leads to several feature detectors.
Therefore, the elements that form the basis of retinal computations will be
explored by explaining how oscillators can lead to a final output with
computational meaning. Linear versus nonlinear systems will be presented and
the retina will be placed in the context of a nonlinear system. Finally,
simulations will be presented exploring the concept of the retina as a
nonlinear system which can perform understandable computations converting a
known input into a predictable output.
| 0 | 0 | 0 | 0 | 1 | 0 |
Learning to Associate Words and Images Using a Large-scale Graph | We develop an approach for unsupervised learning of associations between
co-occurring perceptual events using a large graph. We applied this approach to
successfully solve the image captcha of China's railroad system. The approach
is based on the principle of suspicious coincidence. In this particular
problem, a user is presented with a deformed picture of a Chinese phrase and
eight low-resolution images. They must quickly select the relevant images in
order to purchase their train tickets. This problem presents several
challenges: (1) the teaching labels for both the Chinese phrases and the images
were not available for supervised learning, (2) no pre-trained deep
convolutional neural networks are available for recognizing these Chinese
phrases or the presented images, and (3) each captcha must be solved within a
few seconds. We collected 2.6 million captchas, with 2.6 million deformed
Chinese phrases and over 21 million images. From these data, we constructed an
association graph, composed of over 6 million vertices, and linked these
vertices based on co-occurrence information and feature similarity between
pairs of images. We then trained a deep convolutional neural network to learn a
projection of the Chinese phrases onto a 230-dimensional latent space. Using
label propagation, we computed the likelihood of each of the eight images
conditioned on the latent space projection of the deformed phrase for each
captcha. The resulting system solved captchas with 77% accuracy in 2 seconds on
average. Our work, in answering this practical challenge, illustrates the power
of this class of unsupervised association learning techniques, which may be
related to the brain's general strategy for associating language stimuli with
visual objects on the principle of suspicious coincidence.
| 1 | 0 | 0 | 0 | 0 | 0 |
A dichotomy theorem for nonuniform CSPs | In this paper we prove the Dichotomy Conjecture on the complexity of
nonuniform constraint satisfaction problems posed by Feder and Vardi.
| 1 | 0 | 0 | 0 | 0 | 0 |
Transition from Weak Wave Turbulence to Soliton-Gas | We report an experimental investigation of the effect of finite depth on the
statistical properties of wave turbulence at the surface of water in the
gravity-capillary range. We tune the wave dispersion and the level of
nonlinearity by modifying the depth of water and the forcing respectively. We
use space-time resolved profilometry to reconstruct the deformed surface of
water. When decreasing the water depth, we observe a drastic transition between
weak turbulence at the weakest forcing and a solitonic regime at stronger
forcing. We characterize the transition between both states by studying their
Fourier Spectra. We also study the efficiency of energy transfer in the weak
turbulence regime. We report a loss of efficiency of angular transfer as the
dispersion of the wave is reduced until the system bifurcates into the
solitonic regime.
| 0 | 1 | 0 | 0 | 0 | 0 |
Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model | A model-based approach to forecasting chaotic dynamical systems utilizes
knowledge of the physical processes governing the dynamics to build an
approximate mathematical model of the system. In contrast, machine learning
techniques have demonstrated promising results for forecasting chaotic systems
purely from past time series measurements of system state variables (training
data), without prior knowledge of the system dynamics. The motivation for this
paper is the potential of machine learning for filling in the gaps in our
underlying mechanistic knowledge that cause widely-used knowledge-based models
to be inaccurate. Thus we here propose a general method that leverages the
advantages of these two approaches by combining a knowledge-based model and a
machine learning technique to build a hybrid forecasting scheme. Potential
applications for such an approach are numerous (e.g., improving weather
forecasting). We demonstrate and test the utility of this approach using a
particular illustrative version of a machine learning known as reservoir
computing, and we apply the resulting hybrid forecaster to a low-dimensional
chaotic system, as well as to a high-dimensional spatiotemporal chaotic system.
These tests yield extremely promising results in that our hybrid technique is
able to accurately predict for a much longer period of time than either its
machine-learning component or its model-based component alone.
| 0 | 0 | 0 | 1 | 0 | 0 |
Field-free perpendicular magnetization switching through domain wall motion in Pt/Co/Cr racetracks by spin orbit torques with the assistance of accompanying Joule heating effect | Heavy metal/ferromagnetic layers with perpendicular magnetic anisotropy (PMA)
have potential applications for high-density information storage in racetrack
memories and nonvolatile magnetic random access memories. Writing and erasing
of information in these devices are carried out by domain wall (DW) motion and
deterministic magnetization switching via electric current generated spin
orbital torques (SOTs) with an assistance of in-plane bias field to break the
symmetry. Improvements in energy efficiency could be obtained when the
switching of perpendicular magnetization is controlled by an electric current
generated SOTs without the in-plane bias fields. Here, we report on reversible
electric-current-driven magnetization switching through DW motion in Pt/Co/Cr
trilayers with PMA at room temperature due to the formation of homochiral
Neel-type domain, in which an in-plane effective Dzyaloshinskii-Moriya
interaction field exists. Fully deterministic magnetic magnetization switching
in this trilayers is based on the enhancement of SOTs from a dedicated design
of Pt/Co/Cr structures with two heavy metals Pt and Cr which show the opposite
sign of spin Hall angles. We also demonstrated that the simultaneously
accompanying Joule heating effect also plays a key role for field-free
magnetization switching through the decrease of the propagation field.
| 0 | 1 | 0 | 0 | 0 | 0 |
On Generalizing Decidable Standard Prefix Classes of First-Order Logic | Recently, the separated fragment (SF) of first-order logic has been
introduced. Its defining principle is that universally and existentially
quantified variables may not occur together in atoms. SF properly generalizes
both the Bernays-Schönfinkel-Ramsey (BSR) fragment and the relational monadic
fragment. In this paper the restrictions on variable occurrences in SF
sentences are relaxed such that universally and existentially quantified
variables may occur together in the same atom under certain conditions. Still,
satisfiability can be decided. This result is established in two ways: firstly,
by an effective equivalence-preserving translation into the BSR fragment, and,
secondly, by a model-theoretic argument.
Slight modifications to the described concepts facilitate the definition of
other decidable classes of first-order sentences. The paper presents a second
fragment which is novel, has a decidable satisfiability problem, and properly
contains the Ackermann fragment and---once more---the relational monadic
fragment. The definition is again characterized by restrictions on the
occurrences of variables in atoms. More precisely, after certain
transformations, Skolemization yields only unary functions and constants, and
every atom contains at most one universally quantified variable. An effective
satisfiability-preserving translation into the monadic fragment is devised and
employed to prove decidability of the associated satisfiability problem.
| 1 | 0 | 0 | 0 | 0 | 0 |
Poisson traces, D-modules, and symplectic resolutions | We survey the theory of Poisson traces (or zeroth Poisson homology) developed
by the authors in a series of recent papers. The goal is to understand this
subtle invariant of (singular) Poisson varieties, conditions for it to be
finite-dimensional, its relationship to the geometry and topology of symplectic
resolutions, and its applications to quantizations. The main technique is the
study of a canonical D-module on the variety. In the case the variety has
finitely many symplectic leaves (such as for symplectic singularities and
Hamiltonian reductions of symplectic vector spaces by reductive groups), the
D-module is holonomic, and hence the space of Poisson traces is
finite-dimensional. As an application, there are finitely many irreducible
finite-dimensional representations of every quantization of the variety.
Conjecturally, the D-module is the pushforward of the canonical D-module under
every symplectic resolution of singularities, which implies that the space of
Poisson traces is dual to the top cohomology of the resolution. We explain many
examples where the conjecture is proved, such as symmetric powers of du Val
singularities and symplectic surfaces and Slodowy slices in the nilpotent cone
of a semisimple Lie algebra. We compute the D-module in the case of surfaces
with isolated singularities, and show it is not always semisimple. We also
explain generalizations to arbitrary Lie algebras of vector fields, connections
to the Bernstein-Sato polynomial, relations to two-variable special polynomials
such as Kostka polynomials and Tutte polynomials, and a conjectural
relationship with deformations of symplectic resolutions. In the appendix we
give a brief recollection of the theory of D-modules on singular varieties that
we require.
| 0 | 0 | 1 | 0 | 0 | 0 |
Nonequilibrium transport and Electron-Glass effects in thin GexTe films | We report on results of nonequilibrium transport measurements made on thin
films of germanium-telluride (Ge_xTe) at cryogenic temperatures. Owing to a
rather large deviation from stoichiometry (app. 10% of Ge vacancies), these
films exhibit p-type conductivity with carrier-concentration N>10^20cm^(-3) and
can be made either in the diffusive or strongly-localized regime by a judicious
choice of preparation and post-treatment conditions. In both regimes the system
shows persistent photoconductivity following excitation by a brief exposure to
infrared radiation. Persistent photoconductivity is also observed in GexTe
samples alloyed with Mn. However, in both Ge_xTe and GeMn_xTe_y the effect is
much weaker than that observable in GeSb_xTe_y alloys suggesting that antimony
plays an important role in the phenomenon. Structural studies of these films
reveal an unusual degree of texture that is rarely realized in
strongly-disordered systems with high carrier-concentrations.
Anderson-localized samples of Ge_xTe exhibit non-ergodic transport which are
characteristic of intrinsic electron-glasses, including a well developed
memory-dip and slow relaxation of the excess conductance created in the excited
state. These results support the conjecture that electron-glass effects with
inherently long relaxation times is a generic property of all
Anderson-localized systems with large carrier-concentration.
| 0 | 1 | 0 | 0 | 0 | 0 |
Non-Gaussian Autoregressive Processes with Tukey g-and-h Transformations | When performing a time series analysis of continuous data, for example from
climate or environmental problems, the assumption that the process is Gaussian
is often violated. Therefore, we introduce two non-Gaussian autoregressive time
series models that are able to fit skewed and heavy-tailed time series data.
Our two models are based on the Tukey g-and-h transformation. We discuss
parameter estimation, order selection, and forecasting procedures for our
models and examine their performances in a simulation study. We demonstrate the
usefulness of our models by applying them to two sets of wind speed data.
| 0 | 0 | 0 | 1 | 0 | 0 |
Frequency responses of the K-Rb-$^{21}$Ne co-magnetometer | The frequency responses of the K-Rb-$^{21}$Ne co-magnetometer to magnetic
field and exotic spin dependent forces are experimentally studied and simulated
in this paper. Both the relationship between the output amplitude, the phase
shift and frequencies are studied. The responses of magnetic field are
experimentally investigated. Due to a lack of input methods, others are
numerically simulated.
| 0 | 1 | 0 | 0 | 0 | 0 |
Some new bounds of placement delivery arrays | Coded caching scheme is a technique which reduce the load during peak traffic
times in a wireless network system. Placement delivery array (PDA in short) was
first introduced by Yan et al.. It can be used to design coded caching scheme.
In this paper, we prove some lower bounds of PDA on the element and some lower
bounds of PDA on the column. We also give some constructions for optimal PDA.
| 1 | 0 | 0 | 0 | 0 | 0 |
Itineraries for Inverse Limits of Tent Maps: a Backward View | Previously published admissibility conditions for an element of
$\{0,1\}^{\mathbb{Z}}$ to be the itinerary of a point of the inverse limit of a
tent map are expressed in terms of forward orbits. We give necessary and
sufficient conditions in terms of backward orbits, which is more natural for
inverse limits. These backward admissibility conditions are not symmetric
versions of the forward ones: in particular, the maximum backward itinerary
which can be realised by a tent map mode locks on intervals of kneading
sequences.
| 0 | 0 | 1 | 0 | 0 | 0 |
EmbedInsight: Automated Grading of Embedded Systems Assignments | Grading in embedded systems courses typically requires a face-to-face
appointment between the student and the instructor because of experimental
setups that are only available in laboratory facilities. Such a manual grading
process is an impediment to both students and instructors. Students have to
wait for several days to get feedback, and instructors may spend valuable time
evaluating trivial aspects of the assignment. As seen with software courses, an
automated grading system can significantly improve the insights available to
the instructor and encourage students to learn quickly with iterative testing.
We have designed and implemented EmbedInsight, an automated grading system for
embedded system courses that accommodates a wide variety of experimental setups
and is scalable to MOOC-style courses. EmbedInsight employs a modular web
services design that separates the user interface and the experimental setup
that evaluates student assignments. We deployed and evaluated EmbedInsight for
our university embedded systems course. We show that our system scales well to
a large number of submissions, and students are satisfied with their overall
experience.
| 1 | 0 | 0 | 0 | 0 | 0 |
On the $p'$-subgraph of the Young graph | Let $p$ be a prime number. In this article we study the restriction to
$\mathfrak{S}_{n-1}$ of irreducible characters of degree coprime to $p$ of
$\mathfrak{S}_n$. In particular, we study the combinatorial properties of the
subgraph $\mathbb{Y}_{p'}$ of the Young graph $\mathbb{Y}$. This is an
extension to odd primes of the work done by Ayyer, Prasad and Spallone for
$p=2$.
| 0 | 0 | 1 | 0 | 0 | 0 |
Electronic origin of melting T-P curves of alkali metals with negative slope and minimum | Group I elements - alkali metals Li, Na, K, Rb and Cs - are examples of
simple metals with one s electron in the valence band. Under pressure these
elements display unusually complex structural behaviour transforming from
close-packed to low symmetry open structures. Unexpectedly complex form was
found for melting curves of alkalis under compression with initial increasing
in accordance to Lindemann criterion and further decreasing to very low melting
point. To understand complex and low symmetry structures in compressed alkalis
a transformation of the electron energy levels was suggested which involves an
overlap between the valence band and outer core electrons. Within the model of
the Fermi sphere - Brillouin zone interaction one can understand the complex
melting curve of alkalis.
| 0 | 1 | 0 | 0 | 0 | 0 |
Gene Shaving using influence function of a kernel method | Identifying significant subsets of the genes, gene shaving is an essential
and challenging issue for biomedical research for a huge number of genes and
the complex nature of biological networks,. Since positive definite kernel
based methods on genomic information can improve the prediction of diseases, in
this paper we proposed a new method, "kernel gene shaving (kernel canonical
correlation analysis (kernel CCA) based gene shaving). This problem is
addressed using the influence function of the kernel CCA. To investigate the
performance of the proposed method in a comparison of three popular gene
selection methods (T-test, SAM and LIMMA), we were used extensive simulated and
real microarray gene expression datasets. The performance measures AUC was
computed for each of the methods. The achievement of the proposed method has
improved than the three well-known gene selection methods. In real data
analysis, the proposed method identified a subsets of $210$ genes out of $2000$
genes. The network of these genes has significantly more interactions than
expected, which indicates that they may function in a concerted effort on colon
cancer.
| 0 | 0 | 0 | 1 | 1 | 0 |
Compressing Green's function using intermediate representation between imaginary-time and real-frequency domains | New model-independent compact representations of imaginary-time data are
presented in terms of the intermediate representation (IR) of analytical
continuation. This is motivated by a recent numerical finding by the authors
[J. Otsuki et al., arXiv:1702.03056]. We demonstrate the efficiency of the IR
through continuous-time quantum Monte Carlo calculations of an Anderson
impurity model. We find that the IR yields a significantly compact form of
various types of correlation functions. The present framework will provide
general ways to boost the power of cutting-edge diagrammatic/quantum Monte
Carlo treatments of many-body systems.
| 0 | 1 | 0 | 1 | 0 | 0 |
Machine Learning for the Geosciences: Challenges and Opportunities | Geosciences is a field of great societal relevance that requires solutions to
several urgent problems facing our humanity and the planet. As geosciences
enters the era of big data, machine learning (ML) -- that has been widely
successful in commercial domains -- offers immense potential to contribute to
problems in geosciences. However, problems in geosciences have several unique
challenges that are seldom found in traditional applications, requiring novel
problem formulations and methodologies in machine learning. This article
introduces researchers in the machine learning (ML) community to these
challenges offered by geoscience problems and the opportunities that exist for
advancing both machine learning and geosciences. We first highlight typical
sources of geoscience data and describe their properties that make it
challenging to use traditional machine learning techniques. We then describe
some of the common categories of geoscience problems where machine learning can
play a role, and discuss some of the existing efforts and promising directions
for methodological development in machine learning. We conclude by discussing
some of the emerging research themes in machine learning that are applicable
across all problems in the geosciences, and the importance of a deep
collaboration between machine learning and geosciences for synergistic
advancements in both disciplines.
| 1 | 1 | 0 | 0 | 0 | 0 |
Generalized singular value thresholding operator to affine matrix rank minimization problem | It is well known that the affine matrix rank minimization problem is NP-hard
and all known algorithms for exactly solving it are doubly exponential in
theory and in practice due to the combinational nature of the rank function. In
this paper, a generalized singular value thresholding operator is generated to
solve the affine matrix rank minimization problem. Numerical experiments show
that our algorithm performs effectively in finding a low-rank matrix compared
with some state-of-art methods.
| 0 | 0 | 1 | 0 | 0 | 0 |
Unifying the Brascamp-Lieb Inequality and the Entropy Power Inequality | The entropy power inequality (EPI) and the Brascamp-Lieb inequality (BLI) can
be viewed as information inequalities concerning entropies of linear
transformations of random variables. The EPI provides lower bounds for the
entropy of linear transformations of random vectors with independent
components. The BLI, on the other hand, provides upper bounds on the entropy of
a random vector in terms of the entropies of its linear transformations. In
this paper, we present a new entropy inequality that generalizes both the BLI
and EPI by considering a variety of independence relations among the components
of a random vector. Our main technical contribution is in the proof strategy
that leverages the "doubling trick" to prove Gaussian optimality for certain
entropy expressions under independence constraints.
| 1 | 0 | 0 | 0 | 0 | 0 |
Risk ratios for contagious outcomes | The risk ratio is a popular tool for summarizing the relationship between a
binary covariate and outcome, even when outcomes may be dependent.
Investigations of infectious disease outcomes in cohort studies of individuals
embedded within clusters -- households, villages, or small groups -- often
report risk ratios. Epidemiologists have warned that risk ratios may be
misleading when outcomes are contagious, but the nature and severity of this
error is not well understood. In this study, we assess the epidemiologic
meaning of the risk ratio when outcomes are contagious. We first give a
structural definition of infectious disease transmission within clusters, based
on the canonical susceptible-infective epidemic model. From this standard
characterization, we define the individual-level ratio of instantaneous risks
(hazard ratio) as the inferential target, and evaluate the properties of the
risk ratio as an estimate of this quantity. We exhibit analytically and by
simulation the circumstances under which the risk ratio implies an effect whose
direction is opposite that of the true individual-level hazard ratio. In
particular, the risk ratio can be greater than one even when the covariate of
interest reduces both individual-level susceptibility to infection, and
transmissibility once infected. We explain these findings in the epidemiologic
language of confounding and relate the direction bias to Simpson's paradox.
| 0 | 0 | 0 | 1 | 0 | 0 |
Instrument Orientation-Based Metrics for Surgical Skill Evaluation in Robot-Assisted and Open Needle Driving | The technical skill of surgeons directly impacts patient outcomes. Advanced
tracking systems enable the development of objective motion-based metrics for
skill evaluation, but these metrics are not sufficient to evaluate the
performance in complex surgical tasks. In this study, we developed metrics for
surgical skill evaluation that are based on the orientation of the surgical
instruments. Experienced robotic surgeons and novice users performed
teleoperated (using the da Vinci Research Kit) and open needle-driving. Task
time and the rate of orientation change successfully distinguished between
experienced surgeons and novice users. Path length and the normalized angular
displacement allowed for a good separation only in part of the experiment. Our
new promising metrics for surgical skill evaluation captured technical aspects
that are taught during surgeons' training. They provide complementing
evaluation to those of classical metrics. Orientation-based metrics add value
to skill assessment and may be an adjunct to classic objective metrics
providing more granular discrimination of skills.
| 1 | 0 | 0 | 0 | 0 | 0 |
Formal Methods for Adaptive Control of Dynamical Systems | We develop a method to control discrete-time systems with constant but
initially unknown parameters from linear temporal logic (LTL) specifications.
We introduce the notions of (non-deterministic) parametric and adaptive
transition systems and show how to use tools from formal methods to compute
adaptive control strategies for finite systems. For infinite systems, we first
compute abstractions in the form of parametric finite quotient transition
systems and then apply the techniques for finite systems. Unlike traditional
adaptive control methods, our approach is correct by design, does not require a
reference model, and can deal with a much wider range of systems and
specifications. Illustrative case studies are included.
| 1 | 0 | 1 | 0 | 0 | 0 |
Sublayer of Prandtl boundary layers | The aim of this paper is to investigate the stability of Prandtl boundary
layers in the vanishing viscosity limit: $\nu \to 0$. In \cite{Grenier}, one of
the authors proved that there exists no asymptotic expansion involving one
Prandtl's boundary layer with thickness of order $\sqrt\nu$, which describes
the inviscid limit of Navier-Stokes equations. The instability gives rise to a
viscous boundary sublayer whose thickness is of order $\nu^{3/4}$. In this
paper, we point out how the stability of the classical Prandtl's layer is
linked to the stability of this sublayer. In particular, we prove that the two
layers cannot both be nonlinearly stable in $L^\infty$. That is, either the
Prandtl's layer or the boundary sublayer is nonlinearly unstable in the sup
norm.
| 0 | 0 | 1 | 0 | 0 | 0 |
Effects of a Price limit Change on Market Stability at the Intraday Horizon in the Korean Stock Market | This paper investigates the effects of a price limit change on the volatility
of the Korean stock market's (KRX) intraday stock price process. Based on the
most recent transaction data from the KRX, which experienced a change in the
price limit on June 15, 2015, we examine the change in realized variance after
the price limit change to investigate the overall effects of the change on the
intraday market volatility. We then analyze the effects in more detail by
applying the discrete Fourier transform (DFT) to the data set. We find evidence
that the market becomes more volatile in the intraday horizon because of the
increase in the amplitudes of the low-frequency components of the price
processes after the price limit change. Therefore, liquidity providers are in a
worse situation than they were prior to the change.
| 0 | 0 | 0 | 0 | 0 | 1 |
Adversarial Perturbations Against Real-Time Video Classification Systems | Recent research has demonstrated the brittleness of machine learning systems
to adversarial perturbations. However, the studies have been mostly limited to
perturbations on images and more generally, classification that does not deal
with temporally varying inputs. In this paper we ask "Are adversarial
perturbations possible in real-time video classification systems and if so,
what properties must they satisfy?" Such systems find application in
surveillance applications, smart vehicles, and smart elderly care and thus,
misclassification could be particularly harmful (e.g., a mishap at an elderly
care facility may be missed). We show that accounting for temporal structure is
key to generating adversarial examples in such systems. We exploit recent
advances in generative adversarial network (GAN) architectures to account for
temporal correlations and generate adversarial samples that can cause
misclassification rates of over 80% for targeted activities. More importantly,
the samples also leave other activities largely unaffected making them
extremely stealthy. Finally, we also surprisingly find that in many scenarios,
the same perturbation can be applied to every frame in a video clip that makes
the adversary's ability to achieve misclassification relatively easy.
| 0 | 0 | 0 | 1 | 0 | 0 |
Wasserstein Identity Testing | Uniformity testing and the more general identity testing are well studied
problems in distributional property testing. Most previous work focuses on
testing under $L_1$-distance. However, when the support is very large or even
continuous, testing under $L_1$-distance may require a huge (even infinite)
number of samples. Motivated by such issues, we consider the identity testing
in Wasserstein distance (a.k.a. transportation distance and earthmover
distance) on a metric space (discrete or continuous).
In this paper, we propose the Wasserstein identity testing problem (Identity
Testing in Wasserstein distance). We obtain nearly optimal worst-case sample
complexity for the problem. Moreover, for a large class of probability
distributions satisfying the so-called "Doubling Condition", we provide nearly
instance-optimal sample complexity.
| 1 | 0 | 1 | 0 | 0 | 0 |
Concordances from differences of torus knots to $L$-space knots | It is known that connected sums of positive torus knots are not concordant to
$L$-space knots. Here we consider differences of torus knots. The main result
states that the subgroup of the concordance group generated by two positive
torus knots contains no nontrivial $L$-space knots other than the torus knots
themselves. Generalizations to subgroups generated by more than two torus knots
are also considered.
| 0 | 0 | 1 | 0 | 0 | 0 |
The classification of Rokhlin flows on C*-algebras | We study flows on C*-algebras with the Rokhlin property. We show that every
Kirchberg algebra carries a unique Rokhlin flow up to cocycle conjugacy, which
confirms a long-standing conjecture of Kishimoto. We moreover present a
classification theory for Rokhlin flows on C*-algebras satisfying certain
technical properties, which hold for many C*-algebras covered by the Elliott
program. As a consequence, we obtain the following further classification
theorems for Rokhlin flows. Firstly, we extend the statement of Kishimoto's
conjecture to the non-simple case: Up to cocycle conjugacy, a Rokhlin flow on a
separable, nuclear, strongly purely infinite C*-algebra is uniquely determined
by its induced action on the prime ideal space. Secondly, we give a complete
classification of Rokhlin flows on simple classifiable $KK$-contractible
C*-algebras: Two Rokhlin flows on such a C*-algebra are cocycle conjugate if
and only if their induced actions on the cone of lower-semicontinuous traces
are affinely conjugate.
| 0 | 0 | 1 | 0 | 0 | 0 |
Unusual evolution of B_{c2} and T_c with inclined fields in restacked TaS_2 nanosheets | Recently we reported an enhanced superconductivity in restacked monolayer
TaS_2 nanosheets compared with the bulk TaS_2, pointing to the exotic physical
properties of low dimensional systems. Here we tune the superconducting
properties of this system with magnetic field along different directions, where
a strong Pauli paramagnetic spin-splitting effect is found in this system.
Importantly, an unusual enhancement as high as 3.8 times of the upper critical
field B_{c2}, as compered with the Ginzburg-Landau (GL) model and Tinkham
model, is observed under the inclined external magnetic field. Moreover, with
the out-of-plane field fixed, we find that the superconducting transition
temperature T_c can be enhanced by increasing the in-plane field and forms a
dome-shaped phase diagram. An extended GL model considering the special
microstructure with wrinkles was proposed to describe the results. The
restacked crystal structure without inversion center along with the strong
spin-orbit coupling may also play an important role for our observations.
| 0 | 1 | 0 | 0 | 0 | 0 |
Bounded game-theoretic semantics for modal mu-calculus | We introduce a new game-theoretic semantics (GTS) for the modal mu-calculus.
Our so-called bounded GTS replaces parity games with novel alternative
evaluation games where only finite paths arise. Infinite paths are not needed
even when the considered transition system is infinite.
| 1 | 0 | 1 | 0 | 0 | 0 |
Putative spin liquid in the triangle-based iridate Ba$_3$IrTi$_2$O$_9$ | We report on thermodynamic, magnetization, and muon spin relaxation
measurements of the strong spin-orbit coupled iridate Ba$_3$IrTi$_2$O$_9$,
which constitutes a new frustration motif made up a mixture of edge- and
corner-sharing triangles. In spite of strong antiferromagnetic exchange
interaction of the order of 100~K, we find no hint for long-range magnetic
order down to 23 mK. The magnetic specific heat data unveil the $T$-linear and
-squared dependences at low temperatures below 1~K. At the respective
temperatures, the zero-field muon spin relaxation features a persistent spin
dynamics, indicative of unconventional low-energy excitations. A comparison to
the $4d$ isostructural compound Ba$_3$RuTi$_2$O$_9$ suggests that a concerted
interplay of compass-like magnetic interactions and frustrated geometry
promotes a dynamically fluctuating state in a triangle-based iridate.
| 0 | 1 | 0 | 0 | 0 | 0 |
Herding behavior in cryptocurrency markets | There are no solid arguments to sustain that digital currencies are the
future of online payments or the disruptive technology that some of its former
participants declared when used to face critiques. This paper aims to solve the
cryptocurrency puzzle from a behavioral finance perspective by finding the
parallelism between biases present in financial markets that could be applied
to cryptomarkets. Moreover, it is suggested that cryptocurrencies' prices are
driven by herding, hence this study test herding behavior under asymmetric and
symmetric conditions and the existence of different herding regimes by
employing the Markov-Switching approach.
| 0 | 0 | 0 | 0 | 0 | 1 |
Los agujeros negros y las ondas del Doctor Einstein | We describe the main scientific developments that lead LIGO project to the
detection of the gravitational waves: general relativity, black holes and
gravitational waves predictions; numerical relativity and the collision and
coalescence simulations of binary black holes and the development of different
kind of gravitational wave detectors. Most important, this detection is
confirming the existence of the enigmatic black holes.
| 0 | 1 | 0 | 0 | 0 | 0 |
Symmetries of flat manifolds, Jordan property and the general Zimmer program | We obtain a sufficient and necessary condition for a finite group that could
act effectively on closed flat manifolds. Let $G=E_{n}(R)$ the elementary
subgroup of a linear group, $EU_{n}(R,\Lambda )$ the elementary subgroup of a
unitary group, $\mathrm{SAut}(F_{n})$ the special automorphism group of a free
group or $\mathrm{SOut}(F_{n})$ the special outer automorphism group of a free
group. As applications, we prove that when $n\geq 3$ every group action of $G$
on a closed flat manifold $M^{k}$ ($k<n$) by homeomorphisms is trivial. This
confirms a conjecture related to Zimmer's program for flat manifolds. Moreover,
it is also proved that the group of homeomorphisms of closed flat manifolds are
Jordan with Jordan constants depending only on dimensions.
| 0 | 0 | 1 | 0 | 0 | 0 |
Hidden Fermi Liquidity and Topological Criticality in the Finite Temperature Kitaev Model | The fate of exotic spin liquid states with fractionalized excitations at
finite temperature ($T$) is of great interest, since signatures of
fractionalization manifest in finite-temperature ($T$) dynamics in real
systems, above the tiny magnetic ordering scales. Here, we study a
Jordan-Wigner fermionized Kitaev spin liquid at finite $T$ employing combined
Exact diagonalization and Monte Carlo simulation methods. We uncover $(i)$
checkerboard or stripy-ordered flux crystals depending on density of flux, and
$(ii)$ establish, surprisingly, that: $(a)$ the finite-$T$ version of the $T=0$
transition from a gapless to gapped phases in the Kitaev model is a Mott
transition of the fermions, belonging to the two-dimensional Ising universality
class. These transitions correspond to a topological transition between a
string condensate and a dilute closed string state $(b)$ the Mott "insulator"
phase is a precise realization of Laughlin's gossamer (here, p-wave)
superconductor (g-SC), and $(c)$ the Kitaev Toric Code phase (TC) is a {\it
fully} Gutzwiller-projected p-wave SC. These findings establish the finite-$T$
QSL phases in the $d = 2$ to be {\it hidden} Fermi liquid(s) of neutral
fermions.
| 0 | 1 | 0 | 0 | 0 | 0 |
Semi-automated labelling of medical images: benefits of a collaborative work in the evaluation of prostate cancer in MRI | Purpose: The goal of this study is to show the advantage of a collaborative
work in the annotation and evaluation of prostate cancer tissues from
T2-weighted MRI compared to the commonly used double blind evaluation.
Methods: The variability of medical findings focused on the prostate gland
(central gland, peripheral and tumoural zones) by two independent experts was
firstly evaluated, and secondly compared with a consensus of these two experts.
Using a prostate MRI database, experts drew regions of interest (ROIs)
corresponding to healthy prostate (peripheral and central zones) and cancer
using a semi-automated tool. One of the experts then drew the ROI with
knowledge of the other expert's ROI.
Results: The surface area of each ROI as the Hausdorff distance and the Dice
coefficient for each contour were evaluated between the different experiments,
taking the drawing of the second expert as the reference. The results showed
that the significant differences between the two experts became non-significant
with a collaborative work.
Conclusions: This study shows that collaborative work with a dedicated tool
allows a better consensus between expertise than using a double blind
evaluation. Although we show this for prostate cancer evaluation in T2-weighted
MRI, the results of this research can be extrapolated to other diseases and
kind of medical images.
| 1 | 1 | 0 | 0 | 0 | 0 |
Lexical Features in Coreference Resolution: To be Used With Caution | Lexical features are a major source of information in state-of-the-art
coreference resolvers. Lexical features implicitly model some of the linguistic
phenomena at a fine granularity level. They are especially useful for
representing the context of mentions. In this paper we investigate a drawback
of using many lexical features in state-of-the-art coreference resolvers. We
show that if coreference resolvers mainly rely on lexical features, they can
hardly generalize to unseen domains. Furthermore, we show that the current
coreference resolution evaluation is clearly flawed by only evaluating on a
specific split of a specific dataset in which there is a notable overlap
between the training, development and test sets.
| 1 | 0 | 0 | 0 | 0 | 0 |
Complete Semantics to empower Touristic Service Providers | The tourism industry has a significant impact on the world's economy,
contributes 10.2% of the world's gross domestic product in 2016. It becomes a
very competitive industry, where having a strong online presence is an
essential aspect for business success. To achieve this goal, the proper usage
of latest Web technologies, particularly schema.org annotations is crucial. In
this paper, we present our effort to improve the online visibility of touristic
service providers in the region of Tyrol, Austria, by creating and deploying a
substantial amount of semantic annotations according to schema.org, a widely
used vocabulary for structured data on the Web. We started our work from
Tourismusverband (TVB) Mayrhofen-Hippach and all touristic service providers in
the Mayrhofen-Hippach region and applied the same approach to other TVBs and
regions, as well as other use cases. The rationale for doing this is
straightforward. Having schema.org annotations enables search engines to
understand the content better, and provide better results for end users, as
well as enables various intelligent applications to utilize them. As a direct
consequence, the region of Tyrol and its touristic service increase their
online visibility and decrease the dependency on intermediaries, i.e. Online
Travel Agency (OTA).
| 1 | 0 | 0 | 0 | 0 | 0 |
Reducing variance in importance-weighted cross-validation under covariate shift | Covariate shift classification problems can in principle be tackled by
importance-weighting of training samples. However, the sampling variance of the
risk estimator is often scaled up dramatically by employing such weighting. One
of the consequences of this is that during cross-validation -- when the
importance-weighted risk is repeatedly estimated -- suboptimal hyperparameter
estimates are produced. We study the sampling variance of the
importance-weighted risk estimator as a function of the width of the source
distribution. We show that introducing a control variate can reduce its
sampling variance, which leads to improved regularization parameter estimates
when the training data is smaller in scale than the test data.
| 1 | 0 | 0 | 1 | 0 | 0 |
Comparing Aggregators for Relational Probabilistic Models | Relational probabilistic models have the challenge of aggregation, where one
variable depends on a population of other variables. Consider the problem of
predicting gender from movie ratings; this is challenging because the number of
movies per user and users per movie can vary greatly. Surprisingly, aggregation
is not well understood. In this paper, we show that existing relational models
(implicitly or explicitly) either use simple numerical aggregators that lose
great amounts of information, or correspond to naive Bayes, logistic
regression, or noisy-OR that suffer from overconfidence. We propose new simple
aggregators and simple modifications of existing models that empirically
outperform the existing ones. The intuition we provide on different (existing
or new) models and their shortcomings plus our empirical findings promise to
form the foundation for future representations.
| 1 | 0 | 0 | 1 | 0 | 0 |
The Sad State of Entrepreneurship in America: What Educators Can Do About It | The entrepreneurial scene suffers from a sick venture capital industry, a
number of imponderable illogics, and, maybe, misplaced adulation from students
and the public. The paper details these problems, finds root causes, and
prescribes action for higher education professionals and institutions.
| 1 | 0 | 0 | 0 | 0 | 0 |
Filtering Variational Objectives | When used as a surrogate objective for maximum likelihood estimation in
latent variable models, the evidence lower bound (ELBO) produces
state-of-the-art results. Inspired by this, we consider the extension of the
ELBO to a family of lower bounds defined by a particle filter's estimator of
the marginal likelihood, the filtering variational objectives (FIVOs). FIVOs
take the same arguments as the ELBO, but can exploit a model's sequential
structure to form tighter bounds. We present results that relate the tightness
of FIVO's bound to the variance of the particle filter's estimator by
considering the generic case of bounds defined as log-transformed likelihood
estimators. Experimentally, we show that training with FIVO results in
substantial improvements over training the same model architecture with the
ELBO on sequential data.
| 1 | 0 | 0 | 1 | 0 | 0 |
Annealing stability of magnetic tunnel junctions based on dual MgO free layers and [Co/Ni] based thin synthetic antiferromagnet fixed system | We study the annealing stability of bottom-pinned perpendicularly magnetized
magnetic tunnel junctions based on dual MgO free layers and thin fixed systems
comprising a hard [Co/Ni] multilayer antiferromagnetically coupled to thin a Co
reference layer and a FeCoB polarizing layer. Using conventional magnetometry
and advanced broadband ferromagnetic resonance, we identify the properties of
each sub-unit of the magnetic tunnel junction and demonstrate that this
material option can ensure a satisfactory resilience to the 400$^\circ$C
thermal annealing needed in solid-state magnetic memory applications. The dual
MgO free layer possesses an anneal-robust 0.4 T effective anisotropy and
suffers only a minor increase of its Gilbert damping from 0.007 to 0.010 for
the toughest annealing conditions. Within the fixed system, the ferro-coupler
and texture-breaking TaFeCoB layer keeps an interlayer exchange above 0.8
mJ/m$^2$, while the Ru antiferrocoupler layer within the synthetic
antiferromagnet maintains a coupling above -0.5 mJ/m$^2$. These two strong
couplings maintain the overall functionality of the tunnel junction upon the
toughest annealing despite the gradual degradation of the thin Co layer
anisotropy that may reduce the operation margin in spin torque memory
applications. Based on these findings, we propose further optimization routes
for the next generation magnetic tunnel junctions.
| 0 | 1 | 0 | 0 | 0 | 0 |
The Eigenoption-Critic Framework | Eigenoptions (EOs) have been recently introduced as a promising idea for
generating a diverse set of options through the graph Laplacian, having been
shown to allow efficient exploration. Despite its initial promising results, a
couple of issues in current algorithms limit its application, namely: (1) EO
methods require two separate steps (eigenoption discovery and reward
maximization) to learn a control policy, which can incur a significant amount
of storage and computation; (2) EOs are only defined for problems with discrete
state-spaces and; (3) it is not easy to take the environment's reward function
into consideration when discovering EOs. To addresses these issues, we
introduce an algorithm termed eigenoption-critic (EOC) based on the
Option-critic (OC) framework [Bacon17], a general hierarchical reinforcement
learning (RL) algorithm that allows learning the intra-option policies
simultaneously with the policy over options. We also propose a generalization
of EOC to problems with continuous state-spaces through the Nyström
approximation. EOC can also be seen as extending OC to nonstationary settings,
where the discovered options are not tailored for a single task.
| 1 | 0 | 0 | 0 | 0 | 0 |
A perturbation analysis of some Markov chains models with time-varying parameters | We study some regularity properties in locally stationary Markov models which
are fundamental for controlling the bias of nonparametric kernel estimators. In
particular, we provide an alternative to the standard notion of derivative
process developed in the literature and that can be used for studying a wide
class of Markov processes. To this end, for some families of V-geometrically
ergodic Markov kernels indexed by a real parameter u, we give conditions under
which the invariant probability distribution is differentiable with respect to
u, in the sense of signed measures. Our results also complete the existing
literature for the perturbation analysis of Markov chains, in particular when
exponential moments are not finite. Our conditions are checked on several
original examples of locally stationary processes such as integer-valued
autoregressive processes, categorical time series or threshold autoregressive
processes.
| 0 | 0 | 1 | 1 | 0 | 0 |
Exploring patterns of demand in bike sharing systems via replicated point process models | Understanding patterns of demand is fundamental for fleet management of bike
sharing systems. In this paper we analyze data from the Divvy system of the
city of Chicago. We show that the demand of bicycles can be modeled as a
multivariate temporal point process, with each dimension corresponding to a
bike station in the network. The availability of daily replications of the
process allows nonparametric estimation of the intensity functions, even for
stations with low daily counts, and straightforward estimation of pairwise
correlations between stations. These correlations are then used for clustering,
revealing different patterns of bike usage.
| 0 | 0 | 0 | 1 | 0 | 0 |
High-performance nanoscale topological energy transduction | The realization of high-performance, small-footprint, on-chip inductors
remains a challenge in radio-frequency and power microelectronics, where they
perform vital energy transduction in filters and power converters. Modern
planar inductors consist of metallic spirals that consume significant chip
area, resulting in low inductance densities. We present a novel method for
magnetic energy transduction that utilizes ferromagnetic islands (FIs) on the
surface of a 3D time-reversal-invariant topological insulator (TI) to produce
paradigmatically different inductors. Depending on the chemical potential, the
FIs induce either an anomalous or quantum anomalous Hall effect in the
topological surface states. These Hall effects direct current around the FIs,
concentrating magnetic flux and producing a highly inductive device. Using a
novel self-consistent simulation that couples AC non-equilibrium Green
functions to fully electrodynamic solutions of Maxwell's equations, we
demonstrate excellent inductance densities up to terahertz frequencies, thus
harnessing the unique properties of topological materials for practical device
applications.
| 0 | 1 | 0 | 0 | 0 | 0 |
Multigrid-based inversion for volumetric radar imaging with asteroid interior reconstruction as a potential application | This study concentrates on advancing mathematical and computational
methodology for radar tomography imaging in which the unknown volumetric
velocity distribution of a wave within a bounded domain is to be reconstructed.
Our goal is to enable effective simulation and inversion of a large amount of
full-wave data within a realistic 2D or 3D geometry. For propagating and
inverting the wave, we present a rigorous multigrid-based forward approach
which utilizes the finite-difference time-domain method and a nested finite
element grid structure. Based on the multigrid approach, we introduce and
validate a multiresolution algorithm which allows regularization of the unknown
distribution through a coarse-to-fine inversion scheme. In this approach,
sparse signals can be effectively inverted, as the coarse fluctuations are
reconstructed before the finer ones. Furthermore, the number of nonzero entries
in the system matrix can be compressed and thus the inversion procedure can be
speeded up. As a test scenario we investigate satellite-based asteroid interior
reconstruction. We use both full-wave and projected wave data and estimate the
accuracy of the inversion under different error sources: noise and positioning
inaccuracies. The results suggest that the present full-wave inversion approach
allows recovering the interior with a single satellite recording backscattering
data. It seems that robust results can be achieved, when the peak-to-peak
signal-to-noise ratio is above 10 dB. Furthermore, it seems that reconstructing
the deep interior can be enhanced if two satellites can be utilized in the
measurements.
| 0 | 1 | 0 | 0 | 0 | 0 |
Fluid dynamics of diving wedges | Diving induces large pressures during water entry, accompanied by the
creation of cavity and water splash ejected from the free water surface. To
minimize impact forces, divers streamline their shape at impact. Here, we
investigate the impact forces and splash evolution of diving wedges as a
function of the wedge opening angle. A gradual transition from impactful to
smooth entry is observed as the wedge angle decreases. After submersion, diving
wedges experience significantly smaller drag forces (two-fold smaller) than
immersed wedges. Our experimental findings compare favorably with existing
force models upon the introduction of empirically-based corrections. We
experimentally characterize the shapes of the cavity and splash created by the
wedge and find that they are independent of the entry velocity at short times,
but that the splash exhibits distinct variations in shape at later times. We
propose a one-dimensional model of the splash that takes into account gravity,
surface tension and aerodynamics forces. The model shows, in conjunction with
experimental data, that the splash shape is dominated by the interplay between
a destabilizing Venturi-suction force due to air rushing between the splash and
the water surface and a stabilizing force due to surface tension. Taken
together, these findings could direct future research aimed at understanding
and combining the mechanisms underlying all stages of water entry in
application to engineering and bio-related problems, including naval
engineering, disease spreading or platform diving.
| 0 | 1 | 0 | 0 | 0 | 0 |
Scenic: Language-Based Scene Generation | Synthetic data has proved increasingly useful in both training and testing
machine learning models such as neural networks. The major problem in synthetic
data generation is producing meaningful data that is not simply random but
reflects properties of real-world data or covers particular cases of interest.
In this paper, we show how a probabilistic programming language can be used to
guide data synthesis by encoding domain knowledge about what data is useful.
Specifically, we focus on data sets arising from "scenes", configurations of
physical objects; for example, images of cars on a road. We design a
domain-specific language, Scenic, for describing "scenarios" that are
distributions over scenes. The syntax of Scenic makes it easy to specify
complex relationships between the positions and orientations of objects. As a
probabilistic programming language, Scenic allows assigning distributions to
features of the scene, as well as declaratively imposing hard and soft
constraints over the scene. A Scenic scenario thereby implicitly defines a
distribution over scenes, and we formulate the problem of sampling from this
distribution as "scene improvisation". We implement an improviser for Scenic
scenarios and apply it in a case study generating synthetic data sets for a
convolutional neural network designed to detect cars in road images. Our
experiments demonstrate the usefulness of our approach by using Scenic to
analyze and improve the performance of the network in various scenarios.
| 1 | 0 | 0 | 0 | 0 | 0 |
An exactly solvable model for Dynamic Nuclear polarization | We introduce a solvable model of driven fermions that elucidates the role of
the localization transition in driven disordered magnets, as used in the
context of dynamic nuclear polarization. Instead of spins, we study a set of
non-interacting fermions that are coupled locally to nuclear spins and tend to
hyperpolarize them. The induced hyperpolarization is a fingerprint of the
driven steady state of the fermions, which undergo an Anderson Localization
(AL) transition upon increasing the disorder. Our central result is that the
maximal hyperpolarization level is always found close to the localization
transition. In the limit of small nuclear moments the maximum is pinned to the
transition, and the hyperpolarization is strongly enhanced by multi-fractal
correlations in the critical state of the nearly localized driven system, its
magnitude reflecting multi-fractal scaling.
| 0 | 1 | 0 | 0 | 0 | 0 |
The Research Data Alliance: Building Bridges to Enable Scientific Data Sharing | The Research Data Alliance is an international organization which aims at
building the technical and sociological bridges that enable the open sharing of
scientific data. It is a remarkable forum to discuss all the aspects of
scientific data sharing with colleagues from all around the world: in November
2016, it has 4 500 members from 115 countries. The biannual Plenary meetings,
which gather several hundred participants, are rotating between different
regions. The March 2017 one will be held in Barcelona and the September 2017
one in Montreal, after Tokyo and Denver in 2016. The RDA work is organized
bottom-up, with Working Groups which have 18 months to produce implementable
deliverables and Interest Groups which serve as platforms of communication and
discussion and also produce important outputs such as surveys and
recommendations. There are currently 27 Working Groups and 45 Interest Groups,
tackling a wide diversity of subjects, including community needs, reference for
sharing, data stewardship and services, and topics related to the base
infrastructure of data sharing. Some scientific communities use the RDA as a
neutral forum to define their own disciplinary data sharing framework, with
major successes such as the Wheat Data Interoperability Working Group which
worked in coordination with the International Wheat Initiative. Astronomy has
the IVOA to define its interoperability standards, and so we do not need to
create a Group for that purpose in the RDA. But many topics discussed in the
RDA have a strong interest for us, for instance on data citation or
certification of data repositories. We have a lot to share from what we have
learnt in building our disciplinary global data infrastructure; we also have a
lot to learn from others. The paper discusses RDA current themes or results of
interest for astronomy data providers, and current liaisons with astronomy.
| 0 | 1 | 0 | 0 | 0 | 0 |
Modulated magnetic structure of Fe3PO7 as seen by 57Fe Mössbauer spectroscopy | The paper reports new results of the 57Fe Mössbauer measurements on
Fe3PO4O3 powder sample recorded at various temperatures including the point of
magnetic phase transition TN ~ 163K. The spectra measured above TN consist of
quadrupole doublet with high quadrupole splitting of D300K ~ 1.10 mm/s,
emphasizing that Fe3+ ions are located in crystal positions with a strong
electric field gradient (EFG). In order to predict the sign and orientation of
the main components of the EFG tensor we calculated monopole lattice
contributions to the EFG. In the temperature range T < TN, the experimental
spectra were fitted assuming that the electric hyperfine interactions are
modulated when the Fe3+ spin (S) rotates with respect to the EFG axis and
emergence of spatial anisotropy of the hyperfine field Hhf = SÃI at 57Fe
nuclei. These data were analyzed to estimate the components of the anisotropic
hyperfine coupling tensor (Ã). The large anharmonicity parameter, m ~ 0.94,
of the spiral spin structure results from easy-axis anisotropy in the plane of
the iron spin rotation. The temperature evolution of the hyperfine field Hhf(T)
was described by Bean-Rodbell model that takes into account that the exchange
magnetic interactions are strong function of the lattice spacing. The obtained
Mössbauer data are in qualitative agreement with previous neutron diffraction
data for a modulated helical magnetic structure in strongly frustrated
Fe3PO4O3.
| 0 | 1 | 0 | 0 | 0 | 0 |
Mutation invariance for the zeroth coefficients of the colored HOMFLY polynomial | We show that the zeroth coefficient of the cables of the HOMFLY polynomial
(colored HOMFLY polynomials) does not distinguish mutants. This makes a sharp
contrast with the total HOMFLY polynomial whose 3-cables can distinguish
mutants.
| 0 | 0 | 1 | 0 | 0 | 0 |
Seasonal Variation of the Underground Cosmic Muon Flux Observed at Daya Bay | The Daya Bay Experiment consists of eight identically designed detectors
located in three underground experimental halls named as EH1, EH2, EH3, with
250, 265 and 860 meters of water equivalent vertical overburden, respectively.
Cosmic muon events have been recorded over a two-year period. The underground
muon rate is observed to be positively correlated with the effective
atmospheric temperature and to follow a seasonal modulation pattern. The
correlation coefficient $\alpha$, describing how a variation in the muon rate
relates to a variation in the effective atmospheric temperature, is found to be
$\alpha_{\text{EH1}} = 0.362\pm0.031$, $\alpha_{\text{EH2}} = 0.433\pm0.038$
and $\alpha_{\text{EH3}} = 0.641\pm0.057$ for each experimental hall.
| 0 | 1 | 0 | 0 | 0 | 0 |
Valid Inference Corrected for Outlier Removal | Ordinary least square (OLS) estimation of a linear regression model is
well-known to be highly sensitive to outliers. It is common practice to first
identify and remove outliers by looking at the data then to fit OLS and form
confidence intervals and p-values on the remaining data as if this were the
original data collected. We show in this paper that this "detect-and-forget"
approach can lead to invalid inference, and we propose a framework that
properly accounts for outlier detection and removal to provide valid confidence
intervals and hypothesis tests. Our inferential procedures apply to any outlier
removal procedure that can be characterized by a set of quadratic constraints
on the response vector, and we show that several of the most commonly used
outlier detection procedures are of this form. Our methodology is built upon
recent advances in selective inference (Taylor & Tibshirani 2015), which are
focused on inference corrected for variable selection. We conduct simulations
to corroborate the theoretical results, and we apply our method to two classic
data sets considered in the outlier detection literature to illustrate how our
inferential results can differ from the traditional detect-and-forget strategy.
A companion R package, outference, implements these new procedures with an
interface that matches the functions commonly used for inference with lm in R.
| 0 | 0 | 1 | 1 | 0 | 0 |
On the error term of a lattice counting problem, II | Under the Riemann Hypothesis, we improve the error term in the asymptotic
formula related to the counting lattice problem studied in a first part of this
work. The improvement comes from the use of Weyl's bound for exponential sums
of polynomials and a device due to Popov allowing us to get an improved main
term in the sums of certain fractional parts of polynomials.
| 0 | 0 | 1 | 0 | 0 | 0 |
Gamma-Ray Emission from Arp 220: Indications of an Active Galactic Nucleus | Extragalactic cosmic ray populations are important diagnostic tools for
tracking the distribution of energy in nuclei and for distinguishing between
activity powered by star formation versus active galactic nuclei (AGNs). Here,
we compare different diagnostics of the cosmic ray populations of the nuclei of
Arp 220 based on radio synchrotron observations and the recent gamma-ray
detection. We find the gamma-ray and radio emission to be incompatible; a joint
solution requires at minimum a factor of 4 - 8 times more energy coming from
supernovae and a factor of 40 - 70 more mass in molecular gas than is observed.
We conclude that this excess of gamma-ray flux in comparison to all other
diagnostics of star-forming activity indicates that there is an AGN present
that is providing the extra cosmic rays, likely in the western nucleus.
| 0 | 1 | 0 | 0 | 0 | 0 |
The fundamental factor of optical interference | It has been widely accepted that electric field alone is the fundamental
factor for optical interference, since Wiener's experiments in 1890 proved that
the electric field plays such a dominant role. A group of experiments were
demonstrated against Wiener's experiments under the condition that the
interference fringes made by optical standing waves could have been
distinguished from the fringes of equal thickness between the inner surface of
emulsion and the plane mirror used to build the optical standing waves. It was
found that the Bragg diffraction from the interference fringes formed by the
standing waves did not exist. This means optical standing waves did not blacken
the photographic emulsion, or the electric field did not play such a dominant
role. Therefore, instead of the electric-field energy density solely in
proportion to the electric-field square, Energy Flux in Interference was
proposed to represent the intensity of optical interference-field and approved
in the derivation of equations for the interference. The derived equations
indicate that both the electric-field vector and the magnetic-field vector are
in phase and have equal amount of energy densities at the interference maxima
of two light beams. Thus, the magnetic-field vector acts the same role as the
electric-field vector on light interacting with substance. The fundamental
factor of optical interference is electromagnetic energy flux densities rather
than electric-field alone, or the intensity of optical interference fringes
should be the energy flux density, not electric-field energy density.
| 0 | 1 | 0 | 0 | 0 | 0 |
Evidence for a Dusty Dark Dwarf Galaxy in the Quadruple Lens MG0414+0534 | We report the $4 \, \sigma$ detection of a faint object with a flux of ~ 0.3
mJy, in the vicinity of the quadruply lensed QSO MG0414+0534 using the Atacama
Large Millimeter/submillimeter array (ALMA) Band 7. The object is most probably
a dusty dark dwarf galaxy, which has not been detected in either the optical,
near-infrared (NIR) or radio (cm) bands. An anomaly in the flux ratio of the
lensed images observed in Band 7 and the mid-infrared (MIR) band and the
reddening of the QSO light color can be simultaneously explained if we consider
the object as a lensing substructure with an ellipticity ~ 0.7 at a redshift of
$0.5 \lesssim z \lesssim 1$. Using the best-fit lens models with three lenses,
we find that the dark matter plus baryon mass associated with the object is
$\sim 10^9\, M_{\odot}$, the dust mass is $\sim 10^7\,M_{\odot}$ and the linear
size is $\gtrsim 5\,$kpc. Thus our findings suggest that the object is a dusty
dark dwarf galaxy. A substantial portion of faint submillimeter galaxies (SMGs)
in the universe may be attributed to such dark objects.
| 0 | 1 | 0 | 0 | 0 | 0 |
Universal abstract elementary classes and locally multipresentable categories | We exhibit an equivalence between the model-theoretic framework of universal
classes and the category-theoretic framework of locally multipresentable
categories. We similarly give an equivalence between abstract elementary
classes (AECs) admitting intersections and locally polypresentable categories.
We use these results to shed light on Shelah's presentation theorem for AECs.
| 0 | 0 | 1 | 0 | 0 | 0 |
q-Viscous Burgers' Equation: Dynamical Symmetry, Shock Solitons and q-Semiclassical Expansion | We propose new type of $q$-diffusive heat equation with nonsymmetric
$q$-extension of the diffusion term. Written in relative gradient variables
this system appears as the $q$- viscous Burgers' equation. Exact solutions of
this equation in polynomial form as generalized Kampe de Feriet polynomials,
corresponding dynamical symmetry and description in terms of Bell polynomials
are derived. We found the generating function for these polynomials by
application of dynamical symmetry and the Zassenhaus formula. We have
constructed and analyzed shock solitons and their interactions with different
$q$. We obtain modification of the soliton relative speeds depending on value
of $q$.For $q< 1$ the soliton speed becomes bounded from above and as a result
in addition to usual Burgers soliton process of fusion, we found a new
phenomena, when soliton with higher amplitude but smaller velocity is fissing
to two solitons. q-Semiclassical expansion of these equations are found in
terms of Bernoulli polynomials in power of $\ln q$.
| 0 | 1 | 0 | 0 | 0 | 0 |
Comparison of invariant metrics and distances on strongly pseudoconvex domains and worm domains | We prove that for a strongly pseudoconvex domain $D\subset\mathbb C^n$, the
infinitesimal Carathéodory metric $g_C(z,v)$ and the infinitesimal Kobayashi
metric $g_K(z,v)$ coincide if $z$ is sufficiently close to $bD$ and if $v$ is
sufficiently close to being tangential to $bD$. Also, we show that every two
close points of $D$ sufficiently close to the boundary and whose difference is
almost tangential to $bD$ can be joined by a (unique up to reparameterization)
complex geodesic of $D$ which is also a holomorphic retract of $D$.
The same continues to hold if $D$ is a worm domain, as long as the points are
sufficiently close to a strongly pseudoconvex boundary point. We also show that
a strongly pseudoconvex boundary point of a worm domain can be globally
exposed, this has consequences for the behavior of the squeezing function.
| 0 | 0 | 1 | 0 | 0 | 0 |
The strong ring of simplicial complexes | We define a ring R of geometric objects G generated by finite abstract
simplicial complexes. To every G belongs Hodge Laplacian H as the square of the
Dirac operator determining its cohomology and a unimodular connection matrix
L). The sum of the matrix entries of the inverse of L is the Euler
characteristic. The spectra of H as well as inductive dimension add under
multiplication while the spectra of L multiply. The nullity of the Hodge of H
are the Betti numbers which can now be signed. The map assigning to G its
Poincare polynomial is a ring homomorphism from R the polynomials. Especially
the Euler characteristic is a ring homomorphism. Also Wu characteristic
produces a ring homomorphism. The Kuenneth correspondence between cohomology
groups is explicit as a basis for the product can be obtained from a basis of
the factors. The product in R produces the strong product for the connection
graphs and leads to tensor products of connection Laplacians. The strong ring R
is also a subring of the full Stanley-Reisner ring S Every element G can be
visualized by its Barycentric refinement graph G1 and its connection graph G'.
Gauss-Bonnet, Poincare-Hopf or the Brouwer-Lefschetz extend to the strong ring.
The isomorphism of R with a subring of the strong Sabidussi ring shows that the
multiplicative primes in R are the simplicial complexes and that every
connected element in the strong ring has a unique prime factorization. The
Sabidussi ring is dual to the Zykov ring, in which the Zykov join is the
addition. The connection Laplacian of the d-dimensional lattice remains
invertible in the infinite volume limit: there is a mass gap in any dimension.
| 1 | 0 | 1 | 0 | 0 | 0 |
Holonomy representation of quasi-projective leaves of codimension one foliations | We prove that a representation of the fundamental group of a quasi-projective
manifold into the group of formal diffeomorphisms of one variable either is
virtually abelian or, after taking the quotient by its center, factors through
an orbicurve.
| 0 | 0 | 1 | 0 | 0 | 0 |
Super Extensions of the Short Pulse Equation | From a super extension of the Wadati, Konno and Ichikawa scheme for
integrable systems and using a $\mathrm{osp(1,2)}$ valued connection 1-form we
obtain super generalizations for the Short Pulse equation as well for the
Elastic Beam equation.
| 0 | 1 | 0 | 0 | 0 | 0 |
Nonequational Stable Groups | We introduce a combinatorial criterion for verifying whether a formula is not
the conjunction of an equation and a co-equation. Using this, we give a
transparent proof for the nonequationality of the free group, which was
originally proved by Sela. Furthermore, we extend this result to arbitrary free
products of groups (except $\mathbb{Z}_2*\mathbb{Z}_2$), providing an abundance
of new stable nonequational theories.
| 0 | 0 | 1 | 0 | 0 | 0 |
Analyzing biological and artificial neural networks: challenges with opportunities for synergy? | Deep neural networks (DNNs) transform stimuli across multiple processing
stages to produce representations that can be used to solve complex tasks, such
as object recognition in images. However, a full understanding of how they
achieve this remains elusive. The complexity of biological neural networks
substantially exceeds the complexity of DNNs, making it even more challenging
to understand the representations that they learn. Thus, both machine learning
and computational neuroscience are faced with a shared challenge: how can we
analyze their representations in order to understand how they solve complex
tasks?
We review how data-analysis concepts and techniques developed by
computational neuroscientists can be useful for analyzing representations in
DNNs, and in turn, how recently developed techniques for analysis of DNNs can
be useful for understanding representations in biological neural networks. We
explore opportunities for synergy between the two fields, such as the use of
DNNs as in-silico model systems for neuroscience, and how this synergy can lead
to new hypotheses about the operating principles of biological neural networks.
| 0 | 0 | 0 | 0 | 1 | 0 |
Recurrences in an isolated quantum many-body system | Even though the evolution of an isolated quantum system is unitary, the
complexity of interacting many-body systems prevents the observation of
recurrences of quantum states for all but the smallest systems. For large
systems one can not access the full complexity of the quantum states and the
requirements to observe a recurrence in experiments reduces to being close to
the initial state with respect to the employed observable. Selecting an
observable connected to the collective excitations in one-dimensional
superfluids, we demonstrate recurrences of coherence and long range order in an
interacting quantum many-body system containing thousands of particles. This
opens up a new window into the dynamics of large quantum systems even after
they reached a transient thermal-like state.
| 0 | 1 | 0 | 0 | 0 | 0 |
Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization | We tackle the issue of classifier combinations when observations have
multiple views. Our method jointly learns view-specific weighted majority vote
classifiers (i.e. for each view) over a set of base voters, and a second
weighted majority vote classifier over the set of these view-specific weighted
majority vote classifiers. We show that the empirical risk minimization of the
final majority vote given a multiview training set can be cast as the
minimization of Bregman divergences. This allows us to derive a parallel-update
optimization algorithm for learning our multiview model. We empirically study
our algorithm with a particular focus on the impact of the training set size on
the multiview learning results. The experiments show that our approach is able
to overcome the lack of labeled information.
| 0 | 0 | 0 | 1 | 0 | 0 |
Temporal Overbooking of Lambda Functions in the Cloud | We consider the problem of scheduling "serverless computing" instances such
as Amazon Lambda functions. Instead of a quota per tenant/customer, we assume
demand for Lambda functions is modulated by token-bucket mechanisms per tenant.
Based on an upper bound on the stationary number of active "Lambda servers"
considering the execution-time distribution of Lambda functions, we describe an
approach that the cloud could use to overbook Lambda functions for improved
utilization of IT resources. An earlier bound for a single service tier is
extended to the case of multiple service tiers.
| 1 | 0 | 0 | 0 | 0 | 0 |
Orbital degeneracy loci and applications | Degeneracy loci of morphisms between vector bundles have been used in a wide
variety of situations. We introduce a vast generalization of this notion, based
on orbit closures of algebraic groups in their linear representations. A
preferred class of our orbital degeneracy loci is characterized by a certain
crepancy condition on the orbit closure, that allows to get some control on the
canonical sheaf. This condition is fulfilled for Richardson nilpotent orbits,
and also for partially decomposable skew-symmetric three-forms in six
variables. In order to illustrate the efficiency and flexibility of our
methods, we construct in both situations many Calabi--Yau manifolds of
dimension three and four, as well as a few Fano varieties, including some new
Fano fourfolds.
| 0 | 0 | 1 | 0 | 0 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.