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1,802.0246
Upscaling Singular Sources in Weighted Sobolev Spaces by Sub-Grid Corrections
In this paper, we develop a numerical multiscale method to solve elliptic boundary value problems with heterogeneous diffusion coefficients and with singular source terms. When the diffusion coefficient is heterogeneous, this adds to the computational costs, and this difficulty is compounded by a singular source term. For singular source terms, the solution does not belong to the Sobolev space $H^1$, but to the space $W^{1,p}$ for some $p<2$. Hence, the problem may be reformulated in a distance-weighted Sobolev space. Using this formulation, we develop a method to upscale the multiscale coefficient near the singular sources by incorporating corrections into the coarse-grid. Using a sub-grid correction method, we correct the basis functions in a distance-weighted Sobolev space and show that these corrections can be truncated to design a computationally efficient scheme with optimal convergence rates. Due to the nature of the formulation in weighted spaces, the variational form must be posed on the cross product of complementary spaces. Thus, two such sub-grid corrections must be computed, one for each multiscale space of the cross product. A key ingredient of this method is the use of quasi-interpolation operators to construct the fine scale spaces. Therefore, we develop a weighted projective quasi-interpolation that can be used for a general class of Muckenhoupt weight functions. We verify the optimal convergence of the method in some numerical examples with singular point sources and line fractures, and with oscillatory and heterogeneous diffusion coefficients.
math.NA
in this paper we develop a numerical multiscale method to solve elliptic boundary value problems with heterogeneous diffusion coefficients and with singular source terms when the diffusion coefficient is heterogeneous this adds to the computational costs and this difficulty is compounded by a singular source term for singular source terms the solution does not belong to the sobolev space h1 but to the space w1p for some p2 hence the problem may be reformulated in a distanceweighted sobolev space using this formulation we develop a method to upscale the multiscale coefficient near the singular sources by incorporating corrections into the coarsegrid using a subgrid correction method we correct the basis functions in a distanceweighted sobolev space and show that these corrections can be truncated to design a computationally efficient scheme with optimal convergence rates due to the nature of the formulation in weighted spaces the variational form must be posed on the cross product of complementary spaces thus two such subgrid corrections must be computed one for each multiscale space of the cross product a key ingredient of this method is the use of quasiinterpolation operators to construct the fine scale spaces therefore we develop a weighted projective quasiinterpolation that can be used for a general class of muckenhoupt weight functions we verify the optimal convergence of the method in some numerical examples with singular point sources and line fractures and with oscillatory and heterogeneous diffusion coefficients
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1,802.02461
Rotation of the photospheric magnetic field through solar cycles 21, 22, 23
Rotation of the large scale solar magnetic field has a great importance for the understanding of solar dynamic, for the search of longitidinal structure and for the study of solar-terrestrial relations. 30-year long observations taken at the Wilcox Solar Observatory (USA) in 21-23 cycles have been analysed carefully to deduce magnetic field rotation rate at different latitudes in both hemispheres and its variability in time. The WSO data appear to indicate that additionally to the differential rotation along the latitudes there are running waves of fast rotation of the magnetic field. These torsional waves are running from the poles to the equator with a period of 11 years. The rotation of the magnetic field (RMF) is almost rigid at latitudes above 55 degrees in both hemispheres. The rotation rate in the sub-polar regions is slower when the magnetic field is strong there (during minima of solar activity), and faster when the magnetic field changes polarity (during maxima of solar activity).
astro-ph.SR physics.geo-ph physics.plasm-ph
rotation of the large scale solar magnetic field has a great importance for the understanding of solar dynamic for the search of longitidinal structure and for the study of solarterrestrial relations 30year long observations taken at the wilcox solar observatory usa in 2123 cycles have been analysed carefully to deduce magnetic field rotation rate at different latitudes in both hemispheres and its variability in time the wso data appear to indicate that additionally to the differential rotation along the latitudes there are running waves of fast rotation of the magnetic field these torsional waves are running from the poles to the equator with a period of 11 years the rotation of the magnetic field rmf is almost rigid at latitudes above 55 degrees in both hemispheres the rotation rate in the subpolar regions is slower when the magnetic field is strong there during minima of solar activity and faster when the magnetic field changes polarity during maxima of solar activity
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1,802.02462
Systematic Analysis of Low/Hard State RXTE Spectra of GX 339-4 to Constrain the Geometry of the System
One of the popular models for the low/hard state of Black Hole Binaries is that the standard accretion disk is truncated and the hot inner region produces via Comptonization, the hard X-ray flux. This is supported by the value of the high energy photon index, which is often found to be small $\sim$ 1.7 ($<$ 2) implying that the hot medium is seed photons starved. On the other hand, the suggestive presence of a broad relativistic Fe line during the hard state would suggest that the accretion disk is not truncated but extends all the way to the inner most stable circle orbit. In such a case, it is a puzzle why the hot medium would remain photon starved. The broad Fe line should be accompanied by a broad smeared reflection hump at $\sim$ 30 keV and it may be that this additional component makes the spectrum hard and the intrinsic photon index is larger, i.e. $>$ 2. This would mean that the medium is not photon deficient, reconciling the presence of a broad Fe line in the observed hard state. To test this hypothesis, we have analyzed the RXTE observations of GX 339-4 from the four outbursts during 2002-2011 and identify the observations when the system was in the hard state and showed a broad Fe line. We have then attempted to fit these observations with models, which include smeared reflection to understand whether the intrinsic photon index can indeed be large. We find that, while for some observations the inclusion of reflection does increase the photon index, there are hard state observations with broad Fe line that have photon indices less than 2.
astro-ph.HE
one of the popular models for the lowhard state of black hole binaries is that the standard accretion disk is truncated and the hot inner region produces via comptonization the hard xray flux this is supported by the value of the high energy photon index which is often found to be small sim 17 2 implying that the hot medium is seed photons starved on the other hand the suggestive presence of a broad relativistic fe line during the hard state would suggest that the accretion disk is not truncated but extends all the way to the inner most stable circle orbit in such a case it is a puzzle why the hot medium would remain photon starved the broad fe line should be accompanied by a broad smeared reflection hump at sim 30 kev and it may be that this additional component makes the spectrum hard and the intrinsic photon index is larger ie 2 this would mean that the medium is not photon deficient reconciling the presence of a broad fe line in the observed hard state to test this hypothesis we have analyzed the rxte observations of gx 3394 from the four outbursts during 20022011 and identify the observations when the system was in the hard state and showed a broad fe line we have then attempted to fit these observations with models which include smeared reflection to understand whether the intrinsic photon index can indeed be large we find that while for some observations the inclusion of reflection does increase the photon index there are hard state observations with broad fe line that have photon indices less than 2
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1,802.02463
Second order differentiation formula on $RCD^*(K,N)$ spaces
Aim of this paper is to prove the second order differentiation formula for $H^{2,2}$ functions along geodesics in $RCD^*(K,N)$ spaces with $N < \infty$. This formula is new even in the context of Alexandrov spaces, where second order differentiation is typically related to semiconvexity. We establish this result by showing that $W_2$-geodesics can be approximated up to second order, in a sense which we shall make precise, by entropic interpolation. In turn this is achieved by proving new, even in the smooth setting, estimates concerning entropic interpolations which we believe are interesting on their own. In particular we obtain: - equiboundedness of the densities along the entropic interpolations, - local equi-Lipschitz continuity of the Schr\"odinger potentials, - a uniform weighted $L^2$ control of the Hessian of such potentials. Finally, the techniques adopted in this paper can be used to show that in the $RCD$ setting the viscous solution of the Hamilton-Jacobi equation can be obtained via a vanishing viscosity method, in accordance with the smooth case. With respect to a previous version, where the space was assumed to be compact, in this paper the second order differentiation formula is proved in full generality.
math.AP
aim of this paper is to prove the second order differentiation formula for h22 functions along geodesics in rcdkn spaces with n infty this formula is new even in the context of alexandrov spaces where second order differentiation is typically related to semiconvexity we establish this result by showing that w_2geodesics can be approximated up to second order in a sense which we shall make precise by entropic interpolation in turn this is achieved by proving new even in the smooth setting estimates concerning entropic interpolations which we believe are interesting on their own in particular we obtain equiboundedness of the densities along the entropic interpolations local equilipschitz continuity of the schrodinger potentials a uniform weighted l2 control of the hessian of such potentials finally the techniques adopted in this paper can be used to show that in the rcd setting the viscous solution of the hamiltonjacobi equation can be obtained via a vanishing viscosity method in accordance with the smooth case with respect to a previous version where the space was assumed to be compact in this paper the second order differentiation formula is proved in full generality
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1,802.02464
Improved Time of Arrival measurement model for non-convex optimization with noisy data
The quadratic system provided by the Time of Arrival technique can be solved analytical or by optimization algorithms. In real environments the measurements are always corrupted by noise. This measurement noise effects the analytical solution more than non-linear optimization algorithms. On the other hand it is also true that local optimization tends to find the local minimum, instead of the global minimum. This article presents an approach how this risk can be significantly reduced in noisy environments. The main idea of our approach is to transform the local minimum to a saddle point, by increasing the number of dimensions.
eess.SP
the quadratic system provided by the time of arrival technique can be solved analytical or by optimization algorithms in real environments the measurements are always corrupted by noise this measurement noise effects the analytical solution more than nonlinear optimization algorithms on the other hand it is also true that local optimization tends to find the local minimum instead of the global minimum this article presents an approach how this risk can be significantly reduced in noisy environments the main idea of our approach is to transform the local minimum to a saddle point by increasing the number of dimensions
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1,802.02465
Phantom fluid supporting traversable wormholes in alternative gravity with extra material terms
Wormholes are tunnels connecting different regions in space-time. They were obtained originally as a solution for Einstein's General Relativity theory and according to this theory they need to be filled by an exotic kind of anisotropic matter. In the present sense, by "exotic matter" we mean matter that does not satisfy the energy conditions. In this article we propose the modelling of wormholes within an alternative gravity theory that proposes an extra material (rather than geometrical) term in its gravitational action. Our solutions are obtained from well-known particular cases of the wormhole metric potentials, named redshift and shape functions, and yield the wormholes to be filled by a phantom fluid, that is, a fluid with equation of state parameter $\omega<-1$. In possession of the solutions for the wormhole material content, we also apply the energy conditions to them. The features of those are carefully discussed.
gr-qc
wormholes are tunnels connecting different regions in spacetime they were obtained originally as a solution for einsteins general relativity theory and according to this theory they need to be filled by an exotic kind of anisotropic matter in the present sense by exotic matter we mean matter that does not satisfy the energy conditions in this article we propose the modelling of wormholes within an alternative gravity theory that proposes an extra material rather than geometrical term in its gravitational action our solutions are obtained from wellknown particular cases of the wormhole metric potentials named redshift and shape functions and yield the wormholes to be filled by a phantom fluid that is a fluid with equation of state parameter omega1 in possession of the solutions for the wormhole material content we also apply the energy conditions to them the features of those are carefully discussed
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1,802.02466
Three Random Intercepts of a Segment
We construct random triangles via uniform sampling of certain families of lines in the plane. Two examples are given. The word "uniform" turns out to be vague; two competing models are examined. Everything we write is well-known to experts. Which model is more appropriate? Our hope is to engage a larger audience in answering this question.
math.HO
we construct random triangles via uniform sampling of certain families of lines in the plane two examples are given the word uniform turns out to be vague two competing models are examined everything we write is wellknown to experts which model is more appropriate our hope is to engage a larger audience in answering this question
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1,802.02467
Mixtures of Factor Analyzers with Fundamental Skew Symmetric Distributions
Mixtures of factor analyzers (MFA) provide a powerful tool for modelling high-dimensional datasets. In recent years, several generalizations of MFA have been developed where the normality assumption of the factors and/or of the errors was relaxed to allow for skewness in the data. However, due to the form of the adopted component densities, the distribution of the factors/errors in most of these models is typically limited to modelling skewness oncentrated in a single direction. Here, we introduce a more flexible finite mixture of factor analyzers based on the class of scale mixtures of canonical fundamental skew normal (SMCFUSN) distributions. This very general class of skew distributions can capture various types of skewness and asymmetry in the data. In particular, the proposed mixture model of SMCFUSN factor analyzers(SMCFUSNFA) can simultaneously accommodate multiple directions of skewness. As such, it encapsulates many commonly used models as special and/or limiting cases, such as models of some versions of skew normal and skew t-factor analyzers, and skew hyperbolic factor analyzers. For illustration, we focus on the t-distribution member of the class of SMCFUSN distributions, leading to mixtures of canonical fundamental skew t-factor analyzers (CFUSTFA). Parameter estimation can be carried out by maximum likelihood via an EM-type algorithm. The usefulness and potential of the proposed model are demonstrated using two real datasets.
stat.ME
mixtures of factor analyzers mfa provide a powerful tool for modelling highdimensional datasets in recent years several generalizations of mfa have been developed where the normality assumption of the factors andor of the errors was relaxed to allow for skewness in the data however due to the form of the adopted component densities the distribution of the factorserrors in most of these models is typically limited to modelling skewness oncentrated in a single direction here we introduce a more flexible finite mixture of factor analyzers based on the class of scale mixtures of canonical fundamental skew normal smcfusn distributions this very general class of skew distributions can capture various types of skewness and asymmetry in the data in particular the proposed mixture model of smcfusn factor analyzerssmcfusnfa can simultaneously accommodate multiple directions of skewness as such it encapsulates many commonly used models as special andor limiting cases such as models of some versions of skew normal and skew tfactor analyzers and skew hyperbolic factor analyzers for illustration we focus on the tdistribution member of the class of smcfusn distributions leading to mixtures of canonical fundamental skew tfactor analyzers cfustfa parameter estimation can be carried out by maximum likelihood via an emtype algorithm the usefulness and potential of the proposed model are demonstrated using two real datasets
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1,802.02468
Efficient Learning of Bounded-Treewidth Bayesian Networks from Complete and Incomplete Data Sets
Learning a Bayesian networks with bounded treewidth is important for reducing the complexity of the inferences. We present a novel anytime algorithm (k-MAX) method for this task, which scales up to thousands of variables. Through extensive experiments we show that it consistently yields higher-scoring structures than its competitors on complete data sets. We then consider the problem of structure learning from incomplete data sets. This can be addressed by structural EM, which however is computationally very demanding. We thus adopt the novel k-MAX algorithm in the maximization step of structural EM, obtaining an efficient computation of the expected sufficient statistics. We test the resulting structural EM method on the task of imputing missing data, comparing it against the state-of-the-art approach based on random forests. Our approach achieves the same imputation accuracy of the competitors, but in about one tenth of the time. Furthermore we show that it has worst-case complexity linear in the input size, and that it is easily parallelizable.
cs.AI
learning a bayesian networks with bounded treewidth is important for reducing the complexity of the inferences we present a novel anytime algorithm kmax method for this task which scales up to thousands of variables through extensive experiments we show that it consistently yields higherscoring structures than its competitors on complete data sets we then consider the problem of structure learning from incomplete data sets this can be addressed by structural em which however is computationally very demanding we thus adopt the novel kmax algorithm in the maximization step of structural em obtaining an efficient computation of the expected sufficient statistics we test the resulting structural em method on the task of imputing missing data comparing it against the stateoftheart approach based on random forests our approach achieves the same imputation accuracy of the competitors but in about one tenth of the time furthermore we show that it has worstcase complexity linear in the input size and that it is easily parallelizable
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1,802.02469
A complete framework for linear filtering of bivariate signals
A complete framework for the linear time-invariant (LTI) filtering theory of bivariate signals is proposed based on a tailored quaternion Fourier transform. This framework features a direct description of LTI filters in terms of their eigenproperties enabling compact calculus and physically interpretable filtering relations in the frequency domain. The design of filters exhibiting fondamental properties of polarization optics (birefringence, diattenuation) is straightforward. It yields an efficient spectral synthesis method and new insights on Wiener filtering for bivariate signals with prescribed frequency-dependent polarization properties. This generic framework facilitates original descriptions of bivariate signals in two components with specific geometric or statistical properties. Numerical experiments support our theoretical analysis and illustrate the relevance of the approach on synthetic data.
eess.SP
a complete framework for the linear timeinvariant lti filtering theory of bivariate signals is proposed based on a tailored quaternion fourier transform this framework features a direct description of lti filters in terms of their eigenproperties enabling compact calculus and physically interpretable filtering relations in the frequency domain the design of filters exhibiting fondamental properties of polarization optics birefringence diattenuation is straightforward it yields an efficient spectral synthesis method and new insights on wiener filtering for bivariate signals with prescribed frequencydependent polarization properties this generic framework facilitates original descriptions of bivariate signals in two components with specific geometric or statistical properties numerical experiments support our theoretical analysis and illustrate the relevance of the approach on synthetic data
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1,802.0247
On the gaps between consecutive primes
Let $p_n$ denote the $n$-th prime. For any $m\geq 1$, there exist infinitely many $n$ such that $p_{n}-p_{n-m}\leq C_m$ for some large constant $C_m>0$, and $$p_{n+1}-p_n\geq \frac{c_m\log n\log\log n\log\log\log\log n}{\log\log\log n}, $$ for some small constant $c_m>0$. Furthermore, we also obtain a related result concerning the least primes in arithmetic progressions.
math.NT math.CO
let p_n denote the nth prime for any mgeq 1 there exist infinitely many n such that p_np_nmleq c_m for some large constant c_m0 and p_n1p_ngeq fracc_mlog nloglog nloglogloglog nlogloglog n for some small constant c_m0 furthermore we also obtain a related result concerning the least primes in arithmetic progressions
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1,802.02471
Local Self-Energies for V and Pd Emergent from a Non-Local LDA+FLEX Implementation
In the spirit of recently developed LDA+U and LDA+DMFT methods we implement a combination of density functional theory in its local density approximation (LDA) with a $k$- and $\omega -$dependent self-energy found from diagrammatic fluctuational exchange (FLEX) approximation. The active Hilbert space here is described by the correlated subset of electrons which allows to tremendously reduce the sizes of matrices needed to represent charge and spin susceptibilities. The method is perturbative in nature but accounts for both bubble and ladder diagrams and accumulates the physics of momentum resolved spin fluctuations missing in such popular approach as GW. As an application, we study correlation effects on band structures in V and Pd. The d-electron self-energies emergent from this calculation are found to be remarkably k-independent. However, when we compare our calculated electronic mass enhancements against LDA+DMFT, we find that for a long standing problem of spin fluctuations in Pd, LDA+FLEX delivers a better agreement with experiment, although this conclusion depends on a particular value of Hubbard $U$ used in the simulation. We also discuss outcomes of recently proposed combinations of k-dependent FLEX with DMFT.
cond-mat.str-el cond-mat.mtrl-sci
in the spirit of recently developed ldau and ldadmft methods we implement a combination of density functional theory in its local density approximation lda with a k and omega dependent selfenergy found from diagrammatic fluctuational exchange flex approximation the active hilbert space here is described by the correlated subset of electrons which allows to tremendously reduce the sizes of matrices needed to represent charge and spin susceptibilities the method is perturbative in nature but accounts for both bubble and ladder diagrams and accumulates the physics of momentum resolved spin fluctuations missing in such popular approach as gw as an application we study correlation effects on band structures in v and pd the delectron selfenergies emergent from this calculation are found to be remarkably kindependent however when we compare our calculated electronic mass enhancements against ldadmft we find that for a long standing problem of spin fluctuations in pd ldaflex delivers a better agreement with experiment although this conclusion depends on a particular value of hubbard u used in the simulation we also discuss outcomes of recently proposed combinations of kdependent flex with dmft
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1,802.02472
Forceless Sadowsky strips are spherical
We show that thin rectangular ribbons, defined as energy-minimising configurations of the Sadowsky functional for narrow developable elastic strips, have a propensity to form spherical shapes in the sense that forceless solutions lie on a sphere. This has implications for ribbonlike objects in (bio)polymer physics and nanoscience that cannot be described by the classical wormlike chain model. A wider class of functionals with this property is identified.
cond-mat.soft
we show that thin rectangular ribbons defined as energyminimising configurations of the sadowsky functional for narrow developable elastic strips have a propensity to form spherical shapes in the sense that forceless solutions lie on a sphere this has implications for ribbonlike objects in biopolymer physics and nanoscience that cannot be described by the classical wormlike chain model a wider class of functionals with this property is identified
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1,802.02473
Radiating solitary waves in coupled Boussinesq equations
In this paper we are consider radiating solitary wave solutions of coupled regularised Boussinesq equations. This type of solution consists of a leading solitary wave with a small-amplitude co-propagating oscillatory tail, and emerges from a pure solitary wave solution of a symmetric reduction of the full system. We construct an asymptotic solution, where the leading order approximation in both components is obtained as a particular solution of the regularised Boussinesq equations in the symmetric case. At the next order, the system uncouples into two linear non-homogeneous ordinary differential equations with variable coefficients, one correcting the localised part of the solution, which we find analytically, and the other describing the co-propagating oscillatory tail. This latter equation is a fourth-order ordinary differential equation and is solved approximately by two different methods, each exploiting the assumption that the leading solitary wave has a small amplitude, and thus enabling an explicit estimate for the amplitude of the oscillating tail. These estimates are compared with corresponding numerical simulations.
nlin.PS
in this paper we are consider radiating solitary wave solutions of coupled regularised boussinesq equations this type of solution consists of a leading solitary wave with a smallamplitude copropagating oscillatory tail and emerges from a pure solitary wave solution of a symmetric reduction of the full system we construct an asymptotic solution where the leading order approximation in both components is obtained as a particular solution of the regularised boussinesq equations in the symmetric case at the next order the system uncouples into two linear nonhomogeneous ordinary differential equations with variable coefficients one correcting the localised part of the solution which we find analytically and the other describing the copropagating oscillatory tail this latter equation is a fourthorder ordinary differential equation and is solved approximately by two different methods each exploiting the assumption that the leading solitary wave has a small amplitude and thus enabling an explicit estimate for the amplitude of the oscillating tail these estimates are compared with corresponding numerical simulations
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1,802.02474
High-level python abstractions for optimal checkpointing in inversion problems
Inversion and PDE-constrained optimization problems often rely on solving the adjoint problem to calculate the gradient of the objec- tive function. This requires storing large amounts of intermediate data, setting a limit to the largest problem that might be solved with a given amount of memory available. Checkpointing is an approach that can reduce the amount of memory required by redoing parts of the computation instead of storing intermediate results. The Revolve checkpointing algorithm o ers an optimal schedule that trades computational cost for smaller memory footprints. Integrat- ing Revolve into a modern python HPC code and combining it with code generation is not straightforward. We present an API that makes checkpointing accessible from a DSL-based code generation environment along with some initial performance gures with a focus on seismic applications.
cs.MS cs.CE
inversion and pdeconstrained optimization problems often rely on solving the adjoint problem to calculate the gradient of the objec tive function this requires storing large amounts of intermediate data setting a limit to the largest problem that might be solved with a given amount of memory available checkpointing is an approach that can reduce the amount of memory required by redoing parts of the computation instead of storing intermediate results the revolve checkpointing algorithm o ers an optimal schedule that trades computational cost for smaller memory footprints integrat ing revolve into a modern python hpc code and combining it with code generation is not straightforward we present an api that makes checkpointing accessible from a dslbased code generation environment along with some initial performance gures with a focus on seismic applications
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1,802.02475
Out-of-Band Radiation from Antenna Arrays Clarified
Non-linearities in radio-frequency (RF) transceiver hardware, particularly in power amplifiers, cause distortion in-band and out-of-band. Contrary to claims made in recent literature, in a multiple-antenna system this distortion is correlated across the antennas in the array. A significant implication of this fact is that out-of-band emissions caused by non-linearities are beamformed, in some cases into the same direction as the useful signal.
cs.IT math.IT
nonlinearities in radiofrequency rf transceiver hardware particularly in power amplifiers cause distortion inband and outofband contrary to claims made in recent literature in a multipleantenna system this distortion is correlated across the antennas in the array a significant implication of this fact is that outofband emissions caused by nonlinearities are beamformed in some cases into the same direction as the useful signal
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1,802.02476
Order continuous operators on pre-Riesz spaces and embeddings
We investigate properties of order continuous operators on pre-Riesz spaces with respect to the embedding of the range space into a vector lattice cover or, in particular, into its Dedekind completion. We show that order continuity is preserved under this embedding for positive operators, but not in general. For the vector lattice $\ell_0^\infty$ of eventually constant sequences, we consider the pre-Riesz space of regular operators on $\ell_0^\infty$ and show that making the range space Dedekind complete does not provide a vector lattice cover of the pre-Riesz space. A similar counterexample is obtained for the directed part of the space of order continuous operators on $\ell_0^\infty$.
math.FA
we investigate properties of order continuous operators on preriesz spaces with respect to the embedding of the range space into a vector lattice cover or in particular into its dedekind completion we show that order continuity is preserved under this embedding for positive operators but not in general for the vector lattice ell_0infty of eventually constant sequences we consider the preriesz space of regular operators on ell_0infty and show that making the range space dedekind complete does not provide a vector lattice cover of the preriesz space a similar counterexample is obtained for the directed part of the space of order continuous operators on ell_0infty
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1,802.02477
Common solar wind drivers behind magnetic storm-magnetospheric substorm dependency
The dynamical relationship between magnetic storms and magnetospheric substorms presents one of the most controversial problems of contemporary geospace research. Here, we tackle this issue by applying a causal inference approach to two corresponding indices in conjunction with several relevant solar wind variables. We demonstrate that the vertical component of the interplanetary magnetic field is the strongest and common driver of both, storms and substorms, and explains their the previously reported association. These results hold during both solar maximum and minimum phases and suggest that, at least based on the analyzed indices, there is no statistical evidence for a direct or indirect dependency between substorms and storms. A physical mechanism by which substorms drive storms or vice versa is, therefore, unlikely.
physics.space-ph
the dynamical relationship between magnetic storms and magnetospheric substorms presents one of the most controversial problems of contemporary geospace research here we tackle this issue by applying a causal inference approach to two corresponding indices in conjunction with several relevant solar wind variables we demonstrate that the vertical component of the interplanetary magnetic field is the strongest and common driver of both storms and substorms and explains their the previously reported association these results hold during both solar maximum and minimum phases and suggest that at least based on the analyzed indices there is no statistical evidence for a direct or indirect dependency between substorms and storms a physical mechanism by which substorms drive storms or vice versa is therefore unlikely
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1,802.02478
On the Stability of Independence Polynomials
The independence polynomial of a graph is the generating polynomial for the number of independent sets of each size, and its roots are called {\em independence roots}. We investigate the stability of such polynomials, that is, conditions under which the roots lie in the left half-plane (all of the real roots of independence polynomial are negative and hence lie in this half-plane). We show stability for all independence polynomials of graphs with independence number at most three, but for larger independence number we show that the independence polynomials can have roots arbitrarily far to the right. We provide families of graphs whose independence polynomials are stable and ones that are not, utilizing various graph operations.
math.CO
the independence polynomial of a graph is the generating polynomial for the number of independent sets of each size and its roots are called em independence roots we investigate the stability of such polynomials that is conditions under which the roots lie in the left halfplane all of the real roots of independence polynomial are negative and hence lie in this halfplane we show stability for all independence polynomials of graphs with independence number at most three but for larger independence number we show that the independence polynomials can have roots arbitrarily far to the right we provide families of graphs whose independence polynomials are stable and ones that are not utilizing various graph operations
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1,802.02479
Virtual photon polarization and dilepton anisotropy in relativistic nucleus-nucleus collisions
The polarization of virtual photons produced in relativistic nucleus-nucleus collisions provides information on the conditions in the emitting medium. In a hydrodynamic framework, the resulting angular anisotropy of the dilepton final state depends on the flow as well as on the transverse momentum and invariant mass of the photon. We illustrate these effects in dilepton production from quark-antiquark annihilation in the QGP phase and $\pi^+\pi^-$ annihilation in the hadronic phase for a static medium in global equilibrium and for a longitudinally expanding system.
hep-ph
the polarization of virtual photons produced in relativistic nucleusnucleus collisions provides information on the conditions in the emitting medium in a hydrodynamic framework the resulting angular anisotropy of the dilepton final state depends on the flow as well as on the transverse momentum and invariant mass of the photon we illustrate these effects in dilepton production from quarkantiquark annihilation in the qgp phase and pipi annihilation in the hadronic phase for a static medium in global equilibrium and for a longitudinally expanding system
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1,802.0248
Click Spam Prevention Model for On-Line Advertisement
This paper shows a vulnerability of the pay-per-click accounting of Google Ads and proposes a statistical tradeoff-based approach to manage this vulnerability. The result of this paper is a model to calculate the overhead cost per click necessary to protect the subscribers and a simple algorithm to implement this protection. Simulations validate the correctness of the model and the economical applicability.
cs.NI
this paper shows a vulnerability of the payperclick accounting of google ads and proposes a statistical tradeoffbased approach to manage this vulnerability the result of this paper is a model to calculate the overhead cost per click necessary to protect the subscribers and a simple algorithm to implement this protection simulations validate the correctness of the model and the economical applicability
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1,802.02481
Weighted Morrey spaces related to Schrodinger operators with potentials satisfying a reverse Holder inequality and fractional integrals
Let $\mathcal L=-\Delta+V$ be a Schr\"odinger operator on $\mathbb R^d$, $d\geq3$, where $\Delta$ is the Laplacian operator on $\mathbb R^d$ and the nonnegative potential $V$ belongs to the reverse H\"older class $RH_s$ for $s\geq d/2$. For given $0<\alpha<d$, the fractional integrals associated to the Schr\"odinger operator $\mathcal L$ is defined by $\mathcal I_{\alpha}={\mathcal L}^{-{\alpha}/2}$.Suppose that $b$ is a locally integrable function on $\mathbb R^d$, the commutator generated by $b$ and $\mathcal I_{\alpha}$ is defined by $[b,\mathcal I_{\alpha}]f(x)=b(x)\cdot \mathcal I_{\alpha}f(x)-\mathcal I_{\alpha}(bf)(x)$. In this paper, we first introduce some kinds of weighted Morrey spaces related to certain nonnegative potentials belonging to the reverse H\"older class $RH_s$ for $s\geq d/2$. Then we will establish the boundedness properties of the fractional integrals $\mathcal I_{\alpha}$ on these new spaces. Furthermore, weighted strong-type estimate for the corresponding commutator $[b,\mathcal I_{\alpha}]$ in the framework of Morrey spaces is also obtained. The classes of weights, the classes of symbol functions as well as weighted Morrey spaces discussed in this paper are larger than $A_{p,q}$, $\mathrm{BMO}(\mathbb R^d)$ and $L^{p,\kappa}(\mu,\nu)$ corresponding to the classical case (that is $V\equiv0$).
math.CA
let mathcal ldeltav be a schrodinger operator on mathbb rd dgeq3 where delta is the laplacian operator on mathbb rd and the nonnegative potential v belongs to the reverse holder class rh_s for sgeq d2 for given 0alphad the fractional integrals associated to the schrodinger operator mathcal l is defined by mathcal i_alphamathcal lalpha2suppose that b is a locally integrable function on mathbb rd the commutator generated by b and mathcal i_alpha is defined by bmathcal i_alphafxbxcdot mathcal i_alphafxmathcal i_alphabfx in this paper we first introduce some kinds of weighted morrey spaces related to certain nonnegative potentials belonging to the reverse holder class rh_s for sgeq d2 then we will establish the boundedness properties of the fractional integrals mathcal i_alpha on these new spaces furthermore weighted strongtype estimate for the corresponding commutator bmathcal i_alpha in the framework of morrey spaces is also obtained the classes of weights the classes of symbol functions as well as weighted morrey spaces discussed in this paper are larger than a_pq mathrmbmomathbb rd and lpkappamunu corresponding to the classical case that is vequiv0
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1,802.02482
The paradigm of complexity. Contributions for hypertext's formal approaches
This article argues for a return to formal approaches of hypertext and builds on the paradigm of complexity to develop the idea of "hypermediator website". A hypermediator website is an intermediate device between a digitalization of book culture and a "real" hypertext writing. If our thinking on the hypermediator website joined the hypertext's notions and the databases, it differs by the relationship reader-device no longer based on information search query but using the visualization of the information.
cs.DL
this article argues for a return to formal approaches of hypertext and builds on the paradigm of complexity to develop the idea of hypermediator website a hypermediator website is an intermediate device between a digitalization of book culture and a real hypertext writing if our thinking on the hypermediator website joined the hypertexts notions and the databases it differs by the relationship readerdevice no longer based on information search query but using the visualization of the information
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1,802.02483
Power-Controlled Hamiltonian Systems: Application to Electrical Systems with Constant Power Loads
We study a type of port-Hamiltonian system, in which the controller or disturbance is not applied to the flow variables, but to the systems power, a scenario that appears in many practical applications. A suitable framework is provided to model these systems and to investigate their shifted passivity properties, based on which, a stability analysis is carried out. The applicability of the results is illustrated with the important problem of stability analysis of electrical circuits with constant power loads.
cs.SY
we study a type of porthamiltonian system in which the controller or disturbance is not applied to the flow variables but to the systems power a scenario that appears in many practical applications a suitable framework is provided to model these systems and to investigate their shifted passivity properties based on which a stability analysis is carried out the applicability of the results is illustrated with the important problem of stability analysis of electrical circuits with constant power loads
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1,802.02484
Dark states in spin-polarized transport through triple quantum dot molecules
We study the spin-polarized transport through a triple quantum dot molecule weakly coupled to ferromagnetic leads. The analysis is performed by means of the real-time diagrammatic technique including up to the second order of perturbation expansion with respect to the tunnel coupling. The emphasis is put on the impact of dark states on spin-resolved transport characteristics. It is shown that the interplay of coherent population trapping and cotunneling processes results in a highly nontrivial behavior of the tunnel magnetoresistance, which can take negative values. Moreover, a super-Poissonian shot noise is found in transport regimes where the current is blocked by the formation of dark states, which can be additionally enhanced by spin-dependence of tunneling processes, depending on magnetic configuration of the device. The mechanisms leading to those effects are thoroughly discussed.
cond-mat.mes-hall
we study the spinpolarized transport through a triple quantum dot molecule weakly coupled to ferromagnetic leads the analysis is performed by means of the realtime diagrammatic technique including up to the second order of perturbation expansion with respect to the tunnel coupling the emphasis is put on the impact of dark states on spinresolved transport characteristics it is shown that the interplay of coherent population trapping and cotunneling processes results in a highly nontrivial behavior of the tunnel magnetoresistance which can take negative values moreover a superpoissonian shot noise is found in transport regimes where the current is blocked by the formation of dark states which can be additionally enhanced by spindependence of tunneling processes depending on magnetic configuration of the device the mechanisms leading to those effects are thoroughly discussed
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1,802.02485
BROJA-2PID: A robust estimator for bivariate partial information decomposition
Makkeh, Theis, and Vicente found in [8] that Cone Programming model is the most robust to compute the Bertschinger et al. partial information decompostion (BROJA PID) measure [1]. We developed a production-quality robust software that computes the BROJA PID measure based on the Cone Programming model. In this paper, we prove the important property of strong duality for the Cone Program and prove an equivalence between the Cone Program and the original Convex problem. Then describe in detail our software and how to use it.\newline\indent
math.OC
makkeh theis and vicente found in 8 that cone programming model is the most robust to compute the bertschinger et al partial information decompostion broja pid measure 1 we developed a productionquality robust software that computes the broja pid measure based on the cone programming model in this paper we prove the important property of strong duality for the cone program and prove an equivalence between the cone program and the original convex problem then describe in detail our software and how to use itnewlineindent
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1,802.02486
The field of quantum $GL(N,\mathbb{C})$ in the C$^*$-algebraic setting
Given a unital $*$-algebra $\mathscr{A}$ together with a suitable positive filtration of its set of irreducible bounded representations, one can construct a C$^*$-algebra $A_0$ with a dense two-sided ideal $A_c$ such that $\mathscr{A}$ maps into the multiplier algebra of $A_c$. When the filtration is induced from a central element in $\mathscr{A}$, we say that $\mathscr{A}$ is an s$^*$-algebra. We also introduce the notion of $\mathscr{R}$-algebra relative to a commutative s$^*$-algebra $\mathscr{R}$, and of Hopf $\mathscr{R}$-algebra. We formulate conditions such that the completion of a Hopf $\mathscr{R}$-algebra gives rise to a continuous field of Hopf C$^*$-algebras over the spectrum of $R_0$. We apply the general theory to the case of quantum $GL(N,\mathbb{C})$ as constructed from the FRT-formalism.
math.QA math.OA
given a unital algebra mathscra together with a suitable positive filtration of its set of irreducible bounded representations one can construct a calgebra a_0 with a dense twosided ideal a_c such that mathscra maps into the multiplier algebra of a_c when the filtration is induced from a central element in mathscra we say that mathscra is an salgebra we also introduce the notion of mathscrralgebra relative to a commutative salgebra mathscrr and of hopf mathscrralgebra we formulate conditions such that the completion of a hopf mathscrralgebra gives rise to a continuous field of hopf calgebras over the spectrum of r_0 we apply the general theory to the case of quantum glnmathbbc as constructed from the frtformalism
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1,802.02487
Invariant states on noncommutative tori
For any number $h$ such that $\hbar:=h/2\pi$ is irrational and any skew-symmetric, non-degenerate bilinear form $\sigma:\mathbb{Z}^{2g}\times \mathbb{Z}^{2g} \to \mathbb{Z}$, let be $\mathcal{A}^h_{g,\sigma}$ be the twisted group $*$-algebra $\mathbb{C}[\mathbb{Z}^{2g}]$ and consider the ergodic group of $*$-automorphisms of $\mathcal{A}^h_{g,\sigma}$ induced by the action of the symplectic group Sp$(\mathbb{Z}^{2g},\sigma)$. We show that the only Sp$(\mathbb{Z}^{2g},\sigma)$-invariant state on $\mathcal{A}^h_{g,\sigma}$ is the trace state $\tau$.
math.OA math-ph math.FA math.MP math.QA
for any number h such that hbarh2pi is irrational and any skewsymmetric nondegenerate bilinear form sigmamathbbz2gtimes mathbbz2g to mathbbz let be mathcalah_gsigma be the twisted group algebra mathbbcmathbbz2g and consider the ergodic group of automorphisms of mathcalah_gsigma induced by the action of the symplectic group spmathbbz2gsigma we show that the only spmathbbz2gsigmainvariant state on mathcalah_gsigma is the trace state tau
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1,802.02488
SCH-GAN: Semi-supervised Cross-modal Hashing by Generative Adversarial Network
Cross-modal hashing aims to map heterogeneous multimedia data into a common Hamming space, which can realize fast and flexible retrieval across different modalities. Supervised cross-modal hashing methods have achieved considerable progress by incorporating semantic side information. However, they mainly have two limitations: (1) Heavily rely on large-scale labeled cross-modal training data which are labor intensive and hard to obtain. (2) Ignore the rich information contained in the large amount of unlabeled data across different modalities, especially the margin examples that are easily to be incorrectly retrieved, which can help to model the correlations. To address these problems, in this paper we propose a novel Semi-supervised Cross-Modal Hashing approach by Generative Adversarial Network (SCH-GAN). We aim to take advantage of GAN's ability for modeling data distributions to promote cross-modal hashing learning in an adversarial way. The main contributions can be summarized as follows: (1) We propose a novel generative adversarial network for cross-modal hashing. In our proposed SCH-GAN, the generative model tries to select margin examples of one modality from unlabeled data when giving a query of another modality. While the discriminative model tries to distinguish the selected examples and true positive examples of the query. These two models play a minimax game so that the generative model can promote the hashing performance of discriminative model. (2) We propose a reinforcement learning based algorithm to drive the training of proposed SCH-GAN. The generative model takes the correlation score predicted by discriminative model as a reward, and tries to select the examples close to the margin to promote discriminative model by maximizing the margin between positive and negative data. Experiments on 3 widely-used datasets verify the effectiveness of our proposed approach.
cs.CV
crossmodal hashing aims to map heterogeneous multimedia data into a common hamming space which can realize fast and flexible retrieval across different modalities supervised crossmodal hashing methods have achieved considerable progress by incorporating semantic side information however they mainly have two limitations 1 heavily rely on largescale labeled crossmodal training data which are labor intensive and hard to obtain 2 ignore the rich information contained in the large amount of unlabeled data across different modalities especially the margin examples that are easily to be incorrectly retrieved which can help to model the correlations to address these problems in this paper we propose a novel semisupervised crossmodal hashing approach by generative adversarial network schgan we aim to take advantage of gans ability for modeling data distributions to promote crossmodal hashing learning in an adversarial way the main contributions can be summarized as follows 1 we propose a novel generative adversarial network for crossmodal hashing in our proposed schgan the generative model tries to select margin examples of one modality from unlabeled data when giving a query of another modality while the discriminative model tries to distinguish the selected examples and true positive examples of the query these two models play a minimax game so that the generative model can promote the hashing performance of discriminative model 2 we propose a reinforcement learning based algorithm to drive the training of proposed schgan the generative model takes the correlation score predicted by discriminative model as a reward and tries to select the examples close to the margin to promote discriminative model by maximizing the margin between positive and negative data experiments on 3 widelyused datasets verify the effectiveness of our proposed approach
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1,802.02489
Pressure-driven dynamics of liquid plugs in rectangular microchannels: influence of the transition between quasi-static and dynamic film deposition regimes
In this paper, we study experimentally and theoretically the dynamics of liquid plugs in rectangular microchannels for both unidirectional and cyclic pressure forcing. In both cases, it is shown that the transition between quasi-static and dynamic film deposition behind the liquid plug leads to a dramatic acceleration of the plug, rapidly leading to its rupture. This behaviour proper to channels with sharp corners is recovered from a reduced dimension model based on previous theoretical and numerical developments. In addition, it is shown for cyclic periodic forcing that the plug undergoes stable periodic oscillations if it remains in the quasi-static film deposition regime during the first cycle, while otherwise it accelerates cyclically and ruptures. The transition between these two regimes occurs at a pressure-dependent critical initial length, whose value can be predicted theoretically.
physics.flu-dyn physics.class-ph
in this paper we study experimentally and theoretically the dynamics of liquid plugs in rectangular microchannels for both unidirectional and cyclic pressure forcing in both cases it is shown that the transition between quasistatic and dynamic film deposition behind the liquid plug leads to a dramatic acceleration of the plug rapidly leading to its rupture this behaviour proper to channels with sharp corners is recovered from a reduced dimension model based on previous theoretical and numerical developments in addition it is shown for cyclic periodic forcing that the plug undergoes stable periodic oscillations if it remains in the quasistatic film deposition regime during the first cycle while otherwise it accelerates cyclically and ruptures the transition between these two regimes occurs at a pressuredependent critical initial length whose value can be predicted theoretically
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1,802.0249
Conformal invariance and the Lundgren-Monin-Novikov equations for vorticity fields in 2D turbulence: Refuting a recent claim
The recent claim by Grebenev et al. [J. Phys. A: Math. Theor. 50, 435502 (2017)] that the inviscid 2D Lundgren-Monin-Novikov (LMN) equations on a zero vorticity characteristic naturally would reveal local conformal invariance when only analyzing these by means of a classical Lie-group symmetry approach, is invalid and will be refuted in the present comment. To note is that within this comment the (possible) existence of conformal invariance in 2D turbulence is not questioned, only the conclusion as is given in Grebenev et al. (2017) and their approach how this invariance was derived is what is being criticized and refuted herein. In fact, the algebraic derivation for conformal invariance of the 2D LMN vorticity equations in Grebenev et al. (2017) is flawed. A key constraint of the LMN equations has been wrongly transformed. Providing the correct transformation instead will lead to a breaking of the proclaimed conformal group. The corrected version of Grebenev et al. (2017) just leads to a globally constant scaling in the fields and not to a local one as claimed. In consequence, since in Grebenev et al. (2017) only the first equation within the infinite and unclosed LMN chain is considered, also different Lie-group infinitesimals for the one- and two-point probability density functions (PDFs) will result from this correction, replacing thus the misleading ones proposed.
physics.flu-dyn cond-mat.stat-mech math-ph math.MP
the recent claim by grebenev et al j phys a math theor 50 435502 2017 that the inviscid 2d lundgrenmoninnovikov lmn equations on a zero vorticity characteristic naturally would reveal local conformal invariance when only analyzing these by means of a classical liegroup symmetry approach is invalid and will be refuted in the present comment to note is that within this comment the possible existence of conformal invariance in 2d turbulence is not questioned only the conclusion as is given in grebenev et al 2017 and their approach how this invariance was derived is what is being criticized and refuted herein in fact the algebraic derivation for conformal invariance of the 2d lmn vorticity equations in grebenev et al 2017 is flawed a key constraint of the lmn equations has been wrongly transformed providing the correct transformation instead will lead to a breaking of the proclaimed conformal group the corrected version of grebenev et al 2017 just leads to a globally constant scaling in the fields and not to a local one as claimed in consequence since in grebenev et al 2017 only the first equation within the infinite and unclosed lmn chain is considered also different liegroup infinitesimals for the one and twopoint probability density functions pdfs will result from this correction replacing thus the misleading ones proposed
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1,802.02491
The law of a point process of Brownian excursions in a domain is determined by the law of its trace
We show the result that is stated in the title of the paper, which has consequences about decomposition of Brownian loop-soup clusters in two dimensions.
math.PR
we show the result that is stated in the title of the paper which has consequences about decomposition of brownian loopsoup clusters in two dimensions
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1,802.02492
$T$-odd correlations in polarized top quark decays in the sequential decay $t(\uparrow) \to X_b+W^+(\to \ell^+ + \nu_\ell)$ and in the quasi three-body decay $t(\uparrow) \to X_b+ \ell^+ + \nu_\ell$
We identify the $T$-odd structure functions that appear in the description of polarized top quark decays in the sequential decay $t(\uparrow) \to X_b+W^+(\to \ell^+ + \nu_\ell)$ (two structure functions) and the quasi-three-body decay $t(\uparrow) \to X_b+ \ell^+ + \nu_\ell$ (one structure function). A convenient measure of the magnitude of the $T$-odd structure functions is the contribution of the imaginary part Im $g_R$ of the right-chiral tensor coupling $g_R$ to the $T$-odd structure functions which we work out. Contrary to the case of QCD the NLO electroweak corrections to polarized top quark decays admit of absorptive one-loop vertex contributions. We analytically calculate the imaginary parts of the relevant four electroweak one-loop triangle vertex diagrams and determine their contributions to the $T$-odd helicity structure functions that appear in the description of polarized top quark decays.
hep-ph hep-ex
we identify the todd structure functions that appear in the description of polarized top quark decays in the sequential decay tuparrow to x_bwto ell nu_ell two structure functions and the quasithreebody decay tuparrow to x_b ell nu_ell one structure function a convenient measure of the magnitude of the todd structure functions is the contribution of the imaginary part im g_r of the rightchiral tensor coupling g_r to the todd structure functions which we work out contrary to the case of qcd the nlo electroweak corrections to polarized top quark decays admit of absorptive oneloop vertex contributions we analytically calculate the imaginary parts of the relevant four electroweak oneloop triangle vertex diagrams and determine their contributions to the todd helicity structure functions that appear in the description of polarized top quark decays
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1,802.02493
Up to topological concordance links are strongly quasipositive
We generalize an algorithm of Rudolph to establish that every link is topologically concordant to a strongly quasipositive link.
math.GT
we generalize an algorithm of rudolph to establish that every link is topologically concordant to a strongly quasipositive link
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1,802.02494
Viscous effects on the dynamical evolution of QCD matter during the first-order confinement phase transition in heavy-ion collisions
We investigate viscous effects on the dynamical evolution of QCD matter during the first-order phase transition, which may happen in heavy-ion collisions. We first obtain the first-order phase transition line in the QCD phase diagram under the Gibbs condition by using the MIT bag model and the hadron resonance gas model for the equation of state of partons and hadrons. The viscous pressure, which corresponds to the friction in the energy balance, is then derived from the energy and net baryon number conservation during the phase transition. We find that the viscous pressure relates to the thermodynamic change of the two-phase state and thus affects the timescale of the phase transition. Numerical results are presented for demonstrations.
hep-ph nucl-th
we investigate viscous effects on the dynamical evolution of qcd matter during the firstorder phase transition which may happen in heavyion collisions we first obtain the firstorder phase transition line in the qcd phase diagram under the gibbs condition by using the mit bag model and the hadron resonance gas model for the equation of state of partons and hadrons the viscous pressure which corresponds to the friction in the energy balance is then derived from the energy and net baryon number conservation during the phase transition we find that the viscous pressure relates to the thermodynamic change of the twophase state and thus affects the timescale of the phase transition numerical results are presented for demonstrations
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1,802.02495
The merger of two compact stars: a tool for dense matter nuclear physics
We discuss the different signals, in gravitational and electromagnetic waves, emitted during the merger of two compact stars. We will focus in particular on the possible contraints that those signals can provide on the equation of state of dense matter. Indeed, the stiffness of the equation of state and the particle composition of the merging compact stars, strongly affect e.g. the life time of the post-merger remnant and its gravitational wave signal, the emission of the short gamma-ray-burst, the amount of ejected mass and the related kilonova. The first detection of gravitational waves from the merger of two compact stars in August 2017, GW170817, and the subsequent detections of its electromagnetic counterparts, GRB170817A and AT2017gfo, is the first example of the era of "multi-messenger astronomy": we discuss what we have learned from this detection on the equation of state of compact stars and we provide a tentative interpretation of this event, within the two families scenario, as due to the merger of a hadronic star with a quark star.
astro-ph.HE
we discuss the different signals in gravitational and electromagnetic waves emitted during the merger of two compact stars we will focus in particular on the possible contraints that those signals can provide on the equation of state of dense matter indeed the stiffness of the equation of state and the particle composition of the merging compact stars strongly affect eg the life time of the postmerger remnant and its gravitational wave signal the emission of the short gammarayburst the amount of ejected mass and the related kilonova the first detection of gravitational waves from the merger of two compact stars in august 2017 gw170817 and the subsequent detections of its electromagnetic counterparts grb170817a and at2017gfo is the first example of the era of multimessenger astronomy we discuss what we have learned from this detection on the equation of state of compact stars and we provide a tentative interpretation of this event within the two families scenario as due to the merger of a hadronic star with a quark star
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1,802.02496
Defining the principles for the motion of blood through arteries
This is an annotated translation from Latin of 'Principia pro motu sanguinis per arterias determinando' in which Euler develops the first known work on the mechanics of flows in elastic tubes, intended to the first contest of the Dijon Academy of 1742. In this work, Euler applied the principles of mass conservation and momentum conservation to the one dimensional flow of an incompressible fluid through an elastic tube driven by a piston pump. These would allow the analytical treatment of circulatory physiology and hemodynamics, which still undergird the most advanced numerical methods in use today for blood flow analysis in arterial networks.
physics.hist-ph
this is an annotated translation from latin of principia pro motu sanguinis per arterias determinando in which euler develops the first known work on the mechanics of flows in elastic tubes intended to the first contest of the dijon academy of 1742 in this work euler applied the principles of mass conservation and momentum conservation to the one dimensional flow of an incompressible fluid through an elastic tube driven by a piston pump these would allow the analytical treatment of circulatory physiology and hemodynamics which still undergird the most advanced numerical methods in use today for blood flow analysis in arterial networks
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1,802.02497
Privacy preserving clustering with constraints
The $k$-center problem is a classical combinatorial optimization problem which asks to find $k$ centers such that the maximum distance of any input point in a set $P$ to its assigned center is minimized. The problem allows for elegant $2$-approximations. However, the situation becomes significantly more difficult when constraints are added to the problem. We raise the question whether general methods can be derived to turn an approximation algorithm for a clustering problem with some constraints into an approximation algorithm that respects one constraint more. Our constraint of choice is privacy: Here, we are asked to only open a center when at least $\ell$ clients will be assigned to it. We show how to combine privacy with several other constraints.
cs.CC
the kcenter problem is a classical combinatorial optimization problem which asks to find k centers such that the maximum distance of any input point in a set p to its assigned center is minimized the problem allows for elegant 2approximations however the situation becomes significantly more difficult when constraints are added to the problem we raise the question whether general methods can be derived to turn an approximation algorithm for a clustering problem with some constraints into an approximation algorithm that respects one constraint more our constraint of choice is privacy here we are asked to only open a center when at least ell clients will be assigned to it we show how to combine privacy with several other constraints
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1,802.02498
Spectral Learning of Binomial HMMs for DNA Methylation Data
We consider learning parameters of Binomial Hidden Markov Models, which may be used to model DNA methylation data. The standard algorithm for the problem is EM, which is computationally expensive for sequences of the scale of the mammalian genome. Recently developed spectral algorithms can learn parameters of latent variable models via tensor decomposition, and are highly efficient for large data. However, these methods have only been applied to categorial HMMs, and the main challenge is how to extend them to Binomial HMMs while still retaining computational efficiency. We address this challenge by introducing a new feature-map based approach that exploits specific properties of Binomial HMMs. We provide theoretical performance guarantees for our algorithm and evaluate it on real DNA methylation data.
cs.LG stat.ML
we consider learning parameters of binomial hidden markov models which may be used to model dna methylation data the standard algorithm for the problem is em which is computationally expensive for sequences of the scale of the mammalian genome recently developed spectral algorithms can learn parameters of latent variable models via tensor decomposition and are highly efficient for large data however these methods have only been applied to categorial hmms and the main challenge is how to extend them to binomial hmms while still retaining computational efficiency we address this challenge by introducing a new featuremap based approach that exploits specific properties of binomial hmms we provide theoretical performance guarantees for our algorithm and evaluate it on real dna methylation data
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1,802.02499
Coarse median algebras: The intrinsic geometry of coarse median spaces and their intervals
This paper establishes a new combinatorial framework for the study of coarse median spaces, bridging the worlds of asymptotic geometry, algebra and combinatorics. We introduce a simple and entirely algebraic notion of coarse median algebra which simultaneously generalises the concepts of bounded geometry coarse median spaces and classical discrete median algebras. We study the coarse median universe from the perspective of intervals, with a particular focus on cardinality as a proxy for distance. In particular we prove that the metric on a quasi-geodesic coarse median space of bounded geometry can be constructed up to quasi-isometry using only the coarse median operator. Finally we develop a concept of rank for coarse median algebras in terms of the geometry of intervals and show that the notion of finite rank coarse median algebra provides a natural higher dimensional analogue of Gromov's concept of $\delta$-hyperbolicity.
math.MG math.CO math.GR
this paper establishes a new combinatorial framework for the study of coarse median spaces bridging the worlds of asymptotic geometry algebra and combinatorics we introduce a simple and entirely algebraic notion of coarse median algebra which simultaneously generalises the concepts of bounded geometry coarse median spaces and classical discrete median algebras we study the coarse median universe from the perspective of intervals with a particular focus on cardinality as a proxy for distance in particular we prove that the metric on a quasigeodesic coarse median space of bounded geometry can be constructed up to quasiisometry using only the coarse median operator finally we develop a concept of rank for coarse median algebras in terms of the geometry of intervals and show that the notion of finite rank coarse median algebra provides a natural higher dimensional analogue of gromovs concept of deltahyperbolicity
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1,802.025
Cadre Modeling: Simultaneously Discovering Subpopulations and Predictive Models
We consider the problem in regression analysis of identifying subpopulations that exhibit different patterns of response, where each subpopulation requires a different underlying model. Unlike statistical cohorts, these subpopulations are not known a priori; thus, we refer to them as cadres. When the cadres and their associated models are interpretable, modeling leads to insights about the subpopulations and their associations with the regression target. We introduce a discriminative model that simultaneously learns cadre assignment and target-prediction rules. Sparsity-inducing priors are placed on the model parameters, under which independent feature selection is performed for both the cadre assignment and target-prediction processes. We learn models using adaptive step size stochastic gradient descent, and we assess cadre quality with bootstrapped sample analysis. We present simulated results showing that, when the true clustering rule does not depend on the entire set of features, our method significantly outperforms methods that learn subpopulation-discovery and target-prediction rules separately. In a materials-by-design case study, our model provides state-of-the-art prediction of polymer glass transition temperature. Importantly, the method identifies cadres of polymers that respond differently to structural perturbations, thus providing design insight for targeting or avoiding specific transition temperature ranges. It identifies chemically meaningful cadres, each with interpretable models. Further experimental results show that cadre methods have generalization that is competitive with linear and nonlinear regression models and can identify robust subpopulations.
stat.ML cs.LG
we consider the problem in regression analysis of identifying subpopulations that exhibit different patterns of response where each subpopulation requires a different underlying model unlike statistical cohorts these subpopulations are not known a priori thus we refer to them as cadres when the cadres and their associated models are interpretable modeling leads to insights about the subpopulations and their associations with the regression target we introduce a discriminative model that simultaneously learns cadre assignment and targetprediction rules sparsityinducing priors are placed on the model parameters under which independent feature selection is performed for both the cadre assignment and targetprediction processes we learn models using adaptive step size stochastic gradient descent and we assess cadre quality with bootstrapped sample analysis we present simulated results showing that when the true clustering rule does not depend on the entire set of features our method significantly outperforms methods that learn subpopulationdiscovery and targetprediction rules separately in a materialsbydesign case study our model provides stateoftheart prediction of polymer glass transition temperature importantly the method identifies cadres of polymers that respond differently to structural perturbations thus providing design insight for targeting or avoiding specific transition temperature ranges it identifies chemically meaningful cadres each with interpretable models further experimental results show that cadre methods have generalization that is competitive with linear and nonlinear regression models and can identify robust subpopulations
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1,802.02501
Asymmetric Electric Field Screening in van der Waals Heterostructures
Electric field screening plays an important role in the physical and chemical properties of materials and their devices. Here, we use a compelling set of theoretical and experimental techniques involving van der Waals (vdW) ab initio density functional theory (DFT) simulations, quantum capacitance-based classical model and electric force microscopy (EFM) to elucidate the intrinsic dielectric screening properties of vdW heterostructures (vdWHs) formed by MoS2 and graphene layers. We experimentally observed an asymmetric electric response in the MoS2/Graphene vdWHs under different directions of the external electric field. That is, when the electric fields are shed towards graphene, a large amount of polarized charges screen the fields, but as the sign of the field was reversed, a strong depolarization field was present, and a partial screening was detected. This effect is thickness-dependent, in particular on the number of the MoS2 layers; whereas increased thickness of graphene showed a small effect on their electrical and screening behavior. Our results indicate that asymmetric dipolar contributions at the interface between graphene and MoS2 are the main cause to the unusual field-effect screening in the vdWHs. This work not only provides new insights on the screening properties of a vast amount of heterojunction fabricated so far, but also uncovers the great potential of controlling a fundamental property, such as screening, for device applications.
cond-mat.mes-hall
electric field screening plays an important role in the physical and chemical properties of materials and their devices here we use a compelling set of theoretical and experimental techniques involving van der waals vdw ab initio density functional theory dft simulations quantum capacitancebased classical model and electric force microscopy efm to elucidate the intrinsic dielectric screening properties of vdw heterostructures vdwhs formed by mos2 and graphene layers we experimentally observed an asymmetric electric response in the mos2graphene vdwhs under different directions of the external electric field that is when the electric fields are shed towards graphene a large amount of polarized charges screen the fields but as the sign of the field was reversed a strong depolarization field was present and a partial screening was detected this effect is thicknessdependent in particular on the number of the mos2 layers whereas increased thickness of graphene showed a small effect on their electrical and screening behavior our results indicate that asymmetric dipolar contributions at the interface between graphene and mos2 are the main cause to the unusual fieldeffect screening in the vdwhs this work not only provides new insights on the screening properties of a vast amount of heterojunction fabricated so far but also uncovers the great potential of controlling a fundamental property such as screening for device applications
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1,802.02502
Exact Solution of a Strongly Coupled Gauge Theory in 0+1 Dimensions
Gauged tensor models are a class of strongly coupled quantum mechanical theories. We present the exact analytic solution of a specific example of such a theory: namely the smallest colored tensor model due to Gurau and Witten that exhibits non-linearities. We find explicit analytic expressions for the eigenvalues and eigenstates, and the former agree precisely with previous numerical results on (a subset of) eigenvalues of the ungauged theory. The physics of the spectrum, despite the smallness of $N$, exhibits rudimentary signatures of chaos. This Letter is a summary of our main results: the gory details will appear in a companion paper.
hep-th gr-qc
gauged tensor models are a class of strongly coupled quantum mechanical theories we present the exact analytic solution of a specific example of such a theory namely the smallest colored tensor model due to gurau and witten that exhibits nonlinearities we find explicit analytic expressions for the eigenvalues and eigenstates and the former agree precisely with previous numerical results on a subset of eigenvalues of the ungauged theory the physics of the spectrum despite the smallness of n exhibits rudimentary signatures of chaos this letter is a summary of our main results the gory details will appear in a companion paper
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1,802.02503
A Praise for Defensive Programming: Leveraging Uncertainty for Effective Malware Mitigation
A promising avenue for improving the effectiveness of behavioral-based malware detectors would be to combine fast traditional machine learning detectors with high-accuracy, but time-consuming deep learning models. The main idea would be to place software receiving borderline classifications by traditional machine learning methods in an environment where uncertainty is added, while software is analyzed by more time-consuming deep learning models. The goal of uncertainty would be to rate-limit actions of potential malware during the time consuming deep analysis. In this paper, we present a detailed description of the analysis and implementation of CHAMELEON, a framework for realizing this uncertain environment for Linux. CHAMELEON offers two environments for software: (i) standard - for any software identified as benign by conventional machine learning methods and (ii) uncertain - for software receiving borderline classifications when analyzed by these conventional machine learning methods. The uncertain environment adds obstacles to software execution through random perturbations applied probabilistically on selected system calls. We evaluated CHAMELEON with 113 applications and 100 malware samples for Linux. Our results showed that at threshold 10%, intrusive and non-intrusive strategies caused approximately 65% of malware to fail accomplishing their tasks, while approximately 30% of the analyzed benign software to meet with various levels of disruption. With a dynamic, per-system call threshold, CHAMELEON caused 92% of the malware to fail, and only 10% of the benign software to be disrupted. We also found that I/O-bound software was three times more affected by uncertainty than CPU-bound software. Further, we analyzed the logs of software crashed with non-intrusive strategies, and found that some crashes are due to the software bugs.
cs.CR
a promising avenue for improving the effectiveness of behavioralbased malware detectors would be to combine fast traditional machine learning detectors with highaccuracy but timeconsuming deep learning models the main idea would be to place software receiving borderline classifications by traditional machine learning methods in an environment where uncertainty is added while software is analyzed by more timeconsuming deep learning models the goal of uncertainty would be to ratelimit actions of potential malware during the time consuming deep analysis in this paper we present a detailed description of the analysis and implementation of chameleon a framework for realizing this uncertain environment for linux chameleon offers two environments for software i standard for any software identified as benign by conventional machine learning methods and ii uncertain for software receiving borderline classifications when analyzed by these conventional machine learning methods the uncertain environment adds obstacles to software execution through random perturbations applied probabilistically on selected system calls we evaluated chameleon with 113 applications and 100 malware samples for linux our results showed that at threshold 10 intrusive and nonintrusive strategies caused approximately 65 of malware to fail accomplishing their tasks while approximately 30 of the analyzed benign software to meet with various levels of disruption with a dynamic persystem call threshold chameleon caused 92 of the malware to fail and only 10 of the benign software to be disrupted we also found that iobound software was three times more affected by uncertainty than cpubound software further we analyzed the logs of software crashed with nonintrusive strategies and found that some crashes are due to the software bugs
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1,802.02504
The revolution in physics of the early Nineteenth century revisited in the context of science-and-society interaction
The radical changes in the concepts and approach in Physics at the turn of the Nineteenth century were so deep, that is acknowledged as a revolution. However, in 1970 Thomas Kuhn's careful reconstruction of the researches on the black body problem, the concept itself of the revolution seemed to vanish in his diluted discussion of every details. In the present paper, after an examination of the limitations of Kuhn's response to his critics, I put forward the idea, although it is not new, that these changes in Physics cannot be reduced to a point-like event, but happened instead through multiple successive (and even contradictory) changes in the course of decades. Such as the old quantum hypothesis, wave mechanics, orthodox quantum mechanics. In fact, the innovative perspectives started in the 1980s have been considered as a third quantum revolution. My basic argument is that these changes, in order to be really understood, must be interpreted not as mere specific changes in Physics, but framed in the context of the deep social, cultural, and economic changes during those turbulent years. The main steps are outlined.
physics.hist-ph quant-ph
the radical changes in the concepts and approach in physics at the turn of the nineteenth century were so deep that is acknowledged as a revolution however in 1970 thomas kuhns careful reconstruction of the researches on the black body problem the concept itself of the revolution seemed to vanish in his diluted discussion of every details in the present paper after an examination of the limitations of kuhns response to his critics i put forward the idea although it is not new that these changes in physics cannot be reduced to a pointlike event but happened instead through multiple successive and even contradictory changes in the course of decades such as the old quantum hypothesis wave mechanics orthodox quantum mechanics in fact the innovative perspectives started in the 1980s have been considered as a third quantum revolution my basic argument is that these changes in order to be really understood must be interpreted not as mere specific changes in physics but framed in the context of the deep social cultural and economic changes during those turbulent years the main steps are outlined
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1,802.02505
The monodromy of meromorphic projective structures
We study projective structures on a surface having poles of prescribed orders. We obtain a monodromy map from a complex manifold parameterising such structures to the stack of framed $\mathrm{PGL}_2(\mathbb{C})$ local systems on the associated marked bordered surface. We prove that the image of this map is contained in the union of the domains of the cluster charts. We discuss a number of open questions concerning this monodromy map.
math.GT math.AG math.DG
we study projective structures on a surface having poles of prescribed orders we obtain a monodromy map from a complex manifold parameterising such structures to the stack of framed mathrmpgl_2mathbbc local systems on the associated marked bordered surface we prove that the image of this map is contained in the union of the domains of the cluster charts we discuss a number of open questions concerning this monodromy map
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1,802.02506
Can Local Stress Enhancement Induce Stability in Fracture Processes? Part I: Apparent Stability
By comparing the evolution of the local and equal load sharing fiber bundle models, we point out the paradoxical result that stresses seem to make the local load sharing model stable when the equal load sharing model is not. We explain this behavior by demonstrating that it is only an apparent stability in the local load sharing model, which originates from a statistical effect due to sample averaging. Even though we use the fiber bundle model to demonstrate the apparent stability, we argue that it is a more general feature of fracture processes.
cond-mat.dis-nn
by comparing the evolution of the local and equal load sharing fiber bundle models we point out the paradoxical result that stresses seem to make the local load sharing model stable when the equal load sharing model is not we explain this behavior by demonstrating that it is only an apparent stability in the local load sharing model which originates from a statistical effect due to sample averaging even though we use the fiber bundle model to demonstrate the apparent stability we argue that it is a more general feature of fracture processes
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1,802.02507
Measuring third party tracker power across web and mobile
Third-party networks collect vast amounts of data about users via web sites and mobile applications. Consolidations among tracker companies can significantly increase their individual tracking capabilities, prompting scrutiny by competition regulators. Traditional measures of market share, based on revenue or sales, fail to represent the tracking capability of a tracker, especially if it spans both web and mobile. This paper proposes a new approach to measure the concentration of tracking capability, based on the reach of a tracker on popular websites and apps. Our results reveal that tracker prominence and parent-subsidiary relationships have significant impact on accurately measuring concentration.
cs.CY
thirdparty networks collect vast amounts of data about users via web sites and mobile applications consolidations among tracker companies can significantly increase their individual tracking capabilities prompting scrutiny by competition regulators traditional measures of market share based on revenue or sales fail to represent the tracking capability of a tracker especially if it spans both web and mobile this paper proposes a new approach to measure the concentration of tracking capability based on the reach of a tracker on popular websites and apps our results reveal that tracker prominence and parentsubsidiary relationships have significant impact on accurately measuring concentration
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1,802.02508
Spectral Phase Control of Interfering Chirped Pulses for High-Energy Narrowband Terahertz Generation
Highly-efficient optical generation of narrowband terahertz (THz) radiation enables unexplored technologies and sciences from compact electron acceleration to charge manipulation in solids. State-of-the-art conversion efficiencies are currently achieved using difference-frequency generation (DFG) driven by temporal beating of chirped pulses but remain, however, far lower than desired or predicted. Here we show that high-order spectral phase fundamentally limits the efficiency of narrowband DFG using chirped-pulse beating and resolve this limitation by introducing a novel technique based on tuning the relative spectral phase of the pulses. For optical terahertz generation, we demonstrate a 13-fold enhancement in conversion efficiency for 1%-bandwidth, 0.361 THz pulses, yielding a record energy of 0.6 mJ and exceeding previous optically-generated energies by over an order of magnitude. Our results prove the feasibility of millijoule-scale applications like terahertz-based electron accelerators and light sources and solve the long-standing problem of temporal irregularities in the pulse trains generated by interfering chirped pulses.
physics.optics
highlyefficient optical generation of narrowband terahertz thz radiation enables unexplored technologies and sciences from compact electron acceleration to charge manipulation in solids stateoftheart conversion efficiencies are currently achieved using differencefrequency generation dfg driven by temporal beating of chirped pulses but remain however far lower than desired or predicted here we show that highorder spectral phase fundamentally limits the efficiency of narrowband dfg using chirpedpulse beating and resolve this limitation by introducing a novel technique based on tuning the relative spectral phase of the pulses for optical terahertz generation we demonstrate a 13fold enhancement in conversion efficiency for 1bandwidth 0361 thz pulses yielding a record energy of 06 mj and exceeding previous opticallygenerated energies by over an order of magnitude our results prove the feasibility of millijoulescale applications like terahertzbased electron accelerators and light sources and solve the longstanding problem of temporal irregularities in the pulse trains generated by interfering chirped pulses
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1,802.02509
Strong Amplifiers of Natural Selection: Proofs
We consider the modified Moran process on graphs to study the spread of genetic and cultural mutations on structured populations. An initial mutant arises either spontaneously (aka \emph{uniform initialization}), or during reproduction (aka \emph{temperature initialization}) in a population of $n$ individuals, and has a fixed fitness advantage $r>1$ over the residents of the population. The fixation probability is the probability that the mutant takes over the entire population. Graphs that ensure fixation probability of~1 in the limit of infinite populations are called \emph{strong amplifiers}. Previously, only a few examples of strong amplifiers were known for uniform initialization, whereas no strong amplifiers were known for temperature initialization. In this work, we study necessary and sufficient conditions for strong amplification, and prove negative and positive results. We show that for temperature initialization, graphs that are unweighted and/or self-loop-free have fixation probability upper-bounded by $1-1/f(r)$, where $f(r)$ is a function linear in $r$. Similarly, we show that for uniform initialization, bounded-degree graphs that are unweighted and/or self-loop-free have fixation probability upper-bounded by $1-1/g(r,c)$, where $c$ is the degree bound and $g(r,c)$ a function linear in $r$. Our main positive result complements these negative results, and is as follows: every family of undirected graphs with (i)~self loops and (ii)~diameter bounded by $n^{1-\epsilon}$, for some fixed $\epsilon>0$, can be assigned weights that makes it a strong amplifier, both for uniform and temperature initialization.
cs.DM
we consider the modified moran process on graphs to study the spread of genetic and cultural mutations on structured populations an initial mutant arises either spontaneously aka emphuniform initialization or during reproduction aka emphtemperature initialization in a population of n individuals and has a fixed fitness advantage r1 over the residents of the population the fixation probability is the probability that the mutant takes over the entire population graphs that ensure fixation probability of1 in the limit of infinite populations are called emphstrong amplifiers previously only a few examples of strong amplifiers were known for uniform initialization whereas no strong amplifiers were known for temperature initialization in this work we study necessary and sufficient conditions for strong amplification and prove negative and positive results we show that for temperature initialization graphs that are unweighted andor selfloopfree have fixation probability upperbounded by 11fr where fr is a function linear in r similarly we show that for uniform initialization boundeddegree graphs that are unweighted andor selfloopfree have fixation probability upperbounded by 11grc where c is the degree bound and grc a function linear in r our main positive result complements these negative results and is as follows every family of undirected graphs with iself loops and iidiameter bounded by n1epsilon for some fixed epsilon0 can be assigned weights that makes it a strong amplifier both for uniform and temperature initialization
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1,802.0251
Control of surface potential at polar domain walls in a nonpolar oxide
Ferroic domain walls could play an important role in microelectronics, given their nanometric size and often distinct functional properties. Until now, devices and device concepts were mostly based on mobile domain walls in ferromagnetic and ferroelectric materials. A less explored path is to make use of polar domain walls in nonpolar ferroelastic materials. Indeed, while the polar character of ferroelastic domain walls has been demonstrated, polarization control has been elusive. Here, we report evidence for the electrostatic signature of the domain-wall polarization in nonpolar calcium titanate (CaTiO3). Macroscopic mechanical resonances excited by an ac electric field are observed as a signature of a piezoelectric response caused by polar walls. On the microscopic scale, the polarization in domain walls modifies the local surface potential of the sample. Through imaging of surface potential variations, we show that the potential at the domain wall can be controlled by electron injection. This could enable devices based on nondestructive information readout of surface potential.
cond-mat.mtrl-sci
ferroic domain walls could play an important role in microelectronics given their nanometric size and often distinct functional properties until now devices and device concepts were mostly based on mobile domain walls in ferromagnetic and ferroelectric materials a less explored path is to make use of polar domain walls in nonpolar ferroelastic materials indeed while the polar character of ferroelastic domain walls has been demonstrated polarization control has been elusive here we report evidence for the electrostatic signature of the domainwall polarization in nonpolar calcium titanate catio3 macroscopic mechanical resonances excited by an ac electric field are observed as a signature of a piezoelectric response caused by polar walls on the microscopic scale the polarization in domain walls modifies the local surface potential of the sample through imaging of surface potential variations we show that the potential at the domain wall can be controlled by electron injection this could enable devices based on nondestructive information readout of surface potential
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1,802.02511
DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction
We train and validate a semi-supervised, multi-task LSTM on 57,675 person-weeks of data from off-the-shelf wearable heart rate sensors, showing high accuracy at detecting multiple medical conditions, including diabetes (0.8451), high cholesterol (0.7441), high blood pressure (0.8086), and sleep apnea (0.8298). We compare two semi-supervised train- ing methods, semi-supervised sequence learning and heuristic pretraining, and show they outperform hand-engineered biomarkers from the medical literature. We believe our work suggests a new approach to patient risk stratification based on cardiovascular risk scores derived from popular wearables such as Fitbit, Apple Watch, or Android Wear.
cs.LG cs.AI stat.ML
we train and validate a semisupervised multitask lstm on 57675 personweeks of data from offtheshelf wearable heart rate sensors showing high accuracy at detecting multiple medical conditions including diabetes 08451 high cholesterol 07441 high blood pressure 08086 and sleep apnea 08298 we compare two semisupervised train ing methods semisupervised sequence learning and heuristic pretraining and show they outperform handengineered biomarkers from the medical literature we believe our work suggests a new approach to patient risk stratification based on cardiovascular risk scores derived from popular wearables such as fitbit apple watch or android wear
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1,802.02512
Large deviations of reaction fluxes
We study a system of interacting particles that randomly react to form new particles. The reaction flux is the rescaled number of reactions that take place in a time interval. We prove a dynamic large-deviation principle for the reaction fluxes under general assumptions that include mass-action kinetics. This result immediately implies the dynamic large deviations for the empirical concentration.
math.PR
we study a system of interacting particles that randomly react to form new particles the reaction flux is the rescaled number of reactions that take place in a time interval we prove a dynamic largedeviation principle for the reaction fluxes under general assumptions that include massaction kinetics this result immediately implies the dynamic large deviations for the empirical concentration
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1,802.02513
Fra\"iss\'e structures and a conjecture of Furstenberg
We study problems concerning the Samuel compactification of the automorphism group of a countable first-order structure. A key motivating question is a problem of Furstenberg and a counter-conjecture by Pestov regarding the difference between $S(G)$, the Samuel compactification, and $E(M(G))$, the enveloping semigroup of the universal minimal flow. We resolve Furstenberg's problem for several automorphism groups and give a detailed study in the case of $G = S_\infty$, leading us to define and investigate several new types of ultrafilter on a countable set.
math.DS math.GR math.LO
we study problems concerning the samuel compactification of the automorphism group of a countable firstorder structure a key motivating question is a problem of furstenberg and a counterconjecture by pestov regarding the difference between sg the samuel compactification and emg the enveloping semigroup of the universal minimal flow we resolve furstenbergs problem for several automorphism groups and give a detailed study in the case of g s_infty leading us to define and investigate several new types of ultrafilter on a countable set
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1,802.02514
B\"uchi-Kamp Theorems for 1-clock ATA
This paper investigates Kamp-like and B\"uchi-like theorems for 1-clock Alternating Timed Automata (1-ATA) and its natural subclasses. A notion of 1-ATA with loop-free-resets is defined. This automaton class is shown to be expressively equivalent to the temporal logic $\regmtl$ which is $\mathsf{MTL[F_I]}$ extended with a regular expression guarded modality. Moreover, a subclass of future timed MSO with k-variable-connectivity property is introduced as logic $\qkmso$. In a Kamp-like result, it is shown that $\regmtl$ is expressively equivalent to $\qkmso$. As our second result, we define a notion of conjunctive-disjunctive 1-clock ATA ($\wf$ 1-ATA). We show that $\wf$ 1-ATA with loop-free-resets are expressively equivalent to the sublogic $\F\regmtl$ of $\regmtl$. Moreover $\F\regmtl$ is expressively equivalent to $\qtwomso$, the two-variable connected fragment of $\qkmso$. The full class of 1-ATA is shown to be expressively equivalent to $\regmtl$ extended with fixed point operators.
cs.LO
this paper investigates kamplike and buchilike theorems for 1clock alternating timed automata 1ata and its natural subclasses a notion of 1ata with loopfreeresets is defined this automaton class is shown to be expressively equivalent to the temporal logic regmtl which is mathsfmtlf_i extended with a regular expression guarded modality moreover a subclass of future timed mso with kvariableconnectivity property is introduced as logic qkmso in a kamplike result it is shown that regmtl is expressively equivalent to qkmso as our second result we define a notion of conjunctivedisjunctive 1clock ata wf 1ata we show that wf 1ata with loopfreeresets are expressively equivalent to the sublogic fregmtl of regmtl moreover fregmtl is expressively equivalent to qtwomso the twovariable connected fragment of qkmso the full class of 1ata is shown to be expressively equivalent to regmtl extended with fixed point operators
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1,802.02515
Design study of random spectrometers for applications at optical frequencies
Compact spectrometers based on disordered planar waveguides exhibit a rather high resolution with a relatively small footprint as compared to conventional spectrometers. This is achieved by multiple scattering of light which - if properly engineered - significantly enhances the effective optical path length. Here a design study of random spectrometers for TE- and TM-polarized light is presented that combines the results of Mie theory, multiple-scattering theory and full electromagnetic simulations. It is shown that the performance of such random spectrometers depends on single scattering quantities, notably on the overall scattering efficiency and the asymmetry parameter. Further, the study shows that a well-developed diffusive regime is not required in practice and that a standard integrated-optical layout is sufficient to obtain efficient devices even for rather weakly scattering systems consisting of low index inclusions in high-index matrices such as pores in planar silicon-nitride based waveguides. This allows for both significant reductions in footprint with acceptable losses in resolution and for device operation in the visible and near-infrared frequency range.
physics.optics physics.ins-det
compact spectrometers based on disordered planar waveguides exhibit a rather high resolution with a relatively small footprint as compared to conventional spectrometers this is achieved by multiple scattering of light which if properly engineered significantly enhances the effective optical path length here a design study of random spectrometers for te and tmpolarized light is presented that combines the results of mie theory multiplescattering theory and full electromagnetic simulations it is shown that the performance of such random spectrometers depends on single scattering quantities notably on the overall scattering efficiency and the asymmetry parameter further the study shows that a welldeveloped diffusive regime is not required in practice and that a standard integratedoptical layout is sufficient to obtain efficient devices even for rather weakly scattering systems consisting of low index inclusions in highindex matrices such as pores in planar siliconnitride based waveguides this allows for both significant reductions in footprint with acceptable losses in resolution and for device operation in the visible and nearinfrared frequency range
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1,802.02516
Towards Understanding the Structure, Dynamics and Bio-activity of Diabetic Drug Metformin
Small molecules are often found to exhibit extraordinarily diverse biological activities. Metformin is one of them. It is widely used as anti-diabetic drug for type-two diabetes. In addition to that, metformin hydrochloride shows anti-tumour activities and increases the survival rate of patients suffering from certain types of cancer namely colorectal, breast, pancreas and prostate cancer. However, theoretical studies of structure and dynamics of metformin have not yet been fully explored. In this work, we investigate the characteristic structural and dynamical features of three mono-protonated forms of metformin hydrochloride with the help of experiments, quantum chemical calculations and atomistic molecular dynamics simulations. We validate our force field by comparing simulation results to that of the experimental findings. Nevertheless, we discover that the non-planar tautomeric form is the most stable. Metformin forms strong hydrogen bonds with surrounding water molecules and its solvation dynamics show unique features. Because of an extended positive charge distribution, metformin possesses features of being a permanent cationic partner toward several targets. We study its interaction and binding ability with DNA using UV spectroscopy, circular dichroism, fluorimetry and metadynamics simulation. We find a non-intercalating mode of interaction. Metformin feasibly forms a minor/major groove-bound state within a few tens of nanoseconds, preferably with AT rich domains. A significant decrease in the free-energy of binding is observed when it binds to a minor groove of DNA.
q-bio.BM cond-mat.soft physics.chem-ph
small molecules are often found to exhibit extraordinarily diverse biological activities metformin is one of them it is widely used as antidiabetic drug for typetwo diabetes in addition to that metformin hydrochloride shows antitumour activities and increases the survival rate of patients suffering from certain types of cancer namely colorectal breast pancreas and prostate cancer however theoretical studies of structure and dynamics of metformin have not yet been fully explored in this work we investigate the characteristic structural and dynamical features of three monoprotonated forms of metformin hydrochloride with the help of experiments quantum chemical calculations and atomistic molecular dynamics simulations we validate our force field by comparing simulation results to that of the experimental findings nevertheless we discover that the nonplanar tautomeric form is the most stable metformin forms strong hydrogen bonds with surrounding water molecules and its solvation dynamics show unique features because of an extended positive charge distribution metformin possesses features of being a permanent cationic partner toward several targets we study its interaction and binding ability with dna using uv spectroscopy circular dichroism fluorimetry and metadynamics simulation we find a nonintercalating mode of interaction metformin feasibly forms a minormajor groovebound state within a few tens of nanoseconds preferably with at rich domains a significant decrease in the freeenergy of binding is observed when it binds to a minor groove of dna
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1,802.02517
Blueprint and Evaluation Instruments for a Course on Software Engineering for Sustainability
We report on a summer school course on Software Engineering for Sustainability (SE4S). We provide a detailed blueprint of the contents taught and its evaluation with the instruments that were used.
cs.SE
we report on a summer school course on software engineering for sustainability se4s we provide a detailed blueprint of the contents taught and its evaluation with the instruments that were used
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1,802.02518
Disconnection by level sets of the discrete Gaussian free field and entropic repulsion
We derive asymptotic upper and lower bounds on the large deviation probability that the level set of the Gaussian free field on $Z^d$, d bigger or equal to three, below a given level disconnects the discrete blow-up of a compact set A from the boundary of the discrete blow-up of a box that contains A, when the level set of the Gaussian free field above this level is in a strongly percolative regime. These bounds substantially strengthen the results of arXiv:1412.3960, where A was a box and the convexity of A played an important role in the proof. We also derive an asymptotic upper bound on the probability that the average of the Gaussian free field well inside the discrete blow-up of A is above a certain level when disconnection occurs. The derivation of the upper bounds uses the solidification estimates for porous interfaces that were derived in the work arXiv:1706.07229 of A.-S. Sznitman and the author to treat a similar disconnection problem for the vacant set of random interlacements. If certain critical levels for the Gaussian free field coincide, an open question at the moment, the asymptotic upper and lower bounds that we obtain for the disconnection probability match in principal order, and conditioning on disconnection lowers the average of the Gaussian free field well inside the discrete blow-up of A, which can be understood as entropic repulsion.
math.PR math-ph math.MP
we derive asymptotic upper and lower bounds on the large deviation probability that the level set of the gaussian free field on zd d bigger or equal to three below a given level disconnects the discrete blowup of a compact set a from the boundary of the discrete blowup of a box that contains a when the level set of the gaussian free field above this level is in a strongly percolative regime these bounds substantially strengthen the results of arxiv14123960 where a was a box and the convexity of a played an important role in the proof we also derive an asymptotic upper bound on the probability that the average of the gaussian free field well inside the discrete blowup of a is above a certain level when disconnection occurs the derivation of the upper bounds uses the solidification estimates for porous interfaces that were derived in the work arxiv170607229 of as sznitman and the author to treat a similar disconnection problem for the vacant set of random interlacements if certain critical levels for the gaussian free field coincide an open question at the moment the asymptotic upper and lower bounds that we obtain for the disconnection probability match in principal order and conditioning on disconnection lowers the average of the gaussian free field well inside the discrete blowup of a which can be understood as entropic repulsion
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1,802.02519
The Ising model coupled to 2d orders
In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter \b{eta} and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in [1] and the Ising model can be correlated or uncorrelated on the random ordes and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.
gr-qc hep-th
in this article we make first steps in coupling matter to causal set theory in the path integral we explore the case of the ising model coupled to the 2d discrete einstein hilbert action restricted to the 2d orders we probe the phase diagram in terms of the wick rotation parameter beta and the ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure the couplings give rise to five different phases the causal sets take on random or crystalline characteristics as described in 1 and the ising model can be correlated or uncorrelated on the random ordes and correlated uncorrelated or anticorrelated on the crystalline orders we find that at least one new phase transition arises in which the ising spins push the causal set into the crystalline phase
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1,802.0252
Combinatorial views on persistent characters in phylogenetics
The so-called binary perfect phylogeny with persistent characters has recently been thoroughly studied in computational biology as it is less restrictive than the well known binary perfect phylogeny. Here, we focus on the notion of (binary) persistent characters, i.e. characters that can be realized on a phylogenetic tree by at most one $0 \rightarrow 1$ transition followed by at most one $1 \rightarrow 0$ transition in the tree, and analyze these characters under different aspects. First, we illustrate the connection between persistent characters and Maximum Parsimony, where we characterize persistent characters in terms of the first phase of the famous Fitch algorithm. Afterwards we focus on the number of persistent characters for a given phylogenetic tree. We show that this number solely depends on the balance of the tree. To be precise, we develop a formula for counting the number of persistent characters for a given phylogenetic tree based on an index of tree balance, namely the Sackin index. Lastly, we consider the question of how many (carefully chosen) binary characters together with their persistence status are needed to uniquely determine a phylogenetic tree and provide an upper bound for the number of characters needed.
q-bio.PE math.CO
the socalled binary perfect phylogeny with persistent characters has recently been thoroughly studied in computational biology as it is less restrictive than the well known binary perfect phylogeny here we focus on the notion of binary persistent characters ie characters that can be realized on a phylogenetic tree by at most one 0 rightarrow 1 transition followed by at most one 1 rightarrow 0 transition in the tree and analyze these characters under different aspects first we illustrate the connection between persistent characters and maximum parsimony where we characterize persistent characters in terms of the first phase of the famous fitch algorithm afterwards we focus on the number of persistent characters for a given phylogenetic tree we show that this number solely depends on the balance of the tree to be precise we develop a formula for counting the number of persistent characters for a given phylogenetic tree based on an index of tree balance namely the sackin index lastly we consider the question of how many carefully chosen binary characters together with their persistence status are needed to uniquely determine a phylogenetic tree and provide an upper bound for the number of characters needed
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1,802.02521
Infinite series in cohomology: attractors and Conley index
In this paper we study the cohomological Conley index of arbitrary isolated invariant continua for continuous maps $f \colon U \subseteq \mathbb{R}^d \to \mathbb{R}^d$ by analyzing the topological structure of their unstable manifold. We provide a simple dynamical interpretation for the first cohomological Conley index, describing it completely, and relate it to the cohomological Conley index in higher degrees. A number of consequences are derived, including new computations of the fixed point indices of isolated invariant continua in dimensions 2 and 3. Our approach exploits certain attractor-repeller decomposition of the unstable manifold, reducing the study of the cohomological Conley index to the relation between the cohomology of an attractor and its basin of attraction. This is a classical problem that, in the present case, is particularly difficult because the dynamics is discrete and the topology of the unstable manifold can be very complicated. To address it we develop a new method that may be of independent interest and involves the summation of power series in cohomology: if $Z$ is a metric space and $K \subseteq Z$ is a compact, global attractor for a continuous map $g \colon Z \to Z$, we show how to interpret series of the form $\sum_{j \ge 0} a_j (g^*)^j$ as endomorphisms of the cohomology group of the pair $(Z,K)$.
math.DS math.AT math.GT
in this paper we study the cohomological conley index of arbitrary isolated invariant continua for continuous maps f colon u subseteq mathbbrd to mathbbrd by analyzing the topological structure of their unstable manifold we provide a simple dynamical interpretation for the first cohomological conley index describing it completely and relate it to the cohomological conley index in higher degrees a number of consequences are derived including new computations of the fixed point indices of isolated invariant continua in dimensions 2 and 3 our approach exploits certain attractorrepeller decomposition of the unstable manifold reducing the study of the cohomological conley index to the relation between the cohomology of an attractor and its basin of attraction this is a classical problem that in the present case is particularly difficult because the dynamics is discrete and the topology of the unstable manifold can be very complicated to address it we develop a new method that may be of independent interest and involves the summation of power series in cohomology if z is a metric space and k subseteq z is a compact global attractor for a continuous map g colon z to z we show how to interpret series of the form sum_j ge 0 a_j gj as endomorphisms of the cohomology group of the pair zk
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1,802.02522
Joint Attention in Driver-Pedestrian Interaction: from Theory to Practice
Today, one of the major challenges that autonomous vehicles are facing is the ability to drive in urban environments. Such a task requires communication between autonomous vehicles and other road users in order to resolve various traffic ambiguities. The interaction between road users is a form of negotiation in which the parties involved have to share their attention regarding a common objective or a goal (e.g. crossing an intersection), and coordinate their actions in order to accomplish it. In this literature review we aim to address the interaction problem between pedestrians and drivers (or vehicles) from joint attention point of view. More specifically, we will discuss the theoretical background behind joint attention, its application to traffic interaction and practical approaches to implementing joint attention for autonomous vehicles.
cs.RO cs.CV
today one of the major challenges that autonomous vehicles are facing is the ability to drive in urban environments such a task requires communication between autonomous vehicles and other road users in order to resolve various traffic ambiguities the interaction between road users is a form of negotiation in which the parties involved have to share their attention regarding a common objective or a goal eg crossing an intersection and coordinate their actions in order to accomplish it in this literature review we aim to address the interaction problem between pedestrians and drivers or vehicles from joint attention point of view more specifically we will discuss the theoretical background behind joint attention its application to traffic interaction and practical approaches to implementing joint attention for autonomous vehicles
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1,802.02523
Plasma Brain Dynamics (PBD): A Mechanism for EEG Waves Under Human Consciousness
EEG signals are records of nonlinear solitary waves in human brains. The waves have several types (e.g., a, b, g, q, d) in response to different levels of consciousness. They are classified into two groups: Group-1 consists of complex storm-like waves (a, b, and g); Group-2 is composed of simple quasilinear waves (q and d). In order to elucidate the mechanism of EEG wave formation and propagation, this paper extends the Vlasov-Maxwell equations of Plasma Brain Dynamics (PBD) to a set of two-fluid, self-similar, nonlinear solitary wave equations. Numerical simulations are performed for different EEG signals. Main results include: (1) The excitation and propagation of the EEG wave packets are dependent of electric and magnetic fields, brain aqua-ions, electron and ion temperatures, masses, and their initial fluid speeds; (2) Group-1 complex waves contain three ingredients: the high-frequency ion-acoustic (IA) mode, the intermediate-frequency lower-hybrid (LH) mode, and the low-frequency ion-cyclotron (IC) mode; (3) Group-2 simple waves fall within the IA band, featured by one or a combination of the three envelopes: sinusoidal, sawtooth, and spiky/bipolar. The study proposes an alternative model to Quantum Brain Dynamics (QBD) by suggesting that the formation and propagation of the nonlinear solitary EEG waves in the brain have the same mechanism as that of the waves in space plasmas
q-bio.NC physics.med-ph
eeg signals are records of nonlinear solitary waves in human brains the waves have several types eg a b g q d in response to different levels of consciousness they are classified into two groups group1 consists of complex stormlike waves a b and g group2 is composed of simple quasilinear waves q and d in order to elucidate the mechanism of eeg wave formation and propagation this paper extends the vlasovmaxwell equations of plasma brain dynamics pbd to a set of twofluid selfsimilar nonlinear solitary wave equations numerical simulations are performed for different eeg signals main results include 1 the excitation and propagation of the eeg wave packets are dependent of electric and magnetic fields brain aquaions electron and ion temperatures masses and their initial fluid speeds 2 group1 complex waves contain three ingredients the highfrequency ionacoustic ia mode the intermediatefrequency lowerhybrid lh mode and the lowfrequency ioncyclotron ic mode 3 group2 simple waves fall within the ia band featured by one or a combination of the three envelopes sinusoidal sawtooth and spikybipolar the study proposes an alternative model to quantum brain dynamics qbd by suggesting that the formation and propagation of the nonlinear solitary eeg waves in the brain have the same mechanism as that of the waves in space plasmas
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1,802.02524
Subleading Regge limit from a soft anomalous dimension
Wilson lines capture important features of scattering amplitudes, for example soft effects relevant for infrared divergences, and the Regge limit. Beyond the leading power approximation, corrections to the eikonal picture have to be taken into account. In this paper, we study such corrections in a model of massive scattering amplitudes in N = 4 super Yang-Mills, in the planar limit, where the mass is generated through a Higgs mechanism. Using known three-loop analytic expressions for the scattering amplitude, we find that the first power suppressed term has a very simple form, equal to a single power law. We propose that its exponent is governed by the anomalous dimension of a Wilson loop with a scalar inserted at the cusp, and we provide perturbative evidence for this proposal. We also analyze other limits of the amplitude and conjecture an exact formula for a total cross-section at high energies.
hep-th hep-ph
wilson lines capture important features of scattering amplitudes for example soft effects relevant for infrared divergences and the regge limit beyond the leading power approximation corrections to the eikonal picture have to be taken into account in this paper we study such corrections in a model of massive scattering amplitudes in n 4 super yangmills in the planar limit where the mass is generated through a higgs mechanism using known threeloop analytic expressions for the scattering amplitude we find that the first power suppressed term has a very simple form equal to a single power law we propose that its exponent is governed by the anomalous dimension of a wilson loop with a scalar inserted at the cusp and we provide perturbative evidence for this proposal we also analyze other limits of the amplitude and conjecture an exact formula for a total crosssection at high energies
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1,802.02525
Spin-charge separation and many-body localization
We study many-body localization for a disordered chain of spin 1/2 fermions. In [Phys. Rev. B \textbf{94}, 241104 (2016)], when both down and up components are exposed to the same strong disorder, the authors observe a power law growth of the entanglement entropy that suggests that many-body localization is not complete; the density (charge) degree of freedom is localized, while the spin degree of freedom is apparently delocalized. We show that this power-like behavior is only a transient effect and that, for longer times, the growth is logarithmic in time suggesting that the spin degree of freedom is also localized, so that the system follows the standard many-body localization scenario. We also study the experimentally relevant case of quasiperiodic disorder.
cond-mat.dis-nn
we study manybody localization for a disordered chain of spin 12 fermions in phys rev b textbf94 241104 2016 when both down and up components are exposed to the same strong disorder the authors observe a power law growth of the entanglement entropy that suggests that manybody localization is not complete the density charge degree of freedom is localized while the spin degree of freedom is apparently delocalized we show that this powerlike behavior is only a transient effect and that for longer times the growth is logarithmic in time suggesting that the spin degree of freedom is also localized so that the system follows the standard manybody localization scenario we also study the experimentally relevant case of quasiperiodic disorder
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1,802.02526
Detecting false correlations: Uncovering a faked Bell-inequality violation
It is possible for two parties, Alice and Bob, to establish a secure communication link by sharing an ensemble of entangled particles, and then using these particles to generate a secret key. One way to establish that the particles are indeed entangled is to verify that they violate a Bell inequality. However, it might be the case that Bob is not trustworthy and wishes Alice to believe that their communications are secure, when in fact they are not. He can do this by managing to have prior knowledge of Alice's measurement device settings and then modifying his own settings based upon this information. In this case it is possible for shared particle states that must satisfy a Bell inequality to appear to violate this inequality, which would also make the system appear secure. When Bob modifies his measurement settings, however, he produces false correlations. Here we demonstrate experimentally that Alice can detect these false correlations, and uncover Bob's trickery, by using loop-state-preparation-and-measurement (SPAM) tomography. More generally, we demonstrate that loop SPAM tomography can detect false correlations (correlated errors) in a two-qubit system without needing to know anything about the prepared states or the measurements, other than the dimensions of the operators that describe them.
quant-ph
it is possible for two parties alice and bob to establish a secure communication link by sharing an ensemble of entangled particles and then using these particles to generate a secret key one way to establish that the particles are indeed entangled is to verify that they violate a bell inequality however it might be the case that bob is not trustworthy and wishes alice to believe that their communications are secure when in fact they are not he can do this by managing to have prior knowledge of alices measurement device settings and then modifying his own settings based upon this information in this case it is possible for shared particle states that must satisfy a bell inequality to appear to violate this inequality which would also make the system appear secure when bob modifies his measurement settings however he produces false correlations here we demonstrate experimentally that alice can detect these false correlations and uncover bobs trickery by using loopstatepreparationandmeasurement spam tomography more generally we demonstrate that loop spam tomography can detect false correlations correlated errors in a twoqubit system without needing to know anything about the prepared states or the measurements other than the dimensions of the operators that describe them
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1,802.02527
Polariton Hall Effect in Transition-Metal Dichalcogenides
We analyze the properties of strongly coupled excitons and photons in systems made of semiconducting two-dimensional transition-metal dichalcogenides embedded in optical cavities. Through a detailed microscopic analysis of the coupling we unveil novel, highly tunable features of the spectrum, that result in polariton splitting and a breaking of light-matter selection rules. The dynamics of the composite polaritons is influenced by the Berry phase arising both from their constituents and from the confinement-enhanced coupling. We find that light-matter coupling emerges as a mechanism that enhances the Berry phase of polaritons well beyond that of its elementary constituents, paving the way to achieve a polariton Hall effect.
cond-mat.mes-hall cond-mat.mtrl-sci
we analyze the properties of strongly coupled excitons and photons in systems made of semiconducting twodimensional transitionmetal dichalcogenides embedded in optical cavities through a detailed microscopic analysis of the coupling we unveil novel highly tunable features of the spectrum that result in polariton splitting and a breaking of lightmatter selection rules the dynamics of the composite polaritons is influenced by the berry phase arising both from their constituents and from the confinementenhanced coupling we find that lightmatter coupling emerges as a mechanism that enhances the berry phase of polaritons well beyond that of its elementary constituents paving the way to achieve a polariton hall effect
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1,802.02528
Classification of Things in DBpedia using Deep Neural Networks
The Semantic Web aims at representing knowledge about the real world at web scale - things, their attributes and relationships among them can be represented as nodes and edges in an inter-linked semantic graph. In the presence of noisy data, as is typical of data on the Semantic Web, a software Agent needs to be able to robustly infer one or more associated actionable classes for the individuals in order to act automatically on it. We model this problem as a multi-label classification task where we want to robustly identify types of the individuals in a semantic graph such as DBpedia, which we use as an exemplary dataset on the Semantic Web. Our approach first extracts multiple features for the individuals using random walks and then performs multi-label classification using fully-connected Neural Networks. Through systematic exploration and experimentation, we identify the effect of hyper-parameters of the feature extraction and the fully-connected Neural Network structure on the classification performance. Our final results show that our method performs better than state-of-the-art inferencing systems like SDtype and SLCN, from which we can conclude that random-walk-based feature extraction of individuals and their multi-label classification using Deep Neural Networks is a promising alternative to these systems for type classification of individuals on the Semantic Web. The main contribution of our work is to introduce a novel approach that allows us to use Deep Neural Networks to identify types of individuals in a noisy semantic graph by extracting features using random walks
cs.AI cs.NE
the semantic web aims at representing knowledge about the real world at web scale things their attributes and relationships among them can be represented as nodes and edges in an interlinked semantic graph in the presence of noisy data as is typical of data on the semantic web a software agent needs to be able to robustly infer one or more associated actionable classes for the individuals in order to act automatically on it we model this problem as a multilabel classification task where we want to robustly identify types of the individuals in a semantic graph such as dbpedia which we use as an exemplary dataset on the semantic web our approach first extracts multiple features for the individuals using random walks and then performs multilabel classification using fullyconnected neural networks through systematic exploration and experimentation we identify the effect of hyperparameters of the feature extraction and the fullyconnected neural network structure on the classification performance our final results show that our method performs better than stateoftheart inferencing systems like sdtype and slcn from which we can conclude that randomwalkbased feature extraction of individuals and their multilabel classification using deep neural networks is a promising alternative to these systems for type classification of individuals on the semantic web the main contribution of our work is to introduce a novel approach that allows us to use deep neural networks to identify types of individuals in a noisy semantic graph by extracting features using random walks
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1,802.02529
Comment on 'Simulation of ultra-relativistic electrons and positrons channeling in crystals with MBN Explorer'
The snapshot model of crystal atoms was implemented in the Monte Carlo code ChaS (Channeling Simulator) and is being successfully used for simulation of ultrarelativistic particle channeling. The model was criticized by Sushko et al. (J. Comp. Phys. 252 (2013) 404-418) who claim that it overestimates the mean scattering angle in a single projectile-atom collision. As a matter of fact, no evidence that would support this claim can be found in the mentioned publication. Moreover, the snapshot model and the model suggested by Sushko et al. yield essentially the same value of the mean scattering angle. Contrary to the claim of Sushko et al., the target electrons can be considered as fixed-position scatterer, corrections due to their finite mass and nonzero initial velocity have a negligible impact on the channeling of light projectiles (electrons and positrons). In contrast to the snapshot model, the model preferred by Sushko et al. does not take into account incoherent scattering of the projectile by crystal electrons. This explains why the two models predict different values of the dechanneling length. The claim that the snapshot model underestimates the dechanneling length is unfounded. In actual fact, this model is in good agreement with experimental data.
physics.acc-ph physics.comp-ph
the snapshot model of crystal atoms was implemented in the monte carlo code chas channeling simulator and is being successfully used for simulation of ultrarelativistic particle channeling the model was criticized by sushko et al j comp phys 252 2013 404418 who claim that it overestimates the mean scattering angle in a single projectileatom collision as a matter of fact no evidence that would support this claim can be found in the mentioned publication moreover the snapshot model and the model suggested by sushko et al yield essentially the same value of the mean scattering angle contrary to the claim of sushko et al the target electrons can be considered as fixedposition scatterer corrections due to their finite mass and nonzero initial velocity have a negligible impact on the channeling of light projectiles electrons and positrons in contrast to the snapshot model the model preferred by sushko et al does not take into account incoherent scattering of the projectile by crystal electrons this explains why the two models predict different values of the dechanneling length the claim that the snapshot model underestimates the dechanneling length is unfounded in actual fact this model is in good agreement with experimental data
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1,802.0253
Magnetic Isotope Effect in the Uranium Isotopes Separation
When uranyl nitrate is photolysed in the water solution, light isotope ${}^{235}{\rm U}$ is separated from isotope ${}^{238}{\rm U}$ ; an enrichment factor $K = 1.04$ . The initial samples were depleted by a light isotope of uranium ${}^{235}{\rm U}$ (degree $\beta = 0.00455$). Regenerated uranyl nitrate was enriched by an isotope of uranium ${}^{235}{\rm U}$ (degree $\alpha = 0.00464$). Uranium tetrafluoride was depleted by an isotope of uranium ${}^{235}{\rm U}$ (degree $\beta = 0.00446$). Uranium isotopes are separated by the magnetic isotope effect (MIE) in uranyl nitrate photoreduction.
physics.chem-ph
when uranyl nitrate is photolysed in the water solution light isotope 235rm u is separated from isotope 238rm u an enrichment factor k 104 the initial samples were depleted by a light isotope of uranium 235rm u degree beta 000455 regenerated uranyl nitrate was enriched by an isotope of uranium 235rm u degree alpha 000464 uranium tetrafluoride was depleted by an isotope of uranium 235rm u degree beta 000446 uranium isotopes are separated by the magnetic isotope effect mie in uranyl nitrate photoreduction
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1,802.02531
Fair comparison of skin detection approaches on publicly available datasets
Skin detection is the process of discriminating skin and non-skin regions in a digital image and it is widely used in several applications ranging from hand gesture analysis to track body parts and face detection. Skin detection is a challenging problem which has drawn extensive attention from the research community, nevertheless a fair comparison among approaches is very difficult due to the lack of a common benchmark and a unified testing protocol. In this work, we investigate the most recent researches in this field and we propose a fair comparison among approaches using several different datasets. The major contributions of this work are an exhaustive literature review of skin color detection approaches, a framework to evaluate and combine different skin detector approaches, whose source code is made freely available for future research, and an extensive experimental comparison among several recent methods which have also been used to define an ensemble that works well in many different problems. Experiments are carried out in 10 different datasets including more than 10000 labelled images: experimental results confirm that the best method here proposed obtains a very good performance with respect to other stand-alone approaches, without requiring ad hoc parameter tuning. A MATLAB version of the framework for testing and of the methods proposed in this paper will be freely available from https://github.com/LorisNanni
cs.CV
skin detection is the process of discriminating skin and nonskin regions in a digital image and it is widely used in several applications ranging from hand gesture analysis to track body parts and face detection skin detection is a challenging problem which has drawn extensive attention from the research community nevertheless a fair comparison among approaches is very difficult due to the lack of a common benchmark and a unified testing protocol in this work we investigate the most recent researches in this field and we propose a fair comparison among approaches using several different datasets the major contributions of this work are an exhaustive literature review of skin color detection approaches a framework to evaluate and combine different skin detector approaches whose source code is made freely available for future research and an extensive experimental comparison among several recent methods which have also been used to define an ensemble that works well in many different problems experiments are carried out in 10 different datasets including more than 10000 labelled images experimental results confirm that the best method here proposed obtains a very good performance with respect to other standalone approaches without requiring ad hoc parameter tuning a matlab version of the framework for testing and of the methods proposed in this paper will be freely available from httpsgithubcomlorisnanni
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1,802.02532
A Spatial Mapping Algorithm with Applications in Deep Learning-Based Structure Classification
Convolutional Neural Network (CNN)-based machine learning systems have made breakthroughs in feature extraction and image recognition tasks in two dimensions (2D). Although there is significant ongoing work to apply CNN technology to domains involving complex 3D data, the success of such efforts has been constrained, in part, by limitations in data representation techniques. Most current approaches rely upon low-resolution 3D models, strategic limitation of scope in the 3D space, or the application of lossy projection techniques to allow for the use of 2D CNNs. To address this issue, we present a mapping algorithm that converts 3D structures to 2D and 1D data grids by mapping a traversal of a 3D space-filling curve to the traversal of corresponding 2D and 1D curves. We explore the performance of 2D and 1D CNNs trained on data encoded with our method versus comparable volumetric CNNs operating upon raw 3D data from a popular benchmarking dataset. Our experiments demonstrate that both 2D and 1D representations of 3D data generated via our method preserve a significant proportion of the 3D data's features in forms learnable by CNNs. Furthermore, we demonstrate that our method of encoding 3D data into lower-dimensional representations allows for decreased CNN training time cost, increased original 3D model rendering resolutions, and supports increased numbers of data channels when compared to purely volumetric approaches. This demonstration is accomplished in the context of a structural biology classification task wherein we train 3D, 2D, and 1D CNNs on examples of two homologous branches within the Ras protein family. The essential contribution of this paper is the introduction of a dimensionality-reduction method that may ease the application of powerful deep learning tools to domains characterized by complex structural data.
cs.CV cs.LG
convolutional neural network cnnbased machine learning systems have made breakthroughs in feature extraction and image recognition tasks in two dimensions 2d although there is significant ongoing work to apply cnn technology to domains involving complex 3d data the success of such efforts has been constrained in part by limitations in data representation techniques most current approaches rely upon lowresolution 3d models strategic limitation of scope in the 3d space or the application of lossy projection techniques to allow for the use of 2d cnns to address this issue we present a mapping algorithm that converts 3d structures to 2d and 1d data grids by mapping a traversal of a 3d spacefilling curve to the traversal of corresponding 2d and 1d curves we explore the performance of 2d and 1d cnns trained on data encoded with our method versus comparable volumetric cnns operating upon raw 3d data from a popular benchmarking dataset our experiments demonstrate that both 2d and 1d representations of 3d data generated via our method preserve a significant proportion of the 3d datas features in forms learnable by cnns furthermore we demonstrate that our method of encoding 3d data into lowerdimensional representations allows for decreased cnn training time cost increased original 3d model rendering resolutions and supports increased numbers of data channels when compared to purely volumetric approaches this demonstration is accomplished in the context of a structural biology classification task wherein we train 3d 2d and 1d cnns on examples of two homologous branches within the ras protein family the essential contribution of this paper is the introduction of a dimensionalityreduction method that may ease the application of powerful deep learning tools to domains characterized by complex structural data
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1,802.02533
Factors of generalised polynomials and automatic sequences
The aim of this short note is to generalise the result of Rampersad--Shallit saying that an automatic sequence and a Sturmian sequence cannot have arbitrarily long common factors. We show that the same result holds if a Sturmian sequence is replaced by an arbitrary sequence whose terms are given by a generalised polynomial (i.e., an expression involving algebraic operations and the floor function) that is not periodic except for a set of density zero.
math.CO cs.FL math.DS
the aim of this short note is to generalise the result of rampersadshallit saying that an automatic sequence and a sturmian sequence cannot have arbitrarily long common factors we show that the same result holds if a sturmian sequence is replaced by an arbitrary sequence whose terms are given by a generalised polynomial ie an expression involving algebraic operations and the floor function that is not periodic except for a set of density zero
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1,802.02534
FixaTons: A collection of Human Fixations Datasets and Metrics for Scanpath Similarity
In the last three decades, human visual attention has been a topic of great interest in various disciplines. In computer vision, many models have been proposed to predict the distribution of human fixations on a visual stimulus. Recently, thanks to the creation of large collections of data, machine learning algorithms have obtained state-of-the-art performance on the task of saliency map estimation. On the other hand, computational models of scanpath are much less studied. Works are often only descriptive or task specific. This is due to the fact that the scanpath is harder to model because it must include the description of a dynamic. General purpose computational models are present in the literature, but are then evaluated in tasks of saliency prediction, losing therefore information about the dynamics and the behaviour. In addition, two technical reasons have limited the research. The first reason is the lack of robust and uniformly used set of metrics to compare the similarity between scanpath. The second reason is the lack of sufficiently large and varied scanpath datasets. In this report we want to help in both directions. We present FixaTons, a large collection of datasets human scanpaths (temporally ordered sequences of fixations) and saliency maps. It comes along with a software library for easy data usage, statistics calculation and implementation of metrics for scanpath and saliency prediction evaluation.
cs.AI cs.CV
in the last three decades human visual attention has been a topic of great interest in various disciplines in computer vision many models have been proposed to predict the distribution of human fixations on a visual stimulus recently thanks to the creation of large collections of data machine learning algorithms have obtained stateoftheart performance on the task of saliency map estimation on the other hand computational models of scanpath are much less studied works are often only descriptive or task specific this is due to the fact that the scanpath is harder to model because it must include the description of a dynamic general purpose computational models are present in the literature but are then evaluated in tasks of saliency prediction losing therefore information about the dynamics and the behaviour in addition two technical reasons have limited the research the first reason is the lack of robust and uniformly used set of metrics to compare the similarity between scanpath the second reason is the lack of sufficiently large and varied scanpath datasets in this report we want to help in both directions we present fixatons a large collection of datasets human scanpaths temporally ordered sequences of fixations and saliency maps it comes along with a software library for easy data usage statistics calculation and implementation of metrics for scanpath and saliency prediction evaluation
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1,802.02535
Directly and Efficiently Optimizing Prediction Error and AUC of Linear Classifiers
The predictive quality of machine learning models is typically measured in terms of their (approximate) expected prediction error or the so-called Area Under the Curve (AUC) for a particular data distribution. However, when the models are constructed by the means of empirical risk minimization, surrogate functions such as the logistic loss are optimized instead. This is done because the empirical approximations of the expected error and AUC functions are nonconvex and nonsmooth, and more importantly have zero derivative almost everywhere. In this work, we show that in the case of linear predictors, and under the assumption that the data has normal distribution, the expected error and the expected AUC are not only smooth, but have closed form expressions, which depend on the first and second moments of the normal distribution. Hence, we derive derivatives of these two functions and use these derivatives in an optimization algorithm to directly optimize the expected error and the AUC. In the case of real data sets, the derivatives can be approximated using empirical moments. We show that even when data is not normally distributed, computed derivatives are sufficiently useful to render an efficient optimization method and high quality solutions. Thus, we propose a gradient-based optimization method for direct optimization of the prediction error and AUC. Moreover, the per-iteration complexity of the proposed algorithm has no dependence on the size of the data set, unlike those for optimizing logistic regression and all other well known empirical risk minimization problems.
cs.LG
the predictive quality of machine learning models is typically measured in terms of their approximate expected prediction error or the socalled area under the curve auc for a particular data distribution however when the models are constructed by the means of empirical risk minimization surrogate functions such as the logistic loss are optimized instead this is done because the empirical approximations of the expected error and auc functions are nonconvex and nonsmooth and more importantly have zero derivative almost everywhere in this work we show that in the case of linear predictors and under the assumption that the data has normal distribution the expected error and the expected auc are not only smooth but have closed form expressions which depend on the first and second moments of the normal distribution hence we derive derivatives of these two functions and use these derivatives in an optimization algorithm to directly optimize the expected error and the auc in the case of real data sets the derivatives can be approximated using empirical moments we show that even when data is not normally distributed computed derivatives are sufficiently useful to render an efficient optimization method and high quality solutions thus we propose a gradientbased optimization method for direct optimization of the prediction error and auc moreover the periteration complexity of the proposed algorithm has no dependence on the size of the data set unlike those for optimizing logistic regression and all other well known empirical risk minimization problems
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1,802.02536
Low-Frequency Noise and Sliding of the Charge Density Waves in Two-Dimensional Materials
There has been a recent renewal of interest in charge-density-wave (CDW) phenomena, primarily driven by the emergence of two-dimensional (2D) layered CDW materials, such as 1T-TaS2, characterized by very high transition temperatures to CDW phases. In the extensively studied classical bulk CDW materials with quasi-1D crystal structure, the charge carrier transport exhibits intriguing sliding behavior, which reveals itself in the frequency domain as "narrowband" and "broadband" noise. Despite the increasing attention on physics of 2D CDWs, there have been few reports of CDW sliding, specifically in quasi-2D rare-earth tritellurides and none on the noise in any of 2D CDW systems. Here we report the results of low-frequency noise (LFN) measurements on 1T-TaS2 thin films - archetypal 2D CDW systems, as they are driven from the nearly commensurate (NC) to incommensurate (IC) CDW phases by voltage and temperature stimuli. We have found that noise in 1T-TaS2 devices has two pronounced maxima at the bias voltages, which correspond to the onset of CDW sliding and the NC-to-IC phase transition. We observed unusual Lorentzian noise features and exceptionally strong noise dependence on electric bias and temperature. We argue that LFN in 2D CDW systems has unique physical origin, different from known fundamental noise types. The specifics of LFN in 2D CDW materials can be explained by invoking the concept of interacting discrete fluctuators in the NC-CDW phase. Noise spectroscopy can serve as a useful tool for understanding electronic transport phenomena in 2D CDW materials characterized by coexistence of different phases and strong CDW pinning.
cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.str-el
there has been a recent renewal of interest in chargedensitywave cdw phenomena primarily driven by the emergence of twodimensional 2d layered cdw materials such as 1ttas2 characterized by very high transition temperatures to cdw phases in the extensively studied classical bulk cdw materials with quasi1d crystal structure the charge carrier transport exhibits intriguing sliding behavior which reveals itself in the frequency domain as narrowband and broadband noise despite the increasing attention on physics of 2d cdws there have been few reports of cdw sliding specifically in quasi2d rareearth tritellurides and none on the noise in any of 2d cdw systems here we report the results of lowfrequency noise lfn measurements on 1ttas2 thin films archetypal 2d cdw systems as they are driven from the nearly commensurate nc to incommensurate ic cdw phases by voltage and temperature stimuli we have found that noise in 1ttas2 devices has two pronounced maxima at the bias voltages which correspond to the onset of cdw sliding and the nctoic phase transition we observed unusual lorentzian noise features and exceptionally strong noise dependence on electric bias and temperature we argue that lfn in 2d cdw systems has unique physical origin different from known fundamental noise types the specifics of lfn in 2d cdw materials can be explained by invoking the concept of interacting discrete fluctuators in the nccdw phase noise spectroscopy can serve as a useful tool for understanding electronic transport phenomena in 2d cdw materials characterized by coexistence of different phases and strong cdw pinning
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1,802.02537
Minimally modified theories of gravity: a playground for testing the uniqueness of general relativity
In a recent paper [1], it was introduced a new class of gravitational theories with two local degrees of freedom. The existence of these theories apparently challenges the distinctive role of general relativity as the unique non-linear theory of massless spin-2 particles. Here we perform a comprehensive analysis of these theories with the aim of (i) understanding whether or not these are actually equivalent to general relativity, and (ii) finding the root of the variance in case these are not. We have found that a broad set of seemingly different theories actually pass all the possible tests of equivalence to general relativity (in vacuum) that we were able to devise, including the analysis of scattering amplitudes using on-shell techniques. These results are complemented with the observation that the only examples which are manifestly not equivalent to general relativity either do not contain gravitons in their spectrum, or are not guaranteed to include only two local degrees of freedom once radiative corrections are taken into account. Coupling to matter is also considered: we show that coupling these theories to matter in a consistent way is not as straightforward as one could expect. Minimal coupling, as well as the most straightforward non-minimal couplings, cannot be used. Therefore, before being able to address any issues in the presence of matter, it would be necessary to find a consistent (and in any case rather peculiar) coupling scheme.
gr-qc hep-th
in a recent paper 1 it was introduced a new class of gravitational theories with two local degrees of freedom the existence of these theories apparently challenges the distinctive role of general relativity as the unique nonlinear theory of massless spin2 particles here we perform a comprehensive analysis of these theories with the aim of i understanding whether or not these are actually equivalent to general relativity and ii finding the root of the variance in case these are not we have found that a broad set of seemingly different theories actually pass all the possible tests of equivalence to general relativity in vacuum that we were able to devise including the analysis of scattering amplitudes using onshell techniques these results are complemented with the observation that the only examples which are manifestly not equivalent to general relativity either do not contain gravitons in their spectrum or are not guaranteed to include only two local degrees of freedom once radiative corrections are taken into account coupling to matter is also considered we show that coupling these theories to matter in a consistent way is not as straightforward as one could expect minimal coupling as well as the most straightforward nonminimal couplings cannot be used therefore before being able to address any issues in the presence of matter it would be necessary to find a consistent and in any case rather peculiar coupling scheme
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1,802.02538
Yes, but Did It Work?: Evaluating Variational Inference
While it's always possible to compute a variational approximation to a posterior distribution, it can be difficult to discover problems with this approximation. We propose two diagnostic algorithms to alleviate this problem. The Pareto-smoothed importance sampling (PSIS) diagnostic gives a goodness of fit measurement for joint distributions, while simultaneously improving the error in the estimate. The variational simulation-based calibration (VSBC) assesses the average performance of point estimates.
stat.ML stat.CO
while its always possible to compute a variational approximation to a posterior distribution it can be difficult to discover problems with this approximation we propose two diagnostic algorithms to alleviate this problem the paretosmoothed importance sampling psis diagnostic gives a goodness of fit measurement for joint distributions while simultaneously improving the error in the estimate the variational simulationbased calibration vsbc assesses the average performance of point estimates
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1,802.02539
Multiple positive bound states for critical Schr\"odinger-Poisson systems
Using variational methods we prove some results about existence and multiplicity of positive bound states of to the following Schr\"odinger-Poisson system: $$ \left\{ \begin{array}{l} \vspace{2mm} -\Delta u+V(x)u+K(x)\phi(x)u=u^5 -\Delta \phi =K(x)u^2\qquad x\in\R^3 \end{array}\right.\quad\quad (SP) $$ We remark that $(SP)$ exhibits a "double" lack of compactness because of the unboundedness of $\R^3$ and the critical growth of the nonlinear term and that in our assumptions ground state solutions of $(SP)$ do not exist.
math.AP
using variational methods we prove some results about existence and multiplicity of positive bound states of to the following schrodingerpoisson system left beginarrayl vspace2mm delta uvxukxphixuu5 delta phi kxu2qquad xinr3 endarrayrightquadquad sp we remark that sp exhibits a double lack of compactness because of the unboundedness of r3 and the critical growth of the nonlinear term and that in our assumptions ground state solutions of sp do not exist
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1,802.0254
Molecular Regulation of Histamine Synthesis
Histamine is a critical mediator of IgE/ cell-mediated anaphylaxis, a neurotransmitter and a regulator of gastric acid secretion. Histamine is a monoamine synthesized from the amino acid histidine through a reaction catalyzed by the enzyme histidine decarboxylase (HDC), which removes carboxyl group from histidine. Despite the importance of histamine, transcriptional regulation of HDC gene expression in mammals is still poorly understood. In this Review, we focus on discussing advances in the understanding of molecular regulation of mammalian histamine synthesis.
q-bio.MN q-bio.GN
histamine is a critical mediator of ige cellmediated anaphylaxis a neurotransmitter and a regulator of gastric acid secretion histamine is a monoamine synthesized from the amino acid histidine through a reaction catalyzed by the enzyme histidine decarboxylase hdc which removes carboxyl group from histidine despite the importance of histamine transcriptional regulation of hdc gene expression in mammals is still poorly understood in this review we focus on discussing advances in the understanding of molecular regulation of mammalian histamine synthesis
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1,802.02541
A Morphing Continuum Analysis of Energy Transfer in Compressible Turbulence
A shock-preserving finite volume solver with the generalized Lax-Friedrichs splitting flux for Morphing Continuum Theory (MCT) is presented and verified. The numerical MCT solver is showcased in a supersonic turbulent flow with Mach 2.93 over an $8^{\circ}$ compression ramp. The simulation results validated MCT with experiments as an alternative for modeling compressible turbulence. The required size of the smallest mesh cell for the MCT simulation is shown to be almost an order larger than that in a similar DNS study. The comparison shows MCT is a much more computationally friendly theory than the classical NS equations. The dynamics of energy cascade at the length-scale of individual eddies is illuminated through the subscale rotation introduced by MCT. In this regard, MCT provides a statistical averaging procedure for capturing energy transfer in compressible turbulence, not found in classical fluid theories. Analysis of the MCT results show the existence of a statistical coupling of the internal and translational kinetic energy fluctuations with the corresponding eddy rotational energy fluctuations, indicating a multiscale transfer of energy. In conclusion, MCT gives a new characterization of the energy cascade within compressible turbulence without the use of excessive computational resources.
physics.flu-dyn
a shockpreserving finite volume solver with the generalized laxfriedrichs splitting flux for morphing continuum theory mct is presented and verified the numerical mct solver is showcased in a supersonic turbulent flow with mach 293 over an 8circ compression ramp the simulation results validated mct with experiments as an alternative for modeling compressible turbulence the required size of the smallest mesh cell for the mct simulation is shown to be almost an order larger than that in a similar dns study the comparison shows mct is a much more computationally friendly theory than the classical ns equations the dynamics of energy cascade at the lengthscale of individual eddies is illuminated through the subscale rotation introduced by mct in this regard mct provides a statistical averaging procedure for capturing energy transfer in compressible turbulence not found in classical fluid theories analysis of the mct results show the existence of a statistical coupling of the internal and translational kinetic energy fluctuations with the corresponding eddy rotational energy fluctuations indicating a multiscale transfer of energy in conclusion mct gives a new characterization of the energy cascade within compressible turbulence without the use of excessive computational resources
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1,802.02542
Disordered fermions, extra dimensions and a solvable Yang-Mills theory
Generalizing disorder couplings of the SYK model by means of SU(N) matrices we formulate a lattice model of fermions in d+1 dimensions. Integration of fermions yields an effective theory of Yang-Mills fields in d dimensions, the latter approaching the standard Yang-Mills theory in the case of heavy fermions and the classical limit of vanishing coupling constant of the theory. Quantum mechanically, the theory is solved using large N approximation of the dual effective theory of Hermitian matrices in d dimensions. The theory is asymptotically free and confines the color. In case of massless fermions the emerging theory is an asymptotic safe QCD theory. We discuss also the relationship of this theory to the SYK model.
hep-lat hep-th
generalizing disorder couplings of the syk model by means of sun matrices we formulate a lattice model of fermions in d1 dimensions integration of fermions yields an effective theory of yangmills fields in d dimensions the latter approaching the standard yangmills theory in the case of heavy fermions and the classical limit of vanishing coupling constant of the theory quantum mechanically the theory is solved using large n approximation of the dual effective theory of hermitian matrices in d dimensions the theory is asymptotically free and confines the color in case of massless fermions the emerging theory is an asymptotic safe qcd theory we discuss also the relationship of this theory to the syk model
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1,802.02543
Self-stabilizing processes
We construct `self-stabilizing' processes {Z(t), t $\in [t_0,t_1)$}. These are random processes which when `localized', that is scaled around t to a fine limit, have the distribution of an $\alpha$(Z(t))-stable process, where $\alpha$ is some given function on R. Thus the stability index at t depends on the value of the process at t. Here we address the case where $\alpha$: R $\to$ (0,1). We first construct deterministic functions which satisfy a kind of autoregressive property involving sums over a plane point set $\Pi$. Taking $\Pi$ to be a Poisson point process then defines a random pure jump process, which we show has the desired localized distributions.
math.PR
we construct selfstabilizing processes zt t in t_0t_1 these are random processes which when localized that is scaled around t to a fine limit have the distribution of an alphaztstable process where alpha is some given function on r thus the stability index at t depends on the value of the process at t here we address the case where alpha r to 01 we first construct deterministic functions which satisfy a kind of autoregressive property involving sums over a plane point set pi taking pi to be a poisson point process then defines a random pure jump process which we show has the desired localized distributions
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1,802.02544
A Dynamic Programming Approach to Evaluating Multivariate Gaussian Probabilities
We propose a method of approximating multivariate Gaussian probabilities using dynamic programming. We show that solving the optimization problem associated with a class of discrete-time finite horizon Markov decision processes with non-Lipschitz cost functions is equivalent to integrating a Gaussian functions over polytopes. An approximation scheme for this class of MDPs is proposed and explicit error bounds under the supremum norm for the optimal cost to go functions are derived.
math.OC
we propose a method of approximating multivariate gaussian probabilities using dynamic programming we show that solving the optimization problem associated with a class of discretetime finite horizon markov decision processes with nonlipschitz cost functions is equivalent to integrating a gaussian functions over polytopes an approximation scheme for this class of mdps is proposed and explicit error bounds under the supremum norm for the optimal cost to go functions are derived
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1,802.02545
In aqua electrochemistry probed by XPEEM: experimental setup, examples, and challenges
Recent developments in environmental and liquid cells equipped with electron transparent graphene windows have enabled traditional surface science spectromicroscopy tools, such as X-ray photoelectron spectroscopy (XPS), photoemission electron microscopy (PEEM), and scanning electron microscopy (SEM) to be applied to study solid-liquid and liquid-gas interfaces. Here, we focus on the experimental implementation of PEEM to probe electrified graphene-liquid interfaces using electrolyte-filled microchannel arrays as a new sample platform. We demonstrate the important methodological advantage of these multi-sample arrays: they enable the combination of the wide field of view hyperspectral imaging capabilities from PEEM with the use of powerful data mining algorithms to reveal spectroscopic and temporal behaviors at the level of the individual microsample or the entire array ensemble
cond-mat.mtrl-sci
recent developments in environmental and liquid cells equipped with electron transparent graphene windows have enabled traditional surface science spectromicroscopy tools such as xray photoelectron spectroscopy xps photoemission electron microscopy peem and scanning electron microscopy sem to be applied to study solidliquid and liquidgas interfaces here we focus on the experimental implementation of peem to probe electrified grapheneliquid interfaces using electrolytefilled microchannel arrays as a new sample platform we demonstrate the important methodological advantage of these multisample arrays they enable the combination of the wide field of view hyperspectral imaging capabilities from peem with the use of powerful data mining algorithms to reveal spectroscopic and temporal behaviors at the level of the individual microsample or the entire array ensemble
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1,802.02546
A mathematical model of the metabolism of a cell. Self-organization and chaos
Using the classical tools of nonlinear dynamics, we study the process of self-organization and the appearance of the chaos in the metabolic process in a cell with the help of a mathematical model of the transformation of steroids by a cell Arthrobacter globiformis. We constructed the phase-parametric diagrams obtained under a variation of the dissipation of the kinetic membrane potential. The oscillatory modes obtained are classified as regular and strange attractors. We calculated the bifurcations, by which the self-organization and the chaos occur in the system, and the transitions "chaos-order", "order-chaos", "order-order", and "chaos-chaos" arise. Feigenbaum's scenarios and the intermittences are found. For some selected modes, the projections of the phase portraits of attractors, Poincar\'e sections, and Poincar\'e maps are constructed. The total spectra of Lyapunov indices for the modes under study are calculated. The structural stability of the attractors is demonstrated. A general scenario of the formation of regular and strange attractors in the given metabolic process in a cell is found. The physical nature of their appearance in the metabolic process is studied.
q-bio.OT nlin.CD
using the classical tools of nonlinear dynamics we study the process of selforganization and the appearance of the chaos in the metabolic process in a cell with the help of a mathematical model of the transformation of steroids by a cell arthrobacter globiformis we constructed the phaseparametric diagrams obtained under a variation of the dissipation of the kinetic membrane potential the oscillatory modes obtained are classified as regular and strange attractors we calculated the bifurcations by which the selforganization and the chaos occur in the system and the transitions chaosorder orderchaos orderorder and chaoschaos arise feigenbaums scenarios and the intermittences are found for some selected modes the projections of the phase portraits of attractors poincare sections and poincare maps are constructed the total spectra of lyapunov indices for the modes under study are calculated the structural stability of the attractors is demonstrated a general scenario of the formation of regular and strange attractors in the given metabolic process in a cell is found the physical nature of their appearance in the metabolic process is studied
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1,802.02547
Learning One Convolutional Layer with Overlapping Patches
We give the first provably efficient algorithm for learning a one hidden layer convolutional network with respect to a general class of (potentially overlapping) patches. Additionally, our algorithm requires only mild conditions on the underlying distribution. We prove that our framework captures commonly used schemes from computer vision, including one-dimensional and two-dimensional "patch and stride" convolutions. Our algorithm-- $Convotron$ -- is inspired by recent work applying isotonic regression to learning neural networks. Convotron uses a simple, iterative update rule that is stochastic in nature and tolerant to noise (requires only that the conditional mean function is a one layer convolutional network, as opposed to the realizable setting). In contrast to gradient descent, Convotron requires no special initialization or learning-rate tuning to converge to the global optimum. We also point out that learning one hidden convolutional layer with respect to a Gaussian distribution and just $one$ disjoint patch $P$ (the other patches may be arbitrary) is $easy$ in the following sense: Convotron can efficiently recover the hidden weight vector by updating $only$ in the direction of $P$.
cs.LG cs.DS stat.ML
we give the first provably efficient algorithm for learning a one hidden layer convolutional network with respect to a general class of potentially overlapping patches additionally our algorithm requires only mild conditions on the underlying distribution we prove that our framework captures commonly used schemes from computer vision including onedimensional and twodimensional patch and stride convolutions our algorithm convotron is inspired by recent work applying isotonic regression to learning neural networks convotron uses a simple iterative update rule that is stochastic in nature and tolerant to noise requires only that the conditional mean function is a one layer convolutional network as opposed to the realizable setting in contrast to gradient descent convotron requires no special initialization or learningrate tuning to converge to the global optimum we also point out that learning one hidden convolutional layer with respect to a gaussian distribution and just one disjoint patch p the other patches may be arbitrary is easy in the following sense convotron can efficiently recover the hidden weight vector by updating only in the direction of p
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1,802.02548
Predicting Hurricane Trajectories using a Recurrent Neural Network
Hurricanes are cyclones circulating about a defined center whose closed wind speeds exceed 75 mph originating over tropical and subtropical waters. At landfall, hurricanes can result in severe disasters. The accuracy of predicting their trajectory paths is critical to reduce economic loss and save human lives. Given the complexity and nonlinearity of weather data, a recurrent neural network (RNN) could be beneficial in modeling hurricane behavior. We propose the application of a fully connected RNN to predict the trajectory of hurricanes. We employed the RNN over a fine grid to reduce typical truncation errors. We utilized their latitude, longitude, wind speed, and pressure publicly provided by the National Hurricane Center (NHC) to predict the trajectory of a hurricane at 6-hour intervals. Results show that this proposed technique is competitive to methods currently employed by the NHC and can predict up to approximately 120 hours of hurricane path.
cs.LG cs.AI cs.CY physics.ao-ph stat.ML
hurricanes are cyclones circulating about a defined center whose closed wind speeds exceed 75 mph originating over tropical and subtropical waters at landfall hurricanes can result in severe disasters the accuracy of predicting their trajectory paths is critical to reduce economic loss and save human lives given the complexity and nonlinearity of weather data a recurrent neural network rnn could be beneficial in modeling hurricane behavior we propose the application of a fully connected rnn to predict the trajectory of hurricanes we employed the rnn over a fine grid to reduce typical truncation errors we utilized their latitude longitude wind speed and pressure publicly provided by the national hurricane center nhc to predict the trajectory of a hurricane at 6hour intervals results show that this proposed technique is competitive to methods currently employed by the nhc and can predict up to approximately 120 hours of hurricane path
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1,802.02549
Maurer-Cartan moduli and theorems of Riemann-Hilbert type
We study Maurer-Cartan moduli spaces of dg algebras and associated dg categories and show that, while not quasi-isomorphism invariants, they are invariants of strong homotopy type, a natural notion that has not been studied before. We prove, in several different contexts, Schlessinger-Stasheff type theorems comparing the notions of homotopy and gauge equivalence for Maurer-Cartan elements as well as their categorified versions. As an application, we re-prove and generalize Block-Smith's higher Riemann-Hilbert correspondence, and develop its analogue for simplicial complexes and topological spaces.
math.AT math.CT math.QA
we study maurercartan moduli spaces of dg algebras and associated dg categories and show that while not quasiisomorphism invariants they are invariants of strong homotopy type a natural notion that has not been studied before we prove in several different contexts schlessingerstasheff type theorems comparing the notions of homotopy and gauge equivalence for maurercartan elements as well as their categorified versions as an application we reprove and generalize blocksmiths higher riemannhilbert correspondence and develop its analogue for simplicial complexes and topological spaces
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1,802.0255
Semi-Amortized Variational Autoencoders
Amortized variational inference (AVI) replaces instance-specific local inference with a global inference network. While AVI has enabled efficient training of deep generative models such as variational autoencoders (VAE), recent empirical work suggests that inference networks can produce suboptimal variational parameters. We propose a hybrid approach, to use AVI to initialize the variational parameters and run stochastic variational inference (SVI) to refine them. Crucially, the local SVI procedure is itself differentiable, so the inference network and generative model can be trained end-to-end with gradient-based optimization. This semi-amortized approach enables the use of rich generative models without experiencing the posterior-collapse phenomenon common in training VAEs for problems like text generation. Experiments show this approach outperforms strong autoregressive and variational baselines on standard text and image datasets.
stat.ML cs.CL cs.LG
amortized variational inference avi replaces instancespecific local inference with a global inference network while avi has enabled efficient training of deep generative models such as variational autoencoders vae recent empirical work suggests that inference networks can produce suboptimal variational parameters we propose a hybrid approach to use avi to initialize the variational parameters and run stochastic variational inference svi to refine them crucially the local svi procedure is itself differentiable so the inference network and generative model can be trained endtoend with gradientbased optimization this semiamortized approach enables the use of rich generative models without experiencing the posteriorcollapse phenomenon common in training vaes for problems like text generation experiments show this approach outperforms strong autoregressive and variational baselines on standard text and image datasets
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1,802.02551
A general existence result for stationary solutions to the Keller-Segel system
We consider a Liouville-type PDE on a smooth bounded planar domain, which is related to stationary solutions of the Keller-Segel's model for chemotaxis. We prove existence of solutions under some algebraic conditions on the parameters. In particular, if the domain is not simply connected, then we can find solution for a generic choice of the parameters. We use variational and Morse-theoretical methods.
math.AP
we consider a liouvilletype pde on a smooth bounded planar domain which is related to stationary solutions of the kellersegels model for chemotaxis we prove existence of solutions under some algebraic conditions on the parameters in particular if the domain is not simply connected then we can find solution for a generic choice of the parameters we use variational and morsetheoretical methods
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1,802.02552
Cracking the Conundrum of F-Supergiant Coronae
Chandra X-ray and HST far-ultraviolet (FUV) observations of three early-F supergiants have shed new light on a previous puzzle involving a prominent member of the class: Alpha Persei (HD20902: F5Ib). The warm supergiant is a moderately strong, hard coronal (T~10MK) X-ray source, but has ten times weaker "sub-coronal" Si IV 139 nm (T~80,000 K) emissions than early-G supergiants of similar high-energy properties. The Alpha Per X-ray excess speculatively was ascribed to a close-in hyperactive G-dwarf companion, which could have escaped previous notice, lost in the glare of the bright star. However, a subsequent dedicated multi-wavelength imaging campaign failed to find any evidence for a resolved secondary. The origin of the Alpha Per high-energy dichotomy then devolved to: (1) an unresolved companion; or (2) intrinsic coronal behavior. Exploring the second possibility, the present program has found that early-F supergiants do appear to belong to a distinct coronal class, characterized by elevated X-ray/FUV ratios, although sharing some similarities with Cepheid variables in their transitory X-ray "high states." Remarkably, the early-F supergiants now are seen to align with the low-activity end of the X-ray/FUV sequence defined by late-type dwarfs, suggesting that the disjoint behavior relative to the G supergiants might be attributed to thinner outer atmospheres on the F types, as in dwarfs, but in this case perhaps caused by a weakened "ionization valve" effect due to overly warm photospheres.
astro-ph.SR
chandra xray and hst farultraviolet fuv observations of three earlyf supergiants have shed new light on a previous puzzle involving a prominent member of the class alpha persei hd20902 f5ib the warm supergiant is a moderately strong hard coronal t10mk xray source but has ten times weaker subcoronal si iv 139 nm t80000 k emissions than earlyg supergiants of similar highenergy properties the alpha per xray excess speculatively was ascribed to a closein hyperactive gdwarf companion which could have escaped previous notice lost in the glare of the bright star however a subsequent dedicated multiwavelength imaging campaign failed to find any evidence for a resolved secondary the origin of the alpha per highenergy dichotomy then devolved to 1 an unresolved companion or 2 intrinsic coronal behavior exploring the second possibility the present program has found that earlyf supergiants do appear to belong to a distinct coronal class characterized by elevated xrayfuv ratios although sharing some similarities with cepheid variables in their transitory xray high states remarkably the earlyf supergiants now are seen to align with the lowactivity end of the xrayfuv sequence defined by latetype dwarfs suggesting that the disjoint behavior relative to the g supergiants might be attributed to thinner outer atmospheres on the f types as in dwarfs but in this case perhaps caused by a weakened ionization valve effect due to overly warm photospheres
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1,802.02553
Wrinkles, folds and plasticity in granular rafts
We investigate the mechanical response of a compressed monolayer of large and dense particles at a liquid-fluid interface: a granular raft. Upon compression, rafts first wrinkle; then, as the confinement increases, the deformation localizes in a unique fold. This characteristic buckling pattern is usually associated to floating elastic sheets and as a result, particle laden interfaces are often modeled as such. Here, we push this analogy to its limits by comparing the first quantitative measurements of the raft morphology to a theoretical continuous elastic model of the interface. We show that although powerful to describe the wrinkle wavelength, the wrinkle-to-fold transition and the fold shape, this elastic description does not capture the finer details of the experiment. We describe an unpredicted secondary wavelength, a compression discrepancy with the model and a hysteretic behavior during compression cycles, all of which are a signature of the intrinsic discrete and frictional nature of granular rafts. It suggests also that these composite materials exhibit both plastic transition and jamming dynamics.
cond-mat.soft
we investigate the mechanical response of a compressed monolayer of large and dense particles at a liquidfluid interface a granular raft upon compression rafts first wrinkle then as the confinement increases the deformation localizes in a unique fold this characteristic buckling pattern is usually associated to floating elastic sheets and as a result particle laden interfaces are often modeled as such here we push this analogy to its limits by comparing the first quantitative measurements of the raft morphology to a theoretical continuous elastic model of the interface we show that although powerful to describe the wrinkle wavelength the wrinkletofold transition and the fold shape this elastic description does not capture the finer details of the experiment we describe an unpredicted secondary wavelength a compression discrepancy with the model and a hysteretic behavior during compression cycles all of which are a signature of the intrinsic discrete and frictional nature of granular rafts it suggests also that these composite materials exhibit both plastic transition and jamming dynamics
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1,802.02554
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
Over the past ten years, driven by large scale optimisation problems arising from machine learning, the development of stochastic optimisation methods have witnessed a tremendous growth. However, despite their popularity, the theoretical understandings of these methods are quite limited in contrast to the deterministic optimisation methods. In this paper, we present a local convergence analysis for a typical type of stochastic optimisation methods: proximal variance reduced stochastic gradient methods, and mainly focus on the SAGA [12] and Prox-SVRG [43] algorithms. Under the assumption that the non-smooth component of the optimisation problem is partly smooth relative to a smooth manifold, we present a unified framework for the local convergence analysis of the SAGA/Prox-SVRG algorithms: (i) the sequences generated by the SAGA/Prox-SVRG are able to identify the smooth manifold in a finite number of iterations; (ii) then the sequence enters a local linear convergence regime. Beyond local convergence analysis, we also discuss various possibilities for accelerating these algorithms, including adapting to better local parameters, and applying higher-order deterministic/stochastic optimisation methods which can achieve super-linear convergence. Concrete examples arising from machine learning are considered to verify the obtained results.
math.OC
over the past ten years driven by large scale optimisation problems arising from machine learning the development of stochastic optimisation methods have witnessed a tremendous growth however despite their popularity the theoretical understandings of these methods are quite limited in contrast to the deterministic optimisation methods in this paper we present a local convergence analysis for a typical type of stochastic optimisation methods proximal variance reduced stochastic gradient methods and mainly focus on the saga 12 and proxsvrg 43 algorithms under the assumption that the nonsmooth component of the optimisation problem is partly smooth relative to a smooth manifold we present a unified framework for the local convergence analysis of the sagaproxsvrg algorithms i the sequences generated by the sagaproxsvrg are able to identify the smooth manifold in a finite number of iterations ii then the sequence enters a local linear convergence regime beyond local convergence analysis we also discuss various possibilities for accelerating these algorithms including adapting to better local parameters and applying higherorder deterministicstochastic optimisation methods which can achieve superlinear convergence concrete examples arising from machine learning are considered to verify the obtained results
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1,802.02555
Correlations of occupation numbers in the canonical ensemble and application to BEC in a 1D harmonic trap
We study statistical properties of $N$ non-interacting identical bosons or fermions in the canonical ensemble. We derive several general representations for the $p$-point correlation function of occupation numbers $\overline{n_1\cdots n_p}$. We demonstrate that it can be expressed as a ratio of two $p\times p$ determinants involving the (canonical) mean occupations $\overline{n_1}$, ..., $\overline{n_p}$, which can themselves be conveniently expressed in terms of the $k$-body partition functions (with $k\leq N$). We draw some connection with the theory of symmetric functions, and obtain an expression of the correlation function in terms of Schur functions. Our findings are illustrated by revisiting the problem of Bose-Einstein condensation in a 1D harmonic trap, for which we get analytical results. We get the moments of the occupation numbers and the correlation between ground state and excited state occupancies. In the temperature regime dominated by quantum correlations, the distribution of the ground state occupancy is shown to be a truncated Gumbel law. The Gumbel law, describing extreme value statistics, is obtained when the temperature is much smaller than the Bose-Einstein temperature.
cond-mat.stat-mech cond-mat.quant-gas
we study statistical properties of n noninteracting identical bosons or fermions in the canonical ensemble we derive several general representations for the ppoint correlation function of occupation numbers overlinen_1cdots n_p we demonstrate that it can be expressed as a ratio of two ptimes p determinants involving the canonical mean occupations overlinen_1 overlinen_p which can themselves be conveniently expressed in terms of the kbody partition functions with kleq n we draw some connection with the theory of symmetric functions and obtain an expression of the correlation function in terms of schur functions our findings are illustrated by revisiting the problem of boseeinstein condensation in a 1d harmonic trap for which we get analytical results we get the moments of the occupation numbers and the correlation between ground state and excited state occupancies in the temperature regime dominated by quantum correlations the distribution of the ground state occupancy is shown to be a truncated gumbel law the gumbel law describing extreme value statistics is obtained when the temperature is much smaller than the boseeinstein temperature
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1,802.02556
Current Flow Group Closeness Centrality for Complex Networks
Current flow closeness centrality (CFCC) has a better discriminating ability than the ordinary closeness centrality based on shortest paths. In this paper, we extend this notion to a group of vertices in a weighted graph, and then study the problem of finding a subset $S$ of $k$ vertices to maximize its CFCC $C(S)$, both theoretically and experimentally. We show that the problem is NP-hard, but propose two greedy algorithms for minimizing the reciprocal of $C(S)$ with provable guarantees using the monotoncity and supermodularity. The first is a deterministic algorithm with an approximation factor $(1-\frac{k}{k-1}\cdot\frac{1}{e})$ and cubic running time; while the second is a randomized algorithm with a $(1-\frac{k}{k-1}\cdot\frac{1}{e}-\epsilon)$-approximation and nearly-linear running time for any $\epsilon > 0$. Extensive experiments on model and real networks demonstrate that our algorithms are effective and efficient, with the second algorithm being scalable to massive networks with more than a million vertices.
cs.DS cs.SI
current flow closeness centrality cfcc has a better discriminating ability than the ordinary closeness centrality based on shortest paths in this paper we extend this notion to a group of vertices in a weighted graph and then study the problem of finding a subset s of k vertices to maximize its cfcc cs both theoretically and experimentally we show that the problem is nphard but propose two greedy algorithms for minimizing the reciprocal of cs with provable guarantees using the monotoncity and supermodularity the first is a deterministic algorithm with an approximation factor 1frackk1cdotfrac1e and cubic running time while the second is a randomized algorithm with a 1frackk1cdotfrac1eepsilonapproximation and nearlylinear running time for any epsilon 0 extensive experiments on model and real networks demonstrate that our algorithms are effective and efficient with the second algorithm being scalable to massive networks with more than a million vertices
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1,802.02557
Neyman-Pearson classification: parametrics and sample size requirement
The Neyman-Pearson (NP) paradigm in binary classification seeks classifiers that achieve a minimal type II error while enforcing the prioritized type I error controlled under some user-specified level $\alpha$. This paradigm serves naturally in applications such as severe disease diagnosis and spam detection, where people have clear priorities among the two error types. Recently, Tong, Feng and Li (2018) proposed a nonparametric umbrella algorithm that adapts all scoring-type classification methods (e.g., logistic regression, support vector machines, random forest) to respect the given type I error upper bound $\alpha$ with high probability, without specific distributional assumptions on the features and the responses. Universal the umbrella algorithm is, it demands an explicit minimum sample size requirement on class $0$, which is often the more scarce class, such as in rare disease diagnosis applications. In this work, we employ the parametric linear discriminant analysis (LDA) model and propose a new parametric thresholding algorithm, which does not need the minimum sample size requirements on class $0$ observations and thus is suitable for small sample applications such as rare disease diagnosis. Leveraging both the existing nonparametric and the newly proposed parametric thresholding rules, we propose four LDA-based NP classifiers, for both low- and high-dimensional settings. On the theoretical front, we prove NP oracle inequalities for one proposed classifier, where the rate for excess type II error benefits from the explicit parametric model assumption. Furthermore, as NP classifiers involve a sample splitting step of class $0$ observations, we construct a new adaptive sample splitting scheme that can be applied universally to NP classifiers, and this adaptive strategy reduces the type II error of these classifiers.
stat.ME math.ST stat.ML stat.TH
the neymanpearson np paradigm in binary classification seeks classifiers that achieve a minimal type ii error while enforcing the prioritized type i error controlled under some userspecified level alpha this paradigm serves naturally in applications such as severe disease diagnosis and spam detection where people have clear priorities among the two error types recently tong feng and li 2018 proposed a nonparametric umbrella algorithm that adapts all scoringtype classification methods eg logistic regression support vector machines random forest to respect the given type i error upper bound alpha with high probability without specific distributional assumptions on the features and the responses universal the umbrella algorithm is it demands an explicit minimum sample size requirement on class 0 which is often the more scarce class such as in rare disease diagnosis applications in this work we employ the parametric linear discriminant analysis lda model and propose a new parametric thresholding algorithm which does not need the minimum sample size requirements on class 0 observations and thus is suitable for small sample applications such as rare disease diagnosis leveraging both the existing nonparametric and the newly proposed parametric thresholding rules we propose four ldabased np classifiers for both low and highdimensional settings on the theoretical front we prove np oracle inequalities for one proposed classifier where the rate for excess type ii error benefits from the explicit parametric model assumption furthermore as np classifiers involve a sample splitting step of class 0 observations we construct a new adaptive sample splitting scheme that can be applied universally to np classifiers and this adaptive strategy reduces the type ii error of these classifiers
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1,802.02558
Intentional Control of Type I Error over Unconscious Data Distortion: a Neyman-Pearson Approach to Text Classification
This paper addresses the challenges in classifying textual data obtained from open online platforms, which are vulnerable to distortion. Most existing classification methods minimize the overall classification error and may yield an undesirably large type I error (relevant textual messages are classified as irrelevant), particularly when available data exhibit an asymmetry between relevant and irrelevant information. Data distortion exacerbates this situation and often leads to fallacious prediction. To deal with inestimable data distortion, we propose the use of the Neyman-Pearson (NP) classification paradigm, which minimizes type II error under a user-specified type I error constraint. Theoretically, we show that the NP oracle is unaffected by data distortion when the class conditional distributions remain the same. Empirically, we study a case of classifying posts about worker strikes obtained from a leading Chinese microblogging platform, which are frequently prone to extensive, unpredictable and inestimable censorship. We demonstrate that, even though the training and test data are susceptible to different distortion and therefore potentially follow different distributions, our proposed NP methods control the type I error on test data at the targeted level. The methods and implementation pipeline proposed in our case study are applicable to many other problems involving data distortion.
stat.ME cs.LG stat.AP stat.ML
this paper addresses the challenges in classifying textual data obtained from open online platforms which are vulnerable to distortion most existing classification methods minimize the overall classification error and may yield an undesirably large type i error relevant textual messages are classified as irrelevant particularly when available data exhibit an asymmetry between relevant and irrelevant information data distortion exacerbates this situation and often leads to fallacious prediction to deal with inestimable data distortion we propose the use of the neymanpearson np classification paradigm which minimizes type ii error under a userspecified type i error constraint theoretically we show that the np oracle is unaffected by data distortion when the class conditional distributions remain the same empirically we study a case of classifying posts about worker strikes obtained from a leading chinese microblogging platform which are frequently prone to extensive unpredictable and inestimable censorship we demonstrate that even though the training and test data are susceptible to different distortion and therefore potentially follow different distributions our proposed np methods control the type i error on test data at the targeted level the methods and implementation pipeline proposed in our case study are applicable to many other problems involving data distortion
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1,802.02559
Mechanical Stresses Estimation in Silicon and Glass Bonded at Elevated Temperature
During electrostatic bonding, also known as anodic bonding, silicon is bonded to glass by applying an external voltage and simultaneous heating to temperatures of 200...450 $\deg$C. While cooling to working temperature after bonding happened pieces are mutually deformed. Due to linear thermal expansion coefficients mismatch of anodically bonded glass and silicon samples an internal stress state is generated. Such stresses are called thermal mismatch stresses. The aim of this paper is a determination of technological and design solutions to achieve minimal thermal mismatch stresses in resulting bond. The nonlinear dependence of linear thermal expansion coefficients of bonded samples' materials on temperature makes it difficult to minimize thermal mismatch stresses by chosing materials with close average thermal expansion coefficients in particular temperature range. To assess means of lowering thermal mismatch stress in this paper two different ways to describe assembly are used: two thin bonded layers and multilayered composite material. Based on properties of two brands of glass (LK5, Borofloat 33) and silicon used with described mathematical models thermal mismatch stresses at temperature $T_w$ in samples bonded at several different temperatures $T_b$ are evaluated. Bonded silicon surface stress dependence of glass to silicon wafer thickness ratio is evaluated. Based on such evaluations one can say that by varying thickness of glass bonded to silicon one can obtain zero thermal mismatch stress at a particular depth of material or obtain stress of some defined value at this depth. Models of assembly description used in this paper can be used to optimize anodic bonding process parameters. Such usage aimed to minimize thermal mismatch stresses at device working temperatures is presented in this paper.
cond-mat.mtrl-sci cond-mat.mes-hall physics.app-ph
during electrostatic bonding also known as anodic bonding silicon is bonded to glass by applying an external voltage and simultaneous heating to temperatures of 200450 degc while cooling to working temperature after bonding happened pieces are mutually deformed due to linear thermal expansion coefficients mismatch of anodically bonded glass and silicon samples an internal stress state is generated such stresses are called thermal mismatch stresses the aim of this paper is a determination of technological and design solutions to achieve minimal thermal mismatch stresses in resulting bond the nonlinear dependence of linear thermal expansion coefficients of bonded samples materials on temperature makes it difficult to minimize thermal mismatch stresses by chosing materials with close average thermal expansion coefficients in particular temperature range to assess means of lowering thermal mismatch stress in this paper two different ways to describe assembly are used two thin bonded layers and multilayered composite material based on properties of two brands of glass lk5 borofloat 33 and silicon used with described mathematical models thermal mismatch stresses at temperature t_w in samples bonded at several different temperatures t_b are evaluated bonded silicon surface stress dependence of glass to silicon wafer thickness ratio is evaluated based on such evaluations one can say that by varying thickness of glass bonded to silicon one can obtain zero thermal mismatch stress at a particular depth of material or obtain stress of some defined value at this depth models of assembly description used in this paper can be used to optimize anodic bonding process parameters such usage aimed to minimize thermal mismatch stresses at device working temperatures is presented in this paper
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