September 2020 arXiv papers

Tanweer Rashid, Ahmed Abdulkadir, Ilya M. Nasrallah, Jeffrey B. Ware

Lobar cerebral microbleeds (CMBs) and localized non-hemorrhage iron deposits in the basal ganglia have been associated with brain aging, vascular disease and neurodegenerative disorders. Particularly, CMBs are small lesions and require multiple neuroimaging modalities for accurate detection. Quantitative susceptibility mapping (QSM) derived from in vivo magn

Farid Aliniaeifard, Victor Wang, Stephanie van Willigenburg

We prove a general inclusion-exclusion relation for the extended chromatic symmetric function of a weighted graph, which specializes to (extended) $k$-deletion, and we give two methods to obtain numerous new bases from weighted graphs for the algebra of symmetric functions. Moreover, we classify when two weighted paths have equal extended chromatic symmetric

Jonathan J. Fortney, Channon Visscher, Mark S. Marley, Callie E. Hood

The atmospheric pressure-temperature profiles for transiting giant planets cross a range of chemical transitions. Here we show that the particular shape of these irradiated profiles for warm giant planets below 1300 K lead to striking differences in the behavior of non-equilibrium chemistry compared to brown dwarfs of similar temperatures. Our particular foc

Xin Guo, Renyuan Xu, Thaleia Zariphopoulou

Entropy regularization has been extensively adopted to improve the efficiency, the stability, and the convergence of algorithms in reinforcement learning. This paper analyzes both quantitatively and qualitatively the impact of entropy regularization for Mean Field Game (MFG) with learning in a finite time horizon. Our study provides a theoretical justificati

Kashin Sugishita, Mason A. Porter, Mariano Beguerisse-Díaz, Naoki Masuda

In social networks, interaction patterns typically change over time. We study opinion dynamics on tie-decay networks in which tie strength increases instantaneously when there is an interaction and decays exponentially between interactions. Specifically, we formulate continuous-time Laplacian dynamics and a discrete-time DeGroot model of opinion dynamics on

Andrei A. Klishin, David J. Singer, Greg van Anders

Patterns of avoidance, adjacency, and association in complex systems design emerge from the system's underlying logical architecture (functional relationships among components) and physical architecture (component physical properties and spatial location). Understanding the physical--logical architecture interplay that gives rise to patterns of arrangeme

Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski

We give a algorithm for exact sampling from the Bingham distribution $p(x)\propto \exp(x^\top A x)$ on the sphere $\mathcal S^{d-1}$ with expected runtime of $\operatorname{poly}(d, λ_{\max}(A)-λ_{\min}(A))$. The algorithm is based on rejection sampling, where the proposal distribution is a polynomial approximation of the pdf, and can be sampled from by expl

Alexander V. Kolesnikov, Elisabeth M. Werner

Motivated by the geodesic barycenter problem from optimal transportation theory, we prove a natural generalization of the Blaschke-Santalo inequality and the affine isoperimetric inequalities for many sets and many functions. We derive from it an entropy bound for the total Kantorovich cost appearing in the barycenter problem. We also establish a "pointw

Amirhossein Arzani, Scott T. M. Dawson

High-fidelity modeling of blood flow is crucial for enhancing our understanding of cardiovascular disease. Despite significant advances in computational and experimental characterization of blood flow, the knowledge that we can acquire from such investigations remains limited by the presence of uncertainty in parameters, low spatiotemporal resolution, and me

Sergi Abadal, Akshay Jain, Robert Guirado, Jorge López-Alonso

Graph Neural Networks (GNNs) have exploded onto the machine learning scene in recent years owing to their capability to model and learn from graph-structured data. Such an ability has strong implications in a wide variety of fields whose data is inherently relational, for which conventional neural networks do not perform well. Indeed, as recent reviews can a

Yiyu Zhou, Jiapeng Zhao, Boris Braverman, Kai Pang

The orbital angular momentum (OAM) of photons presents a degree of freedom for enhancing the secure key rate of free-space quantum key distribution (QKD) through mode-division multiplexing (MDM). However, atmospheric turbulence can lead to substantial modal crosstalk, which is a long-standing challenge to MDM for free-space QKD. Here, we show that the digita

J. C. Saunders

In 2013, Strauch asked how various sequences of real numbers defined from trigonometric functions such as $x_n=(\cos n)^n$ distributed themselves$\pmod 1$. Strauch's inquiry is motivated by several such distribution results. For instance, Luca proved that the sequence $x_n=(\cos αn)^n\pmod 1$ is dense in $[0,1]$ for any fixed real number $α$ such that $α

Afura Taylor, Vijay Varma

When two black holes merge, a tremendous amount of energy is released in the form of gravitational radiation in a short span of time, making such events among the most luminous phenomenon in the universe. Models that predict the peak luminosity of black hole mergers are of interest to the gravitational wave community, with potential applications in tests of

Ramin Ayanzadeh, John Dorband, Milton Halem, Tim Finin

We present \emph{multi-qubit correction} (MQC) as a novel postprocessing method for quantum annealers that views the evolution in an open-system as a Gibbs sampler and reduces a set of excited states to a new synthetic state with lower energy value. After sampling from the ground state of a given (Ising) Hamiltonian, MQC compares pairs of excited states to r

Gaurav Vishwakarma, Aditya Sonpal, Johannes Hachmann

This review aims to draw attention to two issues of concern when we set out to make machine learning work in the chemical and materials domain, i.e., statistical loss function metrics for the validation and benchmarking of data-derived models, and the uncertainty quantification of predictions made by them. They are often overlooked or underappreciated topics

Ioannis Anagnostides, Paolo Penna

In this work, we establish near-linear and strong convergence for a natural first-order iterative algorithm that simulates Von Neumann's Alternating Projections method in zero-sum games. First, we provide a precise analysis of Optimistic Gradient Descent/Ascent (OGDA) -- an optimistic variant of Gradient Descent/Ascent -- for \emph{unconstrained} bilinea

Qingxuan Jiang, Tian Lan, Kasso Okoudjou, Robert Strichartz

We develop a theory of Sobolev orthogonal polynomials on the Sierpiński gasket ($SG$). These orthogonal polynomials arise through the Gram-Schmidt orthogonalisation process applied on the set of monomials on $SG$ using several notions of a Sobolev inner products. After establishing some recurrence relations for these orthogonal polynomials, we give estimates

Pritam Sarkar, Ali Etemad

Electrocardiogram (ECG) is the electrical measurement of cardiac activity, whereas Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood circulation. While both signals are used for heart rate monitoring, from a medical perspective, ECG is more useful as it carries additional cardiac information. Despite many attempts toward inco

Gerhard Schindl

For the ultradifferentiable weight sequence setting it is known that the Borel map which assigns to each function the infinite jet of derivatives (at 0) is surjective onto the corresponding weighted sequence class if and only if the sequence is strongly nonquasianalytic for both the Roumieu- and Beurling-type classes. Sequences which are nonquasianalytic but

Vahagn Aslanyan, Sebastian Eterović, Jonathan Kirby

We prove some unconditional cases of the Existential Closedness problem for the modular $j$-function. For this, we show that for any finitely generated field we can find a "convenient" set of generators. This is done by showing that in any field equipped with functions replicating the algebraic behaviour of the modular $j$-function and its derivative

Shu Sun, Hangsong Yan

In wireless systems aided by reconfigurable intelligent surfaces (RISs), channel state information plays a pivotal role in achieving the performance gain of RISs. Mobility renders accurate channel estimation (CE) more challenging due to the Doppler effect. In this letter, we propose two practical wideband CE schemes incorporating Doppler shift adjustment (DS

Francisco J. de Anda, Stephen F. King

We propose a theory of quark and lepton mass and mixing with non-universal $Z'$ couplings based on a 5d Standard Model with quarks and leptons transforming as triplets under a new gauged $SO(3)$ isospin. In the 4d effective theory, the $SO(3)$ isospin is broken to $U(1)'$, through a $S^1/(\mathbb{Z}_2\times \mathbb{Z}'_2)$ orbifold, then subseque

Charles Vial

We introduce a new ascending filtration, that we call the co-radical filtration in analogy with the basic theory of co-algebras, on the Chow groups of pointed smooth projective varieties. In the case of zero-cycles on projective hyper-Kähler manifolds, we conjecture it agrees with a filtration introduced by Voisin. This is established for moduli spaces of st

Mostafa Mohammadkarimi, Octavia A. Dobre, Moe Z. Win

Existing wireless communication systems have been mainly designed to provide substantial gain in terms of data rates. However, 5G and Beyond will depart from this scheme, with the objective not only to provide services with higher data rates. One of the main goals is to support massive machine-type communications (mMTC) in the IoT applications. Supporting ma

Ali Dehghani, Seyed Hossein Hendi

In the context of Black Hole Chemistry (BHC), holographic phase transitions of asymptotically anti-de Sitter (AdS) charged topological black holes (TBHs) in massive gravity coupled to Power Maxwell Invariant (PMI) electrodynamics are discussed in the grand canonical (fixed $U(1)$ potential, $Φ$) ensemble. Considering all higher-order graviton's self-inte

Chao Zheng, Kun Yang, Xin Wan

We investigate the effect of surface disorder on the chiral surface states of a three-dimensional quantum Hall system. Utilizing a transfer-matrix method, we find that the localization length of the surface state along the magnetic field decreases with the surface disorder strength in the weak disorder regime, but increases anomalously in the strong disorder

Nicolò Crescini, Giovanni Carugno, Giuseppe Ruoso

We describe and operate a novel spin-magnetometer based on the phase modulation of cavity magnon polaritons. In this scheme a rf magnetic field is detected through the sidebands it induces on a pump, and the experimental configuration allows for a negligible pump noise and a high frequency readout. The demonstrator setup, based on a copper cavity coupled to

Niels Breckwoldt, Thore Posske, Michael Thorwart

Braiding Majorana zero-modes around each other is a promising route towards topological quantum computing. Yet, two competing maxims emerge when implementing Majorana braiding in real systems: On the one hand, perfect braiding should be conducted adiabatically slowly to avoid non-topological errors. On the other hand, braiding must be conducted fast such tha

Vincent Cohen-Addad, Karthik C. S., Euiwoong Lee

The k-means objective is arguably the most widely-used cost function for modeling clustering tasks in a metric space. In practice and historically, k-means is thought of in a continuous setting, namely where the centers can be located anywhere in the metric space. For example, the popular Lloyd's heuristic locates a center at the mean of each cluster. De

F. M. da Silva, L. C. N. Santos, C. C. Barros

In this work we study rapidly rotating stars by considering the Rastall theory of gravity. We obtain and solve the equations by numerical methods for two usual parametrization of polytropic stars. Then the mass-radius relations, moments of inertia and other results of interest are obtained and compared with the ones for non-rotating stars.

Shiv Upadhyay, Amanda Dumi, James Shee, Kenneth D. Jordan

The diffusion Monte Carlo (DMC), auxiliary field quantum Monte Carlo (AFQMC), and equation-of-motion coupled cluster (EOM-CC) methods are used to calculate the electron binding energy (EBE) of the non-valence anion state of a model (H$_2$O)$_4$ cluster. Two geometries are considered, one at which the anion is unbound and the other at which it is bound in the

A. H. Ajjath, Pooja Mukherjee, V. Ravindran, Aparna Sankar

We present a formalism that sums up both soft-virtual (SV) and next to SV (NSV) contributions to all orders in perturbative QCD for the rapidity distribution of any colorless particle produced in hadron colliders. We have exploited the factorization properties and the renormalisation group (RG) invariance of the differential cross-section to achieve this. Us

Nathan Steinle, Michael Kesden

Binary black holes (BBHs) can form from the collapsed cores of isolated high-mass binary stars. The masses and spins of these BBHs are determined by the complicated interplay of phenomena such as tides, winds, accretion, common-envelope evolution (CEE), supernova natal kicks, and stellar core-envelope coupling. The gravitational waves emitted during the merg

Lisa Sauermann, Yuval Wigderson

Motivated by higher vanishing multiplicity generalizations of Alon's Combinatorial Nullstellensatz and its applications, we study the following problem: for fixed $k\geq 1$ and $n$ large with respect to $k$, what is the minimum possible degree of a polynomial $P\in \mathbb{R}[x_1,\dots,x_n]$ with $P(0,\dots,0)\neq 0$ such that $P$ has zeroes of multiplic

David Gómez-Ullate, Yves Grandati, Robert Milson

We provide a complete classification and an explicit representation of rational solutions to the fourth Painlevé equation PIV and its higher order generalizations known as the $A_{2n}$-Painlevé or Noumi-Yamada systems. The construction of solutions makes use of the theory of cyclic dressing chains of Schrödinger operators. Studying the local expansions of th

Jaideep Pathak, Mustafa Mustafa, Karthik Kashinath, Emmanuel Motheau

Simulation of turbulent flows at high Reynolds number is a computationally challenging task relevant to a large number of engineering and scientific applications in diverse fields such as climate science, aerodynamics, and combustion. Turbulent flows are typically modeled by the Navier-Stokes equations. Direct Numerical Simulation (DNS) of the Navier-Stokes

B. A. Stuart, Seokhwan Choi, Jisun Kim, Lukas Muechler

Drumhead surface states that link together loops of nodal lines arise in Dirac nodal-line semimetals as a consequence of the topologically non-trivial band crossings. We used low-temperature scanning tunneling microscopy and Fourier-transformed scanning tunneling spectroscopy to investigate the quasiparticle interference (QPI) properties of ZrSiTe. Our resul

Valerio Faraoni, Andrea Giusti, Tyler F. Bean

We point out an association between anomalies in the Hawking quasilocal mass (or, in spherical symmetry, in its better known version, the Misner-Sharp-Hernandez mass) and unphysical properties of the spacetime geometry. While anomalous behaviors show up in certain quantum-corrected black holes, they are not unique to this context and signal serious physical

Ioannis Papakis, Abhijit Sarkar, Anuj Karpatne

This paper proposes a novel method for online Multi-Object Tracking (MOT) using Graph Convolutional Neural Network (GCNN) based feature extraction and end-to-end feature matching for object association. The Graph based approach incorporates both appearance and geometry of objects at past frames as well as the current frame into the task of feature learning.

Eisa Hedayati, Timothy C. Havens, Jeremy P. Bos

Light field (LF) imaging has gained significant attention due to its recent success in 3-dimensional (3D) displaying and rendering as well as augmented and virtual reality usage. Nonetheless, because of the two extra dimensions, LFs are much larger than conventional images. We develop a JPEG-assisted learning-based technique to reconstruct an LF from a JPEG

Fei Gao, Fan Xia, Kwun Chuen Gary Chan

In many medical studies, an ultimate failure event such as death is likely to be affected by the occurrence and timing of other intermediate clinical events. Both event times are subject to censoring by loss-to-follow-up but the nonterminal event may further be censored by the occurrence of the primary outcome, but not vice versa. To study the effect of an i

Yi-Jheng Lin, Che-Hao Yu, Tzu-Hsuan Liu, Cheng-Shang Chang

In comparison with individual testing, group testing (also known as pooled testing) is more efficient in reducing the number of tests and potentially leading to tremendous cost reduction. As indicated in the recent article posted on the US FDA website, the group testing approach for COVID-19 has received a lot of interest lately. There are two key elements i

Eirik Valseth, Pouria Behnoudfar, Clint Dawson, Albert Romkes

We establish stable finite element (FE) approximations of convection-diffusion initial boundary value problems using the automatic variationally stable finite element (AVS-FE) method. The transient convection-diffusion problem leads to issues in classical FE methods as the differential operator can be considered singular perturbation in both space and time.

Dimitrios Bachtis, Gert Aarts, Biagio Lucini

We present a physical interpretation of machine learning functions, opening up the possibility to control properties of statistical systems via the inclusion of these functions in Hamiltonians. In particular, we include the predictive function of a neural network, designed for phase classification, as a conjugate variable coupled to an external field within

Giulio Codogni, Thomas Krämer

We show that the degree of Gauss maps on abelian varieties is semicontinuous in families, and we study its jump loci. As an application we obtain that in the case of theta divisors this degree answers the Schottky problem. Our proof computes the degree of Gauss maps by specialization of Lagrangian cycles on the cotangent bundle. We also get similar results f

Tabish Qureshi

A realizable delayed-choice quantum eraser, using a modified Mach-Zehnder (MZ) interferometer and polarization entangled photons, is theoretically analyzed here. The signal photon goes through a modified MZ interferometer, and the polarization of the idler photon provides path information for the signal photon. The setup is very similar to the delayed-choice

Khadeejah Bepari, Sarah Malik, Michael Spannowsky, Simon Williams

The interpretation of measurements of high-energy particle collisions relies heavily on the performance of full event generators. By far the largest amount of time to predict the kinematics of multi-particle final states is dedicated to the calculation of the hard process and the subsequent parton shower step. With the continuous improvement of quantum devic

Giovanni Ferrari, Ludovico Lami, Thomas Theurer, Martin B. Plenio

We study asymptotic state transformations in continuous variable quantum resource theories. In particular, we prove that monotones displaying lower semicontinuity and strong superadditivity can be used to bound asymptotic transformation rates in these settings. This removes the need for asymptotic continuity, which cannot be defined in the traditional sense

Wai-Tong Louis Fan, Michael Jolly, Ali Pakzad

We consider the incompressible 3D Navier-Stokes equations subject to a shear induced by noisy movement of part of the boundary. The effect of the noise is quantified by upper bounds on the first two moments of the dissipation rate. The expected value estimate is consistent with the Kolmogorov dissipation law, recovering an upper bound as in [15] for the dete

Kerem C. Tezcan, Neerav Karani, Christian F. Baumgartner, Ender Konukoglu

Undersampling the k-space during MR acquisitions saves time, however results in an ill-posed inversion problem, leading to an infinite set of images as possible solutions. Traditionally, this is tackled as a reconstruction problem by searching for a single "best" image out of this solution set according to some chosen regularization or prior. This ap

Mohammad Saber Hashemi, Masoud Safdari, Azadeh Sheidaei

A supervised machine learning (ML) based computational methodology for the design of particulate multifunctional composite materials with desired thermal conductivity (TC) is presented. The design variables are physical descriptors of the material microstructure that directly link microstructure to the material's properties. A sufficiently large and unif

Thomas Kite, Andrea Ravenni, Subodh P. Patil, Jens Chluba

Gravitational waves (GWs) have the potential to probe the entirety of cosmological history due to their nearly perfect decoupling from the thermal bath and any intervening matter after emission. In recent years, GW cosmology has evolved from merely being an exciting prospect to an actively pursued avenue for discovery, and the early results are very promisin

Mohit Chandra, Ashwin Pathak, Eesha Dutta, Paryul Jain

While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate speech, offensive language, sexist and racist opinions, etc. Detection and curtailment of such abusive content is critical for avoiding its psychological impact on victim communiti

Yi Ling, Yuxuan Liu, Zhuo-Yu Xian

We study the information paradox for the eternal black hole with charges on a doubly-holographic model in general dimensions, where the charged black hole on a Planck brane is coupled to the baths on the conformal boundaries. In the case of weak tension, the brane can be treated as a probe such that its backreaction to the bulk is negligible. We analytically

Rafael T. Amorim, Alessandra A. Verri

We study the spectrum of the Dirichlet Laplacian operator in a two-dimensional twisted strip embedded in $\mathbb R^d$ with $d \geq 2$. It is shown that a local twisting perturbation can create discrete eigenvalues for the operator. In particular, we also study the case where the twisted effect "grows" at infinity while the width of the strip goes to

Xiaorun Zang, Godofredo Bautista, Léo Turquet, Tero Setälä

Efficient optical excitation of hybridized plasmon modes in nanoantennas is vital to achieve many promising functionalities, but it can be challenging due to a field-profile mismatch between the incident light and the hybrid mode. We present a general approach for efficient hybrid-mode excitation by focusing the incident light field in the basis of cylindric

Hongtaek Jung, Sungkyung Kang, Seungwon Kim

We show that the differences between various concordance invariants of knots, including Rasmussen's $s$-invariant and its generalizations $s_n$-invariants, give lower bounds to the Turaev genus of knots. Using the fact that our bounds are nontrivial for some quasi-alternating knots, we show the additivity of Turaev genus for a certain class of knots. Thi

Hong-Ye Hu, Dian Wu, Yi-Zhuang You, Bruno Olshausen

Flow-based generative models have become an important class of unsupervised learning approaches. In this work, we incorporate the key ideas of renormalization group (RG) and sparse prior distribution to design a hierarchical flow-based generative model, RG-Flow, which can separate information at different scales of images and extract disentangled representat

Varun Vaidya

I develop an Effective Field Theory (EFT) framework to compute jet substructure observables for heavy ion collision experiments. As an illustration, I consider dijet events that accompany the formation of a weakly coupled Quark Gluon Plasma(QGP) medium in a heavy ion collision and look at an observable insensitive to jet selection bias: the simultaneous meas

Pietro Bergamini, Piero Rosati, Eros Vanzella, Gabriel Bartosch Caminha

We present a new high-precision parametric strong lensing model of the galaxy cluster MACS J0416.1-2403, at z=0.396, which takes advantage of the MUSE Deep Lensed Field (MDLF), with 17.1h integration in the northeast region of the cluster, and Hubble Frontier Fields data. We spectroscopically identify 182 multiple images from 48 background sources at 0.9<z<6

Theodoros Nakas, Konstantinos S. Rigatos

There has been recent progress towards understanding the dynamics of world-volume fermions that arise as open-string modes from brane intersections in the probe limit $(N_f/N_c \rightarrow 0)$. In this work we consider all possible BPS brane junctions in Type IIA/B supergravity theories. We study in detail the dynamics of these states by deriving their equat

Sultan Hassan, Max Gronke

Lyman-$α$ (Ly$α$) emitting galaxies are powerful tools to probe the late stages of cosmic reionization. The observed sudden drop in Ly$α$ fraction at $z>6$ is often interpreted as a sign of reionization, since the intergalactic medium (IGM) is more neutral and opaque to Ly$α$ photons. Crucially, this interpretation of the observations is only valid under the

Astrid Eichhorn, Johannes Lumma, Jan M. Pawlowski, Manuel Reichert

We calculate the gravitational-wave spectra produced by the electroweak phase transition with TeV-scale Beyond-Standard-Model physics in the early universe. Our study captures the effect of quantum and thermal fluctuations within a non-perturbative framework. We discover a universal relation between the mean bubble separation and the strength parameter of th

Rebecca K. Leane, Juri Smirnov

We present exoplanets as new targets to discover Dark Matter (DM). Throughout the Milky Way, DM can scatter, become captured, deposit annihilation energy, and increase the heat flow within exoplanets. We estimate upcoming infrared telescope sensitivity to this scenario, finding actionable discovery or exclusion searches. We find that DM with masses above abo

Niklas Casper, Wolfram Brenig

We study the impact of trimerization (breathing) of the nearest-neighbor (NN) exchange on the planar XY spin-1/2 ferromagnet on the kagome lattice, including additional four-site ring exchange. For uniform NN exchange, this model has previously been shown to transit from a long-range ordered ferromagnet into a Z2 quantum spin liquid by virtue of the ring exc

Samuel Häusler, Philipp Fabritius, Jeffrey Mohan, Martin Lebrat

We study thermoelectric currents of neutral, fermionic atoms flowing through a mesoscopic channel connecting a hot and a cold reservoir across the superfluid transition. The thermoelectric response results from a competition between density-driven diffusion from the cold to the hot reservoir and the channel favoring transport of energetic particles from hot

V. Sosa Fiscella, S. del Palacio, L. Combi, C. O. Lousto

The Argentine Institute of Radio astronomy (IAR) is equipped with two single-dish 30-m radio antennas capable of performing daily observations of pulsars and radio transients in the southern hemisphere at 1.4 GHz. We aim to contribute to pulsar timing studies related to short time-scale interstellar scintillation and searches for sources of continuous gravit

Taishi Ikeda, Laura Bernard, Vitor Cardoso, Miguel Zilhao

We show that light scalars can form quasibound states around binaries. In the nonrelativistic regime, these states are formally described by the quantum-mechanical Schrodinger equation for a one-electron heteronuclear diatomic molecule. We performed extensive numerical simulations of scalar fields around black hole binaries showing that a scalar structure co

Eslam Khalaf, Nick Bultinck, Ashvin Vishwanath, Michael P. Zaletel

We present a systematic study of the low-energy collective modes for different insulating states at integer fillings in twisted bilayer graphene. In particular, we provide a simple counting rule for the total number of soft modes, and analyze their energies and symmetry quantum numbers in detail. To study the soft mode spectra, we employ time dependent Hartr

Nathan Secrest, Sebastian von Hausegger, Mohamed Rameez, Roya Mohayaee

We study the large-scale anisotropy of the Universe by measuring the dipole in the angular distribution of a flux-limited, all-sky sample of 1.36 million quasars observed by the Wide-field Infrared Survey Explorer (WISE). This sample is derived from the new CatWISE2020 catalog, which contains deep photometric measurements at 3.4 and 4.6 $μ$m from the cryogen

Ikhyun Cho, U Kang

How can we efficiently compress a model while maintaining its performance? Knowledge Distillation (KD) is one of the widely known methods for model compression. In essence, KD trains a smaller student model based on a larger teacher model and tries to retain the teacher model&#39;s level of performance as much as possible. However, existing KD methods suffer

Sareen Shah

Normalized relational databases are a common method for storing data, but pulling out usable denormalized data for consumption generally requires either direct access to the source data or creation of an appropriate view or table by a database administrator. End-users are thus limited in their ability to explore and use data that is stored in this manner. Pr

Qin Fei, Zhu Yi, Yingjie Yang

We derive the reconstruction formulae for the inflation model with the non-minimal derivative coupling term. If reconstructing the potential from the tensor-to-scalar ratio, we could obtain the potential without using the high friction limit. As an example, we reconstruct the potential from the parametrization $r=8α/(N+β)^γ$, which is a general form of the $

Xuan Tao, Andrew Day, Lan Ling, Samuel Drapeau

Spoofing is an illegal act of artificially modifying the supply to drive temporarily prices in a given direction for profit. In practice, detection of such an act is challenging due to the complexity of modern electronic platforms and the high frequency at which orders are channeled. We present a micro-structural study of spoofing in a simple static setting.

Siddhant Agrawal, Andrea R. Nahmod

We consider the 2D incompressible Euler equation on a corner domain $Ω$ with angle $νπ$ with $\frac{1}{2}<ν<1$. We prove that if the initial vorticity $ω_0 \in L^{1}(Ω)\cap L^{\infty}(Ω)$ and if $ω_0$ is non-negative and supported on one side of the angle bisector of the domain, then the weak solutions are unique. This is the first result which proves unique

Nicolas Crampé, Luc Frappat, Julien Gaboriaud, Loïc Poulain d&#39;Andecy

The original Askey-Wilson algebra introduced by Zhedanov encodes the bispectrality properties of the eponym polynomials. The name &#39;Askey-Wilson algebra&#39; is currently used to refer to a variety of related structures that appear in a large number of contexts. We review these versions, sort them out and establish the relations between them. We focus on

Amin Gohari, Gerhard Kramer

An information measure based on fractional partitions of a set is used to derive a general dependence balance inequality for communication. This inequality is used to obtain new upper bounds on reliable and secret rates for multiterminal channels. For example, we obtain a new upper bound on the rate of shared randomness generated among terminals, a counterpa

Claus Köstler, Arundhathi Krishnan, Stephen J. Wills

We introduce a new distributional invariance principle, called `partial spreadability&#39;, which emerges from the representation theory of the Thompson monoid $F^+$ in noncommutative probability spaces. We show that a partially spreadable sequence of noncommutative random variables is adapted to a local Markov filtration. Conversely we show that a large cla

Marwen Belkaid, Luiz Pessoa

Over the past decades, research in cognitive and affective neuroscience has emphasized that emotion is crucial for human intelligence and in fact inseparable from cognition. Concurrently, there has been growing interest in simulating and modeling emotion-related processes in robots and artificial agents. In this opinion paper, our goal is to provide a snapsh

Sanxing Chen, Aidan San, Xiaodong Liu, Yangfeng Ji

In Text-to-SQL semantic parsing, selecting the correct entities (tables and columns) for the generated SQL query is both crucial and challenging; the parser is required to connect the natural language (NL) question and the SQL query to the structured knowledge in the database. We formulate two linking processes to address this challenge: schema linking which

Zoë Holmes, Andrew Arrasmith, Bin Yan, Patrick J. Coles

Scrambling processes, which rapidly spread entanglement through many-body quantum systems, are difficult to investigate using standard techniques, but are relevant to quantum chaos and thermalization. In this Letter, we ask if quantum machine learning (QML) could be used to investigate such processes. We prove a no-go theorem for learning an unknown scrambli

Yogyata Pathania, Dipanjan Chakraborty, Felix Höfling

A binary liquid near its consolute point exhibits critical fluctuations of the local composition; the diverging correlation length has always challenged simulations. The method of choice for the calculation of critical points in the phase diagram is a scaling analysis of finite-size corrections, based on a sequence of widely different system sizes. Here, we

Yangyang Lyu

We consider the continuous parabolic Anderson model with the Gaussian fields under the measure-valued initial conditions, the covariances of which are nonhomogeneous in time and fractional rough in space. We mainly study the spatial behaviors for the Feynman-Kac formulas in Stratonovich&#39;s sense. Benefited from the application of Feynman-Kac formula based

M. Yarmohammadi, C. Meyer, B. Fauseweh, B. Normand

We consider the dynamical properties of a gapped quantum spin system coupled to the electric field of a laser, which drives the resonant excitation of specific phonon modes that modulate the magnetic interactions. We deduce the quantum master equations governing the time-evolution of both the lattice and spin sectors, by developing a Lindblad formalism with

Atabey Kaygun

We calculate suitably localized Hochschild homologies of various quantum groups and Podleś spheres after realizing them as generalized Weyl algebras (GWAs). We use the fact that every GWA is birationally equivalent to a smash product with a 1-torus. We also address and solve the birational equivalence problem, and the birational smoothness problem for GWAs.

Daniel Daigle

We prove Freudenburg&#39;s Freeness Conjecture: Let B be the polynomial ring in three variables over a field of characteristic zero, let D : B --> B be a nonzero locally nilpotent derivation, and let A = ker(D). Then B is a free A-module, and there exists a basis $(e_i)_{i \in \mathbb{N}}$ of B such that deg$_D(e_i) = i$ for all $i \in \mathbb{N}$.

Carson Eisenach, Yagna Patel, Dhruv Madeka

Recent advances in neural forecasting have produced major improvements in accuracy for probabilistic demand prediction. In this work, we propose novel improvements to the current state of the art by incorporating changes inspired by recent advances in Transformer architectures for Natural Language Processing. We develop a novel decoder-encoder attention for

Danhyang Lee, Li-Chun Zhang, Jae-Kwang Kim

By record linkage one joins records residing in separate files which are believed to be related to the same entity. In this paper we approach record linkage as a classification problem, and adapt the maximum entropy classification method in text mining to record linkage, both in the supervised and unsupervised settings of machine learning. The set of links w

Kumari Gaurav Rana, Rafael Lopes Seeger, Sandra Ruiz-Gómez, Roméo Juge

Magnetic skyrmions are topological spin textures holding great potential as nanoscale information carriers. Recently, skyrmions have been predicted in antiferromagnets, with key advantages in terms of stability, size, and dynamical properties over their ferromagnetic analogs. However, their experimental demonstration is still lacking. Here, we show the impri

Robert R. Hoffman, William J. Clancey, Shane T. Mueller

Current discussions of &#34;Explainable AI&#34; (XAI) do not much consider the role of abduction in explanatory reasoning (see Mueller, et al., 2018). It might be worthwhile to pursue this, to develop intelligent systems that allow for the observation and analysis of abductive reasoning and the assessment of abductive reasoning as a learnable skill. Abductiv

Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song

We introduce Performers, Transformer architectures which can estimate regular (softmax) full-rank-attention Transformers with provable accuracy, but using only linear (as opposed to quadratic) space and time complexity, without relying on any priors such as sparsity or low-rankness. To approximate softmax attention-kernels, Performers use a novel Fast Attent

Davood Momeni

An interesting deformation of the Jackiw-Teitelboim (JT) gravity has been proposed by Witten by adding a potential term $U(ϕ)$ as a self-coupling of the scalar dilaton field. During calculating the path integral over fields, a constraint comes from integration over $ϕ$ as $R(x)+2=2αδ(\vec{x}-\vec{x}&#39;)$. The resulting Euclidean metric suffered from a coni

ATLAS Collaboration

A search for heavy resonances decaying into a pair of $Z$ bosons leading to $\ell^+\ell^-\ell&#39;^+\ell&#39;^-$ and $\ell^+\ell^-ν\barν$ final states, where $\ell$ stands for either an electron or a muon, is presented. The search uses proton-proton collision data at a centre-of-mass energy of 13 TeV collected from 2015 to 2018 that corresponds to the full i

A. Ben Hassine, T. Chtioui, M. Elhamdadi, S. Mabrouk

We introduce a notion of left-symmetric Rinehart algebras, which is a generalization of a left-symmetric algebras. The left multiplication gives rise to a representation of the corresponding sub-adjacent Lie-Rinehart algebra. We construct left-symmetric Rinehart algebra from O-operators on Lie-Rinehart algebra. We extensively investigate representations of a

Nicolas Gontier, Koustuv Sinha, Siva Reddy, Christopher Pal

We are interested in understanding how well Transformer language models (TLMs) can perform reasoning tasks when trained on knowledge encoded in the form of natural language. We investigate their systematic generalization abilities on a logical reasoning task in natural language, which involves reasoning over relationships between entities grounded in first-o

Daria Gusenkova, Martin Spiecker, Richard Gebauer, Madita Willsch

Reading out the state of superconducting artificial atoms typically relies on dispersive coupling to a readout resonator. For a given system noise temperature, increasing the circulating photon number $\bar{n}$ in the resonator enables a shorter measurement time and is therefore expected to reduce readout errors caused by spontaneous atom transitions. Howeve

Christopher T. Hill, Graham G. Ross

Theories of scalars and gravity, with non-minimal interactions, $\sim (M_P^2 +F(ϕ) )R +L(ϕ)$, have graviton exchange induced contact terms. These terms arise in single particle reducible diagrams with vertices $\propto q^2$ that cancel the Feynman propagator denominator $1/q^2$ and are familiar in various other physical contexts. In gravity these lead to add

S. Pezzuto, M. Benedettini, J. Di Francesco, P. Palmeirim

(Abridged) In this paper, we present analyses of images taken with the Herschel ESA satellite from 70mu to 500mu. We first constructed column density and dust temperature maps. Next, we identified compact cores in the maps, and characterize the cores using modified blackbody fits to their SEDs: we identified 684 starless cores, of which 199 are bound and pot

Fernando Antonio Flor, Gabrielle Olinger, Rene Bellwied

We present calculations of the chemical freeze-out temperature (T_ch) based on particle yields from STAR and ALICE measured at collision energies ranging from sqrt{s_{NN}} = 11.5 GeV to 5.02 TeV. Employing the Grand Canonical Ensemble approach using the Thermal-FIST Hadron Resonance Gas model package, we show evidence for a flavour-dependent chemical freeze-

Jonathan Malmaud, Roger Levy, Yevgeni Berzak

In this work, we analyze how human gaze during reading comprehension is conditioned on the given reading comprehension question, and whether this signal can be beneficial for machine reading comprehension. To this end, we collect a new eye-tracking dataset with a large number of participants engaging in a multiple choice reading comprehension task. Our analy