October 2020 arXiv papers — page 102

Raul de Queiroz Mendes, Eduardo Godinho Ribeiro, Nicolas dos Santos Rosa, Valdir Grassi

Inferring the depth of images is a fundamental inverse problem within the field of Computer Vision since depth information is obtained through 2D images, which can be generated from infinite possibilities of observed real scenes. Benefiting from the progress of Convolutional Neural Networks (CNNs) to explore structural features and spatial image information,

Benjamin Cameron, Cem Tasan

Recent developments in imaging techniques and correlation algorithms enable measurement of strain fields on a deforming material at high spatial and temporal resolution. In such cases, the computation of the stress field from the known deformation field becomes an interesting possibility. This is known as an inverse problem. Current approaches to this proble

Wei-Yang Liu, Jiunn-Wei Chen

We investigate the renormalon ambiguity from bubble-chain diagrams in the isovector unpolarized quasi-parton distribution function (PDF) of a hadron. We confirm the assertion by Braun, Vladimirov and Zhang (arXiv:1810.00048) that the leading IR renormalon ambiguity is formally an $\mathcal{O}({\Lambda}^2_{QCD}/x^2P_z^2)$ effect, with $x$ the parton momentum

R. Lange, N. Huntemann, J. M. Rahm, C. Sanner

We compare two optical clocks based on the $^2$S$_{1/2}(F=0)\to {}^2$D$_{3/2}(F=2)$ electric quadrupole (E2) and the $^2$S$_{1/2}(F=0)\to {}^2$F$_{7/2}(F=3)$ electric octupole (E3) transition of $^{171}$Yb$^{+}$ and measure the frequency ratio $ν_{\mathrm{E3}}/ν_{\mathrm{E2}}=0.932\,829\,404\,530\,965\,376(32)$. We determine the transition frequency $ν_{E3}=

Aditya Chowdhury, Nissim Kanekar, Jayaram Chengalur, Shiv Sethi

The baryonic processes in galaxy evolution include gas infall onto galaxies to form neutral atomic hydrogen (HI), the conversion of HI to the molecular state (H$_2$), and, finally, the conversion of H$_2$ to stars. Understanding galaxy evolution thus requires understanding the evolution of both the stars, and the neutral atomic and molecular gas, the primary

Yanbing Mao, Naira Hovakimyan, Petros Voulgaris, Lui Sha

This paper proposes a novel model inference procedure to identify system matrix from a single noisy trajectory over a finite-time interval. The proposed inference procedure comprises an observation data processor, a redundant data processor and an ordinary least-square estimator, wherein the data processors mitigate the influence of observation noise on infe

Aleksey Generozov

The Galactic centre contains several young populations within its central parsec: a disk between $\sim$0.05 and 0.5 pc from the centre, and the isotropic S-star cluster extending an order of magnitude further inwards in radius. Recent observations (i.e. spectroscopy and hypervelocity stars) suggest that some S-stars originate in the disk. In particular, the

Paul Staat, Harald Elders-Boll, Markus Heinrichs, Rainer Kronberger

Physical layer key generation is a promising candidate for cryptographic key establishment between two wireless communication parties. It offers information-theoretic security and is an attractive alternative to public-key techniques. Here, the inherent randomness of wireless radio channels is used as a shared entropy source to generate cryptographic key mat

T. Eftekhari, B. Margalit, C. M. B. Omand, E. Berger

We present the largest and deepest late-time radio and millimeter survey to date of superluminous supernovae (SLSNe) and long duration gamma-ray bursts (LGRBs) to search for associated non-thermal synchrotron emission. Using the Karl G. Jansky Very Large Array (VLA) and the Atacama Large Millimeter/submillimeter Array (ALMA), we observed 43 sources at 6 and

Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu

Recent approaches to efficiently ensemble neural networks have shown that strong robustness and uncertainty performance can be achieved with a negligible gain in parameters over the original network. However, these methods still require multiple forward passes for prediction, leading to a significant computational cost. In this work, we show a surprising res

Yin Li, Yueying Ni, Rupert A. C. Croft, Tiziana Di Matteo

Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in Artificial Intelligence (specifically Deep Learning) to address this problem. Neural networks have been developed to learn from high-resolution (HR) image data, and then make accurate super-resolution (SR) versions of differe

Tobias Sutter, Bart P. G. Van Parys, Daniel Kuhn

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be expressed as the minimizer of a surrogate optimization model constructed from the data. The quality of a da

Maria Gabriela Navarro, Dante Minniti, Roberto Capuzzo-Dolcetta, Javier Alonso-Garcia

The projected density distribution of type ab RR Lyrae (RRab) stars was characterised from the innermost regions of the Milky Way to the halo, with the aim of placing constraints on the Galaxys evolution. The compiled sample (N_RRab = 64,850) stems from fundamental mode RR Lyrae variables identified by the VVV, OGLE, and Gaia surveys. The distribution is wel

Ersilia Guarini, Pierluca Carenza, Javier Galan, Maurizio Giannotti

The Sun is a well-studied astrophysical source of axion-like particles (ALPs), produced mainly through the Primakoff process. Moreover, in the Sun there exist large-scale magnetic fields that catalyze an additional ALP production via a coherent conversion of thermal photons. We study this contribution to the solar ALP emissivity, typically neglected in previ

Kenji Yasuda, Xirui Wang, Kenji Watanabe, Takashi Taniguchi

2D ferroelectrics with robust polarization down to atomic thicknesses provide novel building blocks for functional heterostructures. Experimental reports, however, remain scarce because of the requirement of a layered polar crystal. Here, we demonstrate a rational design approach to engineering 2D ferroelectrics from a non-ferroelectric parent compound via e

Carlos Bravo-Prieto

We present the enhanced feature quantum autoencoder, or EF-QAE, a variational quantum algorithm capable of compressing quantum states of different models with higher fidelity. The key idea of the algorithm is to define a parameterized quantum circuit that depends upon adjustable parameters and a feature vector that characterizes such a model. We assess the v

Johannes Aspman, Elias Furrer, Jan Manschot

The space of vacua of many four-dimensional, $\mathcal{N}=2$ supersymmetric gauge theories can famously be identified with a family of complex curves. For gauge group $SU(2)$, this gives a fully explicit description of the low-energy effective theory in terms of an elliptic curve and associated modular fundamental domain. The two-dimensional space of vacua f

Oliver DeWolfe, Kenneth Higginbotham

We discuss how electromagnetically dualizing a 1-form to a 2-form in AdS$_5$ exchanges regular and alternate boundary conditions, and thus gauges the originally global $U(1)$ symmetry in the dual field theory. The generalized symmetry current dual to the 2-form in the bulk is identified as the dual field strength of the gauged $U(1)$, and the associated doub

Andreas Crivellin, Christoph Greub, Dario Müller, Francesco Saturnino

Leptoquarks are hypothetical new particles, which couple quarks directly to leptons. They experienced a renaissance in recent years as they are prime candidates to explain the so-called \textit{flavor anomalies}, i.e. the deviations between the Standard Model predictions and measurements in $b\to s\ell^{+}\ell^{-}$ and $b\to cτν$ processes and in the anomalo

Chao Yin, Andrew Lucas

We present a framework for understanding the dynamics of operator size, and bounding the growth of out-of-time-ordered correlators, in models of large-$S$ spins. Focusing on the dynamics of a single spin, we show the finiteness of the Lyapunov exponent in the large-$S$ limit; our bounds are tighter than the best known Lieb-Robinson-type bounds on these syste

Stefan Meingast, João Alves, Alena Rottensteiner

In this paper, we present a novel view on the morphology and the dynamical state of 10 prominent, nearby ($\leq$ 500 pc), and young ($\sim$30-300 Myr) open star clusters with Gaia DR2: $α\,$Per, Blanco 1, IC 2602, IC 2391, Messier 39, NGC 2451A, NGC 2516, NGC 2547, Platais 9, and the Pleiades. We introduce a pioneering member identification method that is in

Jessica E. Doppel, Laura V. Sales, Julio F. Navarro, Mario G. Abadi

Globular clusters (GCs) are often used to estimate the dark matter content of galaxies, especially dwarfs, where other kinematic tracers are lacking. These estimates typically assume spherical symmetry and dynamical equilibrium, assumptions that may not hold for the sparse GC population of dwarfs in galaxy clusters. We use a catalog of GCs tagged onto the Il

Ioana A. Zelko, Douglas P. Finkbeiner

Spectral distortions of the cosmic microwave background (CMB) are sensitive to energy injection by exotic physics in the early universe. The proposed Primordial Inflation Explorer (PIXIE) mission has the raw sensitivity to provide meaningful limits on new physics, but only if foreground emission can be adequately modeled. We quantify the impact of interstell

Kai Koike

We study the long-time behavior of a point mass moving in a one-dimensional viscous compressible fluid. Previously, we showed that the velocity of the point mass $V(t)$ satisfies a decay estimate $V(t)=O(t^{-3/2})$~[K. Koike, J. Differential Equations \textbf{271} (2021) 356--413]. This result was obtained as a corollary to pointwise estimates of solutions t

Mohammed AlAloul, Mahmoud Rasras

Graphene has emerged as an ultrafast optoelectronic material for on-chip photodetector applications. The 2D nature of graphene enables its facile integration with complementary metal-oxide semiconductor (CMOS) microelectronics and silicon photonics, yet graphene absorbs only $\sim$2.3% of light. Plasmonic metals can enhance the responsivity of graphene photo

Axel Brandenburg, Upasana Das

Radiation transport plays important roles in stellar atmospheres, but the effects of turbulence are being obscured by other effects such as stratification. Using radiative hydrodynamic simulations of forced turbulence, we determine the decay rates of sinusoidal large-scale temperature perturbations of different wavenumbers in the optically thick and thin reg

Sherry Gong, Marco Marengon

We use unoriented versions of instanton and knot Floer homology to prove inequalities involving the Euler characteristic and the number of local maxima appearing in unorientable cobordisms, which mirror results of a recent paper by Juhasz, Miller, and Zemke concerning orientable cobordisms. Most of the subtlety in our argument lies in the fact that maps for

K. Zatrimaylov

We propose a simple geometrical mechanism for the flattening of galactic rotation curves, the local compression of field lines around their planes induced either by the presence of thin string-like objects at the centers of galaxies or by elongated dark-matter halos, and elaborate on its possible role in Nature. We fit 83 rotation curves from the SPARC datab

Amelia Holcomb, Geovandro C. C. F. Pereira, Bhargav Das, Michele Mosca

Hyperledger Fabric is a prominent and flexible solution for building permissioned distributed ledger platforms. Access control and identity management relies on a Membership Service Provider (MSP) whose cryptographic interface only handles standard PKI methods for authentication: RSA and ECDSA classical signatures. Also, MSP-issued credentials may use only o

G. Fanizza, G. Franchini, M. Gasperini, L. Tedesco

We compute the modified friction coefficient controlling the propagation of tensor metric perturbations in the context of a generalized cosmological scenario based on a theory of gravity with quadratic curvature corrections. In such a context we discuss the differences between gravitational and electromagnetic luminosity distance, as well as the differences

Le Xu, Lei Cheng, Ngai Wong, Yik-Chung Wu

Tensor train (TT) decomposition, a powerful tool for analyzing multidimensional data, exhibits superior performance in many machine learning tasks. However, existing methods for TT decomposition either suffer from noise overfitting, or require extensive fine-tuning of the balance between model complexity and representation accuracy. In this paper, a fully Ba

Alexander S. Wein

We study the algorithmic task of finding a large independent set in a sparse Erdős-Rényi random graph with $n$ vertices and average degree $d$. The maximum independent set is known to have size $(2 \log d / d)n$ in the double limit $n \to \infty$ followed by $d \to \infty$, but the best known polynomial-time algorithms can only find an independent set of hal

Jayadev Acharya, Clément L. Canonne, Ziteng Sun, Himanshu Tyagi

We consider distributed parameter estimation using interactive protocols subject to local information constraints such as bandwidth limitations, local differential privacy, and restricted measurements. We provide a unified framework enabling us to derive a variety of (tight) minimax lower bounds for different parametric families of distributions, both contin

Matthew P. Leighton, Laurent Kreplak, Andrew D. Rutenberg

The lysyl oxidase (LOX) enzyme that catalyses cross-link formation during the assembly of collagen fibrils in vivo is too large to diffuse within assembled fibrils, and so is incompatible with a fully equilibrium mechanism for fibril formation. We propose that enzymatic cross-links are formed at the fibril surface during the growth of collagen fibrils; as a

Brandon Bavier, Efstratia Kalfagianni

We consider hyperbolic links that admit alternating projections on surfaces in compact, irreducible 3-manifolds. We show that, under some mild hypotheses, the volume of the complement of such a link is bounded below in terms of a Kauffman bracket function defined on link diagrams on the surface. In the case that the 3-manifold is a thickened surface, this Ka

Michael Heigl, Sabri Koraltan, Marek Vaňatka, Robert Kraft

Skyrmions and antiskyrmions are topologically protected spin structures with opposite topological charge. Particularly in coexisting phases, these two types of magnetic quasi-particles may show fascinating physics and potential for spintronic devices. While skyrmions are observed in a wide range of materials, until now antiskyrmions were exclusive to materia

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $ξ$ be a non-constant real-valued random variable with finite support, and let $M_{n}(ξ)$ denote an $n\times n$ random matrix with entries that are independent copies of $ξ$. For $ξ$ which is not uniform on its support, we show that \begin{align*} \mathbb{P}[M_{n}(ξ)\text{ is singular}] &= \mathbb{P}[\text{zero row or column}] + (1+o_n(1))\mathbb{P}[\tex

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $p \in (0,1/2)$ be fixed, and let $B_n(p)$ be an $n\times n$ random matrix with i.i.d. Bernoulli random variables with mean $p$. We show that for all $t \ge 0$, \[\mathbb{P}[s_n(B_n(p)) \le tn^{-1/2}] \le C_p t + 2n(1-p)^{n} + C_p (1-p-ε_p)^{n},\] where $s_n(B_n(p))$ denotes the least singular value of $B_n(p)$ and $C_p, ε_p > 0$ are constants depending

Christoph Alt, Balint Radics, André Rubbia

We report on an updated sensitivity for proton decay via $p \rightarrow \barν K^+ $ at large, dual phase liquid argon time projection chambers (LAr TPCs). Our work builds on a previous study in which several nucleon decay channels have been simulated and analyzed [arXiv:hep-ph/0701101]. At the time several assumptions were needed to be made on the detector a

Georgios Daskalopoulos, Karen Uhlenbeck

We exhibit the duality between best Lipschitz (infinity harmonic) maps and least gradient maps in the case of maps from surfaces to the circle. We show that given a homotopy class of a map from a surface to the circle the infinity harmonic map defines a geodesic lamination on the surface and the dual least gradient map defines a transverse measure on the lam

Ali Assem Mahmoud, Karen Yeats

In this article we study an asymptotic expansion for $C_n$, the number of connected chord diagrams on $n$ chords. The expansion is obtained in earlier work by means of alien derivatives applied to the generating series of connected chord diagrams; we seek a combinatorial interpretation. The main outcome presented here is a new combinatorial interpretation fo

Ghazi Felhi, Joseph Leroux, Djamé Seddah

Even though Variational Autoencoders (VAEs) are widely used for semi-supervised learning, the reason why they work remains unclear. In fact, the addition of the unsupervised objective is most often vaguely described as a regularization. The strength of this regularization is controlled by down-weighting the objective on the unlabeled part of the training set

ATLAS Collaboration

Several extensions of the Standard Model predict the production of dark matter particles at the LHC. An uncharted signature of dark matter particles produced in association with $VV=W^\pm W^\mp$ or $ZZ$ pairs from a decay of a dark Higgs boson $s$ is searched for using 139 fb$^{-1}$ of $pp$ collisions recorded by the ATLAS detector at a center-of-mass energy

Kosar Abolfath Beigi, Kamran Divaani-Aazar, Massoud Tousi

Let R be a local ring and C a semidualizing module of R. We investigate the behavior of certain classes of generalized Cohen-Macaulay R-modules under the Foxby equivalence between the Auslander and Bass classes with respect to C. In particular, we show that generalized Cohen-Macaulay R-modules are invariant under this equivalence and if M is a finitely gener

Eduardo Godinho Ribeiro, Raul de Queiroz Mendes, Valdir Grassi

In order to explore robotic grasping in unstructured and dynamic environments, this work addresses the visual perception phase involved in the task. This phase involves the processing of visual data to obtain the location of the object to be grasped, its pose and the points at which the robot`s grippers must make contact to ensure a stable grasp. For this, t

Peter Lunts, Antoine Georges, E. Miles Stoudenmire, Matthew Fishman

We numerically solve the Hubbard model on the Bethe lattice with finite coordination number $z=3$, and determine its zero-temperature phase diagram. For this purpose, we introduce and develop the `variational uniform tree state' (VUTS) algorithm, a tensor network algorithm which generalizes the variational uniform matrix product state algorithm to tree t

Miquel Huix-Rotllant, Nicolas Ferré

Electrostatic potential fitting method (ESPF) is a powerful way of defining atomic charges derived from quantum density matrices fitted to reproduce a quantum mechanical charge distribution in the presence of an external electrostatic potential. These can be used in the Hamiltonian to define a robust and efficient electrostatic embedding QM/MM method. The or

A. Imparato

A 1D model of interacting particles moving over a periodic substrate and in a position dependent temperature profile is considered. When the substrate and the temperature profile are spatially asymmetric a center-of-mass velocity develops, corresponding to a directed transport of the chain. This autonomous system can thus transform heath currents into motion

Bin Wang, Yaolin Jiang

Structure-preserving algorithms and algorithms with uniform error bound have constituted two interesting classes of numerical methods. In this paper, we blend these two kinds of methods for solving nonlinear Hamiltonian systems with highly oscillatory solution, and the blended algorithms inherit and respect the advantage of each method. Two kinds of algorith

Yannick Meurice, Ryo Sakai, Judah Unmuth-Yockey

We discuss the successes and limitations of statistical sampling for a sequence of models studied in the context of lattice QCD and emphasize the need for new methods to deal with finite-density and real-time evolution. We show that these lattice models can be reformulated using tensorial methods where the field integrations in the path-integral formalism ar

Javier Rubio-Herrero, Carlos Ortiz Marrero, Wai-Tong Louis Fan

Atmospheric modeling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. With the aid of real-world air quality data collected hourly in different stations

Xinchi Qiu, Titouan Parcollet, Daniel J. Beutel, Taner Topal

Despite impressive results, deep learning-based technologies also raise severe privacy and environmental concerns induced by the training procedure often conducted in data centers. In response, alternatives to centralized training such as Federated Learning (FL) have emerged. Perhaps unexpectedly, FL, in particular, is starting to be deployed at a global sca

Asta Heinesen

We present the luminosity distance series expansion to third order in redshift for a general space-time with no assumption on the metric tensor or the field equations prescribing it. It turns out that the coefficients of this general 'Hubble law' can be expressed in terms of a finite number of physically interpretable multipole coefficients. The mult

Fabio Deelan Cunden, Paolo Facchi, Giuseppe Florio, Giovanni Gramegna

The class of incoherent operations induces a pre-order on the set of quantum pure states, defined by the possibility of converting one state into the other by transformations within the class. We prove that if two $n$-dimensional pure states are chosen independently according to the natural uniform distribution, then the probability that they are comparable

T. Mayer, H. Werner, F. Schmid, R. Diaz-Pardo

The challenge of parasitic bulk doping in Bi-based 3D topological insulator materials is still omnipresent, especially when preparing samples by molecular beam epitaxy (MBE). Here, we present a heterostructure approach for epitaxial BSTS growth. A thin n-type Bi$_2$Se$_3$ (BS) layer is used as an epitaxial and electrostatic seed which drastically improves th

Jiaqi Yang, Wei Hu, Jason D. Lee, Simon S. Du

We study how representation learning can improve the efficiency of bandit problems. We study the setting where we play $T$ linear bandits with dimension $d$ concurrently, and these $T$ bandit tasks share a common $k (\ll d)$ dimensional linear representation. For the finite-action setting, we present a new algorithm which achieves $\widetilde{O}(T\sqrt{kN} +

Clemens Schindler, Denis Gorbunov, Sergei Zherlitsyn, Stanislaw Galeski

In this study, we report on the observation of de Haas-van Alphen-type quantum oscillations (QO) in the ultrasound velocity of NbP as well as `giant QO' in the ultrasound attenuation in pulsed magnetic fields. The difference of the QO amplitude for different acoustic modes reveals a strong anisotropy of the effective deformation potential, which we estim

Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera

Algorithmic fairness is typically studied from the perspective of predictions. Instead, here we investigate fairness from the perspective of recourse actions suggested to individuals to remedy an unfavourable classification. We propose two new fairness criteria at the group and individual level, which -- unlike prior work on equalising the average group-wise

Björn Eichmann, Jörg P. Rachen

The nonthermal source abundances of elements play a crucial role in the understanding of cosmic ray (CR) phenomena from a few GeV up to several tens of EeV. We present a first systematic approach to describe the change of the abundances from the thermal to the nonthermal state via diffusive shock acceleration by a temporally evolving shock. We consider hereb

Kosuke Shibata, Kohji Yanagawa

For a partition $λ$ of $n \in \mathbb{N}$, let $I^{\rm Sp}_λ$ be the ideal of $R=K[x_1,\ldots,x_n]$ generated by all Specht polynomials of shape $λ$. We assume that ${\rm char}(K)=0$. Then $R/I^{\rm Sp}_{(n-2,2)}$ is Gorenstein, and $R/I^{\rm Sp}_{(d,d,1)}$ is a Cohen-Macaulay ring with a linear free resolution. In this paper, we construct minimal free resol

Boya Zhang, Robert B. Gramacy, Leah Johnson, Kenneth A. Rose

Delta smelt is an endangered fish species in the San Francisco estuary that have shown an overall population decline over the past 30 years. Researchers have developed a stochastic, agent-based simulator to virtualize the system, with the goal of understanding the relative contribution of natural and anthropogenic factors suggested as playing a role in their

D. Karakhanyan, R. Kirschner

Exteded Yangian algebras of orthogonal and symplectic types are defined by the Yang-Baxter RLL relation involving the fundamental R-matrix with $so(n)$ or $sp(2m)$ symmetry. We study representations of highest weight characterized by weight function ratios. We consider the algebra relations for the linear and the quadratic evaluations and the resulting condi

Maria Attarian, Brett D. Roads, Michael C. Mozer

Deep-learning vision models have shown intriguing similarities and differences with respect to human vision. We investigate how to bring machine visual representations into better alignment with human representations. Human representations are often inferred from behavioral evidence such as the selection of an image most similar to a query image. We find tha

Jason Kaye, Denis Golež

We propose a method to improve the computational and memory efficiency of numerical solvers for the nonequilibrium Dyson equation in the Keldysh formalism. It is based on the empirical observation that the nonequilibrium Green's functions and self energies arising in many problems of physical interest, discretized as matrices, have low rank off-diagonal bloc

Harbir Antil, Patrick Dondl, Ludwig Striet

Fueled by many applications in random processes, imaging science, geophysics, etc., fractional Laplacians have recently received significant attention. The key driving force behind the success of this operator is its ability to capture non-local effects while enforcing less smoothness on functions. In this paper, we introduce a spectral method to approximate

Jae-Hoon Kwon, Sin-Myung Lee

We introduce a new approach to the study of finite-dimensional representations of the quantum group of the affine Lie superalgebra $\mathrm{L}\mathfrak{gl}_{M|N}=\mathbb{C}[t,t^{-1}]\otimes\mathfrak{gl}_{M|N}$ ($M\neq N$). We explain how the representations of the quantum group of $\mathrm{L}\mathfrak{gl}_{M|N}$ are directly related to those of the quantum a

Simone Marchesi, Jean Vallès

In this paper we characterize the rank two vector bundles on $\mathbb{P}^2$ which are invariant under the actions of the parabolic subgroups $G_p:=\mathrm{Stab}_p(\mathrm{PGL}(3))$ fixing a point in the projective plane, $G_L:=\mathrm{Stab}_L(\mathrm{PGL}(3))$ fixing a line, and when $p\in L$, the Borel subgroup $\mathbf{B} = G_p \cap G_L$ of $\mathrm{PGL}(3

Mpendulo Cele, Sophie Marques

In this paper, we investigate the existence of an elementary abelian closure in characteristic not $2$ for biquadratic extensions. We discover that it exists for any non-cyclic extension. We make use of it to obtain a classification for this class of extensions up to isomorphism via descent. This permits us to describe the geometry of this moduli space in gr

Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr

In order to quickly adapt to new data, few-shot learning aims at learning from few examples, often by using already acquired knowledge. The new data often differs from the previously seen data due to a domain shift, that is, a change of the input-target distribution. While several methods perform well on small domain shifts like new target classes with simil

Samson Abramsky, Nihil Shah

Combinatorial games are widely used in finite model theory, constraint satisfaction, modal logic and concurrency theory to characterize logical equivalences between structures. In particular, Ehrenfeucht-Fraisse games, pebble games, and bisimulation games play a central role. We show how each of these types of games can be described in terms of an indexed fa

Namitha Brijit Bejoy, Nitin. K Singh, Balanarayan Pananghat, G. Naresh Patwari

Photoexcitation of van der Waals complexes can lead to several decay pathways depending on the nature of the potential energy surfaces. Upon excitation of a chromophore in a complex, ionization of its weakly bound neighbour via energy transfer happens via a unique relaxation process known as intermolecular Coulombic decay (ICD); a phenomenon of renewed focus

Xiang Zhang, Kai Wan, Hua Sun, Mingyue Ji

We consider the problem of cache-aided Multiuser Private Information Retrieval (MuPIR) which is an extension of the single-user cache-aided PIR problem to the case of multiple users. In MuPIR, each of the $K_{\rm u}$ cache-equipped users wishes to privately retrieve a message out of $K$ messages from $N$ databases each having access to the entire message lib

Ángel L. Corps, Armando Relaño

We study the spectral statistics of quantum systems with finite Hilbert spaces. We derive a theorem showing that eigenlevels in such systems cannot be globally uncorrelated, even in the case of fully integrable dynamics, as a consequence of the unfolding procedure. We provide an analytic expression for the power spectrum of the $δ_n$ statistic for a model of

Charles Topliff, Morris Cohen, William Bristow

Many systems used by society are extremely vulnerable to space weather events such as solar flares and geomagnetic storms which could potentially cause catastrophic damage. In recent years, many works have emerged to provide early warning to such systems by forecasting these events through some proxy, but these approaches have largely focused on a specific p

Wolter Groenevelt, Erik Koelink

We study a Lax pair in a $2$-parameter Lie algebra in various representations. The overlap coefficients of the eigenfunctions of $L$ and the standard basis are given in terms of orthogonal polynomials and orthogonal functions. Moreover, eigenfunctions for the operator $L$ for a Lax pair for $\mathfrak{sl}(d+1,\mathbb C)$ are studied in certain representation

Ankush Das, Henry DeYoung, Andreia Mordido, Frank Pfenning

Session types statically describe communication protocols between concurrent message-passing processes. Unfortunately, parametric polymorphism even in its restricted prenex form is not fully understood in the context of session types. In this paper, we present the metatheory of session types extended with prenex polymorphism and, as a result, nested recursiv

J. Emmanuel Johnson, Valero Laparra, Maria Piles, Gustau Camps-Valls

Information theory is an excellent framework for analyzing Earth system data because it allows us to characterize uncertainty and redundancy, and is universally interpretable. However, accurately estimating information content is challenging because spatio-temporal data is high-dimensional, heterogeneous and has non-linear characteristics. In this paper, we

Peter J. Haine, Mauro Porta, Jean-Baptiste Teyssier

The purpose of this paper is to explain why the functor that sends a stratified topological space $S$ to the $\infty$-category of constructible (hyper)sheaves on $S$ with coefficients in a large class of presentable $\infty$categories is homotopy-invariant. To do this, we first establish a number of results in the unstratified setting, i.e., the setting of l

Cheng Yu, Bo Wang, Bo Yang, Robby T. Tan

Estimating 3D human poses from a monocular video is still a challenging task. Many existing methods' performance drops when the target person is occluded by other objects, or the motion is too fast/slow relative to the scale and speed of the training data. Moreover, many of these methods are not designed or trained under severe occlusion explicitly, maki

Abu Naser, Cong Wu, Mehran Sadeghi Lahijani, Mohsen Gavahi

The cloud infrastructure must provide security for High-Performance Computing (HPC) applications of sensitive data to execute in such an environment. However, supporting security in the communication infrastructure of today's public cloud is challenging, because current networks for data centers are so fast that adding encryption can incur very significa

Nelson Padilla, Juan Magana, Joaquin Sureda, Ignacio Araya

We study the effect of dark matter (DM) being encapsulated in primordial black holes (PBHs) on the power spectrum of density fluctuations $P(k)$; we also look at its effect on the abundance of haloes and their clustering. We allow the growth of Poisson fluctuations since matter and radiation equality and study both monochromatic and extended PBH mass distrib

Jimmy Lin, Rodrigo Nogueira, Andrew Yates

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in response to a query. Although the most common formulation of text ranking is search, instances of the task can also be found in many natural language processing applications. This survey provides an overview of text ranking with neural network architectures known as t

Ritabrata Dutta, Karim Zouaoui-Boudjeltia, Christos Kotsalos, Alexandre Rousseau

Cardio/cerebrovascular diseases (CVD) have become one of the major health issue in our societies. But recent studies show that the present pathology tests to detect CVD are ineffectual as they do not consider different stages of platelet activation or the molecular dynamics involved in platelet interactions and are incapable to consider inter-individual vari

Jacob Russell, Kate M. Vokes

We prove that any graph of multicurves satisfying certain natural properties is either hyperbolic, relatively hyperbolic, or thick. Further, this geometric characterization is determined by the set of subsurfaces that intersect every vertex of the graph. This extends previously established results for the pants graph and the separating curve graph to a broad

Guy Henniart, Marie-France Vignéras

We investigate the irreducible cuspidal $C$-representations of a reductive $p$-adic group $G$ over a field $C$ of characteristic different from $p$. When $C$ is algebraically closed, for many groups $G$, a list of cuspidal $C$-types $(J,λ)$ has been produced satisfying exhaustion, sometimes for a restricted kind of cuspidal representations, and often unicity

Marios Bounakis, Ian G. Moss, Gerasimos Rigopoulos

We study a Hyperinflation model involving a field doublet on a hyperbolic field-space manifold and an exponential potential, providing a concise treatment of the evolution of the entropic and adiabatic perturbations around the homogeneous hyperbolic attractor solution. We find that the adiabatic spectral index narrows down the admissible values of the potent

Frank Volmer, Inga Seidler, Timo Bisswanger, Jhih-Sian Tu

We discuss how the emission of electrons and ions during electron-beam-induced physical vapor deposition can cause problems in micro- and nanofabrication processes. After giving a short overview of different types of radiation emitted from an electron-beam (e-beam) evaporator and how the amount of radiation depends on different deposition parameters and cond

Abhishek Kumar Jha, Akshay Chatla, Bindu A. Bambah

Two and three flavor oscillating neutrinos are shown to exhibit the properties bipartite and tripartite quantum entanglement. The two and three flavor neutrinos are mapped to qubit states used in quantum information theory. Such quantum bits of the neutrino state can be encoded on a IBMQ computer using quantum computing as a tool. We show the implementation

Golshan Madraki, Isabella Grasso, Jacqueline Otala, Yu Liu

Misinformation/disinformation about COVID-19 has been rampant on social media around the world. In this study, we investigate COVID-19 misinformation/ disinformation on social media in multiple languages - Farsi (Persian), Chinese, and English, about multiple countries - Iran, China, and the United States (US), and on multiple platforms such as Twitter, Face

Sören Christensen, Berenice Anne Neumann, Tobias Sohr

We discuss a class of explicitly solvable mean field type control problems/mean field games with a clear economic interpretation. More precisely, we consider long term average impulse control problems with underlying general one-dimensional diffusion processes motivated by optimal harvesting problems in natural resource management. We extend the classical st

Ray Bai, Veronika Rockova, Edward I. George

High-dimensional data sets have become ubiquitous in the past few decades, often with many more covariates than observations. In the frequentist setting, penalized likelihood methods are the most popular approach for variable selection and estimation in high-dimensional data. In the Bayesian framework, spike-and-slab methods are commonly used as probabilisti

Yann Desmarais, Denis Mottet, Pierre Slangen, Philippe Montesinos

Human pose estimation is a very active research field, stimulated by its important applications in robotics, entertainment or health and sports sciences, among others. Advances in convolutional networks triggered noticeable improvements in 2D pose estimation, leading modern 3D markerless motion capture techniques to an average error per joint of 20 mm. Howev

E. I. Guendelman, E. Zamlung, D. Benisty

A new symmetry for Newtonian Dynamics is analyzed, this corresponds to going to an accelerated frame, which introduces a constant gravitational field into the system and subsequently. We consider the addition of a linear contribution to the gravitational potential \(ϕ\) which can be used to cancel the gravitational field induced by going to the accelerated f

Dan John Velasco

Low-resource languages such as Filipino suffer from data scarcity which makes it challenging to develop NLP applications for Filipino language. The use of Transfer Learning (TL) techniques alleviates this problem in low-resource setting. In recent years, transformer-based models are proven to be effective in low-resource tasks but faces challenges in accessi

Vivek S. Borkar, D. Manjunath

The non-population conserving SIR (SIR-NC) model to describe the spread of infections in a community is proposed and studied. Unlike the standard SIR model, SIR-NC does not assume population conservation. Although similar in form to the standard SIR, SIR-NC admits a closed form solution while allowing us to model mortality, and also provides different, and a

Francois De Saint Moulin, Charles Wiame, Claude Oestges, Luc Vandendorpe

We consider a relay network based on Unmanned Aerial Vehicles (UAV). Terrestrial Base Stations (TBS) and UAV Relay Nodes (RN) are modelled using two Homogeneous Poisson Point Processes (HPPP). UAVs can hover at a fixed position or move following specific displacement schemes. The Coverage Probability (CP) of a typical user equipment (UE) is derived, either w

Carlos Henrique de Lima, Ben Keeshan, Heather E. Logan, Yue Zhang

We study the experimental constraints on dark sector CP violation that enters the visible sector through a Higgs portal coupling $H^{\dagger} H Z^{\prime}_{μν} \widetilde Z^{\prime μν}$, where the $Z^{\prime}$ is from a new U(1) gauge symmetry which is assumed to couple to lepton number. We compute explicitly the leading two-loop contribution of this effecti

Johann Brehmer, Kyle Cranmer

Our predictions for particle physics processes are realized in a chain of complex simulators. They allow us to generate high-fidelity simulated data, but they are not well-suited for inference on the theory parameters with observed data. We explain why the likelihood function of high-dimensional LHC data cannot be explicitly evaluated, why this matters for d

Konstantinos Deligiannis, Davide Squizzato, Anna Minguzzi, Léonie Canet

Exciton-polariton condensates under driven-dissipative conditions are predicted to belong to the Kardar-Parisi-Zhang (KPZ) universality class, the dynamics of the condensate phase satisfying the same equation as for classical stochastic interface growth at long distance. We show that by engineering an external confinement for one-dimensional polaritons we ca

Paul-Henry Leemann

We prove that every connected locally finite regular graph has a double cover which is isomorphic to a Schreier graph.