May 2022 arXiv papers — page 77

V. K. Oikonomou, Ifigeneia Giannakoudi

In this work we shall study the late-time dynamics of several $F(R)$ gravity models. By appropriately expressing the field equations in terms of the redshift and of a statefinder function, we shall solve numerically the field equations using appropriate physical motivated initial conditions. We consider models which, by construction, are described by a nearl

Mostafa Karimi, Changliang Liu, Kenichi Kumatani, Yao Qian

Self-supervised learning (SSL) methods have proven to be very successful in automatic speech recognition (ASR). These great improvements have been reported mostly based on highly curated datasets such as LibriSpeech for non-streaming End-to-End ASR models. However, the pivotal characteristics of SSL is to be utilized for any untranscribed audio data. In this

Salvatore Bottaro, Marco Costa, Oleg Popov

The goal of this work is to find the simplest UV completions of Accidental Composite Dark Matter models that can dynamically generate an asymmetry for the Dark Matter candidate, the lightest dark baryon, and simultaneously annihilate the symmetric component. In this framework Dark Matter is an accidentally stable bound state of a confining $\mathrm{SU}(N)$ g

Aditya Ghosh, Kobi Kremnizer, S. Waleed Noor, Charles F. Santos

In this article, we introduce a general approach for deriving zero-free half-planes for the Riemann zeta function $\zeta$ by identifying topological vector spaces of analytic functions with specific properties. This approach is applied to weighted $\ell^2$ spaces and classical Hardy spaces $ H^p $ ($ 0<p\leq2 $). As a consequence precise conditions are obtai

Eliezer Batista, William Hautekiet, Joost Vercruysse

We show that the category of partial comodules over a Hopf algebra $H$ is comonadic over ${\sf Vect}_k$ and provide an explicit construction of this comonad using topological vector spaces. The case when $H$ is finite dimensional is treated in detail. A study of partial representations of linear algebraic groups is initiated; we show that a connected linear

Monu Verma, Santosh Kumar Vipparthi

Inspired from the assets of handcrafted and deep learning approaches, we proposed a RARITYNet: RARITY guided affective emotion learning framework to learn the appearance features and identify the emotion class of facial expressions. The RARITYNet framework is designed by combining the shallow (RARITY) and deep (AffEmoNet) features to recognize the facial exp

Manuel Carlan, Thomas Kneib

We propose a novel Bayesian model framework for discrete ordinal and count data based on conditional transformations of the responses. The conditional transformation function is estimated from the data in conjunction with an a priori chosen reference distribution. For count responses, the resulting transformation model is novel in the sense that it is a Baye

Nikolay Kuznetsov

The "potato kugel" theorem of Aharonov, Schiffer and Zalcman, which concerns an inverse property of harmonic functions, is extended to the settings of the modified Helmholtz and Helmholtz equations that describe nuclear forces and acoustic waves respectively.

Shuoyang Wang, Guanqun Cao, Zuofeng Shang

We propose a new approach, called as functional deep neural network (FDNN), for classifying multi-dimensional functional data. Specifically, a deep neural network is trained based on the principle components of the training data which shall be used to predict the class label of a future data function. Unlike the popular functional discriminant analysis appro

Marcelo Ferreira da Silva, Carlos A. S. Silva

A new kind of duality has been proposed by Carr related to the quantum description of black holes, the so-called Compton/Schwarzschild duality \cite{Carr:2015nqa}. In this context, a new form for a Generalized Uncertainty Principle has arisen, which must bring us an interesting new route to a quantum description of spacetime. In the present paper, we shall i

Jacek Dziarmaga, Marek M. Rams

Linear quench of the transverse field drives the quantum Ising chain across a quantum critical point from the paramagnetic to the ferromagnetic phase. We focus on normal and anomalous quadratic correlators between fermionic kink creation and annihilation operators. They depend not only on the Kibble-Zurek (KZ) correlation length but also on a dephasing lengt

Toshiaki Koike-Akino, Pu Wang, Ye Wang

Beyond data communications, commercial-off-the-shelf Wi-Fi devices can be used to monitor human activities, track device locomotion, and sense the ambient environment. In particular, spatial beam attributes that are inherently available in the 60-GHz IEEE 802.11ad/ay standards have shown to be effective in terms of overhead and channel measurement granularit

Md Ferdous Pervej, Jianlin Guo, Kyeong Jin Kim, Kieran Parsons

While privacy concerns entice connected and automated vehicles to incorporate on-board federated learning (FL) solutions, an integrated vehicle-to-everything communication with heterogeneous computation power aware learning platform is urgently necessary to make it a reality. Motivated by this, we propose a novel mobility, communication and computation aware

Wei Huang, Xingyu Zhao, Alec Banks, Victoria Cox

Deep Learning (DL) is increasingly used in safety-critical applications, raising concerns about its reliability. DL suffers from a well-known problem of lacking robustness, especially when faced with adversarial perturbations known as Adversarial Examples (AEs). Despite recent efforts to detect AEs using advanced attack and testing methods, these approaches

Jing Wang, Jiahui Zou, HaiYing Wang

Faced with massive data, subsampling is a commonly used technique to improve computational efficiency, and using nonuniform subsampling probabilities is an effective approach to improve estimation efficiency. For computational efficiency, subsampling is often implemented with replacement or through Poisson subsampling. However, no rigorous investigation has

Abdulaziz Al-Meer, Saif Al-Kuwari

Physical Unclonable Function (PUF) has recently attracted interested from both industry and academia as a potential alternative approach to secure Internet of Things (IoT) devices from the more traditional computational based approach using conventional cryptography. PUF is promising solution for lightweight security, where the manufacturing fluctuation proc

Kirby Nielsen, Luca Rigotti

We elicit incomplete preferences over monetary gambles with subjective uncertainty. Subjects rank gambles, and these rankings are used to estimate preferences; payments are based on estimated preferences. About 40\% of subjects express incompleteness, but they do so infrequently. Incompleteness is similar for individuals with precise and imprecise beliefs, a

Apurva Patil, Takashi Tanaka

We present an analytical method to estimate the continuous-time collision probability of motion plans for autonomous agents with linear controlled Ito dynamics. Motion plans generated by planning algorithms cannot be perfectly executed by autonomous agents in reality due to the inherent uncertainties in the real world. Estimating end-to-end risk is crucial t

CMS Collaboration

An inclusive search for long-lived exotic particles decaying to a pair of muons is presented. The search uses data collected by the CMS experiment at the CERN LHC in proton-proton collisions at $\sqrt{s}$ = 13 TeV in 2016 and 2018 and corresponding to an integrated luminosity of 97.6 fb$^{-1}$. The experimental signature is a pair of oppositely charged muons

Francesco Devoti, Placido Mursia, Vincenzo Sciancalepore, Xavier Costa-Perez

Aerial communication is gradually taking an assertive role within common societal behaviors by means of unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and fixed-wing aircrafts (FWAs). Such devices can assist general operations in a diverse set of heterogeneous applications, such as video-surveillance, remote delivery and connectivity provis

H. Wakeling, S. A. De La Motte, M. Barrett, E. Prencipe

These proceedings accompany the Belle II talk in the Science in Society parallel session delivered during Lepton Photon 2021. In this talk we present updated membership statistics using 10 years of data with a diversity and inclusion lens, and we present Belle II's most recent activities to aid and improve diversity and inclusion. This report has the intenti

P. Buttà, B. Goddard, T. M. Hodgson, M. Ottobre

We consider interacting particle dynamics with Vicsek type interactions, and their macroscopic PDE limit, in the non-mean-field regime; that is, we consider the case in which each particle/agent in the system interacts only with a prescribed subset of the particles in the system (for example, those within a certain distance). In this non-mean-field regime th

Guowei Wu, Shipei Liu, Xiaoya Fan

Symbolic Music Generation relies on the contextual representation capabilities of the generative model, where the most prevalent approach is the Transformer-based model. The learning of musical context is also related to the structural elements in music, i.e. intro, verse, and chorus, which are currently overlooked by the research community. In this paper, w

Simone Giacomelli, Marina Moleti, Raffaele Savelli

D3 branes in the vicinity of an E6, E7, or E8 stack of 7-branes in flat space are known to host at low energy a famous class of strongly-coupled N = 2 superconformal field theories featuring exceptional global symmetry. What if, instead, the 7-branes wrap an orbifold? We give a systematic characterization of such theories in the case of C2/Zn, and determine

Salil Koner, Ana-Maria Staicu, Arnab Maity

Wearable devices for continuous monitoring of electronic health increased attention due to their richness in information. Often, inference is drawn from features that quantify some summary of the data, leading to a loss of information that could be useful when one utilizes the functional nature of the response. When functional trajectories are observed repea

Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang

The collection and curation of large-scale medical datasets from multiple institutions is essential for training accurate deep learning models, but privacy concerns often hinder data sharing. Federated learning (FL) is a promising solution that enables privacy-preserving collaborative learning among different institutions, but it generally suffers from perfo

Luisa F. Higueras-Montaño, Natalia Jonard-Pérez

Denote by $\mathcal{K}_0^n$ the family of all closed convex sets $A\subset\mathbb{R}^n$ containing the origin $0\in\mathbb R^n$. For $A\in\mathcal{K}_0^n,$ its polar set is denoted by $A^\circ.$ In this paper, we investigate the topological nature of the polar mapping $A\to A^\circ$ on $(\mathcal{K}_0^n, d_{AW})$, where $d_{AW}$ denotes the Attouch-Wets metr

Thomas A. Callister, Simona J. Miller, Katerina Chatziioannou, Will M. Farr

The spin properties of merging black holes observed with gravitational waves can offer novel information about the origin of these systems. The magnitude and orientations of black hole spins offer a record of binaries' evolutionary history, encoding information about massive stellar evolution and the astrophysical environments in which binary black holes are

Sam Hughes, Patrick S. Nairne, Davide Spriano

We characterise hyperbolic groups in terms of quasigeodesics in the Cayley graph forming regular languages. We also obtain a quantitative characterisation of hyperbolicity of geodesic metric spaces by the non-existence of certain local (3,0)-quasigeodesic loops. As an application we make progress towards a question of Shapiro regarding groups admitting a uni

Joaquín Arias, Seppo Törmä, Manuel Carro, Gopal Gupta

Building Information Modeling (BIM) produces three-dimensional models of buildings combining the geometrical information with a wide range of properties. BIM is slowly but inevitably revolutionizing the architecture, engineering, and construction (AEC) industry. Buildings need to be compliant with regulations about stability, safety, and environmental impact

Alessio Mei, Biswajit Banerjee, Gor Oganesyan, Om Sharan Salafia

An energetic $\rm \gamma$-ray burst (GRB), GRB 211211A, was observed on 2021 December 11 by the Neil Gehrels Swift Observatory. Despite its long duration, typically associated with bursts produced by the collapse of massive stars, the discovery of an optical-infrared kilonova and a quasi-periodic oscillation during a gamma-ray precursor points to a compact o

Zobeir Raisi, John Zelek

Signage is everywhere and a robot should be able to take advantage of signs to help it localize (including Visual Place Recognition (VPR)) and map. Robust text detection & recognition in the wild is challenging due to such factors as pose, irregular text, illumination, and occlusion. We propose an end-to-end scene text spotting model that simultaneously outp

Songling Shan

Let $G$ be a simple graph with maximum degree $\Delta(G)$. A subgraph $H$ of $G$ is overfull if $|E(H)|>\Delta(G)\lfloor \frac{1}{2}|V(H)| \rfloor$. Chetwynd and Hilton in 1986 conjectured that a graph $G$ with $\Delta(G)>\frac{1}{3}|V(G)|$ has chromatic index $\Delta(G)$ if and only if $G$ contains no overfull subgraph. Let $0<\varepsilon <1$ and $G$ be a l

Hennadii Yerzhakov, Roni Ilan, Efrat Shimshoni, Jonathan Ruhman

Topological superconductors are predicted to exhibit outstanding phenomena, including non-abelian anyon excitations, heat-carrying edge states, and topological nodes in the Bogoliubov spectra. Nonetheless, and despite major experimental efforts, we are still lacking unambiguous signatures of such exotic phenomena. In this context, the recent discovery of coe

Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

We study repeated two-player games where one of the players, the learner, employs a no-regret learning strategy, while the other, the optimizer, is a rational utility maximizer. We consider general Bayesian games, where the payoffs of both the optimizer and the learner could depend on the type, which is drawn from a publicly known distribution, but revealed

Hari Hara Suthan Chittoor, Osvaldo Simeone

Quantum networking relies on the management and exploitation of entanglement. Practical sources of entangled qubits are imperfect, producing mixed quantum state with reduced fidelity with respect to ideal Bell pairs. Therefore, an important primitive for quantum networking is entanglement distillation, whose goal is to enhance the fidelity of entangled qubit

E. A. Meier Valdés, B. M. Morris, R. D. Wells, N. Schanche

55 Cnc e is in a 0.73 day orbit transiting a Sun-like star. It has been observed that the occultation depth of this Super-Earth, with a mass of 8$M_{\bigoplus}$ and radius of 2$R_{\bigoplus}$, changes significantly over time at mid-infrared wavelengths. Observations with Spitzer measured a change in its day-side brightness temperature of 1200 K, possibly dri

Michael O. Ogunbunmi, Svilen Bobev

Ca$_{10}$GdCdSb$_9$ is a new Zintl phase with a large unit cell volume (~2500 {\AA}3) and a very complex, disordered structure, which can drive the realization of ultralow thermal conductivity in this material. The measured Seebeck coefficient, $\alpha$, for single-crystalline Ca$_{10}$GdCdSb$_9$ approaches 350 $\mu$V/K at 600 K. The experimentally determine

J. L. Wise, N. Roubinowitz, W. Belzig, D. M. Basko

Radiative heat transfer between bodies is often dominated by a narrow resonance in the transmission, e.~g. due to a cavity mode or a surface excitation. However, this resonant character is not visible in the average heat current. Here, we show that the noise spectrum of heat current can serve as a direct probe of the heat-carrying excitations. Namely, the re

M. A. Gómez-Muñoz, L. Sabin, R. Raddi, R. D. Wells

White dwarf (WD) stars are often associated with the central stars of planetary nebulae (CSPNe) on their way to the cooling track. A large number of WD star candidates have been identified thanks to optical large-scale surveys such as Gaia DR2 and EDR3. However, hot-WD/CSPNe stars are quite elusive in optical bands due to their high temperatures and low opti

Parker C. Lusk, Jonathan P. How

Using pole and plane objects in lidar SLAM can increase accuracy and decrease map storage requirements compared to commonly-used point cloud maps. However, place recognition and geometric verification using these landmarks is challenging due to the requirement for global matching without an initial guess. Existing works typically only leverage either pole or

Jose Luis Rosales, Francisco Castejon

Based on the theorized possibilities of resonant ion confinement, for a Deuteron cloud in a Penning-Malmberg trap with a specially configured rotating wall, the opportunity to design a new type of fusion device is prospected. It is proven that, for some trap configurations, nuclear fusion reactions should take place and, in that case, Lawson's criterion for

Joe Caroselli, Arun Narayanan, Yiteng Huang

One of the most challenging scenarios for smart speakers is multi-talker, when target speech from the desired speaker is mixed with interfering speech from one or more speakers. A smart assistant needs to determine which voice to recognize and which to ignore and it needs to do so in a streaming, low-latency manner. This work presents two multi-microphone sp

Rongmon Bordoloi, John M. O'Meara, Keren Sharon, Jane R. Rigby

Reservoirs of dense atomic gas (primarily hydrogen), contain approximately 90 percent of the neutral gas at a redshift of 3, and contribute to 2-3 percent of the total baryons in the Universe. These damped Lyman-${\alpha}$ systems (so called because they absorb Lyman-${\alpha}$ photons from within and from background sources) have been studied for decades, b

Huajie Cheng, Wen Han Chiu, Yaquan Fang, Yu Gao

The Circular Electron Positron Collider (CEPC) is a large-scale collider facility that can serve as a factory of the Higgs, Z, and W bosons and is upgradable to run at the ttbar threshold. This document describes the latest CEPC nominal operation scenario and particle yields and updates the corresponding physics potential. A new detector concept is also brie

Pieter van Dokkum, Zili Shen, Michael A. Keim, Sebastian Trujillo-Gomez

The ultra-diffuse galaxies DF2 and DF4 in the NGC1052 group share several unusual properties: they both have large sizes, rich populations of overluminous and large globular clusters, and very low velocity dispersions indicating little or no dark matter. It has been suggested that these galaxies were formed in the aftermath of high velocity encounters of gas

Francesco Serra, Javi Serra, Enrico Trincherini, Leonardo G. Trombetta

We derive causality constraints on the simplest scalar-tensor theories in which black holes differ from what General Relativity predicts, a scalar coupled to the Gauss-Bonnet or the Chern-Simons terms. Demanding that time advances are unobservable within the regime of validity of these effective field theories, we find their cutoff must be parametrically of

Laura Sberna, Stanislav Babak, Sylvain Marsat, Andrea Caputo

Binaries of relatively massive black holes like GW190521 have been proposed to form in dense gas environments, such as the disks of Active Galactic Nuclei (AGNs), and they might be associated with transient electromagnetic counterparts. The interactions of this putative environment with the binary could leave a significant imprint at the low gravitational wa

Michael Zevin, Daniel E. Holz

The population of binary black hole mergers identified through gravitational waves has uncovered unexpected features in the intrinsic properties of black holes in the universe. One particularly surprising and exciting result is the possible existence of black holes in the pair-instability mass gap, $\sim50-120~M_\odot$. Dense stellar environments can populat

Quang H. Tran, Taylor J. Hoyt, Wendy L. Freedman, Barry F. Madore

We determine the distance to the Sculptor Dwarf Spheroidal via three Population II stellar distance indicators: (a) the Tip of the Red Giant Branch (TRGB), (b) RR Lyrae variables (RRLs), and (c) the ridgeline of the blue horizontal branch (HB). High signal-to-noise, wide-field $VI$ imaging that covers an area $48' \times 48'$ and reaches a photometric depth

Emanuele Berti, Vitor Cardoso, Mark Ho-Yeuk Cheung, Francesco Di Filippo

Black hole spectroscopy with gravitational waves is an important tool to measure the mass and spin of astrophysical black holes and to test their Kerr nature. Next-generation ground- and space-based detectors will observe binary black hole mergers with large signal-to-noise ratios and perform spectroscopy routinely. It was recently shown that small perturbat

Lucas Tendick, Martin Kliesch, Hermann Kampermann, Dagmar Bruß

The advantage that quantum systems provide for certain quantum information processing tasks over their classical counterparts can be quantified within the general framework of resource theories. Certain distance functions between quantum states have successfully been used to quantify resources like entanglement and coherence. Perhaps surprisingly, such a dis

Peizhi Mai, Edwin W. Huang, Jiachen Yu, Benjamin E. Feldman

Motivated by recent experimental work on moir\'e systems in a strong magnetic field, we compute the compressibility as well as the spin correlations and Hofstadter spectrum of spinful electrons on a honeycomb lattice with Hubbard interactions using the determinantal quantum Monte Carlo method. While the interactions in general preserve quantum and anomalous

Pedro De La Torre Luque, Ottavio Fornieri, Tim Linden

TeV halos are regions of enhanced photon emissivity surrounding pulsars. While multiple sources have been discovered, a self-consistent explanation of their radial profile and spherically-symmetric morphology remains elusive due to the difficulty in confining high-energy electrons and positrons within ~20 pc regions of the interstellar medium. One proposed s

Jasleen Matharu, Casey Papovich, Raymond C. Simons, Ivelina Momcheva

Using spatially resolved H-alpha emission line maps of star-forming galaxies, we study the evolution of gradients in galaxy assembly over a wide range in redshift ($0.5<z<1.7$). Our $z\sim0.5$ measurements come from deep Hubble Space Telescope WFC3 G102 grism spectroscopy obtained as part of the CANDELS Lyman-alpha Emission at Reionization (CLEAR) Experiment

Hansveer Singh, Romain Vasseur, Sarang Gopalakrishnan

We introduce and explore an interacting integrable cellular automaton, the Fredkin staircase, that lies outside the existing classification of such automata, and has a structure that seems to lie beyond that of any existing Bethe-solvable model. The Fredkin staircase has two families of ballistically propagating quasiparticles, each with infinitely many spec

Lukas Homeier, Annabelle Bohrdt, Simon Linsel, Eugene Demler

Gauge fields coupled to dynamical matter are ubiquitous in many disciplines of physics, ranging from particle to condensed matter physics, but their implementation in large-scale quantum simulators remains challenging. Here we propose a realistic scheme for Rydberg atom array experiments in which a $\mathbb{Z}_2$ gauge structure with dynamical charges emerge

David B. Massey

We consider a homogeneous polynomial of degree equal to a prime power and examine the cohomology of the Milnor fiber.

Nirat Saini, Khoi Pham, Abhinav Shrivastava

We study the problem of compositional zero-shot learning for object-attribute recognition. Prior works use visual features extracted with a backbone network, pre-trained for object classification and thus do not capture the subtly distinct features associated with attributes. To overcome this challenge, these studies employ supervision from the linguistic sp

Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai

3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technology to a larger audience, we propose AvatarCLIP, a zero-shot text-driven framework for 3D avatar generation and animation. Unlike professional software that requires expert knowledge

Zhe Chen, Yuchen Duan, Wenhai Wang, Junjun He

This work investigates a simple yet powerful dense prediction task adapter for Vision Transformer (ViT). Unlike recently advanced variants that incorporate vision-specific inductive biases into their architectures, the plain ViT suffers inferior performance on dense predictions due to weak prior assumptions. To address this issue, we propose the ViT-Adapter,

Daniel Licht, Cynthia Gao, Janice Lam, Francisco Guzman

Obtaining meaningful quality scores for machine translation systems through human evaluation remains a challenge given the high variability between human evaluators, partly due to subjective expectations for translation quality for different language pairs. We propose a new metric called XSTS that is more focused on semantic equivalence and a cross-lingual c

Gautam Kamath, Argyris Mouzakis, Vikrant Singhal

We prove new lower bounds for statistical estimation tasks under the constraint of $(\varepsilon, \delta)$-differential privacy. First, we provide tight lower bounds for private covariance estimation of Gaussian distributions. We show that estimating the covariance matrix in Frobenius norm requires $\Omega(d^2)$ samples, and in spectral norm requires $\Omega

Chi-Fong Wong, Yang Chen

We propose a type of hybrid Seesaw model that combines Type-1 and Type-2 Seesaw mechanism in multiplicative way to generate tree level Majorana neutrino mass and provides a Dark Matter candidate. The model extends the Standard Model by extra gauge symmetry $U(1)_{D}$ and hidden sector consisted of chiral fermions and additional scalar fields. After spontaneo

Lucas K. Johnson, Michael J. Mahoney, Eddie Bevilacqua, Stephen V. Stehman

Estimating forest AGB at large scales and fine spatial resolutions has become increasingly important for greenhouse gas accounting, monitoring, and verification efforts to mitigate climate change. Airborne LiDAR is highly valuable for modeling attributes of forest structure including AGB, yet most LiDAR collections take place at local or regional scales cove

Haoqian Zhang, Louis-Henri Merino, Ziyan Qu, Mahsa Bastankhah

Front-running attacks, which benefit from advanced knowledge of pending transactions, have proliferated in the blockchain space since the emergence of decentralized finance. Front-running causes devastating losses to honest participants and continues to endanger the fairness of the ecosystem. We present Flash Freezing Flash Boys (F3B), a blockchain architect

Andrés F. López-Lopera, François Bachoc, Olivier Roustant

We introduce an additive Gaussian process framework accounting for monotonicity constraints and scalable to high dimensions. Our contributions are threefold. First, we show that our framework enables to satisfy the constraints everywhere in the input space. We also show that more general componentwise linear inequality constraints can be handled similarly, s

Tomas Cerny, Davide Taibi

Microservices fuel cloud-native systems with small service sets developed and deployed independently. The independent nature of this modular architecture also leads to challenges and gaps. The intended system design might deviate far from what is eventually produced and maintained as the architecture tends to degrade over time. This paper challenges the audi

T. V. Anoop, Ujjal Das

For $ p \in (1,N)$ and a domain $\Omega$ in $\mathbb{R}^N$, we study the following quasi-linear problem involving the critical growth: \begin{eqnarray*} -\Delta_p u - \mu g|u|^{p-2}u = |u|^{p^{*}-2}u \ \mbox{ in } \mathcal{D}_p(\Omega), \end{eqnarray*} where $\Delta_p$ is the $p$-Laplace operator defined as $\Delta_p(u) = \text{div}(|\nabla u|^{p-2} \nabla u

Fangyin Wei, Rohan Chabra, Lingni Ma, Christoph Lassner

Learning geometry, motion, and appearance priors of object classes is important for the solution of a large variety of computer vision problems. While the majority of approaches has focused on static objects, dynamic objects, especially with controllable articulation, are less explored. We propose a novel approach for learning a representation of the geometr

Nyasha Masamba, Kerstin Eder, Tim Blackmore

Constrained random test generation is one of the most widely adopted methods for generating stimuli for simulation-based verification. Randomness leads to test diversity, but tests tend to repeatedly exercise the same design logic. Constraints are written (typically manually) to bias random tests towards interesting, hard-to-reach, and yet-untested logic. Ho

Tom J. G. Wilson, S. Matt, T. J. Harries, G. J. Herczeg

Radiative transfer modelling offers a powerful tool for understanding the enigmatic hydrogen emission lines from T Tauri stars. This work compares optical and near-IR spectroscopy of 29 T Tauri stars with our grid of synthetic line profiles. The archival spectra, obtained with VLT's X-Shooter, provide simultaneous coverage of many optical and infrared hydrog

A. J. Parameswaran, Amith Shastri K

We give criteria for the Jacobian of a singular curve $X$ with at most ordinary $n$-point singularities to be anti-affine. In particular, for the case of curves with single ordinary double point we exhibit a relation with torsion divisors. If the geometric genus of the singular curve is atleast 3 and the normalization is non-hyperelliptic and non-bielliptic,

Michael Rudow, K. V. Rashmi

Real-time streaming communication requires a high quality of service despite contending with packet loss. Streaming codes are a class of codes best suited for this setting. A key challenge for streaming codes is that they operate in an "online" setting in which the amount of data to be transmitted varies over time and is not known in advance. Mitigating the

Samuel L. Krushkal

A. Grinshpan posed a deep conjecture on the norm of the Grunsky operator generated by univalent functions in the disk. It gives a quantitative answer in terms of the Grunsky coefficients, to which extent a univalent function determines the bound of dilatations of its quasiconformal extensions. We provide the proof of this conjecture and its various analytic,

Sourbh Bhadane, Aaron B. Wagner, Johannes Ballé

Artificial Neural-Network-based (ANN-based) lossy compressors have recently obtained striking results on several sources. Their success may be ascribed to an ability to identify the structure of low-dimensional manifolds in high-dimensional ambient spaces. Indeed, prior work has shown that ANN-based compressors can achieve the optimal entropy-distortion curv

Sabarnya Mitra, Prasad Hegde, Christian Schmidt

Taylor expansion of the thermodynamic potential in powers of the (baryo)chemical potential $\mu_B$ is a well-known method to bypass the Sign Problem of Lattice QCD. Due to the difficulty in calculating the higher order Taylor coefficients, various alternative expansion schemes as well as resummation techniques have been suggested to extend the Taylor series

Lukáš Polcar, Georgios Lukes-Gerakopoulos, Vojtěch Witzany

Inspirals of stellar-mass compact objects into massive black holes, known as extreme mass ratio inspirals (EMRIs), are one of the key targets for upcoming space-based gravitational-wave detectors. In this paper we take the first steps needed to systematically incorporate the effect of external gravitating matter on EMRIs. We model the inspiral as taking plac

Honglin Chen, Rahul Venkatesh, Yoni Friedman, Jiajun Wu

Self-supervised, category-agnostic segmentation of real-world images is a challenging open problem in computer vision. Here, we show how to learn static grouping priors from motion self-supervision by building on the cognitive science concept of a Spelke Object: a set of physical stuff that moves together. We introduce the Excitatory-Inhibitory Segment Extra

Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao

Federated learning allows distributed users to collaboratively train a model while keeping each user's data private. Recently, a growing body of work has demonstrated that an eavesdropping attacker can effectively recover image data from gradients transmitted during federated learning. However, little progress has been made in recovering text data. In this p

Peter T. H. Pang, Tim Dietrich, Michael W. Coughlin, Mattia Bulla

The multi-messenger detection of the gravitational-wave signal GW170817, the corresponding kilonova AT2017gfo and the short gamma-ray burst GRB170817A, as well as the observed afterglow has delivered a scientific breakthrough. For an accurate interpretation of all these different messengers, one requires robust theoretical models that describe the emitted gr

Sunil Pai, Taewon Park, Marshall Ball, Bogdan Penkovsky

As blockchain technology and cryptocurrency become increasingly mainstream, ever-increasing energy costs required to maintain the computational power running these decentralized platforms create a market for more energy-efficient hardware. Photonic cryptographic hash functions, which use photonic integrated circuits to accelerate computation, promise energy

Yuchen Ding

In this note, we disprove two Romanov type conjectures posed by Chen.

Priyanka Kaswan, Sennur Ulukus

We consider a fully connected network consisting of a source that maintains the current version of a file, $n$ nodes that use asynchronous gossip mechanisms to disseminate fresh information in the network, and an adversary who infects the packets at a target node through data timestamp manipulation, with the intent to replace circulation of fresh packets wit

Kei Kobayashi, Hyunchul Park

We study the large-time and small-time asymptotic behaviors of the spectral heat content for time-changed stable processes, where the time change belongs to a large class of inverse subordinators. For the large-time behavior, the spectral heat content decays polynomially with the decay rate determined by the Laplace exponent of the underlying subordinator, w

Max Bain, Arsha Nagrani, Gül Varol, Andrew Zisserman

Our goal in this paper is the adaptation of image-text models for long video retrieval. Recent works have demonstrated state-of-the-art performance in video retrieval by adopting CLIP, effectively hitchhiking on the image-text representation for video tasks. However, there has been limited success in learning temporal aggregation that outperform mean-pooling

Minoru Hirose

Gangl, Kaneko, and Zagier gave explicit linear relations among double zeta values of odd indices coming from the period polynomials of modular forms for ${\rm SL}(2,\mathbb{Z})$. In this paper, we generalize their result to the linear relations among colored double zeta values of level $N$ coming from the modular forms for level $N$ congruence subgroups.

Peter Bubenik, Iryna Hartsock

Motivated by persistent homology and topological data analysis, we consider formal sums on a metric space with a distinguished subset. These formal sums, which we call persistence diagrams, have a canonical 1-parameter family of metrics called Wasserstein distances. We study the topological and metric properties of these spaces. Some of our results are new e

Dipankar Barman, Subhajit Barman, Bibhas Ranjan Majhi

Entanglement harvesting from the quantum field is a well-known fact that, in recent times, is being rigorously investigated further in flat and different curved backgrounds. The usually understood formulation studies the possibility of two uncorrelated Unruh-DeWitt detectors getting entangled over time due to the effects of quantum vacuum fluctuations. Our c

Cormac O'Sullivan

Ramanujan's approximation to the exponential function is reexamined with the help of Perron's saddle-point method. This allows for a wide generalization that includes the results of Buckholtz, and where all the asymptotic expansion coefficients may be given in closed form. Ramanujan's approximation to the exponential integral is treated similarly.

Gokhan Alkac, Mehmet Kemal Gumus, Mehmet Ali Olpak

The double copy of the Coulomb solution in three dimensions is a non-vacuum solution that can be obtained through different matter couplings. It is the static black hole solution of Einstein-Maxwell theory or general relativity minimally coupled to a free scalar field (with one ghost sign in the action in both cases). We consider generalizations of these mat

Iurii Demidov, Dick Carrillo Melgarejo, Antti Pinomaa, Liana Ault

This chapter summarizes the results obtained from a test bed, which is composed of a microgrid and a wireless network, both relying on real and practical premises. This test bed aims to evaluate application protocols considered in the transport layer of the standard IEC-61850. The application is a data gathering system, where IEC-61850 messages are transmitt

Sunil Pai, Zhanghao Sun, Tyler W. Hughes, Taewon Park

Neural networks are widely deployed models across many scientific disciplines and commercial endeavors ranging from edge computing and sensing to large-scale signal processing in data centers. The most efficient and well-entrenched method to train such networks is backpropagation, or reverse-mode automatic differentiation. To counter an exponentially increas

Jonathan Wurtz, Pedro L. S. Lopes, Christoph Gorgulla, Nathan Gemelke

Architectures for quantum computing based on neutral atoms have risen to prominence as candidates for both near and long-term applications. These devices are particularly well suited to solve independent set problems, as the combinatorial constraints can be naturally encoded in the low-energy Hilbert space due to the Rydberg blockade mechanism. Here, we appr

Zhixin Chen, Jie-Ren Deng, Songjun Hou, Xinya Bian

Quantum interference in nano-electronic devices could lead to reduced-energy computing and efficient thermoelectric energy harvesting. When devices are shrunk down to the molecular level it is still unclear to what extent electron transmission is phase coherent, as molecules usually act as scattering centres, without the possibility of showing particle-wave

Christian Fendt, Melis Yardimci

Astrophysical jets are often observed as bent or curved structures. We also know that the different jet sources may be binary in nature, which may lead to a regular, periodic motion of the jet nozzle, an orbital motion or precession. Here, we present the results of 2D (M)HD simulations in order to investigate how a precessing or orbiting jet nozzle affects t

Beiduo Chen, Wu Guo, Quan Liu, Kun Tao

Multilingual BERT (mBERT), a language model pre-trained on large multilingual corpora, has impressive zero-shot cross-lingual transfer capabilities and performs surprisingly well on zero-shot POS tagging and Named Entity Recognition (NER), as well as on cross-lingual model transfer. At present, the mainstream methods to solve the cross-lingual downstream tas

Ricardo Paszko

We propose and analytically solve a simple Euclidean model for quantum gravity in one dimension. The geometry is parametrized by angles associated with a circle of fixed radius $\ell$, allowing the use of the normalized Haar measure of U(1) and character expansions. In the case of an open curve, the continuum limit is trivial: the size of the universe is inf

L. Bayón, P. Fortuny, J. M. Grau, A. M. Oller-Marcén

In this paper, we present a novel method for computing the asymptotic values of both the optimal threshold, and the probability of success in sequences of optimal stopping problems. This method, based on the resolution of a first-order linear differential equation, makes it possible to systematically obtain these values in many situations. As an example, we

Pedro Abdalla, Nikita Zhivotovskiy

We provide an estimator of the covariance matrix that achieves the optimal rate of convergence (up to constant factors) in the operator norm under two standard notions of data contamination: We allow the adversary to corrupt an $\eta$-fraction of the sample arbitrarily, while the distribution of the remaining data points only satisfies that the $L_{p}$-margi