May 2022 arXiv papers — page 9

Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin

We develop a variant of the Monteiro-Svaiter (MS) acceleration framework that removes the need to solve an expensive implicit equation at every iteration. Consequently, for any $p\ge 2$ we improve the complexity of convex optimization with Lipschitz $p$th derivative by a logarithmic factor, matching a lower bound. We also introduce an MS subproblem solver th

Sungwon Kim, Heeseung Kim, Sungroh Yoon

We propose Guided-TTS 2, a diffusion-based generative model for high-quality adaptive TTS using untranscribed data. Guided-TTS 2 combines a speaker-conditional diffusion model with a speaker-dependent phoneme classifier for adaptive text-to-speech. We train the speaker-conditional diffusion model on large-scale untranscribed datasets for a classifier-free gu

Dilpreet Kaur, Harish Kishnani, Amit Kulshrestha

It was shown by Lubotzky in 2014 that automorphism invariant subsets of finite simple groups which contain identity are always word images. In this article, we study word maps on finite nilpotent groups and show that for arbitrary finite groups, the number of automorphism invariant subsets containing identity which are not word images, referred to as word im

Arnab Ganguly, Riten Mitra, Jinpu Zhou

The paper has two major themes. The first part of the paper establishes certain general results for infinite-dimensional optimization problems on Hilbert spaces. These results cover the classical representer theorem and many of its variants as special cases and offer a wider scope of applications. The second part of the paper then develops a systematic appro

Joseph Early, Tom Bewley, Christine Evers, Sarvapali Ramchurn

We generalise the problem of reward modelling (RM) for reinforcement learning (RL) to handle non-Markovian rewards. Existing work assumes that human evaluators observe each step in a trajectory independently when providing feedback on agent behaviour. In this work, we remove this assumption, extending RM to capture temporal dependencies in human assessment o

Benedikt Jahnel, Sanjoy Kumar Jhawar, Anh Duc Vu

We prove phase transitions for continuum percolation in a Boolean model based on a Cox point process with nonstabilizing directing measure. The directing measure, which can be seen as a stationary random environment for the classical Poisson--Boolean model, is given by a planar rectangular Poisson line process. This Manhattan grid type construction features

Milan Paštéka

In the first part of this paper the notion of natural metric on the set of natural numbers is defined. It is such metric that the completion of N is a compact metric space that a probability borel measure exists in order that the sequence {n} is uniformly distributed. A necessary and sufficient condition where a given metric is natural. Later we study the pr

Panagiotis Christeas, Logan Thomas

The next decade will feature an abundance of novel cosmological data, while many fundamental questions about inflation remain. Given this, there is ample need for maximally efficient calculations, especially in non-standard scenarios for the early Universe. In inflationary cosmology, observables are computed within the framework of in-in perturbation theory.

Stefano Buccheri, Ulisse Stefanelli

We consider a class of elliptic and parabolic problems, featuring a specific nonlocal operator of fractional-laplacian type, where integration is taken on variable domains. Both elliptic and parabolic problems are proved to be uniquely solvable in the viscosity sense. Moreover, some spectral properties of the elliptic operator are investigated, proving exist

Dahun Kim, Jun Xie, Huiyu Wang, Siyuan Qiao

We present TubeFormer-DeepLab, the first attempt to tackle multiple core video segmentation tasks in a unified manner. Different video segmentation tasks (e.g., video semantic/instance/panoptic segmentation) are usually considered as distinct problems. State-of-the-art models adopted in the separate communities have diverged, and radically different approach

Nikos D. Fakotakis, Stavros Nousias, Gerasimos Arvanitis, Evangelia I. Zacharaki

Asthma is a common, usually long-term respiratory disease with negative impact on global society and economy. Treatment involves using medical devices (inhalers) that distribute medication to the airways and its efficiency depends on the precision of the inhalation technique. There is a clinical need for objective methods to assess the inhalation technique,

Yoshimichi Nakatsuka, Ercan Ozturk, Alex Shamis, Andrew Paverd

Hardware-based Trusted Execution Environments (TEEs) are becoming increasingly prevalent in cloud computing, forming the basis for confidential computing. However, the security goals of TEEs sometimes conflict with existing cloud functionality, such as VM or process migration, because TEE memory cannot be read by the hypervisor, OS, or other software on the

Lorcan O. Conlon, Tobias Vogl, Christian D. Marciniak, Ivan Pogorelov

Entanglement is a fundamental feature of quantum mechanics and holds great promise for enhancing metrology and communications. Much of the focus of quantum metrology so far has been on generating highly entangled quantum states that offer better sensitivity, per resource, than what can be achieved classically. However, to reach the ultimate limits in multi-p

Dennis Y. Menn, Tzu-hsun Feng, Hung-yi Lee

Neural networks have demonstrated state-of-the-art performance in various machine learning fields. However, the introduction of malicious perturbations in input data, known as adversarial examples, has been shown to deceive neural network predictions. This poses potential risks for real-world applications such as autonomous driving and text identification. I

Samuel Bryant, Benjamin Machta

One of the primary computational requirements of a cellular system is the ability to transfer information between spatially separated components. To accomplish this, biology uses diverse physical channels including production or release of second-messengers molecules and electrical depolarization of the plasma membrane. To send reliable information, these pr

Bai Yang Wang, Tiffany C. Wang, Yu-Te Hsu, Motoki Osada

The consequences of varying the rare-earth element in the superconducting infinite-layer nickelates have been much debated. Here we show striking differences in the magnitude and anisotropy of the superconducting upper critical field across the La-, Pr-, and Nd-nickelates. These 5 distinctions originate from the 4f electron characteristics of the rare-earth

Kyle Bower, Kirill Serkh, Spyros Alexakis, Adam R Stinchcombe

We present a novel numerical method for solving the elliptic partial differential equation problem for the electrostatic potential with piecewise constant conductivity. We employ an integral equation approach for which we derive a system of well-conditioned integral equations by representing the solution as a sum of single layer potentials. The kernel of the

Alexander Avdoshkin, Fedor K. Popov

Consider a set of quantum states $| \psi(x) \rangle$ parameterized by $x$ taken from some parameter space $M$. We demonstrate how all geometric properties of this manifold of states are fully described by a scalar gauge-invariant Bargmann invariant $P^{(3)}(x_1, x_2, x_3)=\operatorname{tr}[P(x_1) P(x_2)P(x_3)]$, where $P(x) = |\psi(x)\rangle \langle\psi(x)|$

Aaron Landesman, Daniel Litt

Let $\Sigma_{g,n}$ be an orientable surface of genus $g$ with $n$ punctures. We study actions of the mapping class group of $\Sigma_{g,n}$ via Hodge-theoretic and arithmetic techniques. We show that if $$\rho: \pi_1(\Sigma_{g,n})\to GL_r(\mathbb{C})$$ is a representation whose conjugacy class has finite orbit under the mapping class group, and $r<\sqrt{g+1}$

N. W. C. Leigh, N. C. Stone, J. J. Webb, W. Lyra

We recently derived, using the density-of-states approximation, analytic distribution functions for the outcomes of direct single-binary scatterings (Stone & Leigh 2019). Using these outcome distribution functions, we present in this paper a self-consistent statistical mechanics-based analytic model obtained using the Fokker-Planck limit of the Boltzmann equ

Sitian Qian, Tianyi Yang, Sen Deng, Jie Xiao

Addressing the mass origin and properties of neutrinos is of strong interest to particle physics, baryogenesis and cosmology. Popular explanations involve physics beyond the standard model, for example, the dimension-5 Weinberg operator or heavy Majorana neutrinos arising from ``seesaw'' models. The current best direct limits on the electron neutrino mass, d

Elisabeta Lusso, Rosa Valiante, Fabio Vito

In the last decades, luminous accreting super-massive black holes have been discovered within the first Gyr after the Big Bang, but their origin is still an unsolved mystery. We discuss our state-of-the-art theoretical knowledge of their formation physics and early growth, and describe the results of dedicated observational campaigns in the X-ray band. We al

Luca Buoninfante

In quantum field theory, a consistent prescription to define and deform integration contours in the complex energy plane is needed to evaluate loop integrals and compute scattering amplitudes. In some nonlocal field theories, including string field theory, interaction vertices contain transcendental functions of momenta that can diverge along certain complex

Meng Cheng, Po-Shen Hsin, Chao-Ming Jian

We present a general algebraic framework for gauging a 0-form compact, connected Lie group symmetry in (2+1)d topological phases. Starting from a symmetry fractionalization pattern of the Lie group $G$, we first extend $G$ to a larger symmetry group $\tilde{G}$, such that there is no fractionalization with respect to $\tilde{G}$ in the topological phase, and

Marco Michel, Sebastian Zell

We present $TimeEvolver$, a program for computing time evolution in a generic quantum system. It relies on well-known Krylov subspace techniques to tackle the problem of multiplying the exponential of a large sparse matrix $i H$, where $H$ is the Hamiltonian, with an initial vector $v$. The fact that $H$ is Hermitian makes it possible to provide an easily co

Dávid Szász-Schagrin, Gábor Takács

The false vacuum is a metastable state that can occur in quantum field theory, and its decay was first studied semi-classically by Coleman. In this work we consider the 1+1 dimensional $\varphi^4$ theory, which is the simplest model that provides a realisation of this problem. We realise the decay as a quantum quench and study the subsequent evolution using

Jenny August, Man-Wai Cheung, Eleonore Faber, Sira Gratz

We study a category $\mathcal{C}_2$ of $\mathbb{Z}$-graded MCM modules over the $A_\infty$ curve singularity and demonstrate it has infinite type $A$ cluster combinatorics. In particular, we show that this Frobenius category (or a suitable subcategory) is stably equivalent to the infinite type $A$ cluster categories of Holm-Jorgensen, Fisher and Paquette-Yil

Junmo Jeon, SungBin Lee

Exotic tiling patterns of quasicrystals have gotten a lot of attention for unique quantum phenomena such as critical state and multifractality. In this regard, finding new quasi-periodic tiling patterns and the relevant quantum states is one of the main interests in quasicrystals. Here, we focus on new types of quasicrystals described by coexisting phason fl

Naritaka Oshita, Hayato Motohashi, Sousuke Noda

We compute the graybody factor and evaporation rate of a rotating black hole in the presence of a hypothetical reflective surface slightly outside the outer horizon radius, assuming that it spontaneously emits thermal radiation due to quantum-gravitational effects such as firewalls or stretched horizons. As a result of a resonance caused by a cavity between

Stefan Hollands, Áron D. Kovács, Harvey S. Reall

We investigate the second law of black hole mechanics in gravitational theories with higher derivative terms in the action. Wall has described a method for defining an entropy that satisfies the second law to linear order in perturbations around a stationary black hole. We show that this can be extended to define an entropy that satisfies the second law to q

Gabriele Franciolini, Konstantinos Kritos, Emanuele Berti, Joseph Silk

Current gravitational-wave observations set the most stringent bounds on the abundance of primordial black holes (PBHs) in the solar mass range. This constraint, however, inherently relies on the merger rate predicted by PBH models. Previous analyses have focused mainly on two binary formation mechanisms: early Universe assembly out of decoupling from the Hu

Ke Huang, DinhDuy Vu, Xiao Li, S. Das Sarma

We study many-body localization (MBL) in the quasiperiodic $t_1$-$t_2$ model, focusing on the role of next-nearest-neighbor (NNN) hopping $t_2$, which introduces a single-particle mobility edge. The calculated phase diagram can be divided into three distinct regimes, depending on the strength of the short-range interaction $U$. For weak interactions ($U\ll t

Aritra Banerjee, Arpan Bhattacharyya, Priya Drashni, Srinidhi Pawar

We probe the contraction from $2d$ relativistic CFTs to theories with Bondi-Metzner-Sachs (BMS) symmetries, or equivalently Conformal Carroll symmetries, using diagnostics of quantum chaos. Starting from an Ultrarelativistic limit on a relativistic scalar field theory and following through at the quantum level using an oscillator representation of states, on

Michael Collier, Djuna Croon, Rebecca K. Leane

A sub-fraction of dark matter or new particles trapped inside celestial objects can significantly alter their macroscopic properties. We investigate the new physics imprint on celestial objects by using a generic framework to solve the Tolman-Oppenheimer-Volkoff (TOV) equations for up to two fluids. We test the impact of populations of new particles on celes

Yanhui Yang, Suoqing Ji

Radiative turbulent mixing layers (TMLs) are ubiquitous in astrophysical environments, e.g., the circumgalactic medium (CGM), and are triggered by the shear velocity at interfaces between different gas phases. To understand the shear velocity dependence of TMLs, we perform a set of 3D hydrodynamic simulations with an emphasis on the TML properties at high Ma

Connor Bottrell, Maan H. Hani

The most direct way to confront observed galaxies with those formed in numerical simulations is to forward-model simulated galaxies into synthetic observations. Provided that synthetic galaxy observations include similar constraints and limitations as real observations, they can be used to (1) carry out even-handed comparisons of observation and theory and (

Aditya Chowdhury, Nissim Kanekar, Jayaram N. Chengalur

Measurements of the atomic hydrogen (HI) properties of high-redshift galaxies are critical to understanding the decline in the star-formation rate (SFR) density of the Universe after its peak $\approx8-11$ Gyr ago. Here, we use $\approx510$ hours of observations with the upgraded Giant Metrewave Radio Telescope to measure the dependence of the average HI mas

Federico Roccati, Benedetto Militello, Emilio Fiordilino, Rosario Iaria

A direct quantization of the Newtonian interaction between two masses is known to establish entanglement, which if detected would witness the quantum nature of the gravitational field. Gravitational interaction is yet compatible also with gravitational decoherence models relying on classical channels, hence unable to create entanglement. Here, we show in par

Caroline Jonas, Jean-Luc Lehners, Jerome Quintin

Complex metrics are a double-edged sword: they allow one to replace singular spacetimes, such as those containing a big bang, with regular metrics, yet they can also describe unphysical solutions in which quantum transitions may be more probable than ordinary classical evolution. In the cosmological context, we investigate a criterion proposed by Witten (bas

M. Spavone, E. Iodice, G. D'Ago, G. van de Ven

This work is based on high quality integral-field spectroscopic data obtained with the Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope (VLT). The 21 brightest ($m_B\leq 15$ mag) early-type galaxies (ETGs) inside the virial radius of the Fornax cluster are observed out to distances of $\sim2-3\ R_{\rm e}$. Deep imaging from the VLT Survey

Lakshya Bhardwaj, Mathew Bullimore, Andrea E. V. Ferrari, Sakura Schafer-Nameki

We propose the general idea that 't Hooft anomalies of generalized global symmetries can be understood in terms of the properties of solitonic defects, which generically are non-topological defects. The defining property of such defects is that they act as sources for background fields of generalized symmetries. 't Hooft anomalies arise when solitonic defect

Lorenzo Rossi

In this thesis, I present the first numerical scheme able to perform Cauchy evolutions of asymptotically AdS spacetimes with reflective boundary conditions under no symmetry requirements on the solution. The scheme is based on the generalised harmonic formulation of the Einstein equations. The main difficulty in removing all symmetry assumptions can be phras

Sunmyon Chon, Haruka Ono, Kazuyuki Omukai, Raffaella Schneider

We study star cluster formation at low metallicities of $Z/Z_\odot=10^{-4}$--$10^{-1}$ using three-dimensional hydrodynamics simulations. Particular emphasis is put on how the stellar mass distribution is affected by the cosmic microwave background radiation (CMB), which sets the temperature floor to the gas. Starting from the collapse of a turbulent cloud,

Nickolas Kokron, Shi-Fan Chen, Martin White, Joseph DeRose

Simulations have become an indispensable tool for accurate modelling of observables measured in galaxy surveys, but can be expensive if very large dynamic range in scale is required. We describe how to combine Lagrangian perturbation theory models with N-body simulations to reduce the effects of finite computational volume in the prediction of ensemble avera

Luca Di Luzio, Federico Mescia, Enrico Nardi, Shohei Okawa

It has been recently pointed out that in certain axion models it is possible to suppress simultaneously both the axion couplings to nucleons and electrons, realising the so-called astrophobic axion scenarios, wherein the tight bounds from SN1987A and from stellar evolution of red giants and white dwarfs are greatly relaxed. So far, however, the conditions fo

Robert Feldmann, Eliot Quataert, Claude-André Faucher-Giguère, Philip F. Hopkins

We introduce a suite of cosmological volume simulations to study the evolution of galaxies as part of the Feedback in Realistic Environments project. FIREbox, the principal simulation of the present suite, provides a representative sample of galaxies (~1000 galaxies with Mstar > 10^8 Msun at z=0) at a resolution (~20 pc, m_b ~ 6x10^4 Msun) comparable to stat

Csaba Csaki, Jay Hubisz, Ameen Ismail, Gabriele Rigo

We explore higher-derivative terms in the low-energy effective action for the dilaton, the Goldstone boson of spontaneously broken scale invariance. Focusing on the simplest holographic realization of spontaneously broken scale invariance, the Randall-Sundrum (RS) scenario, we identify the nonlinear action for the RS dilaton by integrating out Kaluza-Klein g

Sophie Klett, Manfred Lindner, Andreas Trautner

We show that vector-like quarks in the fundamental or higher-dimensional representations of QCD can generate the electro-weak scale in a phenomenologically viable way by chiral symmetry breaking condensates. The thereby generated scales are determined by numerically solving the Dyson-Schwinger equation and these scales are sizable, because they grow with the

Ruben Verresen, Ashvin Vishwanath

The exploration of quantum spin liquids (QSLs) has been guided by different approaches including the resonating valence bond (RVB) picture, deconfined lattice gauge theories and the Kitaev model. More recently, a spin liquid ground state was numerically established on the ruby lattice, inspired by the Rydberg blockade mechanism. Here we unify these varied ap

Verna Dankers, Christopher G. Lucas, Ivan Titov

Unlike literal expressions, idioms' meanings do not directly follow from their parts, posing a challenge for neural machine translation (NMT). NMT models are often unable to translate idioms accurately and over-generate compositional, literal translations. In this work, we investigate whether the non-compositionality of idioms is reflected in the mechanics o

Ashish Kumar, Zhongyu Li, Jun Zeng, Deepak Pathak

Recent advances in legged locomotion have enabled quadrupeds to walk on challenging terrains. However, bipedal robots are inherently more unstable and hence it's harder to design walking controllers for them. In this work, we leverage recent advances in rapid adaptation for locomotion control, and extend them to work on bipedal robots. Similar to existing wo

Olga Anosova, Daniel Widdowson, Vitaliy Kurlin

This paper rigorously solves the challenging problem of recognizing periodic patterns under rigid motion in Euclidean geometry. The 3-dimensional case is practically important for justifying the novelty of solid crystalline materials (periodic crystals) and for patenting medical drugs in a solid tablet form. Past descriptors based on finite subsets fail when

Hao Chen, Thomas Barthel

Tensor networks are used to efficiently approximate states of strongly-correlated quantum many-body systems. More generally, tensor network approximations may allow to reduce the costs for operating on an order-$N$ tensor from exponential to polynomial in $N$, and this has become a popular approach for machine learning. We introduce the idea of imposing low-

Massimiliano Maria Riva, Filippo Vernizzi, Leong Khim Wong

We present a novel calculation of the four-momentum that is radiated into gravitational waves during the scattering of two arbitrarily spinning bodies. Our result, which is accurate to leading order in $G$, to quadratic order in the spins, and to all orders in the velocity, is derived by using a Routhian-based worldline effective field theory formalism in co

Yu Bai, Chi Jin, Song Mei, Ziang Song

A conceptually appealing approach for learning Extensive-Form Games (EFGs) is to convert them to Normal-Form Games (NFGs). This approach enables us to directly translate state-of-the-art techniques and analyses in NFGs to learning EFGs, but typically suffers from computational intractability due to the exponential blow-up of the game size introduced by the c

Alexey Sharapov, Evgeny Skvortsov

Chiral Higher Spin Gravity with cosmological constant is constructed as a Free Differential Algebra, i.e. at the level of equations of motion, which is a smooth deformation of its flat space cousin arXiv:2205.07794. Chiral Higher Spin Gravity is a unique class of local higher spin theories; its very existence implies that there is a closed and, most likely,

Sebastian Hönel, Welf Löwe

Solutions to multi-objective optimization problems can generally not be compared or ordered, due to the lack of orderability of the single objectives. Furthermore, decision-makers are often made to believe that scaled objectives can be compared. This is a fallacy, as the space of solutions is in practice inhomogeneous without linear trade-offs. We present a

Fu-Ming Guo, Yingfang Fan

Lung cancer is the leading cause of cancer-related death worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most common histologic subtypes of non-small-cell lung cancer (NSCLC). Histology is an essential tool for lung cancer diagnosis. Pathologists make classifications according to the dominant subtypes. Although morpholog

Alexander Drewitz, Olof Elias, Alexis Prévost, Johan Tykesson

We study percolative properties of excursion processes and the discrete Gaussian free field (dGFF) in the planar unit disk. We consider discrete excursion clouds, defined using random walks as a two-dimensional version of random interlacements, as well as its scaling limit, defined using Brownian motion. We prove that the critical parameters associated to va

Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang

In this paper, we tackle the problem of learning visual representations from unlabeled scene-centric data. Existing works have demonstrated the potential of utilizing the underlying complex structure within scene-centric data; still, they commonly rely on hand-crafted objectness priors or specialized pretext tasks to build a learning framework, which may har

Andreas Nygaard, Emil Brinch Holm, Steen Hannestad, Thomas Tram

Bayesian parameter inference is an essential tool in modern cosmology, and typically requires the calculation of $10^5$--$10^6$ theoretical models for each inference of model parameters for a given dataset combination. Computing these models by solving the linearised Einstein-Boltzmann system usually takes tens of CPU core-seconds per model, making the entir

Elisabetta Candellero, Tom Hutchcroft

We prove that supercritical branching random walk on a transient graph converges almost surely under rescaling to a random measure on the Martin boundary of the graph. Several open problems and conjectures about this limiting measure are presented.

Luke Taylor, Andrew King, Nicol Harper

Spiking neural networks (SNNs), particularly the single-spike variant in which neurons spike at most once, are considerably more energy efficient than standard artificial neural networks (ANNs). However, single-spike SSNs are difficult to train due to their dynamic and non-differentiable nature, where current solutions are either slow or suffer from training

Francesco Longo, Alessandro Chiurco, Roberto Musmanno, Letizia Nicoletti

This article faces the problem of operative and procedural cooperative training in marine ports with particular attention to harbour pilots and port traffic controller. The design and development of an advanced system, equipped with dedicated hardware in the loop, for cooperative training of operators involved in the last mile of navigation is presented. Ind

Jiemin Fang, Taoran Yi, Xinggang Wang, Lingxi Xie

Neural radiance fields (NeRF) have shown great success in modeling 3D scenes and synthesizing novel-view images. However, most previous NeRF methods take much time to optimize one single scene. Explicit data structures, e.g. voxel features, show great potential to accelerate the training process. However, voxel features face two big challenges to be applied

Chiara Boccato, Robert Seiringer

We consider a gas of bosonic particles confined in a box with Neumann boundary conditions. We prove Bose-Einstein condensation in the Gross-Pitaevskii regime, with an optimal bound on the condensate depletion. Our lower bound for the ground state energy in the box implies (via Neumann bracketing) a lower bound for the ground state energy of the Bose gas in t

Kyle Hayden, Seungwon Kim, Maggie Miller, JungHwan Park

We answer a question of Livingston from 1982 by producing Seifert surfaces of the same genus for a knot in $S^3$ that do not become isotopic when their interiors are pushed into $B^4$. In particular, we identify examples where the surfaces are not even topologically isotopic in $B^4$, examples that are topologically but not smoothly isotopic, and examples of

Matteo Taffetani, Martin G. Walker

When poking a thin shell-like structure, like a plastic water bottle, experience shows that an initial axisymmetric dimple forms around the indentation point. The ridge of this dimple, with increasing indentation, eventually buckles into a polygonal shape. The polygon order generally continues to increase with further indentation. In the case of spherical sh

Enrique Noriega-Atala, Mihai Surdeanu, Clayton T. Morrison

We propose a method to teach an automated agent to learn how to search for multi-hop paths of relations between entities in an open domain. The method learns a policy for directing existing information retrieval and machine reading resources to focus on relevant regions of a corpus. The approach formulates the learning problem as a Markov decision process wi

Louis G. Christie, John A. D. Aston

Invariant and equivariant models incorporate the symmetry of an object to be estimated (here non-parametric regression functions $f : \mathcal{X} \rightarrow \mathbb{R}$). These models perform better (with respect to $L^2$ loss) and are increasingly being used in practice, but encounter problems when the symmetry is falsely assumed. In this paper we present

Xinya Ji, Hang Zhou, Kaisiyuan Wang, Qianyi Wu

Although significant progress has been made to audio-driven talking face generation, existing methods either neglect facial emotion or cannot be applied to arbitrary subjects. In this paper, we propose the Emotion-Aware Motion Model (EAMM) to generate one-shot emotional talking faces by involving an emotion source video. Specifically, we first propose an Aud

John March-Russell, João G. Rosa

We study the production of heavy, $\mu \gtrsim 1$ TeV, bosonic spin $s=0,1$ dark matter (DM) via the simultaneous processes of Hawking evaporation and superradiance (SR) from an initial population of small, $\lesssim 10^6$ kg, primordial black holes (PBHs). Even for small initial PBH spins the SR process can produce extremely dense gravitationally-bound DM B

Yu Sun, Eliza Amatova, Tianze Chen

This paper proposes 12 multi-object grasps (MOGs) types from a human and robot grasping data set. The grasp types are then analyzed and organized into a MOG taxonomy. This paper first presents three MOG data collection setups: a human finger tracking setup for multi-object grasping demonstrations, a real system with Barretthand, UR5e arm, and a MOG algorithm

Ulrich Bauer, Benedikt Fluhr

The extended persistence diagram introduced by Cohen-Steiner, Edelsbrunner, and Harer is an invariant of real-valued continuous functions, which are $\mathbb{F}$-tame in the sense that all open interlevel sets have degree-wise finite-dimensional cohomology with coefficients in a fixed field $\mathbb{F}$. We show that relative interlevel set cohomology (RISC)

T. Gautam, A. Ridolfi, P. C. C. Freire, R. S. Wharton

Globular clusters contain a unique pulsar population, with many exotic systems that can form only in their dense stellar environments. The leap in sensitivity of the upgraded Giant Metrewave Radio Telescope (uGMRT) in India, especially at low radio frequencies ($<$ 1 GHz) has motivated a new search for radio pulsars in a group of eight Southern globular clus

Enrique G. Neyra, Demian A. Biasetti, Fabián Videla, Lorena Rebón

An alternative definition to the main frequency of an ultra-short laser pulse, named principal frequency ($\omega_P$), was recently introduced in E.G. Neyra, et al. Phys. Rev. A 103, 053124 (2021), resulting in a more transparent description of the nonlinear dynamics of a system driven by this coherent source. In this work, we extend the definition of $\omeg

Burak Dagli, Bora Ketenoglu, Saleh Sultansoy

Construction of future Muon Collider (or dedicated mu-ring) tangential to the energy frontier pp colliders will give opportunity to realize mu-p collisions at multi-TeV center of mass energies at a luminosity of order of $10^{33}$ cm$^{-2}$s$^{-1}$ ($10^{34}$ cm$^{-2}$s$^{-1}$). Obviously, such colliders will essentially enlarge the physics search potential

Guido De Philippis, Nicola Fusco, Massimiliano Morini

In this paper we study the regularity properties of $\Lambda$-minimizers of the capillarity energy in a half space with the wet part constrained to be confined inside a given planar region. Applications to a model for nanowire growth are also provided.

Carlos Segovia

This work provides a geometric version of the next-generation matrix method for obtaining the basic reproduction number of an epidemiological model. We exhibit a certain correspondence between any system of ODEs and Petri nets. We observe that any epidemiological model has the basic structures found in the SIR model of Kermack-McKendrick. This means that the

Moon Jeong Park, Jungseul Ok, Yo-Seb Jeon, Dongwoo Kim

Deep learning-based symbol detector gains increasing attention due to the simple algorithm design than the traditional model-based algorithms such as Viterbi and BCJR. The supervised learning framework is often employed to predict the input symbols, where training symbols are used to train the model. There are two major limitations in the supervised approach

Larisa Safina, Simon Bliudze

Behavioural models are a valuable tool for software verification, testing, monitoring, publishing etc. However, they are rarely provided by the software developers and have to be extracted either from the source or from the compiled code. In the context of Java programs, a number of approaches exist for building behavioural models. Most of these approaches r

Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev

We study the Neural Optimal Transport (NOT) algorithm which uses the general optimal transport formulation and learns stochastic transport plans. We show that NOT with the weak quadratic cost might learn fake plans which are not optimal. To resolve this issue, we introduce kernel weak quadratic costs. We show that they provide improved theoretical guarantees

Wenjie Li, Qifan Song, Jean Honorio, Guang Lin

This work establishes the first framework of federated $\mathcal{X}$-armed bandit, where different clients face heterogeneous local objective functions defined on the same domain and are required to collaboratively figure out the global optimum. We propose the first federated algorithm for such problems, named \texttt{Fed-PNE}. By utilizing the topological s

Marc Mars, Gabriel Sánchez-Pérez

General hypersurfaces of any causal character can be studied abstractly using the hypersurface data formalism. In the null case, we write down all tangential components of the ambient Ricci tensor in terms of the abstract data. Using this formalism, we formulate and solve in a completely abstract way the characteristic Cauchy problem of the Einstein vacuum f

Pierluigi Amodio, Luigi Brugnano, Felice Iavernaro

Recently, the efficient numerical solution of Hamiltonian problems has been tackled by defining the class of energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs). Their derivation relies on the expansion of the vector field along the Legendre orthonormal basis. Interestingly, this approach can be extended to cope with other

Christoph Koller, Göran Kauermann, Xiao Xiang Zhu

Technological and computational advances continuously drive forward the broad field of deep learning. In recent years, the derivation of quantities describing theuncertainty in the prediction - which naturally accompanies the modeling process - has sparked general interest in the deep learning community. Often neglected in the machine learning setting is the

Filipp N. Rybakov, Olle Eriksson

We show that non-Abelian vortices can exist in magnetic materials. These are singularity-free textures, are described by spin-lattice and field theory models, and we demonstrate that typical magnetic materials can be quite suitable for their realization and observation. We give a topological classification of these vortices and reveal their connection with A

Yanchao Liu

This paper proposes a new mixed-integer programming (MIP) formulation to optimize split rule selection in the decision tree induction process, and develops an efficient search algorithm that is able to solve practical instances of the MIP model faster than commercial solvers. The formulation is novel for it directly maximizes the Gini reduction, an effective

Thomas Halloran, Félix Desrochers, Emily Z. Zhang, Tong Chen

Recently, Co-based honeycomb magnets have been proposed as promising candidate materials to host the Kitaev spin liquid state. One of the front-runners is BaCo$_2$(AsO$_4$)$_2$ (BCAO), where it was suggested that the exchange processes between Co$^{2+}$ ions via the surrounding edge-sharing oxygen octahedra could give rise to bond-dependent Kitaev interactio

Mayukh R. Gangopadhyay, Hussain Ahmed Khan, Yogesh

We study two of the most theoretically promising models of inflation, namely the Natural inflation and the Mutated Hilltop inflation, in the Einstein-Gauss Bonnet(EGB) gravity framework. In this work, we try to explore these models in EGB framework, keeping the observations from $GW170817$ on the speed of gravitational wave to be equal to the speed of light.

Joseph A. Thas

In the period 1994-1999 Thas wrote a series of three papers on generalized quadrangles of order $(s, s^2)$. In this Part IV we classify all finite translation generalized quadrangles of order $(s, s^2)$ having a kernel of size at least 3, containing a regular line not incident with the translation point. There are several applications on generalized quadrang

Timo Reis, Tatjana Stykel

We study a~quasilinear coupled magneto-quasistatic model from a~systems theoretic perspective.} First, by taking the injected voltages as input and the associated currents as output, we prove that the magneto-quasistatic system is passive. Moreover, by defining suitable Dirac and resistive structures, we show that it admits a~representation as a~port-Hamilto

Miri Zilka, Holli Sargeant, Adrian Weller

We present a survey of tools used in the criminal justice system in the UK in three categories: data infrastructure, data analysis, and risk prediction. Many tools are currently in deployment, offering potential benefits, including improved efficiency and consistency. However, there are also important concerns. Transparent information about these tools, thei

Hui Zhang, Fengjuan Meng, Jianjun Zhang

In this paper, we are concerned with the quasilinear Schr\"{o}dinger equation \begin{equation*} -\Delta u+V(x)u-u\Delta(u^2)=g(u),\ \ x\in \mathbb{R}^{N}, \end{equation*} where $N\geq3$, $V$ is radially symmetric and nonnegative, and $g$ is asymptotically 3-linear at infinity. In the case of $\inf_{\mathbb{R}^N}V>0$, we show the existence of a least energy s

Laura Clinton, Toby Cubitt, Brian Flynn, Filippo Maria Gambetta

Simulation of materials is one of the most promising applications of quantum computers. On near-term hardware the crucial constraint on these simulations is circuit depth. Many quantum simulation algorithms rely on a layer of unitary evolutions generated by each term in a Hamiltonian. This appears in time-dynamics as a single Trotter step, and in variational

Hanzhen Ma, Oriol Rubies-Bigorda, Susanne F. Yelin

When atoms are coupled to a common electromagnetic environment, the exchange of photons through dipole-dipole interactions leads to the emergence of cooperative effects. As a particular example, superradiance arises from spontaneous emission when this exchange leads to constructive interference of the emitted photons. Here, we introduce an integrated method

Dong-Hwan Jang, Sanghyeok Chu, Joonhyuk Kim, Bohyung Han

The size and shape of the receptive field determine how the network aggregates local information and affect the overall performance of a model considerably. Many components in a neural network, such as kernel sizes and strides for convolution and pooling operations, influence the configuration of a receptive field. However, they still rely on hyperparameters

Ralph Chill, Timo Reis, Tatjana Stykel

We consider a~quasilinear model arising from dynamical magnetization. This model is described by a~magneto-quasistatic (MQS) approximation of Maxwell's equations. Assuming that the medium consists of a~conducting and a~non-conducting part, the derivative with respect to time is not fully entering, whence the system can be described by an abstract differentia

Mats O. Tholén, Riccardo Borgani, Giuseppe Ruggero Di Carlo, Andreas Bengtsson

We describe a digital microwave platform called Presto, designed for measurement and control of multiple quantum bits (qubits) and based on the third-generation radio-frequency system on a chip. Presto uses direct digital synthesis to create signals up to 9 GHz on 16 synchronous output ports, while synchronously analyzing response on 16 input ports. Presto h

Kenta Hagiwara, Philipp Rüßmann, Xin Liang Tan, Ying-Jiun Chen

Topological semimetals have recently attracted great attention due to prospective applications governed by their peculiar Fermi surfaces. Weyl semimetals host chiral fermions that manifest as pairs of non-degenerate massless Weyl points in their electronic structure, giving rise to novel macroscopic quantum phenomena such as the chiral anomaly, an unusual ma