July 2022 arXiv papers — page 96

Danila Cherkashin, Alexei Gordeev, Georgii Strukov

This paper deals with the minimum number $m_H(r)$ of edges in an $H$-free graph with the chromatic number more than $r$. We show how bounds on Ramsey and Tur\'an numbers imply bounds on $m_H(r)$.

Roger Blandford, Noemie Globus

A brief summary is given of an alternative interpretation of the Event Horizon Telescope observations of the massive black hole in the nucleus of the nearby galaxy M87. It is proposed that the flow is primarily powered by the black hole rotation, not the release of gravitational energy by the infalling gas. Consequently, the observed millimetre emission is p

Maxim Sukharev, Elena Drobnyh, Ruth Pachter

We investigate the process of the second harmonic generation by plasmonic nano-antennas that exhibit Fano-like resonances. A rigorous fully vectorial Maxwell-hydrodynamics approach is employed to directly calculate the second order susceptibilities as function of the pump frequency, considering a periodic array of nanodolmens comprised of three Au nanorods.

Jonathan D. Chang, Kaiwen Wang, Nathan Kallus, Wen Sun

We study representation learning for Offline Reinforcement Learning (RL), focusing on the important task of Offline Policy Evaluation (OPE). Recent work shows that, in contrast to supervised learning, realizability of the Q-function is not enough for learning it. Two sufficient conditions for sample-efficient OPE are Bellman completeness and coverage. Prior

Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro

A central problem in sequential decision making is to develop algorithms that are practical and computationally efficient, yet support the use of flexible, general-purpose models. Focusing on the contextual bandit problem, recent progress provides provably efficient algorithms with strong empirical performance when the number of possible alternatives ("actio

Natalia Semenova, Vadim Porvatov, Vladislav Tishin, Artyom Sosedka

The problem of travel time estimation is widely considered as the fundamental challenge of modern logistics. The complex nature of interconnections between spatial aspects of roads and temporal dynamics of ground transport still preserves an area to experiment with. However, the total volume of currently accumulated data encourages the construction of the le

Elizabeth Lee, Dhayaa Anbajagane, Priyanka Singh, Jens Chluba

The Sunyaev-Zeldovich (SZ) effect is a powerful tool in modern cosmology. With future observations promising ever improving SZ measurements, the relativistic corrections to the SZ signals from galaxy groups and clusters are increasingly relevant. As such, it is important to understand the differences between three temperature measures: (a) the average relati

Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu

Conventionally, Earth system (e.g., weather and climate) forecasting relies on numerical simulation with complex physical models and are hence both expensive in computation and demanding on domain expertise. With the explosive growth of the spatiotemporal Earth observation data in the past decade, data-driven models that apply Deep Learning (DL) are demonstr

Sam Staton, Ned Summers

De Finetti theorems tell us that if we expect the likelihood of outcomes to be independent of their order, then these sequences of outcomes could be equivalently generated by drawing an experiment at random from a distribution, and repeating it over and over. In particular, the quantum de Finetti theorem says that exchangeable sequences of quantum states are

Masato Kobayashi

Euler discovered recurrence for divisor sum functions as a consequence of the pentagonal numbers theorem. With similar idea and also motivated by Ewell's work in 1977, we prove new recurrences for certain divisor sum functions and triangular numbers.

Itamar Hadas

Let $\mathcal{G}$ be a smooth linear group scheme of finite type. For any positive integer $k$ and a finite field $\mathbb{F}$, let $W_k(\mathbb{F})$ be the ring of Witt vectors of length $k$ over $\mathbb{F}$. We show that the group algebras of $\mathcal{G}(\mathbb{F}[t]/(t^k))$ and $\mathcal{G}(W_k(\mathbb{F}))$ are isomorphic (i.e. the multi-sets of the d

Ignacio J. Araya, Nelson D. Padilla, Marcelo E. Rubio, Joaquín Sureda

We explore the possibility that primordial black holes (PBHs) contain electric charge down to the present day. We find that PBHs should hold a non-zero net charge at their formation, due to either Poisson fluctuations at horizon crossing or high-energy particle collisions. Although initial charge configurations are subject to fast discharge processes through

M. Ashry, K. Ezzat, S. Khalil

We investigate the possibility of explanation for the muon anomalous magnetic moment $g_\mu-2$ in a left-right model with an inverse seesaw mechanism. We emphasize that the observed deviation from the Standard Model predictions can be accommodated in a large part of the parameter space of this class of models, where loops with massive neutrinos and charged H

Fengjiao Li, Xingyu Zhou, Bo Ji

In this paper, we study the problem of global reward maximization with only partial distributed feedback. This problem is motivated by several real-world applications (e.g., cellular network configuration, dynamic pricing, and policy selection) where an action taken by a central entity influences a large population that contributes to the global reward. Howe

Haning Xiu, Harry Liu, Andrea Poli, Guangchao Wan

Concepts from quantum topological states of matter have been extensively utilized in the past decade in creating mechanical metamaterials with topologically protected features, such as one-way edge states and topologically polarized elasticity. Maxwell lattices represent a class of topological mechanical metamaterials that exhibit distinct robust mechanical

Domagoj Vlah, Karlo Šepetanc, Hrvoje Pandžić

Current state-of-the-art solution techniques for solving bilevel optimization problems either assume strong problem regularity criteria or are computationally intractable. In this paper we address power system problems of bilevel structure, commonly arising after the deregulation of the power industry. Such problems are predominantly solved by converting the

Duy-Nguyen Ta, Eric Cousineau, Huihua Zhao, Siyuan Feng

We present our findings in the gap between theory and practice of using conditional energy-based models (EBM) as an implicit representation for behavior-cloned policies. We also clarify several subtle, and potentially confusing, details in previous work in an attempt to help future research in this area. We point out key differences between unconditional and

Carlos F. Álvarez, Marisa Cantarino

We prove the existence of equilibrium states for partially hyperbolic endomorphisms with one-dimensional center bundle. We also prove, regarding a class of potentials, the uniqueness of such measures for endomorphisms defined on the 2-torus that: have a linear model as a factor; and with the condition that this measure gives zero weight to the set where the

Haseeb Younis, Paul Trust, Rosane Minghim

Data visualisation helps understanding data represented by multiple variables, also called features, stored in a large matrix where individuals are stored in lines and variable values in columns. These data structures are frequently called multidimensional spaces.In this paper, we illustrate ways of employing the visual results of multidimensional projection

Antonio W. Cunha, Erin Griffin

In this paper we extend existing results for generalized solitons, called $q$-solitons, to the complete case by considering non-compact solitons. By placing regularity conditions on the vector field $X$ and curvature conditions on $M$, we are able to use the chosen properties of the tensor $q$ to see that such non-compact $q$-solitons are stationary and $q$-

William Golding

In this paper, we study the regularity properties of bounded entropy solutions to the isentropic Euler equations with $\gamma = 3$. First, we use a blow-up technique to obtain a new trace theorem for all such solutions. Second, we use a modified De Giorgi type iteration on the kinetic formulation to show a new partial regularity result on the Riemann invaria

Maryam Khalid, Akane Sano

Emotion prediction plays an essential role in mental health and emotion-aware computing. The complex nature of emotion resulting from its dependency on a person's physiological health, mental state, and his surroundings makes its prediction a challenging task. In this work, we utilize mobile sensing data to predict happiness and stress. In addition to a pers

Justin Alsing, Hiranya Peiris, Daniel Mortlock, Joel Leja

We present a forward modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describing the intrinsic distribution of physical characteristics of galaxies, encoding galaxy evolution physics; a stellar population synthesis model connecting the physical properties o

D. Puentes, Z. Meisel, G. Bollen, A. Hamaker

We report a high precision mass measurement of $^{24}{\rm Si}$, performed with the LEBIT facility at the National Superconducting Cyclotron Laboratory. The atomic mass excess, $10\;753.8$(37) keV, is a factor of 5 more precise than previous results. This substantially reduces the uncertainty of the $^{23}{\rm Al}(p,\gamma)^{24}{\rm Si}$ reaction rate, which

Raymond Li, Ilya Valmianski, Li Deng, Xavier Amatriain

Medical entity span extraction and linking are critical steps for many healthcare NLP tasks. Most existing entity extraction methods either have a fixed vocabulary of medical entities or require span annotations. In this paper, we propose a method for linking an open set of entities that does not require any span annotations. Our method, Open Set Label Atten

Fabian Neumann, Elisabeth Zeyen, Marta Victoria, Tom Brown

Electricity transmission expansion has suffered many delays in Europe in recent decades, despite its significance for integrating renewable electricity into the energy system. A hydrogen network which reuses the existing fossil gas network could not only help to supply demand for low-emission fuels, but could also to balance variations in wind and solar ener

Matthew McKinney, J. Mitchell, S. I. Thomson

Saturn's largest moon, Titan, has an Earth-like volatile cycle, but with methane playing the role of water and surface liquid reservoirs geographically isolated at high latitudes. We recreate Titan's characteristic dry hydroclimate at the equator of an Earth-like climate model without seasons and with water as the condensable by varying a small set of planet

Ryan Arbon

We present a new, computer-assisted, proof that for all triangles in the plane, the equilateral triangle uniquely maximizes the ratio of the first two Dirichlet-Laplacian eigenvalues. This proves an independent proof the triangular Ashbaugh-Benguria-Payne-Polya-Weinberger conjecture first proved in arXiv:0707.3631 [math.SP] and arXiv:2009.00927 [math.SP]. In

Anna Demchenko, Suvidyakumar Homkar, Corinne Bouillet, Christophe Lefèvre

Understanding the polarization switching mechanisms at play in ferroelectric materials is crucial for their exploitation in electronic devices. The conventional centrosymmetric reference structure-based mechanism which accounts for ferroelectricity in most of the usual displacive ferroelectric materials is too energy-demanding for some newly diagnosed ferroe

Evgenia Koumpia, R. D. Oudmaijer, W. -J. de Wit, A. Mérand

The fate of a massive star during the latest stages of its evolution is highly dependent on its mass-loss history and geometry, with the yellow hypergiants being key objects to study those phases of evolution. We present near-IR interferometric observations of the famous yellow hypergiant IRC +10420 and blue spectra taken between 1994-2019. Our 2.2 $\mu$m GR

Mohit Bajaj, Lingyang Chu, Vittorio Romaniello, Gursimran Singh

The popularity of machine learning has increased the risk of unfair models getting deployed in high-stake applications, such as justice system, drug/vaccination design, and medical diagnosis. Although there are effective methods to train fair models from scratch, how to automatically reveal and explain the unfairness of a trained model remains a challenging

Sofiane Mahiou, Kai Xu, Georgi Ganev

We propose a general, flexible, and scalable framework dpart, an open source Python library for differentially private synthetic data generation. Central to the approach is autoregressive modelling -- breaking the joint data distribution to a sequence of lower-dimensional conditional distributions, captured by various methods such as machine learning models

Dibyendu Biswas

From an irreducible representation of GL(n, C) there is a natural way to construct an irreducible representations of GL(n + 1, C) by adding a zero at the end of the highest weight of the irreducible representation of GL(n, C). The paper considers the decomposition of tensor products of irreducible representation of GL(n, C) and of the corresponding irreducib

Calvin McCarter, Nicholas Dronen

Fast approximations to matrix multiplication have the potential to dramatically reduce the cost of neural network inference. Recent work on approximate matrix multiplication proposed to replace costly multiplications with table-lookups by fitting a fast hash function from training data. In this work, we propose improvements to this previous work, targeted to

Arnout van Soesbergen, Zedong Chu, Miaojing Shi, Mark Mulligan

Dam reservoirs play an important role in meeting sustainable development goals and global climate targets. However, particularly for small dam reservoirs, there is a lack of consistent data on their geographical location. To address this data gap, a promising approach is to perform automated dam reservoir extraction based on globally available remote sensing

Chi-Kuang Yeh, Gregory Rice, Joel A. Dubin

We propose a new autocorrelation measure for functional time series that we term spherical autocorrelation. It is based on measuring the average angle between lagged pairs of series after having been projected onto the unit sphere. This new measure enjoys several complimentary advantages compared to existing autocorrelation measures for functional data, sinc

François Charles, Alena Pirutka

Soit $X$ une vari\'et\'e projective et lisse, d\'efinie sur un corps de nombres. Sous l'hypoth\`ese $H^2(X,\mathcal O_X)=0,$ Colliot-Th\'el\`ene et Raskind ont d\'emontr\'e que le sous-groupe de torsion $CH^2(X)_{tors}$ du groupe de Chow en codimension $2$ est fini. Dans cette note, on donne des bornes uniformes pour le groupe fini $CH^2(X)_{tors}$ quand $X$

Xianyang Chen, Jiacai Lu, Stéphane Zaleski, Grétar Tryggvason

The unsteady motion of a gas-liquid interface, such as during splashing or atomization, often results in complex liquid structures embedded in the ambient fluid. Here we explore the use of skeletonization to identify the minimum amount of information needed to describe their geometry. We skeletonize a periodic liquid jet by a modification of a recently intro

Suman Kumar Sahoo, Mikko Salo

In this article we consider a linearized Calder\'on problem for polyharmonic operators of order $2m\ (m\ge 2)$ in the spirit of Calder\'on's original work [Cal80]. We give a uniqueness result for determining coefficients of order $\leq 2m-1$ up to gauge, based on inverting momentum ray transforms.

Yuepeng Yang, Cong Ma

This paper is concerned with noisy matrix completion--the problem of recovering a low-rank matrix from partial and noisy entries. Under uniform sampling and incoherence assumptions, we prove that a tuning-free square-root matrix completion estimator (square-root MC) achieves optimal statistical performance for solving the noisy matrix completion problem. Sim

Dingfan Chen, Ning Yu, Mario Fritz

As a long-term threat to the privacy of training data, membership inference attacks (MIAs) emerge ubiquitously in machine learning models. Existing works evidence strong connection between the distinguishability of the training and testing loss distributions and the model's vulnerability to MIAs. Motivated by existing results, we propose a novel training fra

David Paulius, Alejandro Agostini, Dongheui Lee

Following work on joint object-action representations, functional object-oriented networks (FOON) were introduced as a knowledge graph representation for robots. A FOON contains symbolic concepts useful to a robot's understanding of tasks and its environment for object-level planning. Prior to this work, little has been done to show how plans acquired from F

Alessandro Chiarini, Davide Gatti, Andrea Cimarelli, Maurizio Quadrio

The separating and reattaching turbulent flow past a rectangular cylinder is studied to describe how small and large scales contribute to the sustaining mechanism of the velocity fluctuations. The work is based on the Anisotropic Generalised Kolmogorov Equations (AGKE), exact budget equations for the second-order structure function tensor in the space of sca

Joshua P. Ebenezer, Yixu Chen, Yongjun Wu, Hai Wei

Videos often have to be transmitted and stored at low bitrates due to poor network connectivity during adaptive bitrate streaming. Designing optimal bitrate ladders that would select the perceptually-optimized resolution, frame-rate, and compression level for low-bitrate videos for adaptive streaming across the internet is therefore a task of great interest.

Miguel Esparza, Hamed Farahmand, Samuel Brody, Ali Mostafavi

The use of crowdsourced data has been finding practical use for enhancing situational awareness during disasters. While recent studies have shown promising results regarding the potential of crowdsourced data for flood mapping, little attention has been paid to data imbalances issues that could introduce biases. We examine biases present in crowdsourced repo

Charles Lu, Syed Rakin Ahmed, Praveer Singh, Jayashree Kalpathy-Cramer

Estimating the test performance of software AI-based medical devices under distribution shifts is crucial for evaluating the safety, efficiency, and usability prior to clinical deployment. Due to the nature of regulated medical device software and the difficulty in acquiring large amounts of labeled medical datasets, we consider the task of predicting the te

C. R. Constante-Amores, T. Abadie, L. Kahouadji, S. Shin

We study the effect of insoluble surfactants on the spatio-temporal evolution of turbulent jets. We use three-dimensional numerical simulations and employ an interface-tracking/level-set method that accounts for surfactant-induced Marangoni stresses. The present study builds on our previous work (Constante et al., 2021, J. Fluid Mech., 922, A6) in which we e

Steven Crisostomo, Ryan Pederson, John Kozlowski, Bhupalee Kalita

We explore a variety of unsolved problems in density functional theory, where mathematicians might prove useful. We give the background and context of the different problems, and why progress toward resolving them would help those doing computations using density functional theory. Subjects covered include the magnitude of the kinetic energy in Hartree-Fock

Siddhartha Visveswara Jayanti

In this work, we define the generalized wake-up problem, $GWU(s)$, for a shared memory asynchronous system with $n$ processes. Informally, the problem, which is parametrized by an increasing sequence $s = s_1,\ldots,s_p$, asks that at least $n - i + 1$ processes identify that at least $s_i$ other processes have "woken up" and taken at least one step for each

John Ladan, Stephen W. Morris

Icicles that have grown from slightly impure water develop ripples around their circumference. The ripples have a near-universal wavelength and are thought to be the result of a morphological instability. Using laboratory-grown icicles and various species of impurities, including fluorescent dye, we show that a certain fraction of the impurities remain trapp

Reed Essick, Will M. Farr, Maya Fishbach, Daniel E. Holz

We constrain the distribution of merging compact binaries across the celestial sphere using the GWTC-3 catalog from the LIGO-Virgo-KAGRA Collaborations' (LVK) third observing run. With 63 confident detections from O3, we constrain the relative variability (standard deviation) of the rate density across the sky to be $\lesssim 16\%$ at 90\% confidence assumin

Chirag Raman, Navin Raj Prabhu, Hayley Hung

The quality of daily spontaneous conversations is of importance towards both our well-being as well as the development of interactive social agents. Prior research directly studying the quality of social conversations has operationalized it in narrow terms, associating greater quality to less small talk. Other works taking a broader perspective of interactio

Blair Davey, Joshua Isralowitz

In this article, we investigate systems of generalized Schr\"odinger operators and their fundamental matrices. More specifically, we establish the existence of such fundamental matrices and then prove sharp upper and lower exponential decay estimates for them. The Schr\"odinger operators that we consider have leading coefficients that are bounded and uniform

Darren C. Pagan, Md Abu Jafar Rasel, Rachel E. Lim, Dina Sheyfer

Localized residual stress and elastic strain concentrations in microelectronic devices often affect the electronic performance, resistance to thermomechanical damage, and, likely, radiation tolerance. A primary challenge for characterization of these concentrations is that they exist over sub-$\mu$m length-scales, precluding their characterization by more tr

Mattia Angeli, Gabriel R. Schleder, Efthimios Kaxiras

Twisted multilayers of two-dimensional (2D) materials are an increasingly important platform for investigating quantum phases of matter, and in particular, strongly correlated electrons. The moir\'e pattern introduced by the relative twist between layers creates effective potentials of long-wavelength, leading to electron localization. However, in contrast t

Charles Schwartz

The mission here is to see if we can find bound states for tachyons in some gravitational environment. That could provide an explanation for the phenomena called Dark Matter. Starting with the standard Schwarzschild metric in General Relativity, which is for a static and spherically symmetric source, it appears unlikely that such localized orbits exist. In t

Yousef Yeganeh, Azade Farshad, Nassir Navab

Inpainting has recently been proposed as a successful deep learning technique for unsupervised medical image model discovery. The masks used for inpainting are generally independent of the dataset and are not tailored to perform on different given classes of anatomy. In this work, we introduce a method for generating shape-aware masks for inpainting, which a

Subhajit Pal, Colin Benjamin

We predict that the occurence of zero energy Yu-Shiba-Rusinov(YSR) bound states in two different setups, metal-spin flipper-metal-s-wave superconductor ($N_{1}-sf-N_{2}-S$) and superconductor-metal-spin flipper-metal-superconductor ($S-N_{1}-sf-N_{2}-S$) junctions, can generate multi-fold enhancement of surface-induced odd-frequency superconductivity. On the

Ziyang Zong, Jun He, Lei Zhang, Hai Huan

In theory, the success of unsupervised domain adaptation (UDA) largely relies on domain gap estimation. However, for source free UDA, the source domain data can not be accessed during adaptation, which poses great challenge of measuring the domain gap. In this paper, we propose to use many classifiers to learn the source domain decision boundaries, which pro

Harlin Lee, Aaqib Saeed

This work introduces BRILLsson, a novel binary neural network-based representation learning model for a broad range of non-semantic speech tasks. We train the model with knowledge distillation from a large and real-valued TRILLsson model with only a fraction of the dataset used to train TRILLsson. The resulting BRILLsson models are only 2MB in size with a la

Panpan Fang, Yi-Xiang Wang, Fuxiang Li

Dynamical characterization of equilibrium topological phases has attracted considerable attention in recent years. In this paper, we make a thorough exploration of the non-adiabatic characterization of topological phases under slow quench protocol. We first propose an exactly solvable multi-state Landau-Zener model that can be directly applied to the non-adi

Xu Han, Chang-Ling Zou, Wei Fu, Mingrui Xu

We present a nonlinear multimode superconducting electroacoustic system, where the interplay between superconducting kinetic inductance and piezoelectric strong coupling establishes an effective Kerr nonlinearity among multiple acoustic modes at 10 GHz that could hardly be achieved via intrinsic mechanical nonlinearity. By exciting this multimode Kerr system

Nico Ackermann, Alex Zazunov, Sunghun Park, Reinhold Egger

Excess quasiparticles play a crucial role in superconducting quantum devices ranging from qubits to quantum sensors. In this work we analyze their dynamics for phase-biased finite-length weak links with several Andreev subgap states, where the coupling to a microwave resonator allows for parity state (even/odd) readout. Our theory shows that almost perfect d

Tong Wu, Jing Guo

A multiscale simulation approach is developed to simulate the contact transport properties between semimetal to a monolayer two-dimensional (2D) transition metal dichalcogenide (TMDC) semiconductor. The results elucidate the mechanisms for low contact resistance between semimetal and TMDC semiconductor contacts from a quantum transport perspective. The simul

Mauro Cirio, Neill Lambert, Pengfei Liang, Po-Chen Kuo

We develop a discrete fermion approach for modelling the strong interaction of an arbitrary system interacting with continuum electronic reservoirs. The approach is based on a pseudo-fermion decomposition of the continuum bath correlation functions, and is only limited by the accuracy of this decomposition. We show that to obtain this decomposition one can a

Dimitrios G. Patsatzis, Lucia Russo, Ioannis G. Kevrekidis, Constantinos Siettos

We present an Equation/Variable free machine learning (EVFML) framework for the control of the collective dynamics of complex/multiscale systems modelled via microscopic/agent-based simulators. The approach obviates the need for construction of surrogate, reduced-order models.~The proposed implementation consists of three steps: (A) from high-dimensional age

Niklas Götz, Hannah Elfner

In this work, the qualitative impact of the net baryochemical potential dependence of the shear viscosity to entropy density ratio $\eta/s$ in hydrodynamical simulations is studied. The effect of a predicted non-constant $\eta/s$($\mu_B$) is largely unexplored in hydrodynamic simulations. Previous studies focus only on a temperature dependence or even only a

Liam Peet-Pare, Nidhi Hegde, Alona Fyshe

Fairness researchers in machine learning (ML) have coalesced around several fairness criteria which provide formal definitions of what it means for an ML model to be fair. However, these criteria have some serious limitations. We identify four key shortcomings of these formal fairness criteria, and aim to help to address them by extending performative predic

Florian Domingo, Sebastian Paßehr

The heavy, doublet-dominated Higgs bosons expected in Two-Higgs-Doublet-Model-like extensions of the Standard Model are obvious targets for searches at high-energy colliders, and considerable activity in this sense is currently employed in analyzing the results of the Large Hadron Collider. For sufficiently heavy states, the $SU(2)_{\mathrm{L}}$ symmetry dra

Sergei Gukov, Artan Sheshmani, Shing-Tung Yau

We initiate explicit computations of Vafa-Witten invariants of 3-manifolds, analogous to Floer groups in the context of Donaldson theory. In particular, we explicitly compute the Vafa-Witten invariants of 3-manifolds in a family of concrete examples relevant to various surgery operations (the Gluck twist, knot surgeries, log-transforms). We also describe the

Rounak Meyur, Anil Vullikanti, Samarth Swarup, Henning Mortveit

The power grid is going through significant changes with the introduction of renewable energy sources and incorporation of smart grid technologies. These rapid advancements necessitate new models and analyses to keep up with the various emergent phenomena they induce. A major prerequisite of such work is the acquisition of well-constructed and accurate netwo

Rui Dilão, Nuno Teixeira

We present a solvable biped walking model based on an inverted pendulum with two massless articulated legs capable of walking on uneven floors and inclined planes. The stride of the two-legged robot results from the pendular motion of a standing leg and the articulated motion of a trailing leg. Gaiting is possible due to the alternating role of the legs, the

S. Vallières, J. Powell, T. Connell, M. Evans

Ultrashort electron beams with femtosecond to picosecond bunch durations offer unique opportunities to explore active research areas ranging from ultrafast structural dynamics to ultra-high dose-rate radiobiological studies. We present a straightforward method to generate MeV-ranged electron beams in ambient air through the tight focusing of a few-cycle, mJ-

Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio

Much of the complexity of Recommender Systems (RSs) comes from the fact that they are used as part of more complex applications and affect user experience through a varied range of user interfaces. However, research focused almost exclusively on the ability of RSs to produce accurate item rankings while giving little attention to the evaluation of RS behavio

J. Chisholm, A. Saldana-Lopez, S. Flury, D. Schaerer

Most of the hydrogen in the intergalactic medium (IGM) was rapidly ionized at high-redshifts. While observations have established that reionization occurred, observational constraints on the emissivity of ionizing photons at high-redshift remains elusive. Here, we present a new analysis of the Low-redshift Lyman Continuum Survey (LzLCS) and archival observat

R. M. González Delgado, J. E. Rodríguez-Martín, L. A. Díaz-García, A. de Amorim

The miniJPAS survey has observed $\sim 1$ deg$^2$ on the AEGIS field with 60 bands (spectral resolution of $R \sim 60$) in order to demonstrate the capabilities of the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) that will map $\sim 8000$ deg$^2$ of the northern sky in the next years. This paper shows the power of J-PAS to det

Greg Landsberg

In this talk, I give a historical and personal overview of the events that lead to the discovery of the Higgs boson by the ATLAS and CMS experiments in 2012, and highlight the childhood years of the Higgs boson studies at the Large Hadron Collider. These recollections are based on my time as the CMS Physics Coordinator (2012-2013), and because of this they a

Nicoletta Carabba, Niklas Hörnedal, Adolfo del Campo

Quantum speed limits (QSLs) identify fundamental time scales of physical processes by providing lower bounds on the rate of change of a quantum state or the expectation value of an observable. We introduce a generalization of QSL for unitary operator flows, which are ubiquitous in physics and relevant for applications in both the quantum and classical domain

Yuxun Guo, Xiangdong Ji, Kyle Shiells

We present a global analysis program for the generalized parton distributions (GPDs) based on conformal moment expansion. We apply the strategy of universal moment parameterization to fit both the collinear parton distribution functions (PDFs) from phenomenology and generalized form factors from lattice calculations, and show that the parameterization is fle

Haipeng An, Shuailiang Ge, Wen-Qing Guo, Xiaoyuan Huang

Dark photons can be the ultralight dark matter candidate, interacting with Standard Model particles via kinetic mixing. We propose to search for ultralight dark photon dark matter (DPDM) through the local absorption at different radio telescopes. The local DPDM can induce harmonic oscillations of electrons inside the antenna of radio telescopes. It leads to

DES Collaboration, T. M. C. Abbott, M. Aguena, A. Alarcon

We constrain extensions to the $\Lambda$CDM model using measurements from the Dark Energy Survey's first three years of observations and external data. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data and blind analyses of real data to validate the robust

Pavan Kumar Aluri, Paolo Cea, Pravabati Chingangbam, Ming-Chung Chu

The Cosmological Principle (CP) -- the notion that the Universe is spatially isotropic and homogeneous on large scales -- underlies a century of progress in cosmology. It is conventionally formulated through the Friedmann-Lema\^itre-Robertson-Walker (FLRW) cosmologies as the spacetime metric, and culminates in the successful and highly predictive $\Lambda$-C

Monica Jinwoo Kang, Craig Lawrie, Ki-Hong Lee, Matteo Sacchi

The Higgs branch of 4d $\mathcal{N}=2$ SCFTs can be analyzed via the Hilbert series of the Higgs branch or, in special cases, by computing the Hall-Littlewood index. For any class $\mathcal{S}$ theory corresponding to a genus-zero Riemann surface, they are conjectured to be identical. We present several families of counterexamples. We find that for any class

Aymeric Galan, Georgios Vernardos, Austin Peel, Frédéric Courbin

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a large range in spatial scale, mass scale, and morphology. In this work, we address the problem with a nove

Martin Bauer, Guillaume Rostagni, Jonas Spinner

The phenomenology of axions and axion-like particles strongly depends on their couplings to Standard Model particles. The focus of this paper is the phenomenology of the unique dimension six operator respecting the shift symmetry: the axion-Higgs portal. We compare constraints from Higgs physics, flavor violating and radiative meson decays, bounds from atomi

David M. Long, Philip J. D. Crowley, Vedika Khemani, Anushya Chandran

The dynamical phase diagram of interacting disordered systems has seen substantial revision over the past few years. Theory must now account for a large prethermal many-body localized (MBL) regime in which thermalization is extremely slow, but not completely arrested. We derive a quantitative description of these dynamics in short-ranged one-dimensional syst

Mor Rozner

The meter-size barrier in protoplanetary disks is a major challenge in planet formation, for which many solutions were suggested. One of the leading solutions is dust traps, that halt or slow the inward migration of dust particles. The source and profile of these traps are still not completely known. Warped disks are ubiquitous among accretion disks in gener

Elizabeth A. Ellithorpe, Nathan A. Kaib

The majority of binary star systems that host exoplanets will spend the first portion of their lives within a star-forming cluster that may drive dynamical evolution of the binary-planet system. We perform numerical simulations of S-type planets, with masses and orbital architecture analogous to the solar system's 4 gas giants, orbiting within the influence

A. Songaila, A. J. Barger, L. L. Cowie, E. M. Hu

Recent evidence suggests that high-redshift Ly-alpha emitting galaxies (LAEs) with logL(Ly-alpha) > 43.5 erg/s, referred to as ultraluminous LAEs (ULLAEs), may show less evolution than lower-luminosity LAEs in the redshift range z=5.7-6.6. Here we explore the redshift evolution of the velocity widths of the Ly-alpha emission lines in LAEs over this redshift

Gilad Sadeh, Or Guttman, Eli Waxman

Binary neutron star mergers are expected to produce fast dynamical ejecta, with mildly relativistic velocities extending to $\beta=v/c>0.6$. We consider the radio to X-ray synchrotron emission produced by collisionless shocks driven by such fast ejecta into the interstellar medium. Analytic expressions are given for spherical ejecta with broken power-law mas

Daniel Han, Taysun Kimm, Harley Katz, Julien Devriendt

To understand the impact of radiation feedback during the formation of a globular cluster (GC), we simulate a head-on collision of two turbulent giant molecular clouds (GMCs). A series of idealized radiation-hydrodynamic simulations is performed, with and without stellar radiation or Type II supernovae. We find that a gravitationally bound, compact star clus

Elena F. Sheka

A still amazing identity of the D-G doublet Raman spectra of parental and reduced graphene oxides is considered from the digital twins viewpoint. About thirty DTs, presenting different aspects of the GO structure and properties, were virtually synthesized using atomic spin-density algorithm, which allowed reliably displaying reasons for this extraordinary sp

Kevin Purbhoo

As part of the proof of the Bethe ansatz conjecture for the Gaudin model for $\mathfrak{gl}_n$, Mukhin, Tarasov, and Varchenko described a correspondence between inverse Wronskians of polynomials and eigenspaces of the Gaudin Hamiltonians. Notably, this correspondence afforded the first proof of the Shapiro-Shapiro conjecture. In the present paper, we give a

Christian Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu

In lifelong learning, an agent learns throughout its entire life without resets, in a constantly changing environment, as we humans do. Consequently, lifelong learning comes with a plethora of research problems such as continual domain shifts, which result in non-stationary rewards and environment dynamics. These non-stationarities are difficult to detect an

Paritosh Karnatak, Zarina Mingazheva, Kenji Watanabe, Takashi Taniguchi

Superconductivity in van der Waals materials, such as NbSe$_{2}$ and TaS$_{2}$, is fundamentally novel due to the effects of dimensionality, crystal symmetries, and strong spin-orbit coupling. In this work we perform tunnel spectroscopy on NbSe$_{2}$ by utilizing MoS$_{2}$ or hexagonal Boron Nitride (hBN) as a tunnel barrier. We observe subgap excitations an

Tobias Fritz, Andreas Klingler

The d-separation criterion detects the compatibility of a joint probability distribution with a directed acyclic graph through certain conditional independences. In this work, we study this problem in the context of categorical probability theory by introducing a categorical definition of causal models, a categorical notion of d-separation, and proving an ab

Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong

It is commonly believed that in transfer learning including more pre-training data translates into better performance. However, recent evidence suggests that removing data from the source dataset can actually help too. In this work, we take a closer look at the role of the source dataset's composition in transfer learning and present a framework for probing

Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee

In this paper we study online Reinforcement Learning (RL) in partially observable dynamical systems. We focus on the Predictive State Representations (PSRs) model, which is an expressive model that captures other well-known models such as Partially Observable Markov Decision Processes (POMDP). PSR represents the states using a set of predictions of future ob

Shijie Wu

NLP systems typically require support for more than one language. As different languages have different amounts of supervision, cross-lingual transfer benefits languages with little to no training data by transferring from other languages. From an engineering perspective, multilingual NLP benefits development and maintenance by serving multiple languages wit

Burak Dagli, Bora Ketenoglu, Arif Ozturk, Saleh Sultansoy

Construction of future Muon Collider (or dedicated mu-ring) tangential to nucleus colliders will give opportunity to realize mu-A collisions at multi-TeV center of mass energies at a luminosity of order of 10^29-10^30 cm^-2s^-1. Obviously, such colliders will essentially enlighten fundamentals of strong interactions from quark to nucleus levels as well as cl