July 2022 arXiv papers — page 18

Abhijay Ghildyal, Feng Liu

Existing perceptual similarity metrics assume an image and its reference are well aligned. As a result, these metrics are often sensitive to a small alignment error that is imperceptible to the human eyes. This paper studies the effect of small misalignment, specifically a small shift between the input and reference image, on existing metrics, and accordingl

Alan C. Calder, Catherine Feldman, Eva Siegmann, John Dey

We present efforts at improving the performance of FLASH, a multi-scale, multi-physics simulation code principally for astrophysical applications, by using huge pages on Ookami, an HPE Apollo 80 A64FX platform. FLASH is written principally in modern Fortran and makes use of the PARAMESH library to manage a block-structured adaptive mesh. We explored options

Rowan Border, Jonathan D. Gammell

High-quality observations of the real world are crucial for a variety of applications, including producing 3D printed replicas of small-scale scenes and conducting inspections of large-scale infrastructure. These 3D observations are commonly obtained by combining multiple sensor measurements from different views. Guiding the selection of suitable views is kn

Gabriel Martínez-Carracedo, László Oroszlány, Amador García-Fuente, László Szunyogh

Recently, graphene triangulene chains have been synthesized and their magnetic response has been analyzed by STM methods by Mishra and coworkers (Nature 598, 287 (2021)). Motivated by this study, we determine the exchange bilinear and biquadratic constants of the triangulene chains by calculating two-spin rotations in the spirit of the magnetic force theorem

Elsa M. Teixeira, Bruno J. Barros, Vasco M. C. Ferreira, Noemi Frusciante

We investigate an interacting dark energy model which allows for the kinetic term of the scalar field to couple to dark matter via a power-law interaction. The model is characterised by scaling solutions at early times, which are of high interest to alleviate the coincidence problem, followed by a period of accelerated expansion. We discuss the phenomenology

Remi A. Chou

Consider a user who wishes to store a file in multiple servers such that at least t servers are needed to reconstruct the file, and z colluding servers cannot learn any information about the file. Unlike traditional secret-sharing models, where perfectly secure channels are assumed to be available at no cost between the user and each server, we assume that t

John Hannegan, James D. Siverns, Qudsia Quraishi

Future quantum networks will require the ability to produce matter-photon entanglement at photon frequencies not naturally emitted from the matter qubit. This allows for a hybrid network architecture, where these photons can couple to other tools and quantum technologies useful for tasks such as multiplexing, routing, and storage, but which operate at wavele

Fiorella Rendón, Boyan Sirakov, Mayra Soares

We obtain a global extension of the classical weak Harnack inequality which extends and quantifies the Hopf-Oleinik boundary-point lemma, for uniformly elliptic equations in divergence form. Among the consequences is a boundary gradient estimate, due to Krylov and well-studied for non-divergence form equations, but completely novel in the divergence framewor

Aristotelis Ballas, Christos Diou

Convolutional Neural Networks have become the norm in image classification. Nevertheless, their difficulty to maintain high accuracy across datasets has become apparent in the past few years. In order to utilize such models in real-world scenarios and applications, they must be able to provide trustworthy predictions on unseen data. In this paper, we argue t

G. Parimbelli, C. Carbone, J. Bel, B. Bose

We provide an accurate comparison, against large cosmological $N$-body simulations, of different prescriptions for modelling nonlinear matter power spectra in the presence of massive neutrinos and dynamical dark energy. We test the current most widely used approaches: fitting functions (HALOFIT and HMcode), the halo-model reaction (ReACT) and emulators (bacc

Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski

Vizier is the de-facto blackbox and hyperparameter optimization service across Google, having optimized some of Google's largest products and research efforts. To operate at the scale of tuning thousands of users' critical systems, Google Vizier solved key design challenges in providing multiple different features, while remaining fully fault-tolerant. In th

W. Imoehl

Despite being extensively studied since their initial discovery in 2003, the XYZ states do not yet have a clear interpretation. BESIII recently collected additional data above 4 GeV which can be used to further study these exotic hadron candidates. We present recent studies of $X(3872)\to\pi^0\chi_{c0}$, $e^+e^-\to K^+K^-J/\psi$, $e^+e^-\to$ light hadrons, $

Nicholas F. Marshall, Oscar Mickelin, Amit Singer

We present a fast and numerically accurate method for expanding digitized $L \times L$ images representing functions on $[-1,1]^2$ supported on the disk $\{x \in \mathbb{R}^2 : |x|<1\}$ in the harmonics (Dirichlet Laplacian eigenfunctions) on the disk. Our method, which we refer to as the Fast Disk Harmonics Transform (FDHT), runs in $O(L^2 \log L)$ operatio

Nikolay Barashkov, Trishen S. Gunaratnam, Michael Hofstetter

We establish a coupling between the $\mathcal{P}(\phi)_2$ measure and the Gaussian free field on the two-dimensional unit torus at all spatial scales, quantified by probabilistic regularity estimates on the difference field. Our result includes the well-studied $\phi^4_2$ measure. The proof uses an exact correspondence between the Polchinski renormalisation

Jerzy Dydak, Hussain Rashed

For every proper geodesic space $X$ we introduce its quasi-geometric boundary $\partial_{QG}X$ with the following properties: 1. Every geodesic ray $g$ in $X$ converges to a point of the boundary $\partial_{QG}X$ and for every point $p$ in $\partial_{QG}X$ there is a geodesic ray in $X$ converging to $p$, 2. The boundary $\partial_{QG}X$ is compact metric, 3

Amanda D. French, Sonia Alcantar Anguiano, Mary Bliss, Josef Christ

New data are reported for polyvinylidene fluoride (PVDF), polyphenylene sulfide (PPS), and two forms of polyetherimide (PEI, branded ULTEM 1010 and 9085). Data for starting filaments and both simple and complex printed parts are reported. PVDF filaments and simple printed beads, were found to have values of approximately 30 and 50 ppt for Th-232 and U-238, r

Shixing Yu, Yiyang Ma, Wenhan Yang, Wei Xiang

Existing video frame interpolation methods can only interpolate the frame at a given intermediate time-step, e.g. 1/2. In this paper, we aim to explore a more generalized kind of video frame interpolation, that at an arbitrary time-step. To this end, we consider processing different time-steps with adaptively generated convolutional kernels in a unified way

S. Bethapudi, L. G. Spitler, R. A. Main, D. Z. Li

FRB 20180916B is a repeating fast radio burst (FRB) with an activity period of 16.33 days. In previous observations ranging from $\sim 150-1400$ MHz, the activity window was found to be frequency dependent, with lower frequency bursts occurring later. In this work, we present the highest-frequency detections of bursts from this FRB, using the 100-m Effelsber

Xiyuan Lu, Ashish Chanana, Feng Zhou, Marcelo Davanco

Continuous wave optical parametric oscillation (OPO) provides a flexible approach for accessing mid-infrared wavelengths between 2 $\mu$m to 5 $\mu$m, but has not yet been integrated into silicon nanophotonics. Typically, Kerr OPO uses a single transverse mode family for pump, signal, and idler modes, and relies on a delicate balance to achieve normal (but c

Elīza Gaile, Andis Draguns, Emīls Ozoliņš, Kārlis Freivalds

There has been a growing number of machine learning methods for approximately solving the travelling salesman problem. However, these methods often require solved instances for training or use complex reinforcement learning approaches that need a large amount of tuning. To avoid these problems, we introduce a novel unsupervised learning approach. We use a re

Lalitha Chavali, Tanay Gupta, Paresh Saxena

Intrusion detection systems (IDS) generate a large number of false alerts which makes it difficult to inspect true positives. Hence, alert prioritization plays a crucial role in deciding which alerts to investigate from an enormous number of alerts that are generated by IDS. Recently, deep reinforcement learning (DRL) based deep deterministic policy gradient

V. A. Traag, L. Waltman

The study of biases, such as gender or racial biases, is an important topic in the social and behavioural sciences. However, the literature does not always clearly define the concept. Definitions of bias are often ambiguous or not provided at all. To study biases in a precise manner, it is important to have a well-defined concept of bias. We propose to defin

Alex S. Polanski, Ian J. M. Crossfield, Andrew W. Howard, Howard Isaacson

Using a data-driven machine learning tool we report $T_{\text{eff}}$, $\log{(g)}$, $v\sin{(i)}$, and elemental abundances for 15 elements (C, N, O, Na, Mg, Al, Si, Ca, Ti, V, Cr, Mn, Fe, Ni, Y) for a sample of 25 exoplanet host stars targeted by JWST's first year of observations. The chemical diversity of these stars show that, while a number of their compan

Jan Křetínský, Tobias Meggendorfer, Maximilian Weininger

We consider the problem of computing minimum and maximum probabilities of satisfying an $\omega$-regular property in a bounded-parameter Markov decision process (BMDP). BMDP arise from Markov decision processes (MDP) by allowing for uncertainty on the transition probabilities in the form of intervals where the actual probabilities are unknown. $\omega$-regul

Loyd Waites, Adrian Thompson, Adriana Bungau, Janet M. Conrad

Searches for axion-like particles (ALPs) are motivated by the strong CP problem in particle physics and by unexplained dark matter in astrophysics. In this letter, we discuss novel ALP searches using monoenergetic nuclear de-excitation photons from a beam dump, using IsoDAR as an example. We show that IsoDAR can set limits that close a gap in traditional QCD

Lynnette Hui Xian Ng, Kathleen M. Carley

Despite rapid development, current bot detection models still face challenges in dealing with incomplete data and cross-platform applications. In this paper, we propose BotBuster, a social bot detector built with the concept of a mixture of experts approach. Each expert is trained to analyze a portion of account information, e.g. username, and are combined t

David Torpey, Richard Klein

It is known that representations from self-supervised pre-training can perform on par, and often better, on various downstream tasks than representations from fully-supervised pre-training. This has been shown in a host of settings such as generic object classification and detection, semantic segmentation, and image retrieval. However, some issues have recen

Ben Heuer

For any smooth proper rigid space $X$ over a complete algebraically closed extension $K$ of $\mathbb Q_p$ we give a geometrisation of the $p$-adic Simpson correspondence of rank one in terms of analytic moduli spaces: The $p$-adic character variety is canonically an \'etale twist of the moduli space of topological torsion Higgs line bundles over the Hitchin

Niccolò Ajroldi, Jacopo Diquigiovanni, Matteo Fontana, Simone Vantini

Time evolving surfaces can be modeled as two-dimensional Functional time series, exploiting the tools of Functional data analysis. Leveraging this approach, a forecasting framework for such complex data is developed. The main focus revolves around Conformal Prediction, a versatile nonparametric paradigm used to quantify uncertainty in prediction problems. Bu

Maxym Dudka, Mariana Krasnytska, Juan J. Ruiz-Lorenzo, Yurij Holovatch

Changes in magnetic critical behaviour of quenched structurally-disordered magnets are usually exemplified in experiments and in MC simulations by diluted systems consisting of magnetic and non-magnetic components. By our study we aim to show, that similar effects can be observed not only for diluted magnets with non-magnetic impurities, but may be implement

S. A. Paston, T. I. Zaitseva

We study embedding gravity, a modified theory of gravity, in which our space-time is assumed to be a four-dimensional surface in flat ten-dimensional space. Based on a simple geometric idea, this theory can be reformulated as General Relativity with additional degrees of freedom and contribution to action, which can be interpreted as describing dark matter.

Or Katz, Christopher Monroe

Trapped atomic ion crystals are a leading platform for quantum simulations of spin systems, with programmable and long-range spin-spin interactions mediated by excitations of phonons in the crystal. We describe a complementary approach for quantum simulations of bosonic systems using phonons in trapped-ion crystals, here mediated by excitations of the trappe

Everton M. C. Abreu, Jorge Ananias Neto

One of the challenges of today's theoretical physics is to fully understand the connection between a geometrical object like area and a thermostatistical one like entropy, since area behaves analogously like entropy. The Bekenstein bound suggests a universal constraint for the entropy of a region in a flat space. The Bekenstein-Hawking entropy of black holes

Jacob Fox, Sammy Luo, Huy Tuan Pham

Let $G$ be a $d$-regular graph on $n$ vertices. Frieze, Gould, Karo\'nski and Pfender began the study of the following random spanning subgraph model $H=H(G)$. Assign independently to each vertex $v$ of $G$ a uniform random number $x(v) \in [0,1]$, and an edge $(u,v)$ of $G$ is an edge of $H$ if and only if $x(u)+x(v) \geq 1$. Addressing a problem of Alon an

Bo Ning, Long-tu Yuan

In this paper, we study the stability result of a well-known theorem of Bondy. We prove that for any 2-connected non-hamiltonian graph, if every vertex except for at most one vertex has degree at least $k$, then it contains a cycle of length at least $2k+2$ except for some special families of graphs. Our results imply several previous classical theorems incl

Artyom Sorokin, Nazar Buzun, Leonid Pugachev, Mikhail Burtsev

In many sequential tasks, a model needs to remember relevant events from the distant past to make correct predictions. Unfortunately, a straightforward application of gradient based training requires intermediate computations to be stored for every element of a sequence. This requires to store prohibitively large intermediate data if a sequence consists of t

Zachary Deridder, Nyle Siddiqui, Thomas Reither, Rushit Dave

As technology grows and evolves rapidly, it is increasingly clear that mobile devices are more commonly used for sensitive matters than ever before. A need to authenticate users continuously is sought after as a single-factor or multi factor authentication may only initially validate a user, which does not help if an impostor can bypass this initial validati

Sriram Siva, Maggie Wigness, John G. Rogers, Long Quang

When robots operate in real-world off-road environments with unstructured terrains, the ability to adapt their navigational policy is critical for effective and safe navigation. However, off-road terrains introduce several challenges to robot navigation, including dynamic obstacles and terrain uncertainty, leading to inefficient traversal or navigation failu

Benjamin Strekha, Sean Molesky, Pengning Chao, Matthias Krüger

We exploit fluctuational electrodynamics to present trace expressions for the torque experienced by arbitrary objects in a passive, non-absorbing, rotationally invariant background environment. Specializing to a single object, this formalism, together with recently developed techniques for calculating bounds via Lagrange duality, is then used to derive limit

Kaitlin Gili, Mohamed Hibat-Allah, Marta Mauri, Chris Ballance

In recent proposals of quantum circuit models for generative tasks, the discussion about their performance has been limited to their ability to reproduce a known target distribution. For example, expressive model families such as Quantum Circuit Born Machines (QCBMs) have been almost entirely evaluated on their capability to learn a given target distribution

Jacob Mallet, Rushit Dave, Naeem Seliya, Mounika Vanamala

In the recent years, social media has grown to become a major source of information for many online users. This has given rise to the spread of misinformation through deepfakes. Deepfakes are videos or images that replace one persons face with another computer-generated face, often a more recognizable person in society. With the recent advances in technology

Jeremy R. Lilly, Giacomo Capodaglio, Mark R. Petersen, Steven R. Brus

This paper presents the first scientific application of local time-stepping (LTS) schemes in the Model for Prediction Across Scales-Ocean (MPAS-O). We use LTS schemes in a single-layer, global ocean model that predicts the storm surge around the eastern coast of the United States during Hurricane Sandy. The variable-resolution meshes used are of unprecedente

Nishant Kumar, Sudhan Majhi, A. K. Upadhyay

In this paper, we propose a direct construction of a novel type of code set, which has combined properties of complete complementary code (CCC) and zero-correlation zone (ZCZ) sequences and called it complete complementary-ZCZ (CC-ZCZ) code set. The code set is constructed by using multivariable functions. The proposed construction also provides Golay-ZCZ co

Sushrut Thakar, Deepak Ramasubramanian

The increasing number of inverter based resources (IBRs) connected to modern power systems necessitate accurate modeling of IBRs in stability studies. Measurement-based modeling approaches can create an impedance/admittance model of IBRs to be subsequently used in small signal stability studies. Such measurement-based approaches have previously been successf

Jeremy Côté, Stefanos Kourtis

Many elusive quantum phenomena emerge from the interaction of a quantum system with its classical environment. Quantum simulators enable us to program this interaction by using measurement operations. Measurements generally remove part of the quantum entanglement built between the qubits inside a simulator. While in simple cases entanglement may disappear at

Kris Shaw, Annette Werner

This paper investigates isomorphisms of Bergman fans of matroids respecting different fan structures, which we regard as matroid analogs of birational maps. We show that isomorphisms respecting the fine fan structure are induced by matroid isomorphisms. We introduce Cremona automorphisms of the coarse structure of Bergman fans, which are not induced by matro

M. Yusuf Özkaya, Ümit V. Çatalyürek

This work addresses the NP-Hard problem of acyclic directed acyclic graph (DAG) partitioning problem. The acyclic partitioning problem is defined as partitioning the vertex set of a given directed acyclic graph into disjoint and collectively exhaustive subsets (parts). Parts are to be assigned such that the total sum of the vertex weights within each part sa

Borys Kadets

The paper is concerned with the following version of Hilbert's irreducibility theorem: if $\pi: X \to Y$ is a Galois $G$-covering of varieties over a number field $k$ and $H \subset G$ is a subgroup, then for all sufficiently large and sufficiently divisible $n$ there exist a degree $n$ closed point $y \in |Y|$ and $x \in \pi^{-1}(y)$ for which $k(x)/k(y)$ i

Matteo Capoferri, Leonid Friedlander, Michael Levitin, Dmitri Vassiliev

We establish the two-term spectral asymptotics for boundary value problems of linear elasticity on a smooth compact Riemannian manifold of arbitrary dimension. We also present some illustrative examples and give a historical overview of the subject. In particular, we correct erroneous results published in [J. Geom. Anal. 31 (2021), 10164--10193].

Mikhail Karpukhin, Daniel Stern

We prove the existence of nonconstant harmonic maps of optimal regularity from an arbitrary closed manifold $(M^n,g)$ of dimension $n>2$ to any closed, non-aspherical manifold $N$ containing no stable minimal two-spheres. In particular, this gives the first general existence result for harmonic maps from higher-dimensional manifolds to a large class of posit

M. Gordon, W. H. Li, M. B. Andorf, A. C. Bartnik

Ultrafast electron diffraction (UED) is a technique in which short-pulse electron beams can probe the femtosecond-scale evolution of atomic structure in matter driven far from equilibrium. As an accelerator physics challenge, UED imposes stringent constraints on the brightness of the probe electron beam. The low normalized emittance employed in UED, often at

Haoxiang Li, Peipei Hao, Junjie Zhang, Kyle Gordon

The recent discovery of superconductivity in hole-doped planar nickelates R1-xSrNiO2 (R=Pr,Nd) raises the foundational question of how the electronic structure and electronic correlations of these Ni1+ compounds compare to those of the Cu2+ cuprate superconductors. Here, we present an Angle-Resolved Photoemission Spectroscopy (ARPES) study of the trilayer ni

Mark Tygert

Prior proposals for cumulative statistics suggest making tiny random perturbations to the scores (independent variables in a regression) in order to ensure the scores' uniqueness. Uniqueness means that no score for any member of the population or subpopulation being analyzed is exactly equal to any other member's score. It turns out to be possible to constru

Arne J. Klomp, Lukas Porz, Karsten Albe

The nature of mechanically induced dislocations in SrTiO3 at low temperatures has been a disputed matter for a long time. Here we provide a systematic overview of the existing knowledge on dislocations in stoichiometric SrTiO3 complemented by computational models of several of the proposed dislocation types. Based on atomistic simulations we reveal their str

Yiheng Li, Connelly Barnes, Kun Huang, Fang-Lue Zhang

Optical flow computation is essential in the early stages of the video processing pipeline. This paper focuses on a less explored problem in this area, the 360$^\circ$ optical flow estimation using deep neural networks to support increasingly popular VR applications. To address the distortions of panoramic representations when applying convolutional neural n

Robin Brown, David E. Bernal Neira, Davide Venturelli, Marco Pavone

Recent years have seen significant advances in quantum/quantum-inspired technologies capable of approximately searching for the ground state of Ising spin Hamiltonians. The promise of leveraging such technologies to accelerate the solution of difficult optimization problems has spurred an increased interest in exploring methods to integrate Ising problems as

Cagri Kilic, Yu Gu, Jason N. Gross

Slip detection is of fundamental importance for the safety and efficiency of rovers driving on the surface of extraterrestrial bodies. Current planetary rover slip detection systems rely on visual perception on the assumption that sufficient visual features can be acquired in the environment. However, visual-based methods are prone to suffer in perceptually

Maxime Lucas, Lorenzo Piroli, Jacopo De Nardis, Andrea De Luca

In non-interacting isolated quantum systems out of equilibrium, local subsystems typically relax to non-thermal stationary states. In the standard framework, information on the rest of the system is discarded, and such states are described by a Generalized Gibbs Ensemble (GGE), maximizing the entropy while respecting the constraints imposed by the local cons

Emanuela L. Giacomelli

We consider the Neumann realization of the magnetic laplacian in $\mathbb{R}^3_+$, in the case in which the magnetic field has a piecewise constant strength and a uniform direction. This operator is expected to be an effective model in studying the threshold to the normal state for a 3D superconductor exposed to a discontinuous magnetic field. We review some

Jon E. Froehlich, Michael Saugstad, Manaswi Saha, Matthew Johnson

Despite the important role of sidewalks in supporting mobility, accessibility, and public health, there is a lack of high-quality datasets and corresponding analyses on sidewalk existence and condition. Our work explores a twofold vision: first, to develop scalable mechanisms to locate and assess sidewalks in cities across the world, and second, to use this

Danilo Marchesini, Gabriel Brammer, Takahiro Morishita, Pietro Bergamini

How passive galaxies form, and the physical mechanisms which prevent star formation over long timescales, are some of the most outstanding questions in understanding galaxy evolution. The properties of quiescent galaxies over cosmic time provide crucial information to identify the quenching mechanisms. Passive galaxies have been confirmed and studied out to

Hamza Boumaza, David Langlois

We study neutron star configurations in a simple shift-symmetric subfamily of degenerate higher-order scalar-tensor (DHOST) theories, whose deviations from General Relativity (GR) are characterized by a single parameter. We compute the radial profiles of neutron stars in these theories of modified gravity, using several realistic equations of state for the n

Volodymyr Biloshytskyi, Vladimir Pascalutsa, Lucian Harland-Lang, Bogdan Malaescu

The LHCb Collaboration has recently discovered a structure around 6.9 GeV in the double-$J/\psi$ mass distribution, possibly a first fully-charmed tetraquark state $X(6900)$. Based on vector-meson dominance (VMD) such a state should have a significant branching ratio for decaying into two photons. We show that the recorded LHC data for the light-by-light sca

Ling-Na Wu, André Eckardt

Ultracold atoms offer a unique opportunity to study many-body physics in a clean and well-controlled environment. However, the isolated nature of quantum gases makes it difficult to study transport properties of the system, which are among the key observables in condensed matter physics. In this work, we employ Markovian feedback control to synthesize two ef

Rabeya Basu, Kuntal Chakraborty

In the first part of this article we discuss the relative cases of Quillen-Suslin's local-global principle for the general quadratic (Bak's unitary) groups, and its applications for the (relative) stable and unstable $\mathrm{K}_1$-groups. The second part is dedicated to the graded version of the local-global principle for the general quadratic groups and it

Adam Broussard, Eric Gawiser, Kartheik Iyer

Measurements of short-timescale star formation variations (i.e., "burstiness") are integral to our understanding of star formation feedback mechanisms and the assembly of stellar populations in galaxies. We expand upon the work of Broussard et al. (2019) by introducing a new analysis of galaxy star formation burstiness that accounts for variations in the $Q_

Tao Zhang, Hui-Jun Yao

We introduce the concept of braided anti-flexible bialgebra and construct cocycle bicrossproduct anti-flexible bialgebras. As an application, we solve the extending problem for anti-flexible bialgebras by using some non-abelian cohomology theory.

Egon Balas, Aleksandr M. Kazachkov

We introduce $\mathcal{V}$-polyhedral disjunctive cuts (VPCs) for generating valid inequalities from general disjunctions. Cuts are critical to integer programming solvers, but the benefit from many families is only realized when the cuts are applied recursively, causing numerical instability and "tailing off" of cut strength after several rounds. To mitigat

Emanuela L. Giacomelli

In a dilute system of N fermions with spin 1/2 in three dimensions, we study the correlation energy which is given by the difference between the ground state energy and the energy of the non-interacting Fermi sea state. We review some recent results from the paper by Falconi et al. [Ann. Henri Poincar\'e 22 (2021), 2283-2353], where we make use of the almost

G. Guillamet, M. Rivero, M. Zavala-Aké, M. Vázquez

In this paper, we introduce a novel parallel contact algorithm designed to run efficiently in High-Performance Computing based supercomputers. Particular emphasis is put on its computational implementation in a multiphysics finite element code. The algorithm is based on the method of partial Dirichlet-Neumann boundary conditions and is capable to solve numer

James M. Feagin, John S. Briggs

Unbound wave packets propagating to macroscopic space and time coordinates become proportional to their (Fourier transform) momentum distribution at earlier times whereby the asymptotic coordinates and the initial momenta are connected everywhere by appropriate classical trajectories. This asymptotic imaging theorem is relevant to every quantum reaction invo

C. Brizzolari, P. Carniti, C. Cattadori, E. Cristaldo

The photon detection system of the first far detector (FD1-HD) of the DUNE experiment will detect scintillation photons produced by particle interactions in a kiloton-scale liquid Argon time projection chamber. The photon detectors of choice are silicon photomultipliers (SiPM), 6$\times$6 mm$^2$ each, arranged in groups of 48, which present a significantly l

Yukihiko Nakata

We study the existence of a periodic solution for a differential equation with distributed delay. It is shown that, for a class of distributed delay diferential quations, a symmetric period 2 solution, where the period is twice the maximum delay, is given as a periodic solution of a Hamiltonian system of ordinary differential equations. Proof of the idea is

Francesco Ballarin, Giulia Bevilacqua, Luca Lussardi, Alfredo Marzocchi

We perform a variational analysis of an elastic membrane spanning a closed curve which may sustain bending and torsion. First, we deal with parametrized curves and linear elastic membranes proving the existence of equilibria and finding first-order necessary conditions for minimizers computing the first variation. Second, we study a more general case, both f

Ming-Zhe Han, Yong-Jia Huang, Shao-Peng Tang, Yi-Zhong Fan

We investigate the neutron star (NS) equation of state (EOS) by incorporating multi-messenger data of GW170817, PSR J0030+0451, PSR J0740+6620, and state-of-the-art theoretical progresses, including the information from chiral effective field theory ($\chi$EFT) and perturbative quantum chromodynamics (pQCD) calculation. Taking advantage of the various struct

Kimia Vahdat, Sara Shashaani

In predictive modeling with simulation or machine learning, it is critical to accurately assess the quality of estimated values through output analysis. In recent decades output analysis has become enriched with methods that quantify the impact of input data uncertainty in the model outputs to increase robustness. However, most developments are applicable as

Andrew Lauziere, Ryan Christensen, Hari Shroff

The nematode Caenorhabditis elegans (C. elegans) is used as a model organism to better understand developmental biology and neurobiology. C. elegans features an invariant cell lineage, which has been catalogued and observed using fluorescence microscopy images. However, established methods to track cells in late-stage development fail to generalize once spor

Mohamed El Kadiri

Let $u$ and $v$ be two plurisubharmonic functions in the domain of definition of the Monge-Amp\`ere operator on a domain $\Omega\subset {\bf C}^n$. We prove that if $u=v$ on a plurifinely open set $U\subset \Omega$ that is Borel measurable, then $(dd^cu)^n|_U=(dd^cv)^n|_U$. This result was proved by Bedford and Taylor in the case where $u$ and $v$ are locall

Luisa Beghin, Lorenzo Cristofaro, Janusz Gajda

In the context of non-Gaussian analysis, Schneider [27] introduced grey noise measures, built upon Mittag-Leffler functions; analogously, grey Brownian motion and its generalizations were constructed (see, for example, [25], [6], [7], [8]). In this paper, we construct and study a new non-Gaussian measure, by means of the incomplete-gamma function (exploiting

Solly Coles, Richard Sharp

Consider a transitive Anosov flow on a closed $3$-manifold. After removing a finite set of null-homologous periodic orbits, we study the distribution of the remaining periodic orbits in the homology of the knot complement.

Linjie Lyu, Ayush Tewari, Thomas Leimkuehler, Marc Habermann

Given a set of images of a scene, the re-rendering of this scene from novel views and lighting conditions is an important and challenging problem in Computer Vision and Graphics. On the one hand, most existing works in Computer Vision usually impose many assumptions regarding the image formation process, e.g. direct illumination and predefined materials, to

David Kalaj

In the recent paper, \cite{tilli} Nicola and Tilli proved the Faber-Krahn inequality, which for $p=2$, states the following. If $f\in\mathcal{F}_\alpha^2$ is an entire function from the corresponding Fock space, then $$\frac{1}{\pi}\int_{\Omega} |f(z)|^2 e^{-\pi |z|^2} dx dy \le (1-e^{-|\Omega|}) \|f\|^2_{2,\pi}.$$ Here $\Omega$ is a domain in the complex pl

Guido L. A. Kusters, Cornelis Storm, Paul van der Schoot

We model the behaviour of a single colloid embedded in a cross-linked polymer gel, immersed in a viscous background fluid. External fields actuate the particle into a periodic motion, which deforms the embedding matrix and creates a local micro-cavity, containing the particle and any free volume created by its motion. This cavity exists only as long as the p

Tong Yang, Li Huang, Yue Wang, Rong Xiong

An efficient algorithm to solve the $k$ shortest non-homotopic path planning ($k$-SNPP) problem in a 2D environment is proposed in this paper. Motivated by accelerating the inefficient exploration of the homotopy-augmented space of the 2D environment, our fundamental idea is to identify the non-$k$-optimal path topologies as early as possible and terminate t

Chang Liu, Haifeng Tang, Hui Zhai

Krylov complexity is a novel measure of operator complexity that exhibits universal behavior and bounds a large class of other measures. In this letter, we generalize Krylov complexity from a closed system to an open system coupled to a Markovian bath, where Lindbladian evolution replaces Hamiltonian evolution. We show that Krylov complexity in open systems

Saima Safdar, Benjamin Zwick, George Bourantas, Grand Joldes

Electrocorticography (ECoG) or intracranial electroencephalography (iEEG) monitors electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery when paired with numerical modeling. For solving the inverse problem in epilepsy seizure onset localization, accurate solution of the iEEG forward problem

Guy David, Linhan Li, Svitlana Mayboroda

In the present paper, we consider elliptic operators $L=-\textrm{div}(A\nabla)$ in a domain bounded by a chord-arc surface $\Gamma$ with small enough constant, and whose coefficients $A$ satisfy a weak form of the Dahlberg-Kenig-Pipher condition of approximation by constant coefficient matrices, with a small enough Carleson norm, and show that the elliptic m

Amol R. Holkundkar, Rambabu Rajpoot, Jayendra N. Bandyopadhyay

We studied the high-harmonic generation by the interaction of sub-cycle laser pulses with the He atom. The sub-cycle pulses are modeled using the complex source vector beam model, which is an exact solution to Maxwell's equations and accurately models the sub-cycle field profiles. We observed that the harmonic cutoff could be extended with the variation of t

Yiheng Zhang, Ting Yao, Zhaofan Qiu, Tao Mei

Multi-scale learning frameworks have been regarded as a capable class of models to boost semantic segmentation. The problem nevertheless is not trivial especially for the real-world deployments, which often demand high efficiency in inference latency. In this paper, we thoroughly analyze the design of convolutional blocks (the type of convolutions and the nu

Luca Cavicchioli, Chiara Fort, Michele Modugno, Francesco Minardi

We unravel the coupled dipole dynamics of a two-species Bose-Einstein condensate with tunable interspecies interaction. We produce a degenerate mixture of $^{41}$K-$^{87}$Rb in an optical trap and we study the dipole oscillations of both atomic species in the linear response regime. Varying the interspecies interaction from the weakly to the strongly attract

Gregory M. Stephen, Ivan Naumov, Nicholas A. Blumenschein, Yi-Jan Leo Sun

While heterostructures are ubiquitous tools enabling new physics and device functionalities, the palette of available materials has never been richer. Combinations of two emerging material classes, two-dimensional materials and topological materials, are particularly promising because of the wide range of possible permutations that are easily accessible. Ind

Jinsu Kim, Ohjoon Kwon, Çağlar Kutlu, Woohyun Chung

We report the results of an axion dark matter search over an axion mass range of 9.39-9.51 ${\mu}$eV. A flux-driven Josephson parametric amplifier (JPA) was added to the cryogenic receiver chain. A system noise temperature of as low as 200 mK was achieved, which is the lowest recorded noise among published axion cavity experiments with phase-insensitive JPA

Rabanus Derr, Robert C. Williamson

Fair Machine Learning endeavors to prevent unfairness arising in the context of machine learning applications embedded in society. Despite the variety of definitions of fairness and proposed "fair algorithms", there remain unresolved conceptual problems regarding fairness. In this paper, we dissect the role of statistical independence in fairness and randomn

Susmita Changdar, Susanta Ghosh, Kritika Vijay, Indrani Kar

We thoroughly investigate the effect of nonmagnetic Sn doping on the electronic and magnetic properties of antiferromagnetic topological insulator MnBi$_2$Te$_4$. We observe that Sn doping reduces the out-of-plane antiferromagnetic (AFM) interactions in MnBi$_2$Te$_4$ up to 68\% of Sn concentration and above the system is found to be paramagnetic. In this wa

Qiyang Han

Let $Z_1,\ldots,Z_n$ be i.i.d. isotropic random vectors in $\mathbb{R}^p$, and $T \subset \mathbb{R}^p$ be a compact set. A classical line of empirical process theory characterizes the size of the suprema of the quadratic process \begin{align*} \sup_{t \in T} \bigg| \frac{1}{n}\sum_{i=1}^n \langle Z_i,t \rangle^2-\lVert t \rVert^2 \bigg|, \end{align*} via a

Amineh Mohseni, Mahdi Torabian

In this note we study supergravity models with constrained superfields. We construct a supergravity framework in which all (super)symmetry breaking dynamics happen in vacuum with naturally (or otherwise asymptotically) vanishing energy. Supersymmetry is generically broken in multiple sectors each of them is parametrized by a nilpotent goldstino superfield. D

Sören Schlichting, Ismail Soudi

Collisional broadening in QCD plasmas leads to the emission of medium induced radiation, which governs the energy loss of highly energetic particles or jets. While recent studies have obtained non-perturbative contributions to the collisional broadening kernel $C(b_\bot)$ using lattice simulation of the dimensionally reduced long-distance effective theory of

Lukas Hermann, Max Argus, Adrian Roefer, Abhinav Valada

Setting up robot environments to quickly test newly developed algorithms is still a difficult and time consuming process. This presents a significant hurdle to researchers interested in performing real-world robotic experiments. RobotIO is a python library designed to solve this problem. It focuses on providing common, simple, and well structured python inte

N. Sinthuja, M. Senthilvelan

In this article, we derive rogue wave (RW) solutions of a fifth-order nonlinear Schr\"odinger equation over a double-periodic wave background. Choosing the elliptic functions (combinations of $cn$, $dn$ and $sn$) as seed solutions in the first iteration of Darboux transformation and utilizing the nonlinearization of Lax pair procedure, we create the double-p

Andrea Censi, Emilio Frazzoli, Jonathan Lorand, Gioele Zardini

In many engineering applications it is useful to reason about "negative information". For example, in planning problems, providing an optimal solution is the same as giving a feasible solution (the "positive" information) together with a proof of the fact that there cannot be feasible solutions better than the one given (the "negative" information). We model