arXiv papers from June 2022

Alex Tong Lin, Stanley J. Osher

We introduce a method called MASCOT (Multi-Agent Shape Control with Optimal Transport) to compute optimal control solutions of agents with shape/formation/density constraints. For example, we might want to apply shape constraints on the agents -- perhaps we desire the agents to hold a particular shape along the path, or we want agents to spread out in order

Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov, Sergei V. Kalinin

Unsupervised and semi-supervised ML methods such as variational autoencoders (VAE) have become widely adopted across multiple areas of physics, chemistry, and materials sciences due to their capability in disentangling representations and ability to find latent manifolds for classification and regression of complex experimental data. Like other ML problems,

Javier Correa, Elizabeth Flores

This study examines the tree models of mildly dissipative diffeomorphisms on the disk $\D$. These models are one-dimensional dynamical systems with ergodic aperiodic data as well as some properties of the original dynamics. The focus of this work is their quality as dynamical invariants in both the topological and ergodic sense.

Zhimeng Ouyang, Lei Wu, Qinghua Xiao

The relativistic Vlasov-Maxwell-Landau (r-VML) system and the relativistic Landau equation (r-LAN) are fundamental models that describe the dynamics of an electron gas. In this paper, we introduce a novel weighted energy method and establish the validity of the Hilbert expansion for the r-VML system and r-LAN equation. As the Knudsen number shrinks to zero,

Richie Diurba, Rob Fine, Mandeep Gill, Harvey Newman

This document has been prepared as a Snowmass contributed paper by the Public Policy & Government Engagement topical group (CEF06) within the Community Engagement Frontier. The charge of CEF06 is to review all aspects of how the High Energy Physics (HEP) community engages with government at all levels and how public policy impacts members of the community an

Richie Diurba, Rob Fine, Mandeep Gill, Harvey Newman

This document has been prepared as a Snowmass contributed paper by the Public Policy \& Government Engagement topical group (CEF06) within the Community Engagement Frontier. The charge of CEF06 is to review all aspects of how the High Energy Physics (HEP) community engages with government at all levels and how public policy impacts members of the community a

David A. Ross

The roots of a complex polynomial depend continuously on the coefficients; that is, an infinitesimal perturbation of the coefficients results in an infinitesimal perturbation of the roots. A short, straightforward proof of this is possible using infinitesimals.

Mateus Carneiro, Richie Diurba, Rob Fine, Mandeep Gill

This document has been prepared as a Snowmass contributed paper by the Public Policy \& Government Engagement topical group (CEF06) within the Community Engagement Frontier. The charge of CEF06 is to review all aspects of how the High Energy Physics (HEP) community engages with government at all levels and how public policy impacts members of the community a

Hiromichi Itou, Takahito Kashiwabara

We consider dynamic motion of a linearized elastic body with a crack subject to a modified contact law, which we call the Signorini contact condition of dynamic type, and to the Tresca friction condition. Whereas the modified contact law involves both displacement and velocity, it formally includes the usual non-penetration condition as a special case. We pr

Eric R. Knorr, Baptiste Lemaire, Andrew Lim, Siqiang Luo

We introduce Proteus, a novel self-designing approximate range filter, which configures itself based on sampled data in order to optimize its false positive rate (FPR) for a given space requirement. Proteus unifies the probabilistic and deterministic design spaces of state-of-the-art range filters to achieve robust performance across a larger variety of use

Anamitra Chaudhuri, Georgios Fellouris

The problem of joint sequential detection and isolation is considered in the context of multiple, not necessarily independent, data streams. A multiple testing framework is proposed, where each hypothesis corresponds to a different subset of data streams, the sample size is a stopping time of the observations, and the probabilities of four kinds of error are

Tiziano Dalmonte, Andrea Mazzullo, Ana Ozaki

Non-normal modal logics, interpreted on neighbourhood models which generalise the usual relational semantics, have found application in several areas, such as epistemic, deontic, and coalitional reasoning. We present here preliminary results on reasoning in a family of modal description logics obtained by combining ALC with non-normal modal operators. First,

Xinshao Wang, Yang Hua, Elyor Kodirov, Sankha Subhra Mukherjee

There is a family of label modification approaches including self and non-self label correction (LC), and output regularisation. They are widely used for training robust deep neural networks (DNNs), but have not been mathematically and thoroughly analysed together. We study them and discover three key issues: (1) We are more interested in adopting Self LC as

Sanaz Taheri-Boshrooyeh, Oskar Thorén, Barry Whitehat, Wei Jie Koh

In this paper, we propose WAKU-RLN-RELAY as a spam-protected gossip-based routing protocol that can run in heterogeneous networks. It features a privacy-preserving peer-to-peer (p2p) economic spam protection mechanism. WAKU-RLN-RELAY addresses the performance and privacy issues of the state-of-the-art p2p spam prevention techniques including peer scoring uti

Sanaz Taheri-Boshrooyeh, Oskar Thorén, Barry Whitehat, Wei Jie Koh

WAKU-RLN-RELAY is an anonymous peer-to-peer gossip-based routing protocol that features a privacy-preserving spam-protection with cryptographically guaranteed economic incentives. While being an anonymous routing protocol where routed messages are not attributable to their origin, it allows global identification and removal of spammers. It addresses the perf

Kasra Ghasemi, Sadra Sadraddini, Calin Belta

We develop a novel decentralized control method for a network of perturbed linear systems with dynamical couplings subject to Signal Temporal Logic (STL) specifications. We first transform the STL requirements into set containment problems and then we develop controllers to solve these problems. Our approach is based on treating the couplings between subsyst

Sean A. Rendar, Fenglong Ma

In the growing world of machine learning and data analytics, scholars are finding new and innovative ways to solve real-world problems. One solution comes by way of an intersection between healthcare, sports statistics, and data sciences. Within the realm of Major League Baseball (MLB), pitchers are regarded as the most important roster position. They often

Mohammad Sadek

We consider elliptic surfaces whose coefficients are degree $2$ polynomials in a variable $T$. It was recently shown that for infinitely many rational values of $T$ the resulting elliptic curves have rank at least $1$. In this article, we prove that the Mordell-Weil rank of each such elliptic surface is at most $6$ over $\mathbb Q$. In fact, we show that the

Marcelo Arenas, Pablo Barceló, Miguel Romero, Bernardo Subercaseaux

Formal XAI (explainable AI) is a growing area that focuses on computing explanations with mathematical guarantees for the decisions made by ML models. Inside formal XAI, one of the most studied cases is that of explaining the choices taken by decision trees, as they are traditionally deemed as one of the most interpretable classes of models. Recent work has

Mengya Xu, Mobarakol Islam, Hongliang Ren

Surgical captioning plays an important role in surgical instruction prediction and report generation. However, the majority of captioning models still rely on the heavy computational object detector or feature extractor to extract regional features. In addition, the detection model requires additional bounding box annotation which is costly and needs skilled

Yen-Chang Hsu, Ting Hua, Sungen Chang, Qian Lou

Factorizing a large matrix into small matrices is a popular strategy for model compression. Singular value decomposition (SVD) plays a vital role in this compression strategy, approximating a learned matrix with fewer parameters. However, SVD minimizes the squared error toward reconstructing the original matrix without gauging the importance of the parameter

Nuha Albadi, Maram Kurdi, Shivakant Mishra

Growing evidence suggests that YouTube's recommendation algorithm plays a role in online radicalization via surfacing extreme content. Radical Islamist groups, in particular, have been profiting from the global appeal of YouTube to disseminate hate and jihadist propaganda. In this quantitative, data-driven study, we investigate the prevalence of religiously

Chenmu Zhang, Yuanyue Liu

Two-dimensional (2D) semiconductors have demonstrated great potential for next-generation electronics and optoelectronics. An important property for these applications is the phonon-limited charge carrier mobility. The common approach to calculate the mobility from first principles relies on the interpolation of the electron-phonon coupling (EPC) matrix. How

Amitis Shidani, George Deligiannidis, Arnaud Doucet

We study the ranking problem in generalized linear bandits. At each time, the learning agent selects an ordered list of items and observes stochastic outcomes. In recommendation systems, displaying an ordered list of the most attractive items is not always optimal as both position and item dependencies result in a complex reward function. A very naive exampl

Roberta Pappadà, Francesco Pauli

Machine learning algorithms are routinely used for business decisions that may directly affect individuals, for example, because a credit scoring algorithm refuses them a loan. It is then relevant from an ethical (and legal) point of view to ensure that these algorithms do not discriminate based on sensitive attributes (like sex or race), which may occur unw

Tsuyoshi Murata, Naveed Afzal

Graph convolution is a recent scalable method for performing deep feature learning on attributed graphs by aggregating local node information over multiple layers. Such layers only consider attribute information of node neighbors in the forward model and do not incorporate knowledge of global network structure in the learning task. In particular, the modular

Mark Endo, Kathleen L. Poston, Edith V. Sullivan, Li Fei-Fei

Parkinson's disease (PD) is a neurological disorder that has a variety of observable motor-related symptoms such as slow movement, tremor, muscular rigidity, and impaired posture. PD is typically diagnosed by evaluating the severity of motor impairments according to scoring systems such as the Movement Disorder Society Unified Parkinson's Disease Rating Scal

Denis S. Krotov

A tiling of a vector space $S$ is the pair $(U,V)$ of its subsets such that every vector in $S$ is uniquely represented as the sum of a vector from $U$ and a vector from $V$. A tiling is connected to a perfect codes if one of the sets, say $U$, is projective, i.e., the union of one-dimensional subspaces of $S$. A tiling $(U,V)$ is full-rank if the affine spa

Ronald Fagin, Jonathan Lenchner, Nikhil Vyas, Ryan Williams

In 1981, Neil Immerman described a two-player game, which he called the "separability game" \cite{Immerman81}, that captures the number of quantifiers needed to describe a property in first-order logic. Immerman's paper laid the groundwork for studying the number of quantifiers needed to express properties in first-order logic, but the game seemed to be too

Anna N. Morozovska, Eugene A. Eliseev, Salia Cherifi-Hertel, Dean R. Evans

In the framework of the Landau-Ginzburg-Devonshire (LGD) approach, we studied the possibility of controlling the polarity and chirality of equilibrium domain structures by a homogeneous external electric field in a nanosized ferroelectric core covered with an ultra-thin shell of screening charge. Under certain screening lengths and core sizes, the minimum of

Björn Eichmann, Foteini Oikonomou, Silvia Salvatore, Ralf-Jürgen Dettmar

Multi-wavelength observations indicate that some starburst galaxies show a dominant non-thermal contribution from their central region. These active galactic nuclei (AGN)-starburst composites are of special interest, as both phenomena on their own are potential sources of highly-energetic cosmic rays and associated gamma-ray and neutrino emission. In this wo

Chris Fox, Paul Wiegert

The Near Earth Object Surveillance Satellite (NEOSSat) is a Canadian-led 15 cm Earth-orbiting telescope originally designed to detect asteroids near the Sun. Its design is however also suitable for the observation of exoplanetary transits of bright stars. We used the NEOSSat platform to perform followup observations of several Transiting Exoplanets Survey Sa

Kendrick Qijun Li, Kenneth Martin Rice

Large-sample Bayesian analogs exist for many frequentist methods, but are less well-known for the widely-used 'sandwich' or 'robust' variance estimates. We review existing approaches to Bayesian analogs of sandwich variance estimates and propose a new analog, as the Bayes rule under a form of balanced loss function, that combines elements of standard paramet

Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito

Machine learning models exhibit two seemingly contradictory phenomena: training data memorization, and various forms of forgetting. In memorization, models overfit specific training examples and become susceptible to privacy attacks. In forgetting, examples which appeared early in training are forgotten by the end. In this work, we connect these phenomena. W

Daniel Glasscock

In the topological dynamical system $(X,T)$, a point $x$ simultaneously approximates a point $y$ if there exists a sequence $n_1$, $n_2$, ... of natural numbers for which $T^{n_i} x$, $T^{2n_i}x$, ..., $T^{k n_i} x$ all tend to $y$. In 1978, Furstenberg and Weiss showed that every system possesses a point which simultaneously approximates itself (a multiply

Tommaso Adamo, Lucio Colizzi, Giovanni Dimauro, Gianpaolo Ghiani

The Tourist Trip Design Problem aims to prescribe a sightseeing plan that maximizes tourist satisfaction while taking into account a multitude of parameters and constraints, such as the distances among points of interest, the expected duration of each visit, the opening hours of each attraction, the time available daily. In this article we deal with a varian

Wen Wan, Rishav Harsh, Antonella Meninno, Paul Dreher

Kondo lattices are ideal testbeds for the exploration of heavy-fermion quantum phases of matter. While our understanding of Kondo lattices has traditionally relied on complex bulk f-electron systems, transition metal dichalcogenide heterobilayers have recently emerged as simple, accessible and tunable 2D Kondo lattice platforms where, however, their ground s

Bülent Köklüce

In this paper, we use a modular form approach to evaluate the convolution sums $\sum_{l+42m=n}\sigma (l)\sigma (m)$, $\sum_{2l+21m=n}\sigma (l)\sigma (m),$ $\sum_{3l+14m=n}\sigma (l)\sigma (m)$ and $\sum_{6l+7m=n}\sigma (l)\sigma (m) $ for all positive integers $n\mathbf{,}$ and then use their evaluations to determine the number of representation of a positi

Marvin Teichmann, Andre Aichert, Hanibal Bohnenberger, Philipp Ströbel

Current approaches for classification of whole slide images (WSI) in digital pathology predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest (e.g. tumor tissue), while the second stage processes cropped tiles from these areas in a supervised fashion. During inference, a large number of tiles are combined into a uni

R. R. Rodriguez, B. Ahmadi, G. Suarez, P. Mazurek

Quantum control allows us to address the problem of engineering quantum dynamics for special purposes. While recently the field of quantum batteries has attracted much attention, optimization of their charging has not benefited from the quantum control methods. Here we fill this gap by using an optimization method. We apply for the first time this convergent

W. Daughton, B. J. Albright, S. M. Finnegan, Brian M. Haines

After decades of research, recent laser-driven inertial fusion experiments have demonstrated rapid progress toward achieving thermonuclear ignition using capsule designs with cryogenic fuel layers. The ignition physics for these layered capsules involves a complex interplay between the dynamically forming hot spot and the dense surrounding fuel. Using analyt

ATLAS Collaboration

The Standard Model of particle physics describes the known fundamental particles and forces that make up our universe, with the exception of gravity. One of the central features of the Standard Model is a field that permeates all of space and interacts with fundamental particles. The quantum excitation of this field, known as Higgs field, manifests itself as

Lionel Nganyewou Tidjon, Foutse Khomh

Machine learning is a field of artificial intelligence (AI) that is becoming essential for several critical systems, making it a good target for threat actors. Threat actors exploit different Tactics, Techniques, and Procedures (TTPs) against the confidentiality, integrity, and availability of Machine Learning (ML) systems. During the ML cycle, they exploit

Timo Gervens, Martin Grohe

Quantifying the similarity between two graphs is a fundamental algorithmic problem at the heart of many data analysis tasks for graph-based data. In this paper, we study the computational complexity of a family of similarity measures based on quantifying the mismatch between the two graphs, that is, the "symmetric difference" of the graphs under an optimal a

Tairan Liu, Yuzhu Li, Hatice Ceylan Koydemir, Yijie Zhang

We present a rapid and stain-free quantitative viral plaque assay using lensfree holographic imaging and deep learning. This cost-effective, compact, and automated device significantly reduces the incubation time needed for traditional plaque assays while preserving their advantages over other virus quantification methods. This device captures ~0.32 Giga-pix

Mycal Tucker, Julie Shah, Roger Levy, Noga Zaslavsky

Emergent communication research often focuses on optimizing task-specific utility as a driver for communication. However, human languages appear to evolve under pressure to efficiently compress meanings into communication signals by optimizing the Information Bottleneck tradeoff between informativeness and complexity. In this work, we study how trading off t

S. Valère Bitseki Penda

The main objective of this article is to establish a central limit theorem for additive three-variable functionals of bifurcating Markov chains. We thus extend the central limit theorem under point-wise ergodic conditions studied in Bitseki-Delmas (2022) and to a lesser extent, the results of Bitseki-Delmas (2022) on central limit theorem under $L^{2}$ ergod

Guillermo Badia, Ronald Fagin, Carles Noguera

Many-valued logics in general, and fuzzy logics in particular, usually focus on a notion of consequence based on preservation of full truth, typical represented by the value 1 in the semantics given the real unit interval [0,1]. In a recent paper (\emph{Foundations of Reasoning with Uncertainty via Real-valued Logics}, arXiv:2008.02429v2, 2021), Ronald Fagin

Hugh G. A. Burton, Daniel Marti-Dafcik, David P. Tew, David J. Wales

Quantum computers promise to revolutionise electronic simulations by overcoming the exponential scaling of many-electron problems. While electronic wave functions can be represented using a product of fermionic unitary operators, shallow quantum circuits for exact states have not yet been achieved. We construct universal wave functions from gate-efficient, s

I. Kravtsiv, G. Bokun, M. Holovko, N. Prokopchuk

A solid ionic conductor with cation conductivity in the interelectrode region is studied. Due to their large size, the anions are considered fixed and form a homogeneous neutralizing electric background. The model can be used to describe properties of ceramic conductors. For a statistical mechanical description of such systems, which are characterized by sho

Hanieh Hashemi, Yongqin Wang, Murali Annavaram

Privacy and security-related concerns are growing as machine learning reaches diverse application domains. The data holders want to train or infer with private data while exploiting accelerators, such as GPUs, that are hosted in the cloud. Cloud systems are vulnerable to attackers that compromise the privacy of data and integrity of computations. Tackling su

Alberto Martín-Jiménez, Óscar Jover, Koen Lauwaet, Daniel Granados

Understanding and controlling the interaction between the excitonic states of a quantum emitter and the plasmonic modes of a nanocavity is one of the most relevant current scientific challenges, key for the development of many applications, from quantum information processing devices to polaritonic catalysts. In this paper we demonstrate that the tunnel elec

Noman Bashir, David Irwin, Prashant Shenoy, Abel Souza

The demand for computing is continuing to grow exponentially. This growth will translate to exponential growth in computing's energy consumption unless improvements in its energy-efficiency can outpace increases in its demand. Yet, after decades of research, further improving energy-efficiency is becoming increasingly challenging, as it is already highly opt

Daniele Filippetto, Pietro Musumeci, Renkai Li, Bradley John Siwick

Since the discovery of electron-wave duality, electron scattering instrumentation has developed into a powerful array of techniques for revealing the atomic structure of matter. Beyond detecting local lattice variations in equilibrium structures, recent research efforts have been directed towards the long sought-after dream of visualizing the dynamic evoluti

Vishal Athreya Baskaran, Jolene Ranek, Siyuan Shan, Natalie Stanley

Modern high-throughput single-cell immune profiling technologies, such as flow and mass cytometry and single-cell RNA sequencing can readily measure the expression of a large number of protein or gene features across the millions of cells in a multi-patient cohort. While bioinformatics approaches can be used to link immune cell heterogeneity to external vari

Thomas C. Sideris

A class of isotropic and scale invariant strain energy functions is given for which the corresponding spherically symmetric elastic motion includes bodies whose diameter becomes infinite with time or collapses to zero in finite time, depending on the sign of the residual pressure. The body is surrounded by vacuum so that the boundary surface forces vanish, w

Rahul Kumar Walia, Sushant G Ghosh, Sunil D Maharaj

The Event Horizon Telescope (EHT) observation unveiled the first image of supermassive black hole Sgr A* showing a shadow of diameter $\theta_{sh}= 48.7 \pm 7\,\mu$as with fractional deviation from the Schwarzschild black hole shadow diameter $\delta = -0.08^{+0.09}_{-0.09}~\text{(VLTI)},-0.04^{+0.09}_{-0.10}~\text{(Keck)}$. The Sgr A* shadow size is within

Jiande Zhou, Yves-Marie Ducimetière, Daniel Migliozzi, Ludovic Keiser

Droplet breakup is an important phenomenon in the field of microfluidics to generate daughter droplets. In this work, a novel breakup regime in the widely studied T-junction geometry is reported, where the pinch-off occurs laterally in the two outlet channels, leading to the formation of three daughter droplets, rather than at the center of the junction for

M. E. J. Newman

We study the ranking of individuals, teams, or objects, based on pairwise comparisons between them, using the Bradley-Terry model. Estimates of rankings within this model are commonly made using a simple iterative algorithm first introduced by Zermelo almost a century ago. Here we describe an alternative and similarly simple iteration that provably returns i

Mindy Huerta, Octavio Mendoza, Marco A. Pérez

We present and study the concept of $m$-periodic Gorenstein objects relative to a pair $(\mathcal{A,B})$ of classes of objects in an abelian category, as a generalization of $m$-strongly Gorenstein projective modules over associative rings. We prove several properties in some cases where $(\mathcal{A,B})$ satisfies certain homological conditions, like for in

J. David Brown

Textbook treatments of classical mechanics typically assume that the Lagrangian is nonsingular. That is, the matrix of second derivatives of the Lagrangian with respect to the velocities is invertible. This assumption insures that (i) Lagrange's equations can be solved for the accelerations as functions of coordinates and velocities, and (ii) the definition

John Rached

We obtain bounds on the numbers of intersections between triangulations as the conformal structure of a surface varies along a Teichm{\"u}ller geodesic contained in an $\mathrm{SL}\left(2,\mathbb{R}\right)$-orbit closure of rank 1 in the moduli space of Abelian differentials. For $0 \leq \theta \leq 1$, we obtain an exponential bound on the number of closed

Mariano Chernicoff, Gaston Giribet, Emilio Rubín de Celis

We study extremal surfaces in a traversable wormhole geometry that connects two locally AdS$_5$ asymptotic regions. In the context of the AdS/CFT correspondence, we use these to compute the holographic entanglement entropy for different configurations: First, we consider an extremal surface anchored at the boundary on a spatial $2$-sphere of radius $R$. The

Michel Fruchart, Colin Scheibner, Vincenzo Vitelli

Elasticity typically refers to a material's ability to store energy, while viscosity refers to a material's tendency to dissipate it. In this review, we discuss fluids and solids for which this is not the case. These materials display additional linear response coefficients known as odd viscosity and odd elasticity. We first introduce odd elasticity and odd

Per Sebastian Skardal, Sabina Adhikari, Juan G. Restrepo

We study synchronization dynamics in populations of coupled phase oscillators with higher-order interactions and community structure. We find that the combination of these two properties gives rise to a number of states unsupported by either higher-order interactions or community structure alone, including synchronized states with communities organized into

Keagan Blanchette, Erin Piccirillo, Nassim Bozorgnia, Louis E. Strigari

We study the impact of the dark matter velocity distribution modelling on signals from velocity-dependent dark matter annihilation in Milky Way dwarf spheroidal galaxies. Using the high resolution APOSTLE simulations, we identify analogues corresponding to Milky Way dwarf spheroidal galaxies, and from these directly determine the dark matter pair-wise relati

Jung Hwan Heo, Arash Fayyazi, Amirhossein Esmaili, Massoud Pedram

This paper introduces the sparse periodic systolic (SPS) dataflow, which advances the state-of-the-art hardware accelerator for supporting lightweight neural networks. Specifically, the SPS dataflow enables a novel hardware design approach unlocked by an emergent pruning scheme, periodic pattern-based sparsity (PPS). By exploiting the regularity of PPS, our

Zhijie Wang, Masanori Suganuma, Takayuki Okatani

Unsupervised domain adaptation (UDA) adapts a model trained on one domain (called source) to a novel domain (called target) using only unlabeled data. Due to its high annotation cost, researchers have developed many UDA methods for semantic segmentation, which assume no labeled sample is available in the target domain. We question the practicality of this as

Shuja Khalid, Francisco Matos, Ayman Abunimer, Joel Bartlett

30-day hospital readmission is a long standing medical problem that affects patients' morbidity and mortality and costs billions of dollars annually. Recently, machine learning models have been created to predict risk of inpatient readmission for patients with specific diseases, however no model exists to predict this risk across all patients. We developed a

Xiaojian Du, Ralf Rapp

The evaluation of quarkonium regeneration in ultrarelativistic heavy-ion collisions (URHICs) requires the knowledge of the heavy-quark phase space distributions in the expanding quark-gluon plasma (QGP) fireball. We employ a semi-classical charmonium transport approach where regeneration processes explicitly account for the time-dependent spectra of charm qu

I. I. Khabibullin, E. M. Churazov, A. M. Bykov, N. N. Chugai

We report the discovery of a candidate X-ray supernova remnant SRGe J003602.3+605421=G121.1-1.9 in the course of \textit{SRG}/eROSITA all-sky survey. The object is located at (l,b)=(121.1$^\circ$,-1.9$^\circ$), is $\approx36$ arcmin in angular size and has a nearly circular shape. Clear variations in spectral shape of the X-ray emission across the object are

Samuel Haug, Austin Egbert, Robert J. Marks, Charles Baylis

Radar must adapt to changing environments, and we propose changepoint detection as a method to do so. In the world of increasingly congested radio frequencies, radars must adapt to avoid interference. Many radar systems employ the prediction action cycle to proactively determine transmission mode while spectrum sharing. This method constructs and implements

Ondřej Kincl, Ilya Peshkov, Michal Pavelka, Václav Klika

Smoothed Particle Hydrodynamics (SPH) methods are advantageous in simulations of fluids in domains with free boundary. Special SPH methods have also been developed to simulate solids. However, there are situations where the matter behaves partly as a fluid and partly as a solid, for instance, the solidification front in 3D printing, or any system involving b

Iván Alvarez-Ríos, Francisco S. Guzmán

We introduce a tool that solves the Schr\"odinger-Euler-Poisson system of equations and allows the study of the interaction between ultralight bosonic dark matter, whose dynamics is described with the Schr\"odinger-Poisson system and luminous matter which, as a first approximation, is modeled with a single component compressible ideal fluid. The two matter f

Majidul Rahaman, Ramij Raja, Abhirup Datta, Jack O Burns

Extended, steep, and ultra-steep spectrum radio emission in a galaxy cluster is usually associated with recent mergers. Simulations show that radio phoenixes are aged radio galaxy lobes whose emission reactivates when a low Mach shock compresses it. A85 hosts a textbook example of a radio phoenix at about 320 kpc southwest of the cluster center. We present a

Kazuki Enomoto, Shinya Kanemura, Yushi Mura

We discuss electroweak baryogenesis in aligned two Higgs doublet models. It is known that in this model the severe constraint from the experimental results for the electron electric dipole moment can be avoided by destructive interference among CP-violating effects in the Higgs sector. In our previous work, we showed that the observed baryon number in the Un

Adel Awad, Alexey Golovnev, María-José Guzmán, Waleed El Hanafy

We study various forms of diagonal tetrads that accommodate Black Hole solutions in $f(T)$ gravity with certain symmetries. As is well-known, vacuum spherically symmetric diagonal tetrads lead to rather boring cases of constant torsion scalars. We extend this statement to other possible horizon topologies, namely, spherical, hyperbolic and planar horizons. A

Connor E. Robinson, Catherine C. Espaillat, Joseph E. Rodriguez

Interpreting the short-timescale variability of the accreting, young, low-mass stars known as Classical T Tauri stars remains an open task. Month-long, continuous light curves from the Transiting Exoplanet Survey Satellite (\textit{TESS}) have become available for hundreds of T Tauri stars. With this vast data set, identifying connections between the variabi

V. A. Berezin, V. I. Dokuchaev

We investigated the possibility of the homogeneous and isotropic cosmological solution in Weyl geometry, which differs from the Riemannian geometry by adding the so called Weyl vector. The Weyl gravity is obtained by constructing the gravitational Lagrangian both to be quadratic in curvatures and conformal invariant. It is found that such solution may exist

Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain

The promise of multimodal models for real-world applications has inspired research in visualizing and understanding their internal mechanics with the end goal of empowering stakeholders to visualize model behavior, perform model debugging, and promote trust in machine learning models. However, modern multimodal models are typically black-box neural networks,

Martina Kiechle, Levente Maucha, Valentin Ahrens, Carsten Dubs

We present the design and experimental realization of a device that acts like a spin-wave lens i.e., it focuses spin waves to a specified location. The structure of the lens does not resemble any conventional lens design, it is a nonintuitive pattern produced by a machine learning algorithm. As a spin-wave design tool, we used our custom micromagnetic solver

Christoph Matthies, Mary Sánchez-Gordón, Jens Bæk Jørgensen, Lutz Prechelt

Background: Software Engineering regularly views communication between project participants as a tool for solving various problems in software development. Objective: Formulate research questions in areas related to CHASE. Method: A day-long discussion of five participants at the in-person day of the 15th International Conference on Cooperative and Human Asp

Zixiang Xu, Chi Hoi Yip

Given a finite abelian group $G$ and a subset $J\subset G$ with $0\in J$, let $D_{G}(J,N)$ be the maximum size of $A\subset G^{N}$ such that the difference set $A-A$ and $J^{N}$ have no non-trivial intersection. Recently, this extremal problem has been widely studied for different groups $G$ and subsets $J$. In this paper, we generalize and improve the relev

Yanwei Wang, Ching-Yun Ko, Pulkit Agrawal

One powerful paradigm in visual navigation is to predict actions from observations directly. Training such an end-to-end system allows representations useful for downstream tasks to emerge automatically. However, the lack of inductive bias makes this system data inefficient. We hypothesize a sufficient representation of the current view and the goal view for

Colin M. Huber, Nathaniel S. Barlow, Steven J. Weinstein

This work considers two linear operators which yield wave modes that are classified as neutrally stable, yet have responses that grow or decay in time. Previously, King et al. (Phys. Rev. Fluids, 1, 2016, 073604:1-19) and Huber et al. (IMA J. Appl. Math., 85, 2020, 309-340) examined the one-dimensional (1D) wave propagation governed by these operators. Here,

Caleb M. Shor

We define a reflective numerical semigroup of genus $g$ as a numerical semigroup that has a certain reflective symmetry when viewed within $\mathbb{Z}$ as an array with $g$ columns. Equivalently, a reflective numerical semigroup has one gap in each residue class modulo $g$. In this paper, we give an explicit description for all reflective numerical semigroup

Wengang Zhou, Weilun Wang, Jianmin Bao, Dongdong Chen

Denoising Diffusion Probabilistic Models (DDPMs) have achieved remarkable success in various image generation tasks compared with Generative Adversarial Nets (GANs). Recent work on semantic image synthesis mainly follows the de facto GAN-based approaches, which may lead to unsatisfactory quality or diversity of generated images. In this paper, we propose a n

Francesco Ballini

Let $A$ be an abelian variety defined over a number field $K$. We say that a point $P \in A(\overline{\mathbb{Q}})$ is primitive if there is no $Q \in A(\overline{\mathbb{Q}})$ defined on the field of definition of $P$ over $K$ such that $[N]Q=P$ for some positive integer $N \ge 2$. For any primitive point $P \in A(\overline{\mathbb{Q}})$, positive integer $

Dongqi Fu, Jingrui He, Hanghang Tong, Ross Maciejewski

Directly motivated by security-related applications from the Homeland Security Enterprise, we focus on the privacy-preserving analysis of graph data, which provides the crucial capacity to represent rich attributes and relationships. In particular, we discuss two directions, namely privacy-preserving graph generation and federated graph learning, which can j

Sanjana Das, Hannah Lang, Hamilton Wan, Nancy Xu

Motivated by the study of the summatory $k$-free indicator and totient functions in the classical setting, we investigate their function field analogues. First, we derive an expression for the error terms of the summatory functions in terms of the zeros of the associated zeta function. Under the Linear Independence hypothesis, we explicitly construct the lim

Debmalya Mandal, Stelios Triantafyllou, Goran Radanovic

We introduce the framework of performative reinforcement learning where the policy chosen by the learner affects the underlying reward and transition dynamics of the environment. Following the recent literature on performative prediction~\cite{Perdomo et. al., 2020}, we introduce the concept of performatively stable policy. We then consider a regularized ver

Elsa Magness, Brian Nugent, Leanne Robertson

Let $L$ be a primitive Gaussian line, that is, a line in the complex plane that contains two, and hence infinitely many, coprime Gaussian integers. We prove that there exists an integer $G_L$ such that for every integer $n\geq G_L$ there are infinitely many sequences of $n$ consecutive Gaussian integers on $L$ with the property that none of the Gaussian inte

Atul Dixit, Khushbu Patel

Bhoria, Eyyunni and Maji recently obtained a four-parameter $q$-series identity which gives as special cases not only all five entries of Ramanujan on pages 354 and 355 of his second notebook but also allows them to obtain an analytical proof of a result of Bressoud and Subbarao. Here, we obtain a finite analogue of their identity which naturally gives finit

CMS Collaboration

In July 2012, the ATLAS and CMS Collaborations at the CERN Large Hadron Collider announced the observation of a Higgs boson at a mass of around 125 GeV. Ten years later, and with the data corresponding to the production of 30 times larger number of Higgs bosons, we have learnt much more about the properties of the Higgs boson. The CMS experiment has observed

Nicolas Hölsch, Ioana Doran, Maximilian Beyer, Frédéric Merkt

Precision measurements of transitions between singlet ($S=0$) Rydberg states of H$_2$ belonging to series converging on the $\mathrm{X}^+\,^2\Sigma_g^+(v^+=0,N^+=0)$ state of H$_2^+$ have been carried out by millimetre-wave spectroscopy under field-free conditions and in the presence of weak static electric fields. The Stark effect mixes states with differen

Shuang Dai, Fanlin Meng, Qian Wang, Xizhong Chen

Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumption, can help analyze electricity consumption behaviours of users and enable practical smart energy and smart grid applications. Recent studies have proposed many n

Rosemary K. Guzman, Peter B. Shalen

Under mild topological restrictions, we obtain new linear upper bounds for the dimension of the mod $p$ homology (for any prime $p$) of a finite-volume orientable hyperbolic $3$ manifold $M$ in terms of its volume. A surprising feature of the arguments in the paper is that they require an application of the Four Color Theorem. If $M$ is closed, and either (a

Derek O. Hoare, David S. Matteson, Martin T. Wells

We present an approach to clustering time series data using a model-based generalization of the K-Means algorithm which we call K-Models. We prove the convergence of this general algorithm and relate it to the hard-EM algorithm for mixture modeling. We then apply our method first with an AR($p$) clustering example and show how the clustering algorithm can be

Oskar Thorén, Sanaz Taheri-Boshrooyeh, Hanno Cornelius

Waku is a family of modular protocols that enable secure, censorship-resistant, and anonymous peer-to-peer communication. Waku protocols provide capabilities that make them suitable to run in resource-restricted environments e.g., mobile devices and web browsers. Such capabilities include (i) retrieving historical messaging for mostly-offline devices (ii) ad

Jiahe Shi, Yuning Jiang, Juraj Oravec, Boris Houska

This paper proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) problems with state and input constraints. The algorithm itself is based on a parallel MPC scheme that has originally been designed for systems with input constraints. In this context, one contribution of this paper is the construction of time-varying yet separ