January 2022 arXiv papers — page 84

Adam J. Svahn, Sheryl L. Chang, Rebecca J. Rockett, Oliver M. Cliff

Objectives: To enhance monitoring of high-burden foodborne pathogens, there is opportunity to combine pangenome data with network analysis. Methods: Salmonella enterica subspecies Enterica serovar Enteritidis isolates were referred to the New South Wales (NSW) Enteric Reference Laboratory between August 2015 and December 2019 (1033 isolates in total), inclus

Jun Wu, Elizabeth A. Ainsworth, Sheng Wang, Kaiyu Guan

Plant phenotyping (Guo et al. 2021; Pieruschka et al. 2019) focuses on studying the diverse traits of plants related to the plants' growth. To be more specific, by accurately measuring the plant's anatomical, ontogenetical, physiological and biochemical properties, it allows identifying the crucial factors of plants' growth in different environments. One com

Tatsuki Hayama

A flag domain is an open real group orbit in a complex flag manifold. It has been shown that a flag domain is either pseudoconvex or pseudoconcave. Moreover, generically 1-connected flag domains are pseudoconcave. In this study, for flag domains contained in irreducible Hermitian symmetric spaces of type AIII or CI, we determine which pseudoconcave flag doma

Andy Goldschmidt, James Kunert-Graf, Adrian C. Scott, Zhihao Tan

Baker's yeast (Saccharomyces cerevisiae) is a model organism for studying the morphology that emerges at the scale of multi-cell colonies. To look at how morphology develops, we collect a dataset of time-lapse photographs of the growth of different strains of S. cerevisiae. We discuss the general statistical challenges that arise when using time-lapse photog

James Kakos, Joel R. Primack, Aldo Rodriguez-Puebla, Nicolas Tejos

The stochastic order redshift technique (SORT) is a simple, efficient, and robust method to improve cosmological redshift measurements. The method relies upon having a small ($\sim$10 per cent) reference sample of high-quality redshifts. Within pencil-beam-like sub-volumes surrounding each galaxy, we use the precise dN/d$z$ distribution of the reference samp

Petch Khunpetch, Arghya Majee, Rudolf Podgornik

We formulate a theory of electrostatic interactions in lipid bilayer membranes where both monolayer leaflets contain dissociable moieties that are subject to charge regulation. We specifically investigate the coupling between membrane curvature and charge regulation of a lipid bilayer vesicle using both the linear Debye-H\"uckel (DH) and the non-linear Poiss

Denis Sushentsev, Aleksandr Khvorov, Roman Vasiliev, Yaroslav Golubev

The task of finding the best developer to fix a bug is called bug triage. Most of the existing approaches consider the bug triage task as a classification problem, however, classification is not appropriate when the sets of classes change over time (as developers often do in a project). Furthermore, to the best of our knowledge, all the existing models use t

Hideaki Oshima, Katsumi Oshima

We define inductively unstable n-fold Toda brackets for every n>2 in the category of spaces with base points, and then define stable ones.

U. Bhat, S. Redner

We introduce an idealized model of an intelligent forager in which higher intelligence corresponds to a larger spatial range over which the forager can detect food. Such a forager diffuses randomly whenever the nearest food is more distant than the forager's detection range, $R$, and moves ballistically towards the nearest food inside its detection range. Co

Cheng-Chun Lee, Charles Chou, Ali Mostafavi

The objectives of this study are: (1) to specify evacuation return and home-switch stability as two critical milestones of short-term recovery during and in the aftermath of disasters; and (2) to understand the disparities among subpopulations in the duration of these critical recovery milestones. Using privacy-preserving fine-resolution location-based data,

Robert Dohner, Suk Jai Seo

For a graph G, a dominating set D is a subset of vertices in G where each of the vertices in G is in D or adjacent to some vertex in D. An open-locating-dominating (OLD) set models a system with sensors to detect an intruder in a facility or a faulty component in a network of processors. The goal is to detect and pinpoint an intruder's exact location in a sy

Norbert Weber, Carolina Duczek, Gerrit M. Horstmann, Steffen Landgraf

Lithium-bismuth bimetallic cells are amongst the best explored liquid metal batteries. A simple and fast quasi-one-dimensional cell voltage model for such devices is presented. The equilibrium cell potential is obtained from a complex two-dimensional fit of data drawn from multiple studies of equilibrium cell potential and rendered congruent with the phase d

Sofía Angriman, Pablo D. Mininni, Pablo J. Cobelli

We define and characterize multi-time Lagrangian structure functions using data stemming from two swirling flows with mean flow and turbulent fluctuations: A Taylor-Green numerical flow, and a von K\'arm\'an laboratory experiment. Data is obtained from numerical integration of tracers in the former case, and from three-dimensional particle tracking velocimet

Kyung Ha, Brendan Harding, Andrea L. Bertozzi, Yvonne M. Stokes

Microchannels are well-known in microfluidic applications for the control and separation of microdroplets and cells. Often the objects in the flow experience inertial effects, resulting in dynamics that is a departure from the underlying channel flow dynamics. This paper considers small neutrally buoyant spherical particles suspended in flow through a curved

Johannes O. Royset

Approximations of optimization problems arise in computational procedures and sensitivity analysis. The resulting effect on solutions can be significant, with even small approximations of components of a problem translating into large errors in the solutions. We specify conditions under which approximations are well behaved in the sense of minimizers, statio

Dawei Sun, Jingkai Chen, Sayan Mitra, Chuchu Fan

We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonholonomic dynamics. Existing methods in multi-agent motion planning, especially those based on discrete abstractions and model predictive control (MPC), suffer from limited scalabil

Aimo Hinkkanen, Joseph Miles

We prove that there exists an entire function for which every complex number is an asymptotic value and whose growth is arbitrarily slow subject only to the necessary condition that the function is of infinite order.

Stella Biderman, Kieran Bicheno, Leo Gao

This datasheet describes the Pile, a 825 GiB dataset of human-authored text compiled by EleutherAI for use in large-scale language modeling. The Pile is comprised of 22 different text sources, ranging from original scrapes done for this project, to text data made available by the data owners, to third-party scrapes available online.

Shulei Cao, Maria Dainotti, Bharat Ratra

We show that the Platinum gamma-ray burst (GRB) data compilation, probing the redshift range $0.553 \leq z \leq 5.0$, obeys a cosmological-model-independent three-parameter fundamental plane (Dainotti) correlation and so is standardizable. While they probe the largely unexplored $z \sim 2.3-5$ part of cosmological redshift space, the GRB cosmological paramet

Johanna Devaney

Chord estimation metrics treat chord labels as independent of one another. This fails to represent the pitch relationships between the chords in a meaningful way, resulting in evaluations that must make compromises with complex chord vocabularies and that often require time-consuming qualitative analyses to determine details about how a chord estimation algo

Nikhil X. Bhattasali, Anthony M. Zador, Tatiana A. Engel

Artificial neural networks for motor control usually adopt generic architectures like fully connected MLPs. While general, these tabula rasa architectures rely on large amounts of experience to learn, are not easily transferable to new bodies, and have internal dynamics that are difficult to interpret. In nature, animals are born with highly structured conne

Raju Baral, Jacob Christensen, Parker Hamilton, Feng Ye

Short-range magnetic correlations can significantly increase the thermopower of magnetic semiconductors, representing a noteworthy development in the decades-long effort to develop high-performance thermoelectric materials. Here, we reveal the nature of the thermopower-enhancing magnetic correlations in the antiferromagnetic semiconductor MnTe. Using magneti

Md Atiqul Islam, George C. Alexandropoulos, Besma Smida

Integrated Sensing and Communication (ISAC) has attracted substantial attraction in recent years for spectral efficiency improvement, enabling hardware and spectrum sharing for simultaneous sensing and signaling operations. In-band Full Duplex (FD) is being considered as a key enabling technology for ISAC applications due to its simultaneous transmission and

Gregory B. Sorkin

This recreational mathematics article shows that the game of Snakes and Ladders is intransitive: square 69 has a winning edge over 79, which in turn beats 73, which beats 69. Analysis of the game is a nice illustration of Markov chains, simulations of different sorts, and size-biased sampling. Connecting this to "intransitive dice" illustrates the power of a

Jhilam Sadhukhan, Samuel A. Giuliani, Witold Nazarewicz

Background: A quantitative microscopic understanding of the fission-fragment yield distributions represents a major challenge for nuclear theory as it involves the intricate competition between large-amplitude nuclear collective motion and single-particle nucleonic motion. Purpose: A recently proposed approach to global modeling of fission fragment distribut

Artur Lozovoi, Gyorgy Vizkelethy, Edward Bielejec, Carlos A. Meriles

The application of color centers in wide-bandgap semiconductors to nanoscale sensing and quantum information processing largely rests on our knowledge of the surrounding crystalline lattice, often obscured by the countless classes of point defects the material can host. Here we monitor the fluorescence from a negatively charged nitrogen-vacancy (NV-) center

Jeremy Ash, Laura Lancaster, Chris Gotwalt

We present a novel method for controlling extrapolation in the prediction profiler in the JMP software. The prediction profiler is a graphical tool for exploring high dimensional prediction surfaces for statistical and machine learning models. The profiler contains interactive cross-sectional views, or profile traces, of the prediction surface of a model. Ou

Aras Bacho

The well-posedness of the abstract \textsc{Cauchy} problem for the doubly nonlinear evolution inclusion equation of second order \begin{align*} \begin{cases} u''(t)+\partial \Psi(u'(t))+B(t,u(t))\ni f(t), &\quad t\in (0,T),\, T>0,\\ u(0)=u_0, \quad u'(0)=v_0 \end{cases} \end{align*} in a real separable \textsc{Hilbert} space $\mathscr{H}$, where $u_0\in \mat

Armen E. Allahverdyan, Andranik Khachatryan

A text written using symbols from a given alphabet can be compressed using the Huffman code, which minimizes the length of the encoded text. It is necessary, however, to employ a text-specific codebook, i.e. the symbol-codeword dictionary, to decode the original text. Thus, the compression performance should be evaluated by the full code length, i.e. the len

Bryn Noel Ubald, Pranay Seshadri, Andrew Duncan

This study proposes a radically alternate approach for extracting quantitative information from schlieren images. The method uses a scaled, derivative enhanced Gaussian process model to obtain true density estimates from two corresponding schlieren images with the knife-edge at horizontal and vertical orientations. We illustrate our approach on schlieren ima

Behzad Boroujerdian, Ying Jing, Amit Kumar, Lavanya Subramanian

Domain-specific SoCs (DSSoCs) are attractive solutions for domains with stringent power/performance/area constraints; however, they suffer from two fundamental complexities. On the one hand, their many specialized hardware blocks result in complex systems and thus high development effort. On the other, their many system knobs expand the complexity of design

Alexandra Iacob, Bogdan Cautis, Silviu Maniu

Motivated by scenarios of information diffusion and advertising in social media, we study an influence maximization problem in which little is assumed to be known about the diffusion network or about the model that determines how information may propagate. In such a highly uncertain environment, one can focus on multi-round diffusion campaigns, with the obje

Daniel Bauer, Tom Longley, Yueen Ma, Tony Wilson

In this working paper we explore the use of an NLP system to assist the work of Security Force Monitor (SFM). SFM creates data about the organizational structure, command personnel and operations of police, army and other security forces, which assists human rights researchers, journalists and litigators in their work to help identify and bring to account sp

Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda

Recently several structured pruning techniques have been introduced for energy-efficient implementation of Deep Neural Networks (DNNs) with lesser number of crossbars. Although, these techniques have claimed to preserve the accuracy of the sparse DNNs on crossbars, none have studied the impact of the inexorable crossbar non-idealities on the actual performan

A. Moya, L. M. Sarro, E. Delgado-Mena, W. J. Chaplin

Dating stars is a major challenge with a deep impact on many astrophysical fields. One of the most promising techniques for this is using chemical abundances. Recent space- and ground-based facilities have improved the quantity of stars with accurate observations. This has opened the door for using Bayesian inference tools to maximise the information we can

L. F. Secco, M. Jarvis, B. Jain, C. Chang

We present high signal-to-noise measurements of three-point shear correlations and the third moment of the mass aperture statistic using the first 3 years of data from the Dark Energy Survey. We additionally obtain the first measurements of the configuration and scale dependence of the four three-point shear correlations which carry cosmological information.

Tânia Carvalho, Nuno Moniz, Pedro Faria, Luís Antunes

Machine learning is increasingly used in the most diverse applications and domains, whether in healthcare, to predict pathologies, or in the financial sector to detect fraud. One of the linchpins for efficiency and accuracy in machine learning is data utility. However, when it contains personal information, full access may be restricted due to laws and regul

Mason del Rosario, Zhi Ding

Wireless links using massive MIMO transceivers are vital for next generation wireless communications networks networks. Precoding in Massive MIMO transmission requires accurate downlink channel state information (CSI). Many recent works have effectively applied deep learning (DL) to jointly train UE-side compression networks for delay domain CSI and a BS-sid

Michael G Albrow

FACET is a proposed new subsysem for CMS to search for portals such as dark photons, dark higgs, heavy neutral leptons and axion-like particles in the very forward direction at the High Luminosity LHC. Such particles can penetrate up to 50 m of iron and then decay inside a 14 m$^3$ vacuum pipe made by enlarging an 18 m long section of the LHC pipe to a radiu

Benoît Henry, Sylvie Méléard, Viet Chi Tran

We consider a stochastic individual-based population model with competition, trait-structure affecting reproduction and survival, and changing environment. The changes of traits are described by jump processes, and the dynamics can be approximated in large population by a non-linear PDE with a non-local mutation operator. Using the fact that this PDE admits

Jian Gu, Pasquale Salza, Harald C. Gall

Automatic code summarization is beneficial to daily software development since it could help reduce the requirement of manual writing. Currently, artificial intelligence is undergoing a paradigm shift. The foundation models pretrained on massive data and finetuned to downstream tasks surpass specially customized models. This trend inspired us to consider reu

Robert B. Olsen

To improve the generalizability of impact evaluations, recent research has examined statistical methods for selecting representative samples of sites. However, these methods rely on having rich data on impact moderators for all sites in the target population. This paper offers a new approach to selecting sites for impact studies when rich data on impact mode

Chad Henshaw, Richard O'Shaughnessy, Laura Cadonati

Since the initial discovery of gravitational waves in 2015, significant developments have been made towards waveform interpretation and estimation of compact binary source parameters. We present herein an implementation of the generalized precession parameter $\langle \chi_p \rangle$, which averages over all angular variations on the precession timescale, wi

Sylvain Billiard, Hélène Leman, Thomas Rey, Viet Chi Tran

We study a stochastic individual-based model of interacting plant and pollinator species through a bipartite graph: each species is a node of the graph, an edge representing interactions between a pair of species. The dynamics of the system depends on the between- and within-species interactions: pollination by insects increases plant reproduction rate but h

Andrei A. Bulatov, Akbar Rafiey

Given polynomials $f_0,\dots, f_k$ the Ideal Membership Problem, IMP for short, asks if $f_0$ belongs to the ideal generated by $f_1,\dots, f_k$. In the search version of this problem the task is to find a proof of this fact. The IMP is a well-known fundamental problem with numerous applications. For instance, it underlies many proof systems based on polynom

Ali Karimi, Ahmad Kalhor

In this paper, a straightforward enhancement learning algorithm based on Separation Index (SI) concept is proposed for Convolutional Neural Networks (CNNs). At first, the SI as a supervised complexity measure is explained its usage in better learning of CNNs for classification problems illustrate. Then, a learning strategy proposes through which the first la

Alycia N. Carey, Xintao Wu

Over the past several years, a slew of different methods to measure the fairness of a machine learning model have been proposed. However, despite the growing number of publications and implementations, there is still a critical lack of literature that explains the interplay of fair machine learning with the social sciences of philosophy, sociology, and law.

Dmitri Maslov, Ben Zindorf

We seek to develop better upper bound guarantees on the depth of quantum CZ gate, CNOT gate, and Clifford circuits than those reported previously. We focus on the number of qubits $n\,{\leq}\,$1,345,000 [1], which represents the most practical use case. Our upper bound on the depth of CZ circuits is $\lfloor n/2 + 0.4993{\cdot}\log^2(n) + 3.0191{\cdot}\log(n

Brian A. Powell

The failure of the Euclidean norm to reliably distinguish between nearby and distant points in high dimensional space is well-known. This phenomenon of distance concentration manifests in a variety of data distributions, with iid or correlated features, including centrally-distributed and clustered data. Unsupervised learning based on Euclidean nearest-neigh

Mingtian Zhang, James Townsend, Ning Kang, David Barber

The recently proposed Neural Local Lossless Compression (NeLLoC), which is based on a local autoregressive model, has achieved state-of-the-art (SOTA) out-of-distribution (OOD) generalization performance in the image compression task. In addition to the encouragement of OOD generalization, the local model also allows parallel inference in the decoding stage.

Emiland Garrabe, Giovanni Russo

This survey is focused on certain sequential decision-making problems that involve optimizing over probability functions. We discuss the relevance of these problems for learning and control. The survey is organized around a framework that combines a problem formulation and a set of resolution methods. The formulation consists of an infinite-dimensional optim

Qian Xiao, Yihao Lin, Qizhi Li, Xiquan Zheng

The recently discovered Kagome family ${\mathrm{AV}}_3{\mathrm{Sb}}_5$ (A = K, Rb, Cs) exhibits rich physical phenomena, including non-trivial topological electronic structure, giant anomalous Hall effect, charge density waves (CDW) and superconductivity. Notably, CDW in ${\mathrm{AV}}_3{\mathrm{Sb}}_5$ is evidenced to intertwine with its superconductivity a

João L. Costa, Anne T. Franzen, Jesús Oliver

We identify a large class of systems of semilinear wave equations, on fixed accelerated expanding FLRW spacetimes, with nearly at spatial slices, for which we prove small data future global well-posedness. The family of systems we consider is large in the sense that, among other examples, it includes general wave maps, as well as natural generalizations of s

Camilo Posada, Jan Hladík, Zdeněk Stuchlík

The Tolman VII solution is considered by some as one of the few analytical solutions to Einstein's equations, which describes approximately well the interior of neutron stars (NSs). This solution is characterized by the mass $M$, radius $R$, and an energy density that varies quadratically with the radial coordinate $r$. Recently, Jiang and Yagi proposed a mo

Daniel Tylavsky, Songyan Li, Di Shi

We present a novel method for calculating Pad\'e approximants that is capable of eliminating spurious poles placed at the point of development and of identifying and eliminating spurious poles created by precision limitations and/or noisy coefficients. Information contained in in the eliminated poles is assimilated producing a reduced order Pad\'e approximan

Alina Kononov, Alexandra Olmstead, Andrew D. Baczewski, Andre Schleife

The extreme sensitivity of 2D materials to defects and nanostructure requires precise imaging techniques to verify presence of desirable and absence of undesirable features in the atomic geometry. Helium-ion beams have emerged as a promising materials imaging tool, achieving up to 20 times higher resolution and 10 times larger depth-of-field than conventiona

Miles Martinez, John Pearson

Variational autoencoders are among the most popular methods for distilling low-dimensional structure from high-dimensional data, making them increasingly valuable as tools for data exploration and scientific discovery. However, unlike typical machine learning problems in which a single model is trained once on a single large dataset, scientific workflows pri

Jan Matousek

In semi-inclusive deep inelastic scattering (SIDIS) the non-zero transverse momentum of partons induces azimuthal dependence of the cross-section. For unpolarised nucleon, three azimuthal modulations that can be related to different combinations of twist-two or higher twist transverse momentum dependent PDFs and fragmentation functions arise: the so-called C

I. Zacharoudiou, J. W. S. McCullough, P. V. Coveney

In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated partition, whilst in others they are integral to all compute nodes - often with multiple GPUs per node - and provide the

Sjoerd Dirksen, Shahar Mendelson, Alexander Stollenwerk

We study the problem of generating a hyperplane tessellation of an arbitrary set $T$ in $\mathbb{R}^n$, ensuring that the Euclidean distance between any two points corresponds to the fraction of hyperplanes separating them up to a pre-specified error $\delta$. We focus on random gaussian tessellations with uniformly distributed shifts and derive sharp bounds

Bilal Abu-Salih, Dana Al Qudah, Malak Al-Hassan, Seyed Mohssen Ghafari

The communication revolution has perpetually reshaped the means through which people send and receive information. Social media is an important pillar of this revolution and has brought profound changes to various aspects of our lives. However, the open environment and popularity of these platforms inaugurate windows of opportunities for various cyber threat

Denis Anuprienko

Recently, the nonlinearity continuation method has been used to numerically solve boundary value problems for steady-state Richards equation. The method can be considered as a predictor-corrector procedure with the simplest form which has been applied to date having a trivial, zeroth-order predictor. In this article, effect of a more sophisticated predictor

Yael Eisenberg, Oded Regev, Noah Stephens-Davidowitz

We prove that if $\mathcal{L} \subset \mathbb{R}^n$ is a lattice such that $\det(\mathcal{L}') \geq 1$ for all sublattices $\mathcal{L}' \subseteq \mathcal{L}$, then \[ \sum_{\substack{\mathbf{y}\in\mathcal{L}\\\mathbf{y}\neq\mathbf0}} (\|\mathbf{y}\|^2+q)^{-s} \leq \sum_{\substack{\mathbf{z} \in \mathbb{Z}^n\\\mathbf{z}\neq\mathbf{0}}} (\|\mathbf{z}\|^2+q)^

Brook J Hocking, Thomas Machon

A continuum theory of linearized Helmholtz-Kirchoff point vortex dynamics about a steadily rotating lattice state is developed by two separate methods: firstly by a direct procedure, secondly by taking the long-wavelength limit of Tkachenko's exact solution for a triangular vortex lattice. Solutions to the continuum theory are found, described by arbitrary a

Alejandro Mera, Yi Hui Chen, Ruimin Sun, Engin Kirda

Embedded and Internet-of-Things (IoT) devices have seen an increase in adoption in many domains. The security of these devices is of great importance as they are often used to control critical infrastructure, medical devices, and vehicles. Existing solutions to isolate microcontroller (MCU) resources in order to increase their security face significant chall

Konstantinos Xylogiannopoulos

Pattern detection and string matching are fundamental problems in computer science and the accelerated expansion of bioinformatics and computational biology have made them a core topic for both disciplines. The SARS-CoV-2 pandemic has made such problems more demanding with hundreds or thousands of new genome variants discovered every week, because of constan

Michael Greenacre, Eric Grunsky, John Bacon-Shone, Ionas Erb

The development of John Aitchison's approach to compositional data analysis is followed since his paper read to the Royal Statistical Society in 1982. Aitchison's logratio approach, which was proposed to solve the problematic aspects of working with data with a fixed sum constraint, is summarized and reappraised. It is maintained that the properties on which

ShengLi Tzeng, Hao-Yun Hsu

The HCV package implements the hierarchical clustering for spatial data. It requires clustering results not only homogeneous in non-geographical features among samples but also geographically close to each other within a cluster. We modified typically used hierarchical agglomerative clustering algorithms to introduce the spatial homogeneity, by considering g

Z. Safari, K. Rezazadeh, B. Malekolkalami

We investigate a cosmological scenario in which the dark matter particles can be created during the evolution of the Universe. By regarding the Universe as an open thermodynamic system and using non-equilibrium thermodynamics, we examine the mechanism of gravitational particle production. In this setup, we study the large-scale structure (LSS) formation of t

Danqing Shi, Weiwei Cui, Danqing Huang, Haidong Zhang

Visual elements in an information presentation are often spatially and semantically grouped hierarchically for effective message delivery. Studying the hierarchical grouping information can help researchers and designers better explore layout structures and understand design demographics. However, recovering hierarchical grouping is challenging due to a larg

Tse-Chun Chen, Stephen G. Penny, Timothy A. Smith, Jason A. Platt

Next generation reservoir computing based on nonlinear vector autoregression (NVAR) is applied to emulate simple dynamical system models and compared to numerical integration schemes such as Euler and the $2^\text{nd}$ order Runge-Kutta. It is shown that the NVAR emulator can be interpreted as a data-driven method used to recover the numerical integration sc

Joseph C. Chapman, Nicholas A. Peters

Optical heterodyne detection-based spectrometers are attractive due to their relatively simple construction and ultra-high resolution. Here we demonstrate a proof-of-principle single-mode optical-fiber-based heterodyne spectrometer which has picometer resolution and quantum-limited sensitivity around 1550 nm. Moreover, we report a generalized quantum limit o

Giuseppe Greco, Michele Punturo, Mark Allen, Ada Nebot

We describe the use of Multi Order Coverage (MOC) maps as a practical way to manage complex regions of the sky for the planning of multi-messenger observations. MOC maps are a data structure that provides a multi-resolution representation of irregularly shaped and fragmentary regions over the sky based on the HEALPix (Hierarchical Equal Area isoLatitude Pixe

Iris H. R. Yoon, Robert Ghrist, Chad Giusti

A central challenge in topological data analysis is the interpretation of barcodes. The classical algebraic-topological approach to interpreting homology classes is to build maps to spaces whose homology carries semantics we understand and then to appeal to functoriality. However, we often lack such maps in real data; instead, we must rely on a cross-dissimi

Heinz H. Bauschke, Xianfu Wang

Recently, Simons provided a lemma for a support function of a closed convex set in a general Hilbert space and used it to prove the geometry conjecture on cycles of projections. In this paper, we extend Simons's lemma to closed convex functions, show its connections to Attouch-Thera duality, and use it to characterize (classical and phantom) cycles and gap v

Shangfei Wu, Brenden R. Ortiz, Hengxin Tan, Stephen D. Wilson

We employ polarization-resolved electronic Raman spectroscopy and density functional theory to study the primary and secondary order parameters, as well as their interplay, in the charge density wave (CDW) state of the kagome metal AV3Sb5. Previous x-ray diffraction data at 15K established that the CDW order in CsV3Sb5 comprises of a 2x2x4 structure: one lay

Dibbendu Roy, Aravinda S. Rao, Tansu Alpcan, Akilan Wick

End-to-end (E2E) quality of experience (QoE) for 6G applications depends on the synchronous allocation of networking and computing resources, also known as slicing. However, the relationship between the resources and the E2E QoE outcomes is typically stochastic and non-stationary. Existing works consider known resource demands for slicing and formulate optim

Antonio Lei, Daniel Vallières

Let $\ell$ and $p$ be two distinct primes. We study the $p$-adic valuation of the number of spanning trees in an abelian $\ell$-tower of connected multigraphs. This is analogous to the classical theorem of Washington--Sinnott on the growth of the $p$-part of the class group in a cyclotomic $\mathbb{Z}_\ell$-extension of abelian extensions of $\mathbb{Q}$. Fu

Makoto Ando, Kazuhiro Shimasaku, Rieko Momose, Kei Ito

The redshift of $z\sim1.5$ is the transition epoch of protoclusters (PCs) from the star-forming phase into the quenching phase, and hence an appropriate era to investigate the build up of the quenched population. We define a `core' as the most massive halo in a given PC, where environmental effects are likely to work most effectively, and search for cores at

Dibbendu Roy, Aravinda S. Rao, Tansu Alpcan, Goutam Das

Emerging applications such as Augmented Reality, the Internet of Vehicles and Remote Surgery require both computing and networking functions working in harmony. The End-to-end (E2E) quality of experience (QoE) for these applications depends on the synchronous allocation of networking and computing resources. However, the relationship between the resources an

Toby Shevlane

Structured access is an emerging paradigm for the safe deployment of artificial intelligence (AI). Instead of openly disseminating AI systems, developers facilitate controlled, arm's length interactions with their AI systems. The aim is to prevent dangerous AI capabilities from being widely accessible, whilst preserving access to AI capabilities that can be

Saurya Das, Sujoy K. Modak

It was also shown recently that GUP predicts potentially measurable corrections to the `doubling time' of freely moving Gaussian atomic and molecular wavepackets with a favorable combination of three parameters, {\it e.g.} mass, initial width and mean velocity of a travelling wavepacket. However, it is well known that such wavepackets can come with various s

Rene Carmona, Gokce Dayanikli

In this study, we analyze an advertising competition in a duopoly. We consider two different notions of equilibrium. We model the companies in the duopoly as major players, and the consumers as minor players. In our first game model we identify Nash Equilibria (NE) between all the players. Next we frame the model to lead to the search for Multi-Leader-Follow

Chenning Li, Xiuzhen Guo, Longfei Shangguan, Zhichao Cao

LoRaWAN has emerged as an appealing technology to connect IoT devices but it functions without explicit coordination among transmitters, which can lead to many packet collisions as the network scales. State-of-the-art work proposes various approaches to deal with these collisions, but most functions only in high signal-to-interference ratio (SIR) conditions

Abhishek Hegade K. R., Elias R. Most, Jorge Noronha, Helvi Witek

Black holes in certain modified gravity theories that contain a scalar field coupled to curvature invariants are known to possess (monopole) scalar hair while non-black-hole spacetimes (like neutron stars) do not. Therefore, as a neutron star collapses to a black hole, scalar hair must grow until it settles to the stationary black hole solution with (monopol

Mitchell Plyler, Michael Green, Min Chi

Rationales, snippets of extracted text that explain an inference, have emerged as a popular framework for interpretable natural language processing (NLP). Rationale models typically consist of two cooperating modules: a selector and a classifier with the goal of maximizing the mutual information (MMI) between the "selected" text and the document label. Despi

Jianfeng Gao, Chenyan Xiong, Paul Bennett, Nick Craswell

A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or written form. Recent progress in deep learning has brought tremendous improvements in natural language pro

S. Goldstein, J. L. Lebowitz, E. R. Speer

We describe the extremal translation invariant stationary (ETIS) states of the facilitated exclusion process on $\mathbb{Z}$. In this model all particles on sites with one occupied and one empty neighbor jump at each integer time to the empty neighbor site, and if two particles attempt to jump into the same empty site we choose one randomly to succeed. The E

Peter Taylor, Cormac Breen, Adrian Ottewill

In this paper, we describe an extremely efficient method for computing the renormalized stress-energy tensor of a quantum scalar field in spherically-symmetric black hole spacetimes. The method applies to a scalar field with arbitrary field parameters. We demonstrate the utility of the method by computing the renormalized stress-energy tensor for a scalar fi

Norman E. Trushaev

Various concepts of grammatical compositionality arise in many theories of both natural and artificial languages, and often play a key role in accounts of the syntax-semantics interface. We propose that many instances of compositionality should entail non-trivial combinatorial claims about the expressive power of languages which satisfy these compositional p

Yi Shi, Yalin E. Sagduyu

Federated learning (FL) offers a decentralized learning environment so that a group of clients can collaborate to train a global model at the server, while keeping their training data confidential. This paper studies how to launch over-the-air jamming attacks to disrupt the FL process when it is executed over a wireless network. As a wireless example, FL is

Haipeng An, Kun-Feng Lyu, Lian-Tao Wang, Siyi Zhou

Large excursion of the inflaton field can trigger interesting dynamics. One important example is a first-order phase transition in a spectator sector which couples to the inflaton. Gravitational waves (GWs) from such a first-order phase transition during inflation, an example of an instantaneous source, have an oscillatory feature. In this work, we show that

Jan Jerhot, Babette Döbrich, Fatih Ertas, Felix Kahlhoefer

Proton beam dump experiments are among the most promising strategies to search for light and feebly interacting states such as axion-like particles (ALPs). The interpretation of these experiments is however complicated by the wide range of ALP models and the multitude of different production and decay channels that can induce observable signals. Here we prop

Johan Comparat, Nhut Truong, Andrea Merloni, Annalisa Pillepich

We aim at characterizing the hot phase of the Circum-Galactic Medium in a large sample of galaxies. We stack X-ray events from the SRG/eROSITA eFEDS survey around central galaxies in the GAMA 9hr field to construct radially projected soft X-ray luminosity profiles as a function of their stellar mass and specific star formation rate. We consider samples of qu

Alex Lazarian, Siyao Xu

Alfv\'{e}nic component of MHD turbulence damps Alfv\'{e}nic waves. The consequences of this effect are important for many processes, from cosmic ray (CR) propagation to launching outflows and winds in galaxies and other magnetized systems. We discuss the differences in the damping of the streaming instability by turbulence and the damping of a plane parallel

William DeRocco, Marios Galanis, Robert Lasenby

It is well-known that stars have the potential to be excellent dark matter detectors. Infalling dark matter that scatters within stars could lead to a range of observational signatures, including stellar heating, black hole formation, and modified heat transport. To make robust predictions for such phenomena, it is necessary to calculate the scattering rate

Max Jaarsma, Yibei Li, Ian Moult, Wouter Waalewijn

Track functions describe the collective effect of the fragmentation of quarks and gluons into charged hadrons, making them a key ingredient for jet substructure measurements at hadron colliders, where track-based measurements offer superior angular resolution. The first moment of the track function, describing the average energy deposited in charged particle

Jakob S. den Brok, Frank Bigiel, Kazimierz Sliwa, Toshiki Saito

We present the CO isotopologue Line Atlas within the Whirpool galaxy Survey (CLAWS) based on an IRAM 30-m large programme which provides a benchmark study of numerous, faint CO isotopologues in the mm-wavelength regime across the full disc of M51 (NGC 5194). The survey's core goal is to use the low-J CO isotopologue lines to constrain CO excitation and chemi

Denise Hung, Josef Hanuš, Joseph R. Masiero, David J. Tholen

We present new thermophysical model (TPM) fits of 1,847 asteroids, deriving thermal inertia, diameter, and Bond and visible geometric albedo. We use thermal flux measurements obtained by the Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010; Mainzer et al. 2011) during its fully cryogenic phase, when both the 12$\mu$m (W3) and 22$\mu$m (W4) bands

Markus Q. Huber, Christian S. Fischer, Hèlios Sanchis-Alepuz

The spectrum of glueballs with quantum numbers $J^\mathsf{PC}=0^{\pm+},2^{\pm+},3^{\pm+},4^{\pm+}$ is calculated in quenched quantum chromodynamics from bound state equations. The input is taken from a parameter-free calculation of two- and three-point functions. Our results agree well with lattice results where available and contain also some additional sta