July 2023 arXiv papers — page 60

Talat Nazir, Sergei Silvestrov

Using the setting of $G$-metric spaces, common fixed point theorems for four maps satisfying the weakly commuting conditions are obtained for various generalized contractive conditions. Several examples are also presented to show the validity of main results.

Christopher Grayson, Cheng Tao Yang, Martin Formanek, Johann Rafelski

We characterize in detail the very dense $e^- e^+ \gamma$ plasma present during the Big-Bang Nucleosynthesis (BBN) and explore how it is perturbed electromagnetically by \lq\lq impurities, {\it i.e.\/}, spatially dispersed protons and light nuclei undergoing thermal motion. The internuclear electromagnetic screened potential is obtained (analytically) using

Tuochao Chen, Justin Chan, Shyamnath Gollakota

The emergence of water-proof mobile and wearable devices (e.g., Garmin Descent and Apple Watch Ultra) designed for underwater activities like professional scuba diving, opens up opportunities for underwater networking and localization capabilities on these devices. Here, we present the first underwater acoustic positioning system for smart devices. Unlike co

Iryna Ryzhkova

We study long-time dynamics of strong solutions to a non-homogeneous coupled system consisting of linearized 3D Navier--Stokes equations in a bounded domain and the classical (nonlinear) full von Karman plate equations that account for both transversal and lateral displacements on a flexible part of the boundary. Rotational inertia of the filaments of the pl

Anita Rau, Sophia Bano, Yueming Jin, Pablo Azagra

Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps is challenging. A 3D map of the observed surfaces could enhance the identification of unscreened colon tissue and serve as a training platform. However, reconstructing the colon fr

Andrew McNutt, Ravi Chugh

Augmenting text-based programming with rich structured interactions has been explored in many ways. Among these, projectional editors offer an enticing combination of structure editing and domain-specific program visualization. Yet such tools are typically bespoke and expensive to produce, leaving them inaccessible to many DSL and application designers. We d

Nikhil U. Shinde, Xiao Liang, Florian Richter, Michael C. Yip

The ability to predict future states is crucial to informed decision-making while interacting with dynamic environments. With cameras providing a prevalent and information-rich sensing modality, the problem of predicting future states from image sequences has garnered a lot of attention. Current state-of-the-art methods typically train large parametric model

Justin P. Haldar

We recently published an approach named ROVir (Region-Optimized Virtual coils) that uses the beamforming capabilities of a multichannel magnetic resonance imaging (MRI) receiver array to achieve coil compression (reducing an original set of receiver channels into a much smaller number of virtual channels for the purposes of dimensionality reduction), while s

Zhiyan Ding, Yulong Dong, Yu Tong, Lin Lin

We present a novel ground-state energy estimation algorithm that is robust under global depolarizing error channels. Building upon the recently developed Quantum Exponential Least Squares (QCELS) algorithm, our new approach incorporates significant advancements to ensure robust estimation while maintaining a polynomial cost in precision. By leveraging the sp

Erbin Qiu, Yuan-Hang Zhang, Massimiliano Di Ventra, Ivan K. Schuller

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, we explore an alternative route based on a new class of spiking oscillators we call thermal neuristors, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition in vanadium dioxi

Zhixiang Zhang, Sokbae Lee, Edgar Dobriban

Randomized algorithms, such as random sampling, random projections, and stochastic optimization, are increasingly used to reduce the computational cost of modern statistical analysis. These algorithms introduce algorithmic randomness in addition to the sampling randomness in the data, and this extra source of variation complicates statistical inference. We d

Le Peng, Gaoxiang Luo, sicheng zhou, jiandong chen

Language models (LMs) such as BERT and GPT have revolutionized natural language processing (NLP). However, the medical field faces challenges in training LMs due to limited data access and privacy constraints imposed by regulations like the Health Insurance Portability and Accountability Act (HIPPA) and the General Data Protection Regulation (GDPR). Federate

Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor

Deep learning has shown excellent performance in analysing medical images. However, datasets are difficult to obtain due privacy issues, standardization problems, and lack of annotations. We address these problems by producing realistic synthetic images using a combination of 3D technologies and generative adversarial networks. We propose CUT-seg, a joint tr

Justin Kottinger, Tzvika Geft, Shaull Almagor, Oren Salzman

We consider a Multi-Agent Path Finding (MAPF) setting where agents have been assigned a plan, but during its execution some agents are delayed. Instead of replanning from scratch when such a delay occurs, we propose delay introduction, whereby we delay some additional agents so that the remainder of the plan can be executed safely. We show that finding the m

Meijian Li, Tuomas Lappi, Xingbo Zhao, Carlos A. Salgado

We have developed a non-perturbative light-front Hamiltonian formalism to simulate the real-time evolution of a quark state in a SU(3) colored medium, with a series of works. In this proceeding article, we focus on the transverse momentum broadening of an in-medium quark jet. We perform the numerical simulation of the quark jet evolution in the $\ket{q}+\ket

Jingyi Tang, Zhen Zhang, Jenny Morgan, Erik Hemsing

Despite tremendous progress in x-ray free-electron laser (FEL) science over the last decade, future applications still demand fully coherent, stable x-rays that have not been demonstrated in existing X-ray FEL facilities. In this Letter, we describe an active Q-switched x-ray regenerative amplifier FEL scheme to produce fully coherent, high-brightness, hard

Nihat Ay, Jesse van Oostrum, Adwait Datar

This article studies the Fisher-Rao gradient, also referred to as the natural gradient, of the evidence lower bound (ELBO) which plays a central role in generative machine learning. It reveals that the gap between the evidence and its lower bound, the ELBO, has essentially a vanishing natural gradient within unconstrained optimization. As a result, maximizat

Megan R. Ebers, Jan P. Williams, Katherine M. Steele, J. Nathan Kutz

Sensing is one of the most fundamental tasks for the monitoring, forecasting and control of complex, spatio-temporal systems. In many applications, a limited number of sensors are mobile and move with the dynamics, with examples including wearable technology, ocean monitoring buoys, and weather balloons. In these dynamic systems (without regions of statistic

Clara Novoa, Apan Qasem

The Quadratic Assignment Problem (QAP) is an important combinatorial optimization problem with applications in many areas including logistics and manufacturing. QAP is known to be NP-hard, a computationally challenging problem, which requires the use of sophisticated heuristics in finding acceptable solutions for most real-world data sets. In this paper, we

Jingda Yang, Sudhanshu Arya, Ying Wang

Softwarization and virtualization in 5G and beyond necessitate thorough testing to ensure the security of critical infrastructure and networks, requiring the identification of vulnerabilities and unintended emergent behaviors from protocol designs to their software stack implementation. To provide an efficient and comprehensive solution, we propose a novel a

Peter Danziger, Eric Mendelsohn, Brett Stevens, Tommaso Traetta

The generalized Oberwolfach problem asks for a factorization of the complete graph $K_v$ into prescribed $2$-factors and at most a $1$-factor. When all $2$-factors are pairwise isomorphic and $v$ is odd, we have the classic Oberwolfach problem, which was originally stated as a seating problem: given $v$ attendees at a conference with $t$ circular tables such

Thomas Gauthier, Gabriel Vigny

The aim of this note is to give a proof of Theorem A from our work on the geometric Northcott property in the simpler case of the quadratic family; being in dimension $1$ in both the dynamical space and the parameter space, and having a simple and explicit parametrization of the family allow to simplify the proof and, we hope, make the ideas more apparent.

S. Halilovic, F. Böttcher, K. Zosseder, T. Hamacher

The optimization of open-loop shallow geothermal systems, which includes both design and operational aspects, is an important research area aimed at improving their efficiency and sustainability and the effective management of groundwater as a shallow geothermal resource. This paper investigates various approaches to address optimization problems arising fro

Thomas Gauthier, Gabriel Vigny

When an endomorphism $f:X\to X$ of a projective variety which is polarized by an ample line bundle $L$, i.e. such that $f^*L\simeq L^{\otimes d}$ with $d\geq2$, is defined over a number field, Call and Silverman defined a canonical height $\widehat{h}_f$ for $f$. In a family $(\mathcal{X},\mathcal{f},\mathcal{L})$ parametrized by a curve $S$ together with a

Shruti R. Kulkarni, Aaron Young, Prasanna Date, Narasinga Rao Miniskar

This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experiments conducted at the High Luminosity Large Hadron Collider. We present our approach for developing a compact neuromorphic model that filters out the sensor data based on the parti

Kellin N. Rumsey, Devin Francom, Scott Vander Wiel

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. While sensible in some settings, this approach has obvious

Gianmarco Lazzeri, Hendrik Jung, Peter G. Bolhuis, Roberto Covino

Molecular dynamics is a powerful tool for studying the thermodynamics and kinetics of complex molecular events. However, these simulations can rarely sample the required time scales in practice. Transition path sampling overcomes this limitation by collecting unbiased trajectories capturing the relevant events. Moreover, the integration of machine learning c

Christopher Rieser, Anne Ruiz-Gazen, Christine Thomas-Agnan

We consider models for network indexed multivariate data involving a dependence between variables as well as across graph nodes. In the framework of these models, we focus on outliers detection and introduce the concept of edgewise outliers. For this purpose, we first derive the distribution of some sums of squares, in particular squared Mahalanobis distance

Martin Winter

We present a new, explicit and very geometric construction for the iterated clique graphs of the hexagonal lattice $\mathrm{Hex}$ which makes apparent its clique-divergence and sheds light on some previous observations, such as the boundedness of the degrees and clique sizes of $k^n \mathrm{Hex}$ as $n\to\infty$.

Luis Medrano Navarro, Luis Martín Moreno, Sergio G Rodrigo

The research in Artificial Intelligence methods with potential applications in science has become an essential task in the scientific community last years. Physics Informed Neural Networks (PINNs) is one of this methods and represent a contemporary technique that is based on the fundamentals of neural networks to solve differential equations. These kind of n

Yuanzheng Lei, Yao Cheng, Xianfeng Terry Yang

The trajectory planning problem (TPP) has become increasingly crucial in the research of next-generation transportation systems, but it presents challenges due to the non-linearity of its constraints. One specific case within TPP, namely the Eco-trajectory Planning Problem (EPP), poses even greater computational difficulties due to its nonlinear, high-order,

David van Treeck, Jonas Lähnemann, Guanhui Gao, Sergio Fernández Garrido

Capitalizing on the directed nature of the atomic fluxes in molecular beam epitaxy, we propose and demonstrate the sequential directional deposition of lateral (In,Ga)N shells on GaN nanowires. In this approach, a sub-monolayer thickness of each constituent atomic species, i.e. Ga, In, and N, is deposited subsequently from the same direction by rotating the

Thomas Markovich

Graph convolutional neural networks (GCNs) operate by aggregating messages over local neighborhoods given the prediction task under interest. Many GCNs can be understood as a form of generalized diffusion of input features on the graph, and significant work has been dedicated to improving predictive accuracy by altering the ways of message passing. In this w

Jun Li, Ryan Wu, I-Tai Lu, Dongyin Ren

In this paper, a sparse signal recovery algorithm using Bayesian linear regression with Cauchy prior (BLRC) is proposed. Utilizing an approximate expectation maximization(AEM) scheme, a systematic hyper-parameter updating strategy is developed to make BLRC practical in highly dynamic scenarios. Remarkably, with a more compact latent space, BLRC not only poss

Zichong Chen, Nicholas Balasus, Haipeng Lin, Hannah Nesser

Africa has been identified as a major driver of the current rise in atmospheric methane, and this has been attributed to emissions from wetlands and livestock. Here we show that rapidly increasing rice cultivation is another important source, and estimate that it accounts for 7% of the current global rise in methane emissions. Continued rice expansion to fee

Ryan McConnell

We study well-posedness for a non-integrable generalization of the fifth order KdV, the second member in the KdV heirarchy. In particular, we use differentiation-by-parts to establish well-posedness for $s> 35/64$ in low modulation restricted norm spaces, as well as non-linear smoothing of order $\varepsilon < \min(2(s-35/64), 1)$. As corollaries, we obtain

Dylan Herman, Cody Googin, Xiaoyuan Liu, Yue Sun

Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. We present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modeling, optimization, and machine learning. This Rev

Max Hirsch, Franziska Weber

We study the Landau-de Gennes Q-tensor model of liquid crystals subjected to an electric field and develop a fully discrete numerical scheme for its solution. The scheme uses a convex splitting of the bulk potential, and we introduce a truncation operator for the Q-tensors to ensure well-posedness of the problem. We prove the stability and well-posedness of

Enayat Ullah, Raman Arora

We formalize the problem of machine unlearning as design of efficient unlearning algorithms corresponding to learning algorithms which perform a selection of adaptive queries from structured query classes. We give efficient unlearning algorithms for linear and prefix-sum query classes. As applications, we show that unlearning in many problems, in particular,

Jishnu Mahmud, Raisa Mashtura, Shaikh Anowarul Fattah, Mohammad Saquib

Quantum Machine Learning (QML) has come into the limelight due to the exceptional computational abilities of quantum computers. With the promises of near error-free quantum computers in the not-so-distant future, it is important that the effect of multi-qubit interactions on quantum neural networks is studied extensively. This paper introduces a Quantum Conv

Xin Li, Sima Behpour, Thang Doan, Wenbin He

In this study, we investigate the task of data pre-selection, which aims to select instances for labeling from an unlabeled dataset through a single pass, thereby optimizing performance for undefined downstream tasks with a limited annotation budget. Previous approaches to data pre-selection relied solely on visual features extracted from foundation models,

Mark Carney

In this thesis we will present and discuss various results pertaining to tiling problems and mathematical logic, specifically computability theory. We focus on Wang prototiles, as defined in [32]. We begin by studying Domino Problems, and do not restrict ourselves to the usual problems concerning finite sets of prototiles. We first consider two domino proble

Alexander N. Alvara, Lydia Lee, Emmanuel Sin, Nathan Lambert

Leveraging advancements in micro-scale technology, we propose a fleet of autonomous, low-cost, small solar sails for interplanetary exploration. The Berkeley Low-cost Interplanetary Solar Sail (BLISS) project aims to utilize small-scale technologies to create a fleet of tiny interplanetary femto-spacecraft for rapid, low-cost exploration of the inner solar s

Édouard Bonnet, Julien Duron, John Sylvester, Viktor Zamaraev

We show that for any natural number $s$, there is a constant $\gamma$ and a subgraph-closed class having, for any natural $n$, at most $\gamma^n$ graphs on $n$ vertices up to isomorphism, but no adjacency labeling scheme with labels of size at most $s \log n$. In other words, for every $s$, there is a small (even tiny) monotone class without universal graphs

Michael Günther, Louis Milliken, Jonathan Geuter, Georgios Mastrapas

Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating textual inputs into numerical representations, capturing the semantics of the text. These models excel in applications like dense retrieval and semantic textual similarity. This paper details the development of Jina Embeddings, starting with the creation of h

Stan Gudder

This article introduces the concepts of multi-observables and multi-instruments in quantum mechanics. A multi-observable $A$ (multi-instrument $\mathcal{I}$) has an outcome space of the form $\Omega =\Omega _1\times\cdots\times\Omega _n$ and is denoted by $A_{x_1\cdots x_n}$ ($\mathcal{I}_{x_1\cdots x_n}$) where $(x_1,\ldots ,x_n)\in\Omega$. We also call $A$

Chun-Yen Lin, Xiangjing Liu, Yongge Ma, Cong Zhang

The loop quantization of the conformal Brans-Dicke cosmology is explored in the spatially flat and Bianchi-I setting. The scalar and conformal constraints governing the canonical model are quantized using the loop techniques. The physical Hilbert space of quantum spacetimes satisfying both quantum constraints is then obtained by incorporating the quantum geo

Komlan Payne, Yunkun Zhao, Aditya Ashok Bhosale, Xiaoliang Zhang

$Objective:$ Information on the metabolism of tissues in both healthy and diseased states plays a significant role in the detection and understanding of tumors, neurodegenerative diseases, diabetes, and other metabolic disorders. Hyperpolarized carbon-13 magnetic resonance imaging ($^{13}$C-HPMRI) and deuterium metabolic imaging ($^2$H-DMI) are two emerging

James Freitag, Léo Jimenez, Rahim Moosa

Several structural results about permutation groups of finite rank definable in differentially closed fields of characteristic zero (and other similar theories) are obtained. In particular, it is shown that every finite rank definably primitive permutation group is definably isomorphic to an algebraic permutation group living in the constants. Applications i

Grigori Rozenblum, Nikolai Shirokov

We establish that a generalized H\"{o}lder continuous function on an $(m-2)$-Ahlfors regular compact set in $\mathbb{R}^m$ can be approximated by solutions of an elliptic equation, with the rate of approximation determined by the continuity modulus of the function.

Renjie Luo, Xuanhan Zhao, Tanner J. Legvold, Liyang Chen

Just as electronic shot noise in driven conductors results from the granularity of charge and the statistical variation in the arrival times of charge carriers, there are predictions for fundamental noise in magnon currents due to angular momentum being carried by discrete excitations. The inverse spin Hall effect as a transduction mechanism to convert spin

Milutin Blagojević, Branislav Cvetković

It is shown that energy, entropy and the first law of the Martinez-Troncoso black hole with electric charge and scalar hair (2006) can be consistently described in a general Hamiltonian approach to black hole thermodynamics.

Ahmad Barhoumi, Oleg Lisovyy, Peter D. Miller, Andrei Prokhorov

The third Painlev\'e equation in its generic form, often referred to as Painlev\'e-III($D_6$), is given by $$ \frac{{\rm d}^2u}{{\rm d}x^2} =\frac{1}{u}\left(\frac{{\rm d}u}{{\rm d}x}\right)^2-\frac{1}{x}\frac{{\rm d}u}{{\rm d}x}+\frac{\alpha u^2+\beta}{x}+4u^3-\frac{4}{u}, \qquad \alpha,\beta \in \mathbb C.$$ Starting from a generic initial solution $u_0(x)

Ngan H. Nguyen, Erwin H. Tanin, Marc Kamionkowski

We compute the detailed energy spectra of axions with two-photon coupling produced in stellar cores over a wide range of stellar masses. We focus on main sequence stars and base our calculations on the stellar interior profiles from MESA, for which we provide simple fits in an appendix. The obtained stellar axion spectra, combined with recent models of star

Feng Lin, Valery Levitas, Sorb Yesudhas, Jesse Smith

Deep-focus earthquakes that occur at 350-660 km are theorized to be caused by strain-induced olivine-spinel phase transformation (PT). We introduce and apply dynamic rotational diamond anvil cell with rough diamond anvils to deform San Carlos olivine. While olivine was never transformed to spinel at any pressure at room temperature, we obtained olivine-ringw

Zhewei Liu, Lipai Huang, Chao Fan, Ali Mostafavi

Generating realistic human flows across regions is essential for our understanding of urban structures and population activity patterns, enabling important applications in the fields of urban planning and management. However, a notable shortcoming of most existing mobility generation methodologies is neglect of prediction fairness, which can result in undere

Arunashish Datta, Shreyas Sen

While the number of wearables is steadily growing, the wearables/person wearing them faces a limitation due to the need for charging all of them every day. To unlock the true power of IoB, we need to make these IoB nodes perpetual. However, that is not possible with today's technology. In this paper, we will debate, whether with the advent of Wi-R protocol t

Ina Petkova, Noah Schwartz

We expand the atlas of Legendrian knots in standard contact three-space to knots of arc index 10.

Faezehsadat Shahidi, M. Ethan MacDonald, Dallas Seitz, Geoffrey Messier

Background: Mental illness can lead to adverse outcomes such as homelessness and police interaction and understanding of the events leading up to these adverse outcomes is important. Predictive models may help identify individuals at risk of such adverse outcomes. Using a fixed observation window cohort with logistic regression (LR) or machine learning (ML)

Kanat Tangwongsan, Martin Hirzel, Scott Schneider

Sliding-window aggregation is a foundational stream processing primitive that efficiently summarizes recent data. The state-of-the-art algorithms for sliding-window aggregation are highly efficient when stream data items are evicted or inserted one at a time, even when some of the insertions occur out-of-order. However, real-world streams are often not only

Zoe Fowler, Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib

This paper presents a novel approach to active learning that takes into account the non-independent and identically distributed (non-i.i.d.) structure of a clinical trial setting. There exists two types of clinical trials: retrospective and prospective. Retrospective clinical trials analyze data after treatment has been performed; prospective clinical trials

Alexandru Stanculescu

We present some results from classical homological algebra using the language of cotorsion theories in abelian categories. The results are a couple of foundational facts about homological dimension, the Kunneth formula and the universal coefficients formula. We also present some ''totally acyclic'' cotorsion theories and revisit some results from the literat

Chia-Lung Lin, Wing-Huen Ip, Yao Hsiao, Tzu-Hueng Chang

We present the analysis of 16 classical T Taur stars using LAMOST and TESS data, investigating spectral properties, photometric variations, and mass-accretion rates. All 16 stars exhibit emissions in H$\alpha$ lines, from which the average mass-accretion rate of $1.76\times10^{-9}~M_{\odot}yr^{-1}$ is derived. Two of the stars, DL Tau and Haro 6-13, show mas

Walid S. Saba

Knowledge graphs (KGs) have become the standard technology for the representation of factual information in applications such as recommendation engines, search, and question-answering systems. However, the continual updating of KGs, as well as the integration of KGs from different domains and KGs in different languages, remains to be a major challenge. What

Weiyi Li, Marco G. Giometto

Non-stationarity is the rule in the atmospheric boundary layer (ABL). Under such conditions, the flow may experience departures from equilibrium with the underlying surface stress, misalignment of shear stresses and strain rates, and three-dimensionality in turbulence statistics. Existing ABL flow theories are primarily established for statistically stationa

Tristan S. W. Stevens, Faik C. Meral, Jason Yu, Iason Z. Apostolakis

Echocardiography has been a prominent tool for the diagnosis of cardiac disease. However, these diagnoses can be heavily impeded by poor image quality. Acoustic clutter emerges due to multipath reflections imposed by layers of skin, subcutaneous fat, and intercostal muscle between the transducer and heart. As a result, haze and other noise artifacts pose a r

Weiyi Li, Marco G. Giometto

The transport of energy, mass, and momentum in the atmospheric boundary layer (ABL) is regulated by coherent structures. Although past studies have primarily focused on stationary ABL flows, the majority of real-world ABL flows are non-stationary, and a thorough examination of coherent structures under such conditions is lacking. To fill this gap, this study

Roy S. Zawadzki, Daniel L. Gillen

In observational studies, potential unobserved confounding is a major barrier in isolating the average causal effect (ACE). In these scenarios, two main approaches are often used: confounder adjustment for causality (CAC) and instrumental variable analysis for causation (IVAC). Nevertheless, both are subject to untestable assumptions and, therefore, it may b

Daniel Melvin, Fulu Zheng, Kewei Sun, Zhengjie Tan

Employing the multiple Davydov D$_2$ Ansatz with the time-dependent variational principle, we have investigated photon-assisted Landau-Zener (LZ) transitions and qubit manipulation in a hybrid quantum electrodynamics device. Modelled as a Rabi dimer, the device comprises of two interacting transmission-line resonators, each coupled to a qubit. The qubits, dr

Jun Nishimura, Katsuta Sakai, Atis Yosprakob

It is well known that quantum tunneling can be described by instantons in the imaginary-time path integral formalism. However, its description in the real-time path integral formalism has been elusive. Here we establish a statement that quantum tunneling can be characterized in general by the contribution of complex saddle points, which can be identified by

Zeyu Jiang, João P. C. Bertoldo, Etienne Decencière

Anomaly detection (AD) in images is a fundamental computer vision problem by deep learning neural network to identify images deviating significantly from normality. The deep features extracted from pretrained models have been proved to be essential for AD based on multivariate Gaussian distribution analysis. However, since models are usually pretrained on a

Julia Gaudio, Xiaochun Niu, Ermin Wei

We study the problem of exact community recovery in the Geometric Stochastic Block Model (GSBM), where each vertex has an unknown community label as well as a known position, generated according to a Poisson point process in $\mathbb{R}^d$. Edges are formed independently conditioned on the community labels and positions, where vertices may only be connected

Theodore D. Drivas, Perry L. Johnson, Cristian C. Lalescu, Michael Wilczek

We present an analysis of the Navier-Stokes equations based on a spatial filtering technique to elucidate the multi-scale nature of fully developed turbulence. In particular, the advection of a band-pass-filtered small-scale contribution by larger scales is considered, and rigorous upper bounds are established for the various dynamically active scales. The a

Patrick Redmond, Lindsey Kuper

The Glasgow Haskell Compiler is known for its feature-laden runtime system (RTS), which includes lightweight threads, asynchronous exceptions, and a slew of other features. Their combination is powerful enough that a programmer may complete the same task in many different ways -- some more advisable than others. We present a user-accessible actor framework h

Claudio Bravo, Benoit Loisel

Let $\mathcal{C}$ be a smooth, projective, geometrically integral curve defined over a perfect field $\mathbb{F}$. Let $k=\mathbb{F}(\mathcal{C})$ be the function field of $\mathcal{C}$. Let $\mathbf{G}$ be a split simply connected semisimple $\mathbb{Z}$-group scheme. Let $\mathcal{S}$ be a finite set of places of $\mathcal{C}$. In this paper, we investigat

Ali Noormohammadi-Asl, Ali Ayub, Stephen L. Smith, Kerstin Dautenhahn

With the introduction of collaborative robots, humans and robots can now work together in close proximity and share the same workspace. However, this collaboration presents various challenges that need to be addressed to ensure seamless cooperation between the agents. This paper focuses on task planning for human-robot collaboration, taking into account the

Caroline McCormick, Steven R. Majewski, Verne V. Smith, Christian R. Hayes

Standard stellar evolution theory poorly predicts the surface abundances of chemical species in low-mass, red giant branch (RGB) stars. Observations show an enhancement of p-p chain and CNO cycle products in red giant envelopes, which suggests the existence of non-canonical mixing that brings interior burning products to the surface of these stars. The 12C/1

Aron Schnakenbeck, Robin Mroß, Marcus Völker, Stefan Kowalewski

The graphical modeling language GRAFCET is used as a formal specification language in industrial control design. This paper proposes a structural analysis that approximates the variable values of GRAFCET to allow verification on specification level. GRAFCET has different elements resulting in concurrent behavior, which in general results in a large state spa

P. -O. Downey, O. Gingras, C. -D. Hébert, M. Charlebois

It has been reported that upon doping a Mott insulator, there can be a crossover to a pseudogaped metallic phase followed by a first-order transition to another thermodynamically stable metallic phase. We call this first-order metal-metal transition the Sordi transition. It was argued that the initial reports of Sordi transitions at finite temperature could

Olha Popova, Steven J. Randolph, Sabine M. Neumayer, Liangbo Liang

Resistive switching in thin films has been widely studied in a broad range of materials. Yet the mechanisms behind electroresistive switching have been persistently difficult to decipher and control, in part due to their non-equilibrium nature. Here, we demonstrate new experimental approaches that can probe resistive switching phenomena, utilizing amorphous

Tatiana V. Demidova, Ivan I. Shevchenko

Ways of formation of azimuthal resonant patterns in circumstellar planetesimal disks with planets are considered. Our analytical estimates and massive numerical experiments show that the disk particles that initially reside in zones of low-order mean-motion resonances with the planet may eventually concentrate into potentially observable azimuthal patterns.

Ricardo Campos, Albin Grataloup

This is a survey on recent progress in algebraic deformation theory and the application of algebraic operads to its study. We review the classical homotopical tools in the theory of algebraic operads, namely Koszul duality. We give concrete examples of applications of such tools to various flavours of problems related to deformations of algebraic structures.

CMS Collaboration

The production of prompt $\Lambda^+_\mathrm{c}$ baryons is measured via the exclusive decay channel $\Lambda^+_\mathrm{c}$ $\to$ pK$^-\pi^+$ at a center-of-mass energy per nucleon pair of 5.02 TeV, using proton-proton (pp) and lead-lead (PbPb) collision data collected by the CMS experiment at the CERN LHC. The pp and PbPb data were obtained in 2017 and 2018

CMS Collaboration

Measurements of the charge-dependent two-particle angular correlation function in proton-lead (pPb) collisions at a nucleon-nucleon center-of-mass energy of $\sqrt{s_\mathrm{NN}}$ = 8.16 TeV and lead-lead (PbPb) collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV are reported. The pPb and PbPb data sets correspond to integrated luminosities of 186 nb$^{-1}$ and

Morris M. Yang, Mustafa Ozlu, Samuel Peana, Vahagn Mkhitaryan

In this work a hybrid nanoplasmonic-Weyl Semimetal (WSM) structure is realized for the first time utilizing silver nanopatch antennas and WSM Tantalum Arsenide (TaAs). The studied hybrid WSM-nanoplasmonic structure demonstrated a substantial, over x4.5 enhancement of the second harmonic generation (SHG) process compared to a bare TaAs film. To realize the hy

Yang Xu, Sirui Tang, A. Nicholas Black, Robert W. Boyd

Orthogonal optical coding is widely used in classical multiuser communication networks. Using the phase conjugation property of stimulated parametric down-conversion, we extend the current orthogonal optical coding scheme to the spatial domain to encode and decode image information. In this process, the idler beam inherits the complex conjugate of the field

Guy David, Antoine Gloria, Svitlana Mayboroda

Consider the Schr\"odinger operator $-\triangle+\lambda V$ with non-negative iid random potential $V$ of strength $\lambda>0$. We prove existence and uniqueness of the associated landscape function on the whole space, and show that its correlations decay exponentially. As a main ingredient we establish the (annealed and quenched) exponential decay of the Gre

Zeinab Nezami, Evangelos Pournaras, Amir Borzouie, Jie Xu

Smart mobility becomes paramount for meeting net-zero targets. However, autonomous, self-driving and electric vehicles require more than ever before an efficient, resilient and trustworthy computational offloading backbone that expands throughout the edge-to-cloud continuum. Utilizing on-demand heterogeneous computational resources for smart mobility is chal

Wencheng Ji, Ori Hachmo, Naama Barkai, Ariel Amir

Transcription Factors (TFs) are proteins crucial for regulating gene expression. Effective regulation requires the TFs to rapidly bind to their correct target, enabling the cell to respond efficiently to stimuli such as nutrient availability or the presence of toxins. However, the search process is hindered by slow diffusive movement and the presence of `fal

Charles-Philippe Lajoie, Matthew Lallo, Marcio Meléndez, Nicolas Flagey

We summarize JWST's measured telescope performance across science Cycle 1. The stability of segments alignments is typically better than 10 nanometers RMS between measurements every two days, leading to highly stable point spread functions. The frequency of segment "tilt events" decreased significantly, and larger tilt events ceased entirely, as structures g

Ragil Brand Tsafack Ndongmo, Saleh Mahamat, Thomas Bouetou, Conrad Bertrand Tabi

In this paper, we investigate the influence of perfect fluid dark matter and quantum corrections on the thermodynamics of non-linear magnetic-charged black hole. We consider the metric of the static non-linear magnetic-charged black hole in the background of perfect fluid dark matter. Starting with the black hole temperature and the corrected entropy, we use

Makoto Natsuume, Takashi Okamura

It remains unclear in general how the pole-skipping appears as a physical phenomenon, and we study the issue in the context of the AdS soliton. The pole-skipping has been discussed in black hole backgrounds, but the pole-skipping occurs even in the AdS soliton background. The geometry has a compact $S^1$-direction, and we compute the mass spectrum for the bu

Daniel Shy, Richard S. Woolf, Clio C. Sleator, Eric A. Wulf

There is a growing interest in astrophysics to fill in the observational gamma-ray MeV gap. We, therefore, developed a CsI:Tl calorimeter prototype as a subsystem to a balloon-based Compton and Pair-production telescope known as ComPair. ComPair is a technology demonstrator for a gamma-ray telescope in the MeV range that is comprised of 4 subsystems: the dou

Jonas Stein, Ivo Christ, Nicolas Kraus, Maximilian Balthasar Mansky

As an application domain where the slightest qualitative improvements can yield immense value, finance is a promising candidate for early quantum advantage. Focusing on the rapidly advancing field of Quantum Natural Language Processing (QNLP), we explore the practical applicability of the two central approaches DisCoCat and Quantum-Enhanced Long Short-Term M

Maciej Borodzik

We study local equivalence of bounded complexes over a polynomial ring $R[w]$, where $R$ is a noetherian ring. We provide a homological algebra approach to the results, the variants of which have been proved in many places in the literature.

Kuan-Ting Lin, Ting Hsu, Fahad Aziz, Yu-Chen Lin

This study conducts a theoretical investigation into the signal amplification arising from multiple Rabi sideband coherence within a one-dimensional waveguide quantum electrodynamics system. We utilize a semi-infinite waveguide to drive an anharmonic multi-level transmon with a strong coherent microwave field, examining the scattering behavior by introducing

Lindsay M. Berkhout, Adam P. Beardsley, Daniel C. Jacobs, Raven Braithwaite

We present the Completely Hackable Amateur Radio Telescope (CHART), a project that provides hands-on radio instrumentation and design experience to undergraduates while bringing accessible radio astronomy experiments to high school students and teachers. Here we describe a system which can detect 21-cm emission from the Milky Way which is optimized for cost

Anastasia Tzouvanou, Bertram Bitsch, Gabriele Pichierri

Following the assumption that the disc substructures observed in protoplanetary discs originate from the interaction between the disc and the forming planets embedded therein, we aim to test if these putative planets could represent the progenitors of the currently observed giant exoplanets. We performed N-body simulations assuming initially three, four, fiv

Adrián Agriela, Miguel Campiglia

We consider soft electrons in massless QED at tree-level. The emission amplitude at leading order in the soft electron energy factorizes in a way similar to the soft photon case. We recast the soft electron factorization formula as a Ward identity of an asymptotic charge. This leads to the first example of an asymptotic fermionic symmetry in a theory with no

Aidan Mannion, Thierry Chevalier, Didier Schwab, Lorraine Geouriot

Pre-trained transformer language models (LMs) have in recent years become the dominant paradigm in applied NLP. These models have achieved state-of-the-art performance on tasks such as information extraction, question answering, sentiment analysis, document classification and many others. In the biomedical domain, significant progress has been made in adapti