July 2023 arXiv papers — page 55

Jan-Christoph Schlage-Puchta

We show that the set of prime numbers has exponential alternating complexity, proving a conjecture by Fijalkow. We further show that the set of squarefree integers has essentially maximal possible alternating complexity.

Dmitrii Semenok, Jianning Guo, Di Zhou, Wuhao Chen

Polyhydride superconductors have been shown to possess metallic properties with a Bardeen-Cooper-Schrieffer-type superconducting ground state. Here, we provide evidence for unconventional transport associated with a pseudogap phase in cubic cerium superhydride CeH$_{10}$ ($\textit{T}$$_C$ = 116 K) at pressure of 115-125 GPa. A large negative magnetoresistanc

Florian Nortier

Tachyon condensation in quantum field theory (QFT) plays a central role in models of fundamental interactions and cosmology. Inspired by tower truncation in string field theory, ultraviolet completions were proposed with infinite-derivative form factors that preclude the appearance of pathological ghosts in the particle spectrum, contrary to other local high

Sergei Filippov, Matea Leahy, Matteo A. C. Rossi, Guillermo García-Pérez

Until fault-tolerance becomes implementable at scale, quantum computing will heavily rely on noise mitigation techniques. While methods such as zero noise extrapolation with probabilistic error amplification (ZNE-PEA) and probabilistic error cancellation (PEC) have been successfully tested on hardware recently, their scalability to larger circuits may be lim

Debkanta Ghosh, Keshav Das Agarwal, Pritam Halder, Aditi Sen De

The cluster state acquired by evolving the nearest-neighbor (NN) Ising model from a completely separable state is the resource for measurement-based quantum computation. Instead of an NN system, a variable-range power law interacting Ising model can generate a genuine multipartite entangled (GME) weighted graph state (WGS) that may reveal intrinsic character

Jan-Christoph Schlage-Puchta

We construct an algebra of dimension $2^{\aleph_0}$ consisting only of functions which in no point possess a finite one-sided derivative. We further show that some well known nowhere differentiable functions generate algebras, which contain functions which are differentiable at some points, but where for all functions in the algebra the set of points of diff

Suvendu Ghosh, Snehasish Nandy, Jian-Xin Zhu, A. Taraphder

We investigate quantum transport through a rectangular potential barrier in Weyl semimetals (WSMs) and multi-Weyl semimetals (MSMs), within the framework of Landauer-B\"uttiker formalism. Our study uncovers the role of nodal topology imprinted in the electric current and the shot noise. We find that, in contrast to the finite odd-order conductance and noise

M. S. Mrudul, Peter M. Oppeneer

We theoretically investigate the optically-induced demagnetization of ferromagnetic FePt using the time-dependent density functional theory (TDDFT). We compare the demagnetization mechanism in the perturbative and nonperturbative limits of light-matter interaction and show how the underlying mechanism of the ultrafast demagnetization depends on the driving l

Gianmarco Tiddia, Luca Sergi, Bruno Golosio

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework of learning through this kind of plasticity, capable of taking into account several features of the connectivity and pa

Martin Formanek, John P. Palastro, Dillon Ramsey, Stefan Weber

Vacuum birefringence produces a differential phase between orthogonally polarized components of a weak electromagnetic probe in the presence of a strong electromagnetic field. Despite representing a hallmark prediction of quantum electrodynamics, vacuum birefringence remains untested in pure light configurations due to the extremely large electromagnetic fie

Ming Chen, Sareh Nabi, Marciano Siniscalchi

Contemporary real-world online ad auctions differ from canonical models [Edelman et al., 2007; Varian, 2009] in at least four ways: (1) values and click-through rates can depend upon users' search queries, but advertisers can only partially "tune" their bids to specific queries; (2) advertisers do not know the number, identity, and precise value distribution

Alexander Ortiz

We apply recent circle tangency estimates due to Pramanik--Yang--Zahl to prove sharp weighted Fourier extension estimates for the cone in $\mathbb{R}^3$ and $1$-dimensional weights. The idea of using circle tangency estimates to study Fourier extension of the cone is originally due to Tom Wolff, who used it in part to prove the first decoupling estimates. We

Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet

The rise of Decentralized Federated Learning (DFL) has enabled the training of machine learning models across federated participants, fostering decentralized model aggregation and reducing dependence on a server. However, this approach introduces unique communication security challenges that have yet to be thoroughly addressed in the literature. These challe

Piyali Bhar, Sneha Pradhan, Adnan Malik, P. K. Sahoo

In this study, we explore several new characteristics of a static anisotropic hybrid star with strange quark matter (SQM) and ordinary baryonic matter (OBM) distribution. Here, we use the MIT bag model equation of state to connect the density and pressure of SQM inside stars, whereas the linear equation of state $p_r =\alpha \rho-\beta$ connects the radial p

Ryuto Koike, Masahiro Kaneko, Naoaki Okazaki

Large Language Models (LLMs) have achieved human-level fluency in text generation, making it difficult to distinguish between human-written and LLM-generated texts. This poses a growing risk of misuse of LLMs and demands the development of detectors to identify LLM-generated texts. However, existing detectors lack robustness against attacks: they degrade det

Sam Mellick

Let $G_1$ be a semisimple real Lie group and $G_2$ another locally compact second countable unimodular group. We prove that $G_1 \times G_2$ has fixed price one if $G_1$ has higher rank, or if $G_1$ has rank one and $G_2$ is a $p$-adic split reductive group of rank at least one. As an application we resolve a question of Gaboriau showing $SL(2,\mathbb{Q})$ h

Iris van der Giessen, Raheleh Jalali, Roman Kuznets

We introduce a Gentzen-style framework, called layered sequent calculi, for modal logic K5 and its extensions KD5, K45, KD45, KB5, and S5 with the goal to investigate the uniform Lyndon interpolation property (ULIP), which implies both the uniform interpolation property and the Lyndon interpolation property. We obtain complexity-optimal decision procedures f

George Hulsey, David L. Alderson, Jean Carlson

Birth and death Markov processes can model stochastic physical systems from percolation to disease spread and, in particular, wildfires. We introduce and analyze a birth-death-suppression Markov process as a model of controlled culling of an abstract, dynamic population. Using analytic techniques, we characterize the probabilities and timescales of outcomes

Orhan Donmez

Studying the gravitational collapse of dust particles toward newly formed black holes has gained popularity following the observation of gravitational waves resulting from the merger of black holes. In this paper, we focus on modelling the descent of dust debris toward a black hole using a numerical code that incorporates relativistic hydrodynamics in the fr

David Berenstein, George Hulsey

We describe the application of the quantum mechanical bootstrap to the solution of one-dimensional scattering problems. By fixing a boundary and modulating the Robin parameter of the boundary conditions we are able to extract the reflection coefficient for various potentials and compare to physical expectations. This includes an application of semidefinite p

Nicholas Fleming-Vázquez

We give elementary and explicit sufficient conditions (in particular, a functional correlation bound) for deterministic homogenisation (convergence to a stochastic differential equation) for discrete-time fast-slow systems of the form \[ x_{k+1} = x_k + n^{-1}a_n(x_k,y_k) + n^{-1/2}b_n(x_k,y_k), \quad y_{k+1}=T_n y_k. \] We then prove that these sufficient c

Monika Angwani, Tushar Mahendrakar, Kaustubh Rane

The advances in materials and biological sciences have necessitated the use of molecular simulations to study polymers. The Markov chain Monte Carlo simulations enable the sampling of relevant microstates of polymeric systems by traversing paths that are impractical in molecular dynamics simulations. Several advances in applying Monte Carlo simulations to po

Arjun Karki, Varsha P. Kulkarni, Simon Weng, Céline Péroux

Understanding how galaxies interact with the circumgalactic medium (CGM) requires determining how galaxies morphological and stellar properties correlate with their CGM properties. We report an analysis of 66 well-imaged galaxies detected in HST and VLT MUSE observations and determined to be within $\pm$500 km s$^{-1}$ of the redshifts of strong intervening

Ishita Pushkarna, Árpád Pásztor, Christoph Renner

Synthetic materials and heterostructures obtained by the controlled stacking of exfoliated monolayers are emerging as attractive functional materials owing to their highly tunable properties. We present a detailed scanning tunneling microscopy and spectroscopy study of single layer MoS$_2$-on-gold heterostructures as a function of twist angle. We find that t

Rita T. Sousa, Sara Silva, Catia Pesquita

Knowledge graphs represent facts about real-world entities. Most of these facts are defined as positive statements. The negative statements are scarce but highly relevant under the open-world assumption. Furthermore, they have been demonstrated to improve the performance of several applications, namely in the biomedical domain. However, no benchmark dataset

Saypraseuth Mounsaveng, Issam Laradji, David Vázquez, Marco Perdersoli

Training a deep learning model to classify histopathological images is challenging, because of the color and shape variability of the cells and tissues, and the reduced amount of available data, which does not allow proper learning of those variations. Variations can come from the image acquisition process, for example, due to different cell staining protoco

R. Aiudi, R. Pacelli, A. Vezzani, R. Burioni

Feature learning, or the ability of deep neural networks to automatically learn relevant features from raw data, underlies their exceptional capability to solve complex tasks. However, feature learning seems to be realized in different ways in fully-connected (FC) or convolutional architectures (CNNs). Empirical evidence shows that FC neural networks in the

Mahmoud Ali, Lantao Liu

We propose a new frontier concept called the Gaussian Process Frontier (GP-Frontier) that can be used to locally navigate a robot towards a goal without building a map. The GP-Frontier is built on the uncertainty assessment of an efficient variant of sparse Gaussian Process. Based only on local ranging sensing measurement, the GP-Frontier can be used for nav

Qirui Li, Andreas Mihatsch

We formulate Guo--Jacquet type fundamental lemma conjectures and arithmetic transfer conjectures for inner forms of $GL_{2n}$. Our main results confirm these conjectures for division algebras of invariant $1/4$ and $3/4$.

Cesare Grazioli, Oscar Baseggio, Mauro Stener, Giovanna Fronzoni

The electronic structure of short-chain thiophenes (thiophene, 2,2'-bithiophene and 2,2':5',2'-terthiophene) in the gas phase has been investigated by combining the outcomes of Near-Edge X-ray-Absorption Fine-Structure (NEXAFS) and X-ray Photoemission Spectroscopy (XPS) at the C K-edge with those of density functional theory (DFT) calculations. The calculate

Eloi Tanguy

Optimal Transport has sparked vivid interest in recent years, in particular thanks to the Wasserstein distance, which provides a geometrically sensible and intuitive way of comparing probability measures. For computational reasons, the Sliced Wasserstein (SW) distance was introduced as an alternative to the Wasserstein distance, and has seen uses for trainin

Stef Baas, Richard J. Boucherie, Aleida Braaksma

A sampling-based method is introduced to approximate the Gittins index for a general family of alternative bandit processes. The approximation consists of a truncation of the optimization horizon and support for the immediate rewards, an optimal stopping value approximation, and a stochastic approximation procedure. Finite-time error bounds are given for the

Kamil Khan, Sudeep Pasricha

Network-on-chip (NoC) architectures provide a scalable, high-performance, and reliable interconnect for emerging manycore systems. The routing policies used in NoCs have a significant impact on overall performance. Prior efforts have proposed reinforcement learning (RL)-based adaptive routing policies to avoid congestion and minimize latency in NoCs. The out

Sayan Saha, Louis Legrand, Julien Carron

Clusters of galaxies, being the largest collapsed structures in the universe, offer valuable insights into the nature of cosmic evolution. Precise calibration of the mass of clusters can be obtained by extracting their gravitational lensing signal on the Cosmic Microwave Background (CMB) fluctuations. We extend and test here the performance achieved on clust

Henrique Musseli Cezar, Teresa Duarte Lanna, Daniela Andrade Damasceno, Alexsandro Kirch

Carbon nanostructures are promising materials to improve the performance of current gas separation membrane technologies. From the molecular modeling perspective, an accurate description of the interfacial interactions is mandatory to understand the gas selectivity in the context of greenhouse gases applications. Most of the molecular dynamics simulations st

Aakash Bansal, Siyuan Jiang, Sakib Haque, Collin McMillan

Source code summarization is the task of writing natural language descriptions of source code behavior. Code summarization underpins software documentation for programmers. Short descriptions of code help programmers understand the program quickly without having to read the code itself. Lately, neural source code summarization has emerged as the frontier of

Konstantine Arkoudas

GPT-4 was released in March 2023 to wide acclaim, marking a very substantial improvement across the board over GPT-3.5 (OpenAI's previously best model, which had powered the initial release of ChatGPT). However, despite the genuinely impressive improvement, there are good reasons to be highly skeptical of GPT-4's ability to reason. This position paper discus

Daniela Andrade Damasceno, Henrique Musseli Cezar, Teresa Duarte Lanna, Alexsandro Kirch

We investigate the mechanical and adsorption properties of single-walled carbon nanotubes (SWCNTs) filled with greenhouse gases through Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations using a recently developed parameterization for the cross-terms of the Lenard-Jones (LJ) potential. Carbon nanotubes interact strongly with CO$_2$ co

Daniel C. Hackett, Patrick R. Oare, Dimitra A. Pefkou, Phiala E. Shanahan

The two gravitational form factors of the pion, $A^{\pi}(t)$ and $D^{\pi}(t)$, are computed as functions of the momentum transfer squared $t$ in the kinematic region $0\leq -t< 2~\text{GeV}^2$ on a lattice QCD ensemble with quark masses corresponding to a close-to-physical pion mass $m_{\pi}\approx 170~\text{MeV}$ and $N_f=2+1$ quark flavors. The flavor deco

Eric Schneider, Sushanth Jayanth, Abhisesh Silwal, George Kantor

Robotic pruning of dormant grapevines is an area of active research in order to promote vine balance and grape quality, but so far robotic efforts have largely focused on planar, simplified vines not representative of commercial vineyards. This paper aims to advance the robotic perception capabilities necessary for pruning in denser and more complex vine str

Louis-Paul Rivest, Mamadou Yauck

The properties of the generalized Waring distribution defined on the non negative integers are reviewed. Formulas for its moments and its mode are given. A construction as a mixture of negative binomial distributions is also presented. Then we turn to the Petersen model for estimating the population size $N$ in a two-way capture recapture experiment. We cons

Kaiwen Wang, Junxiong Wang, Yueying Li, Nathan Kallus

Join order selection (JOS) is the problem of ordering join operations to minimize total query execution cost and it is the core NP-hard combinatorial optimization problem of query optimization. In this paper, we present JoinGym, a lightweight and easy-to-use query optimization environment for reinforcement learning (RL) that captures both the left-deep and b

Suhail Haque, Abhijit Chatterjee

Lattice simulations are an important class of problems in crystalline solids, surface science, alloys, adsorption, absorption, separation, catalysis, to name a few. We describe a fast computational method for performing lattice thermodynamic calculations that is based on the use of the reverse Monte Carlo (RMC) technique and multiple short-range order (SRO)

Philippe Lammerts, Philip Lippmann, Yen-Chia Hsu, Fabio Casati

Hate speech moderation remains a challenging task for social media platforms. Human-AI collaborative systems offer the potential to combine the strengths of humans' reliability and the scalability of machine learning to tackle this issue effectively. While methods for task handover in human-AI collaboration exist that consider the costs of incorrect predicti

Jerome Revaud, Yohann Cabon, Romain Brégier, JongMin Lee

Scene coordinates regression (SCR), i.e., predicting 3D coordinates for every pixel of a given image, has recently shown promising potential. However, existing methods remain limited to small scenes memorized during training, and thus hardly scale to realistic datasets and scenarios. In this paper, we propose a generalized SCR model trained once to be deploy

Matthew Doniere, David Garfinkle

We provide a mean curvature flow method for numerical cosmology and test it on cases of inhomogenous inflation. The results show (in a proof of concept way) that the method can handle even large inhomogeneities that result from different regions exiting inflation at different times.

Claire Merriman

The connection between cutting sequences of geodesics on the modular surface $\operatorname{PSL}(2,\mathbb{Z})\backslash\mathbb{H}$ and regular continued fractions was established by Series, and Heersink expanded the cross-section of the geodesic flow on the unit tangent bundle to the modular surface to describe the Farey tent-map as a slowdown of the Gauss

Qi Yang, Shuo Feng, Tianlin Zhao, Saleh Kalantari

Intuition, metacognition, and subjective uncertainty interact in complex ways to shape the creative design process. Design intuition, a designer's innate ability to generate creative ideas and solutions based on implicit knowledge and experience, is often evaluated and refined through metacognitive monitoring. This self-awareness and management of cognitive

Bibek Dash, Suhail Haque, Abhijit Chatterjee

The cluster expansion model (CEM) provides a powerful computational framework for rapid estimation of configurational properties in disordered systems. However, the traditional CEM construction procedure is still plagued by two fundamental problems: (i) even when only a handful of site cluster types are included in the model, these clusters can be correlated

Klaus Zollner, Eike Icking, Jaroslav Fabian

Van der Waals (vdW) heterostructures consisting of Bernal bilayer graphene (BLG) and hexagonal boron nitride (hBN) are investigated. By performing first-principles calculations we capture the essential BLG band structure features for several stacking and encapsulation scenarios. A low-energy model Hamiltonian, comprising orbital and spin-orbit coupling (SOC)

Sagar Adhikari, Pablo Penil, John Ryan Westernacher-Schneider, Alberto Dominguez

PG 1553+113 is a well-known blazar exhibiting evidence of a $\sim\! 2.2$-yr quasi-periodic oscillation (QPO) in radio, optical, X-ray, and $\gamma$-ray bands. Since QPO mechanisms often predict multiple QPOs, we search for a second QPO in its historical optical light curve covering a century of observations. Despite challenging data quality issues, we find h

Krystian Strzałka, Szymon Mazurek, Maciej Wielgosz, Paweł Russek

This paper explores the innovative use of simulation environments to enhance data acquisition and diagnostics in veterinary medicine, focusing specifically on gait analysis in dogs. The study harnesses the power of Blender and the Blenderproc library to generate synthetic datasets that reflect diverse anatomical, environmental, and behavioral conditions. The

Hongxu Chen, Chanwoo Kim

In this short note, we prove an $L^6$-control of the macroscopic part of the linear Boltzmann and Landau equations. This result is an extension of the test function method of Esposito-Guo-Kim-Marra~\cite{EGKM}\cite{EGKM2} to the specular reflection boundary condition, in which we crucially used the Korn's inequality \cite{DV2} and the system of symmetric Poi

Kilian Scheffter, Jonathan Will, Claudius Riek, Herve Jousselin

Ultrashort time-domain spectroscopy and field-resolved spectroscopy of molecular fingerprints are gold standards for detecting samples' constituents and internal dynamics. However, they are hindered by the Nyquist criterion, leading to prolonged data acquisition, processing times, and sizable data volumes. In this work, we present the first experimental demo

M. G. Ivanov, V. A. Dudchenko, V. V. Naumov

For QFT on a lattice of dimension d>=3, the vacuum energy (both bosonic and fermionic) is zero if the Hamiltonian is a function of the square of the momentum, and the calculation of the vacuum energy is performed in the ring of residue classes modulo N. This fact is related to a problem from number theory about the number of ways to represent a number as a s

Álvaro Mozota Frauca

In this paper I introduce the idea of geometrogenesis as suggested in the group field theory literature and I offer a criticism of it. Geometrogenesis in the context of GFT is the idea that what we observe as the big bang is nothing else but a phase transition from a non-geometric phase of the universe to a geometric one which is the one we live in and the o

Jun Le Goh, Joseph S. Miller, Mariya I. Soskova, Linda Westrick

Let At denote the set of infinite sequences of effective dimension t. We determine both how close and how far an infinite sequence of dimension s can be from one of dimension t, measured using the Besicovitch pseudometric. We also identify classes of sequences for which these infima and suprema are realized as minima and maxima. When t < s, we find d(X,At) i

Zack Fitzsimmons, Edith Hemaspaandra

It is important to study how strategic agents can affect the outcome of an election. There has been a long line of research in the computational study of elections on the complexity of manipulative actions such as manipulation and bribery. These problems model scenarios such as voters casting strategic votes and agents campaigning for voters to change their

Jake Song, Elad Deiss-Yehiely, Serra Yesilata, Gareth H. McKinley

Soft biological tissues exhibit a remarkable resilience to large mechanical loads, a property which is associated with the strain stiffening capability of the biopolymer networks that structurally support the tissues. Yet, recent studies have shown that composite systems such as tissues and blood clots exhibit mechanical properties that contradict those of t

Jackson Loper, Noam Solomon, Jeffrey Regier

Modern cell-perturbation experiments expose cells to panels of hundreds of stimuli, such as cytokines or CRISPR guides that perform gene knockouts. These experiments are designed to investigate whether a particular gene is upregulated or downregulated by exposure to each treatment. However, due to high levels of experimental noise, typical estimators of whet

Amit Kumar Mishra

Calibration of sensors is a major challenge especially in inexpensive sensors and sensors installed in inaccessible locations. The feasibility of calibrating sensors without the need for a standard sensor is called blind calibration. There is very little work in the open literature on totally blind calibration. In this work we model the sensing process as a

Xi Zhang, Orla A. Murphy, Paul D. McNicholas

Many common clustering methods cannot be used for clustering multivariate longitudinal data in cases where variables exhibit high autocorrelations. In this article, a copula kernel mixture model (CKMM) is proposed for clustering data of this type. The CKMM is a finite mixture model which decomposes each mixture component's joint density function into its cop

Michael G. Rawson, Audun Myers, Robert Green, Michael Robinson

There is increasing focus on analyzing data represented as hypergraphs, which are better able to express complex relationships amongst entities than are graphs. Much of the critical information about hypergraph structure is available only in the intersection relationships of the hyperedges, and so forming the "intersection complex" of a hypergraph is quite v

Giusy Monzillo, Safet Penjić

Let ${\cal M}$ denote the Bose--Mesner algebra of a commutative $d$-class association scheme ${\mathfrak X}$ (not necessarily symmetric), and $\Gamma$ denote a (strongly) connected (directed) graph with adjacency matrix $A$. Under the assumption that $A$ belongs to ${\cal M}$, we describe the combinatorial structure of $\Gamma$. Moreover, we provide an algeb

Markus Faustmann, Carlo Marcati, Jens Markus Melenk, Christoph Schwab

On polytopal domains in $\mathbb{R}^3$, we prove weighted analytic regularity of solutions to the Dirichlet problem for the integral fractional Laplacian with analytic right-hand side. Employing the Caffarelli-Silvestre extension allows to localize the problem and to decompose the regularity estimates into results on vertex, edge, face, vertex-edge, vertex-f

Peng Huang, Zhiguo Yin, Tianjian Bian, Shigang Hou

A set of nozzle equipment for proton therapy is now being developed at China Institute of Atomic Energy. To facilitate the off-line commissioning of the whole equipment, a set of ionization chamber signal generation system, the test electronics, is designed. The system uses ZYNQ SoC as the main control unit and outputs the beam dose analog signal through DAC

Davide Bilò, Shiri Chechik, Keerti Choudhary, Sarel Cohen

Despite extensive research on distance oracles, there are still large gaps between the best constructions for spanners and distance oracles. Notably, there exist sparse spanners with a multiplicative stretch of $1+\varepsilon$ plus some additive stretch. A fundamental open problem is whether such a bound is achievable for distance oracles as well. Specifical

Neha Bhatia, Anuradha Gupta

The aim of this paper is to discuss the characterizations of the composition operators on Orlicz-Lorentz space to have finite ascent (or descent).

Swarag Thaikkandi, K. M. Sharika

In recent years, recurrent quantification analysis (RQA) and its multi-dimensional version (MdRQA) have emerged as a popular tool for assessing interpersonal behavioral or physiological synchrony in groups of two or more individuals. While experimental data in such studies are typically collected for a fixed, pre-determined duration, naturally occurring phen

Sadok Kallel, Sana Louhichi

In this paper we extend results on reconstruction of probabilistic supports of random i.i.d variables to supports of dependent stationary $\mathbb R^d$-valued random variables. All supports are assumed to be compact of positive reach in Euclidean space. Our main results involve the study of the convergence in the Hausdorff sense of a cloud of stationary depe

James Mason, Clement Erignoux, Robert Jack, Maria Bruna

We consider a lattice model of active matter with exclusion and derive its hydrodynamic description exactly. The hydrodynamic limit leads to an integro-differential equation for the density of particles with a given orientation. Volume exclusion results in nonlinear mobility dependent on spatial density. Such models of active matter can support motility-indu

Anurag Singh, Mahalakshmi Sabanayagam, Krikamol Muandet, Debarghya Ghoshdastidar

Test-time defenses are used to improve the robustness of deep neural networks to adversarial examples during inference. However, existing methods either require an additional trained classifier to detect and correct the adversarial samples, or perform additional complex optimization on the model parameters or the input to adapt to the adversarial samples at

Pao-Kang Chen, Ian Briggs, Chaohan Cui, Liang Zhang

Nonlinear frequency mixing is of critical importance in extending the wavelength range of optical sources. It is also indispensable for emerging applications such as quantum information and photonic signal processing. Conventional lithium niobate with periodic poling is the most widely used device for frequency mixing due to the strong second-order nonlinear

Oscar Jarrin

We consider the steady-state Boussinesq system in the whole three-dimensional space, with the action of external forces and the gravitational acceleration. First, for $3<p\leq +\infty$ we prove the existence of weak $L^p$-solutions. Moreover, within the framework of a slightly modified system, we discuss the possibly non-existence of $L^p-$solutions for $1\l

Elad Hazan, Nimrod Megiddo

A new algorithm for regret minimization in online convex optimization is described. The regret of the algorithm after $T$ time periods is $O(\sqrt{T \log T})$ - which is the minimum possible up to a logarithmic term. In addition, the new algorithm is adaptive, in the sense that the regret bounds hold not only for the time periods $1,\ldots,T$ but also for ev

Sarah Garcia Jones, Nicholas Materise, Ka Wun Leung, Brian D. Isakov

In recent years, the implementation of thin-film Ta has led to improved coherence times in superconducting circuits. Efforts to further optimize this materials set have become a focus of the subfield of materials for superconducting quantum computing. It has been previously hypothesized that grain size could be correlated with device performance. In this wor

Simone Zini, Mirko Paolo Barbato, Flavio Piccoli, Paolo Napoletano

In this work, we assess several deep learning strategies for hyperspectral pansharpening. First, we present a new dataset with a greater extent than any other in the state of the art. This dataset, collected using the ASI PRISMA satellite, covers about 262200 km2, and its heterogeneity is granted by randomly sampling the Earth's soil. Second, we adapted seve

Enrico Cannizzaro, Gabriele Franciolini, Paolo Pani

Gravity theories that modify General Relativity in the slow-motion regime can introduce nonperturbative corrections to the stochastic gravitational-wave background~(SGWB) from supermassive black-hole binaries in the nano-Hertz band, while remaining perturbative in the highly-relativistic regime and satisfying current post-Newtonian~(PN) constraints. We prese

Julio Melio, Silke E. Henkes, Daniela J. Kraft

Floppy microscale spring networks are widely studied in theory and simulations, but no well-controlled experimental system currently exists. Here, we show that square lattices consisting of colloid-supported lipid bilayers functionalized with DNA linkers act as microscale floppy spring networks. We extract their normal modes by inverting the particle displac

Pasquale Blasi, Giovanni Morlino

Cosmic ray acceleration at the termination shock of compact star clusters has recently received much attention, mainly because of the detection of gamma ray emission from some of such astrophysical sources. Here we focus on the acceleration of nuclei at the termination shock and we investigate the role played by proton energy losses and spallation reactions

Mayug Maniparambil, Chris Vorster, Derek Molloy, Noel Murphy

Contrastive pretrained large Vision-Language Models (VLMs) like CLIP have revolutionized visual representation learning by providing good performance on downstream datasets. VLMs are 0-shot adapted to a downstream dataset by designing prompts that are relevant to the dataset. Such prompt engineering makes use of domain expertise and a validation dataset. Mea

A. S. Nikonov, Y. Y. Kovalev, E. V. Kravchenko, I. N. Pashchenko

We present full-track high-resolution radio observations of the jet of the galaxy M87 at 8 and 15 GHz. These observations were taken over three consecutive days in May 2009 using the Very Long Baseline Array (VLBA), one antenna of the Very Large Array (VLA), and the Effelsberg 100 m telescope. Our produced images have dynamic ranges exceeding 20,000:1 and re

Yoel Groman

For a compact set $K$ with contact type boundary in a symplectic manifold $M$ we construct a spectral sequence from the local Floer homology of the Reeb orbits, as studied by \cite{Mclean2012}, to the relative symplectic cohomology of $K$ in $M$ over the Novikov ring. The spectral sequence is functorial with respect to inclusions which are not required to be

Raphael Gastaldello, Antoine Henrot, Ilaria Lucardesi

We study the Blaschke-Santal\'o diagram associated to the area, the perimeter, and the moment of inertia. We work in dimension 2, under two assumptions on the shapes: convexity and the presence of two orthogonal axis of symmetry. We discuss topological and geometrical properties of the diagram. As a by-product we address a conjecture by P\'olya, in the simpl

Jingchen Hu

Suppose $\Omega_0,\Omega_1$ are two bounded strongly $\mathbb{C}$-convex domains in $\mathbb{C}^n$, with $n\geq 2$ and $\Omega_1\supset\overline{\Omega_0}$. Let $\mathcal{R}=\Omega_1\backslash\overline{\Omega_0}$. We call $\mathcal{R}$ a $\mathbb{C}$-convex ring. We will show that for a solution $\Phi$ to the homogenous complex Monge-Amp\`ere equation in $\m

Achinta Kumar Nandi

Suppose $V$ is a singular complex analytic curve inside $\mathbb{C}^{2}$. We investigate when a singular or non-singular complex analytic curve $W$ inside $\mathbb{C}^{2}$ with sufficiently small Hausdorff distance $d_{H}(V, W)$ from $V$ must intersect $V$. We obtain a sufficient condition on $W$ which when satisfied gives an affirmative answer to our questi

Khashayar Khosravi, Renato Paes Leme, Chara Podimata, Apostolis Tsorvantzis

We propose a model for learning with bandit feedback while accounting for deterministically evolving and unobservable states that we call Bandits with Deterministically Evolving States ($B$-$DES$). The workhorse applications of our model are learning for recommendation systems and learning for online ads. In both cases, the reward that the algorithm obtains

Héctor Carrión, Narges Norouzi

Skin diseases affect millions of people worldwide, across all ethnicities. Increasing diagnosis accessibility requires fair and accurate segmentation and classification of dermatology images. However, the scarcity of annotated medical images, especially for rare diseases and underrepresented skin tones, poses a challenge to the development of fair and accura

Takayuki Koike

Let $X$ be a non-singular compact complex surface such that the anticanonical line bundle admits a smooth Hermitian metric with semi-positive curvature. For a non-singular hypersurface $Y$ which defines an anticanonical divisor, we investigate the $\overline{\partial}$ cohomology group $H^1(M, \mathcal{O}_M)$ of the complement $M=X\setminus Y$.

Zhijian Qiao, Zehuan Yu, Huan Yin, Shaojie Shen

In this study, we introduce an online monocular lane mapping approach that solely relies on a single camera and odometry for generating spline-based maps. Our proposed technique models the lane association process as an assignment issue utilizing a bipartite graph, and assigns weights to the edges by incorporating Chamfer distance, pose uncertainty, and late

Tim Boers, Wyger Brink, Leonardo Bianchi, Paola Saccomandi

Background: Needle-based procedures such as fine needle aspiration (FNA) and thermal ablation, are often applied for thyroid nodule diagnosis and therapeutic purposes, respectively. With blood vessels and nerves nearby, these procedures can pose risks in damaging surrounding critical structures. Purpose: The development and validation of innovative strategie

Zhonglei Wang, Shu Yang, Jae Kwang Kim

Valid statistical inference is challenging when the sample is subject to unknown selection bias. Data integration can be used to correct for selection bias when we have a parallel probability sample from the same population with some common measurements. How to model and estimate the selection probability or the propensity score (PS) of a non-probability sam

Zhipeng Zhao, Kun Zhou, Xiaolei Wang, Wayne Xin Zhao

Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations. To develop an effective CRS, high-quality CRS datasets are very crucial. However, existing CRS datasets suffer from the long-tail issue, \ie a large proportion of items are rarely (or even never) mentioned in the conversations, which are cal

Stefano Carignano, Carlos Ramos Marimón, Luca Tagliacozzo

We study the computational complexity of simulating the time-dependent expectation value of a local operator in a one-dimensional quantum system by using temporal matrix product states. We argue that such cost is intimately related to that of encoding temporal transition matrices and their partial traces. In particular, we show that we can upper-bound the ra

Stephen Huan, Joseph Guinness, Matthias Katzfuss, Houman Owhadi

Dense kernel matrices resulting from pairwise evaluations of a kernel function arise naturally in machine learning and statistics. Previous work in constructing sparse approximate inverse Cholesky factors of such matrices by minimizing Kullback-Leibler divergence recovers the Vecchia approximation for Gaussian processes. These methods rely only on the geomet

Christoph Glasmacher, Michael Schuldes, Hendrik Weber, Nicolas Wagener

Scenario-based testing is becoming increasingly important in safety assurance for automated driving. However, comprehensive and sufficiently complete coverage of the scenario space requires significant effort and resources if using only real-world data. To address this issue, driving scenario generation methods are developed and used more frequently, but the

Virgil V. Baran, Emil J. P. Frost, Jens Paaske

A simple impurity solver is shown to capture the impurity-induced superconducting subgap states in quantitative agreement with the numerical renormalization group and quantum Monte-Carlo simulations. The solver is based on the exact diagonalization of a single-impurity Anderson model with discretized superconducting reservoirs including only a small number o

Pankaj Sharma, Narayan Mohanta

Topological superconductors harbor, at their boundaries and vortex cores, zero-energy Majorana bound states, which can be the building blocks in fault-tolerant topological quantum computing. Planar Josephson junctions host such topological superconducting phases, highly tunable by external magnetic field or phase difference between the superconducting leads.

Riddhiman Bhattacharya, Galin L. Jones

Convergence rate analyses of random walk Metropolis-Hastings Markov chains on general state spaces have largely focused on establishing sufficient conditions for geometric ergodicity or on analysis of mixing times. Geometric ergodicity is a key sufficient condition for the Markov chain Central Limit Theorem and allows rigorous approaches to assessing Monte C

Jiajun Zhang, Georgina Cosma, Sarah Bugby, Axel Finke

As the use of artificial intelligent (AI) models becomes more prevalent in industries such as engineering and manufacturing, it is essential that these models provide transparent reasoning behind their predictions. This paper proposes the AI-Reasoner, which extracts the morphological characteristics of defects (DefChars) from images and utilises decision tre