December 2023 arXiv papers — page 46

Adám Margócsy, Edit Mátyus

This work is a collection of initial calculations and formal considerations within the Salpeter-Sucher exact equal-time relativistic quantum electrodynamics framework. The calculations are carried out as preparation for the computation of pair, retardation, and radiative corrections to the relativistic energy of correlated two-spin-1/2-fermion systems. In th

Nima Khosravi

The cosmological constant term can be seen as a constant potential for a (scalar) field. In this viewpoint, at late times, the field is stopped rolling and behaves as a cosmological constant ($w=-1$). While at the early universe, its kinetic term can be dominant and behaves as a stiff fluid ($w=+1$). This new phase lowers the cosmological sound horizon by in

G. Buchalla, F. König, Ch. Müller-Salditt, F. Pandler

We use functional methods to match the Two-Higgs Doublet Model with heavy scalars in the nondecoupling regime to the appropriate nonlinear effective field theory, which takes the form of an electroweak chiral Lagrangian (HEFT). The effective Lagrangian is derived to leading order in the chiral counting. This includes the loop induced $h\to\gamma\gamma$ and $

L. Verra, C. Amoedo, N. Torrado, A. Clairembaud

We show in experiments that a long, underdense, relativistic proton bunch propagating in plasma undergoes the oblique instability, that we observe as filamentation. We determine a threshold value for the ratio between the bunch transverse size and plasma skin depth for the instability to occur. At the threshold, the outcome of the experiment alternates betwe

R. M. Aguirre

The properties of the neutral pion in quark matter under the influence of an external magnetic field are studied. The effects of the anomalous magnetic moments (AMM) of the quarks at finite density is considered. The inclusion of the AMM into the NJL model gives rise to additional magnetic effects. In particular the Dirac sea produce new divergences in the v

Juraj Vladika, Alexander Fichtl, Florian Matthes

Recent advances in natural language processing (NLP) owe their success to pre-training language models on large amounts of unstructured data. Still, there is an increasing effort to combine the unstructured nature of LMs with structured knowledge and reasoning. Particularly in the rapidly evolving field of biomedical NLP, knowledge-enhanced language models (

Yanliang Guo, Sudipta Dhar, Ang Yang, Zekai Chen

The quantum kicked rotor is a paradigmatic model system in quantum physics. As a driven quantum system, it is used to study the transition from the classical to the quantum world and to elucidate the emergence of chaos and diffusion. In contrast to its classical counterpart, it features dynamical localization, specifically Anderson localization in momentum s

Amal Alphonse, Michael Hintermüller, Carlos N. Rautenberg, Gerd Wachsmuth

Quasi-variational inequalities (QVIs) of obstacle type in many cases have multiple solutions that can be ordered. We study a multitude of properties of the operator mapping the source term to the minimal or maximal solution of such QVIs. We prove that the solution maps are locally Lipschitz continuous and directionally differentiable and show existence of op

Werner Bauer, Paul Bergold, François Gay-Balmaz, Cesare Tronci

In order to alleviate the computational costs of fully quantum nonadiabatic dynamics, we present a mixed quantum-classical (MQC) particle method based on the theory of Koopman wavefunctions. Although conventional MQC models often suffer from consistency issues such as the violation of Heisenberg's principle, we overcame these difficulties by blending Koopman

Peilin Du, Jing Zhang, Tiancai Zhang, Rongguo Yang

Continuous-variable measurement-based quantum computation, which requires deterministically generated large-scale cluster state, is a promising candidate for practical, scalable, universal, and fault-tolerant quantum computation. In this work, based on our compact and scalable scheme of generating a two-dimensional spatiotemporal cluster state, a complete ar

Issam Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi

The extraction of a small number of relevant insights from vast amounts of data is a crucial component of data-driven decision-making. However, accomplishing this task requires considerable technical skills, domain expertise, and human labor. This study explores the potential of using Large Language Models (LLMs) to automate the discovery of insights in data

Shengyu Cao, Simai He, Ruoqing Jiang, Jin Xu

Recently multi-armed bandit problem arises in many real-life scenarios where arms must be sampled in batches, due to limited time the agent can wait for the feedback. Such applications include biological experimentation and online marketing. The problem is further complicated when the number of arms is large and the number of batches is small. We consider pu

Megha Gopalakrishna, Yaroslav Pavlyukh, Claudio Verdozzi

Due to their conceptual appeal and computational convenience, two-level systems (TLS) and their generalisations are often used to investigate nonlinear behavior in quantum optics, and to assess the applicability of theoretical methods. Here the focus is on second harmonic generation (SHG) and, as system of interest, on the Dicke model, which consists of seve

Christopher Simic, Tobias Bocklet

Automatic speech recognition (ASR) has reached a level of accuracy in recent years, that even outperforms humans in transcribing speech to text. Nevertheless, all current ASR approaches show a certain weakness against ambient noise. To reduce this weakness, audio-visual speech recognition (AVSR) approaches additionally consider visual information from lip mo

Chunyan Li, Yaroslav V. Kartashov

We show that slow time-periodic variation of the external magnetic field applied to polariton topological insulator based on honeycomb array of microcavity pillars with pronounced TE-TM splitting results in oscillations of the edge states along the boundary of the insulator that are accompanied by slow transverse drift of the center of mass of the edge state

Anouck Braggaar, Christine Liebrecht, Emiel van Miltenburg, Emiel Krahmer

This review gives an extensive overview of evaluation methods for task-oriented dialogue systems, paying special attention to practical applications of dialogue systems, for example for customer service. The review (1) provides an overview of the used constructs and metrics in previous work, (2) discusses challenges in the context of dialogue system evaluati

O. Torbaniuk, M. Paolillo, R. D'Abrusco, C. Vignali

We present an improved study of the relation between supermassive black hole growth and their host galaxy properties in the local Universe (z < 0.33). To this end, we build an extensive sample combining spectroscopic measurements of star-formation rate (SFR) and stellar mass from Sloan Digital Sky Survey, with specific Black Hole accretion rate (sBHAR, $\lam

Arthur France-Lanord, Hadrien Vroylandt, Mathieu Salanne, Benjamin Rotenberg

Identifying optimal collective variables to model transformations, using atomic-scale simulations, is a long-standing challenge. We propose a new method for the generation, optimization, and comparison of collective variables, which can be thought of as a data-driven generalization of the path collective variable concept. It consists in a kernel ridge regres

Jiangmeng Li, Yifan Jin, Hang Gao, Wenwen Qiang

Graph contrastive learning (GCL) aims to align the positive features while differentiating the negative features in the latent space by minimizing a pair-wise contrastive loss. As the embodiment of an outstanding discriminative unsupervised graph representation learning approach, GCL achieves impressive successes in various graph benchmarks. However, such an

Alessio Corti, Helge Ruddat

We introduce the concept of a viable generically Gorenstein toroidal crossing (ggtc) space $Y$. This generalizes the concept of Gorenstein toroidal crossing scheme, which in turn generalizes that of a simple normal crossing scheme. On such a space $Y$, we define a sheaf $\mathcal{LS}_Y$, intrinsic to $Y$, by means of an explicit construction. Our main theore

Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin

Understanding user intentions is essential for improving product recommendations, navigation suggestions, and query reformulations. However, user intentions can be intricate, involving multiple sessions and attribute requirements connected by logical operators such as And, Or, and Not. For instance, a user may search for Nike or Adidas running shoes across v

Michal K. Grzeszczyk, Tadeusz Satlawa, Angela Lungu, Andrew Swift

Pulmonary Hypertension (PH) is a severe disease characterized by an elevated pulmonary artery pressure. The gold standard for PH diagnosis is measurement of mean Pulmonary Artery Pressure (mPAP) during an invasive Right Heart Catheterization. In this paper, we investigate noninvasive approach to PH detection utilizing Magnetic Resonance Imaging, Computer Mod

Saikat Panja, Prachi Saini, Anupam Singh

Let $K$ be an algebraically closed field and $\mathrm{M}(2,K)$ be the $2\times 2$ matrix algebra over $K$ and $\mathrm{GL}(2,K)$ be the invertible elements in $\mathrm{M}(2,K)$. We explore the image of polynomials with constants, namely from the free algebra $\mathrm{M}(2,K)\langle x, y\rangle$. In this article, we compute the images of the polynomial maps g

Valery Gritsenko, Haowu Wang

Jacobi theta functions with rational characteristics can be viewed as vector-valued Jacobi forms. Theta relations usually correspond to different constructions of certain Jacobi forms. From this observation, we extract a new approach, which is called orbits of Jacobi forms, to produce identities on Jacobi theta functions. Our approach not only provides simpl

Kaouther Messaoud, Kathrin Grosse, Mickael Chen, Matthieu Cord

Autonomous vehicles ought to predict the surrounding agents' trajectories to allow safe maneuvers in uncertain and complex traffic situations. As companies increasingly apply trajectory prediction in the real world, security becomes a relevant concern. In this paper, we focus on backdoors - a security threat acknowledged in other fields but so far overlooked

B. Szafran, M. Zegrodnik. M. P. Nowak, R. Citro, P. Wójcik

We investigate the energy spectrum of a single and two electron quantum dot (QD) embedded in two dimensional electron gas at the interface between SrTiO$_3$ and LaAlO$_3$, in the presence of the external magnetic field. For this purpose the three band model of $3d$-electrons defined on the square lattice of Ti ions was utilized. We demonstrate that, for the

Oleg Kruglov, Anna Mastikhina, Oleg Senkevich, Dmitry Sirotkin

We present a novel graph partition algorithm with a theoretical bound for the replication factor of \sqrt(n), which improves known constrained approaches (grid: 2* \sqrt(n)-1, torus: 1.5*\sqrt(n)+1) and provides better performance

Michal K. Grzeszczyk, Anna Lisowska, Arkadiusz Sitek, Aneta Lisowska

Automatic detection and tracking of emotional states has the potential for helping individuals with various mental health conditions. While previous studies have captured physiological signals using wearable devices in laboratory settings, providing valuable insights into the relationship between physiological responses and mental states, the transfer of the

L. M. Railing, M. S. Le, C. M. Lazzarini, H. M. Milchberg

We demonstrate loss-free generation of 3 mJ, 1 kHz, few-cycle (5 fs at 750 nm central wavelength) double pulses with separation from 10 fs to 100 fs, using a helium filled hollow core fiber (HCF) and chirped mirror compressor. Crucial to our scheme are simulation-based modifications to the spectral phase and amplitude of the oscillator seed pulse to eliminat

Simon Muntwiler, Johannes Köhler, Melanie N. Zeilinger

We consider the design of functional estimators, i.e., approaches to compute an estimate of a nonlinear function of the state of a general nonlinear dynamical system subject to process noise based on noisy output measurements. To this end, we introduce a novel functional detectability notion in the form of incremental input/output-to-output stability ($\delt

Alexey Golovnev

I give a brief introduction to and explain the geometry of teleparallel models of modified gravity. In particular I explain why, in my opinion, the covariantised approaches are not needed and the Weitzenb\"ock connection is the most natural representation of the parallel transport structure. An interesting point is that it also applies to the symmetric telep

Mercè Roig, Panagiotis Kotetes, Brian M. Andersen

The superconducting diode effect may exist in bulk systems as well as in junctions when time-reversal and inversion symmetries are simultaneously broken. Magnetization gradients and textures satisfy both requirements and therefore also allow for superconducting diodes. We concretely demonstrate such possibilities in two-dimensional superconductors. We first

Guoliang Yu, Shengxian Li, Anlian Pan, Mingxing Chen

The bistability of charge polarization in ferroelectric materials has long been the basis of ferroelectric devices. However, the ferroelectricity tends to be vanishing as the thickness of materials is reduced to a few nanometers or thinner due to the depolarization field. Instead, they show a paraelectric or an antiferroelectric ordering in the ultra-thin li

Marco Drewes, Yannis Georis, Juraj Klaric, Philipp Klose

Hot viscous plasmas unavoidably emit a gravitational wave background, similar to electromagnetic black body radiation. We study the contribution from hidden particles to the diffuse background emitted by the primordial plasma in the early universe. While this contribution can easily dominate over that from Standard Model particles, we find that both are capp

Da Xu, Qiyuan Wang, Xiaoning Xu

Let L be a finite dimensional simple Lie superalgebra over an algebraically closed field of characteristic different from 2. In this paper, we prove that each skew-supersymmtric super-biderivation of L is inner. Furthermore, we prove that each linear super-commuting map on L is a scalar multiplication map.

Raoul Heese

Quantum computers exhibit an inherent randomness, so it seems natural to consider them for procedural content generation. In this work, a quantum version of the famous (classical) wave function collapse algorithm is proposed. This quantum wave function collapse algorithm is based on the idea that a quantum circuit can be prepared in such a way that it acts a

Hannes Meinlschmidt

In this paper we are concerned with $L^p$-maximal parabolic regularity for abstract nonautonomous parabolic systems and their quasilinear counterpart in negative Sobolev spaces incorporating mixed boundary conditions. Our results are derived in the setting of nonsmooth domains with mixed boundary conditions by an extrapolation technique which also yields uni

Andrew McClung, Mahsa Torfeh, Vincent J. Einck, James J. Watkins

Metasurfaces enable precise control over the properties of light and hold promise for commercial applications. However, fabricating visible metasurfaces suitable for high-volume production is challenging and requires scalable processes. Nanoimprint lithography is a cost-effective and high-throughput technique that can meet this scalability requirement. This

Torben Skrzypek, Arkady A. Tseytlin

We consider type IIB string theory on an $AdS_5 \times S^5/\mathbb{Z}_2$ orbifold background, which should be dual to 4d $\mathcal{N}=2$ superconformal $SU(N)\times SU(N)$ gauge theory with two bi-fundamental hypermultiplets. The correlator of two chiral BPS operators from the twisted sector of this quiver CFT exhibits non-trivial dependence on the 't Hooft

Sylvain Lacroix

These lecture notes present an introduction to classical Affine Gaudin models, which provide a general framework for the systematic construction and study of a large class of integrable two-dimensional field theories. A key role is played by Kac-Moody currents, which are fields satisfying a particular Poisson bracket. After reviewing this notion, we discuss

Yimin Sun, Chao Wang, Yan Peng

The zero-shot performance of visual question answering (VQA) models relies heavily on prompts. For example, a zero-shot VQA for disaster scenarios could leverage well-designed Chain of Thought (CoT) prompts to stimulate the model's potential. However, using CoT prompts has some problems, such as causing an incorrect answer in the end due to the hallucination

Riccardo Borsato

These are pedagogical lecture notes discussing current-current deformations of 2-dimensional field theories. The deformations that are considered here are generated infinitesimally by bilinears of Noether currents corresponding to internal global symmetries of the "seed" theory. When the seed theory is conformal, these deformations are marginal and are often

Emily G. Meekel, Phillippa Partridge, Robert A. I. Paraoan, Joshua J. B. Levinsky

By virtue of their open network structures and low densities, metal--organic frameworks (MOFs) are soft materials that exhibit elastic instabilities at low applied stresses. The conventional strategy for improving elastic stability is to increase the connectivity of the underlying MOF network, which necessarily increases material density and reduces porosity

Abraham Woubie, Enoch Solomon, Eyael Solomon Emiru

In various verification systems, Restricted Boltzmann Machines (RBMs) have demonstrated their efficacy in both front-end and back-end processes. In this work, we propose the use of RBMs to the image clustering tasks. RBMs are trained to convert images into image embeddings. We employ the conventional bottom-up Agglomerative Hierarchical Clustering (AHC) tech

Giulio Foggi Rota, Alessandro Monti, Stefano Olivieri, Marco Edoardo Rosti

Flexible canopy flows are often encountered in natural scenarios, e.g., when crops sway in the wind or when submerged kelp forests are agitated by marine currents. Here, we provide a detailed characterisation of the turbulent flow developed above and between the flexible filaments of a fully submerged dense canopy and we describe their dynamical response to

Melina Sampayo Puelles, Miguel Hoyuelos

Much effort has been put into developing theories for dense fluids, as a result of these efforts many theories work for a certain type of particle or in a certain concentration regime. Rosenfeld proposed a dependence of the self-diffusion coefficient on the excess entropy. Our proposal is similar to Rosenfeld's in that it also attempts to describe diffusion

Tom F. Sterkenburg

Statistical learning theory is often associated with the principle of Occam's razor, which recommends a simplicity preference in inductive inference. This paper distills the core argument for simplicity obtainable from statistical learning theory, built on the theory's central learning guarantee for the method of empirical risk minimization. This core "means

Alexander Köhler, Michael Breuß

The computation of correspondences between shapes is a principal task in shape analysis. To this end, methods based on partial differential equations (PDEs) have been established, encompassing e.g. the classic heat kernel signature as well as numerical solution schemes for geometric PDEs. In this work we focus on the latter approach. We consider here several

Eran Igra

The R\"ossler system is one of the best known chaotic dynamical systems, generating a chaotic attractor which, by the numerical evidence, arises by a period-doubling route to chaos. In this paper we state and prove a topological criterion for the existence of an attractor for the R\"ossler system - and then analyze the dynamics of the non-wandering set by re

Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn

Explanations in Computer Vision are often desired, but most Deep Neural Networks can only provide saliency maps with questionable faithfulness. Self-Explaining Neural Networks (SENN) extract interpretable concepts with fidelity, diversity, and grounding to combine them linearly for decision-making. While they can explain what was recognized, initial realizat

David Gunn, Georgios Styliaris, Tristan Kraft, Barbara Kraus

Two matrix product states (MPS) are in the same phase in the presence of symmetries if they can be transformed into one another via symmetric short-depth circuits. We consider how symmetry-preserving measurements with feedforward alter the phase classification of MPS in the presence of global on-site symmetries. We demonstrate that, for all finite abelian sy

Cosmin Ilie, Katherine Freese, Andreea Petric, Jillian Paulin

The James Webb Space Telescope (JWST) has recently uncovered a new record-breaking quasar, UHZ1, at a redshift of $z\sim10$. This discovery continues JWST's trend of confronting the expectations from the standard $\Lambda$CDM model of cosmology with challenges. Namely, too many very massive galaxies and quasars have been observed at very high redshifts, when

Sunny Kumar Gupta, Michael Urban

The composition of the inner crust of neutron stars is usually studied using phenomenological interactions such as Skyrme energy-density functionals. But most of these functionals do not agree well with ab-initio calculations of very dilute neutron matter. In this work, we study the inner crust of neutron stars in the model of phase coexistence of dense neut

Kadir Gümüş, João dos Reis Frazão, Vincent van Vliet, Sjoerd van der Heide

We experimentally demonstrate adaptive reconciliation for continuous-variable quantum key distribution over a turbulent free-space optical channel. Additionally, we propose a method for optimising the reconciliation efficiency, increasing secret key rates by up to 8.1%.

Jonas Lidal, Jeroen Danon

We use a single-channel scattering formalism to derive general expressions for the Andreev bound-state energies and resulting current--phase relationship in a one-dimensional semiconductor-based SNS-junction, including arbitrarily oriented effective spin--orbit and Zeeman fields and taking into account disorder in the junction in by including a single scatte

Ahmet Haydar Ornek, Deniz Sen, Esmanur Civil

The main aim of this study is to demonstrate how innovative view synthesis and 3D reconstruction techniques can be used to create models of endangered species using monocular RGB images. To achieve this, we employed SyncDreamer to produce unique perspectives and NeuS and NeRF to reconstruct 3D representations. We chose four different animals, including the o

Taiki Takatsu

In this paper, we apply the Bestvina-Mess type formula for relatively hyperbolic groups, which is established by Tomohiro Fukaya, to automorphism groups of K3 surfaces, and we show that the virtual cohomological dimension of automorphism groups of K3 surfaces determined by the covering dimension of the blown-up boundaries associated with their ample cones.

Raul González-Díaz, Lluís Galbany, Tuomas Kangas, Rubén García-Benito

We study the local environmental properties of 418 supernovae (SNe) of all types using data from the Javalambre Photometric Local Universe Survey (J-PLUS), which includes 5 broad- and 7 narrow-band imaging filters, using two independent analyses: 1) the Normalized Cumulative Rank (NCR) method, utilizing all 12 single bands along with five continuum-subtracte

Benjamin Roussel, Pablo Burset, Christian Flindt

Recent experiments have shown that the edge states of a quantum Hall sample can be coupled to a superconductor, so that incoming electrons in the edge states can be Andreev converted by the superconductor as coherent superpositions of an electron and a hole. In parallel, single-electron emitters that operate in the gigahertz regime have been realized on quan

Xiuyuan Hu, Guoqing Liu, Yang Zhao, Hao Zhang

De novo drug design is a pivotal issue in pharmacology and a new area of focus in AI for science research. A central challenge in this field is to generate molecules with specific properties while also producing a wide range of diverse candidates. Although advanced technologies such as transformer models and reinforcement learning have been applied in drug d

Azalea Raad, Ori Lahav, John Wickerson, Piotr Balcer

Software Transactional Memory (STM) is an extensively studied paradigm that provides an easy-to-use mechanism for thread safety and concurrency control. With the recent advent of byte-addressable persistent memory, a natural question to ask is whether STM systems can be adapted to support failure atomicity. In this article, we answer this question by showing

Marzieh Baradaran, Pavel Exner

We analyze the spectrum of a periodic quantum graph of the Cairo lattice form. The used vertex coupling violates the time reversal invariance and its high-energy behavior depends on the vertex degree parity; in the considered example both odd and even parities are involved. The presence of the former implies that the spectrum is dominated by gaps. In additio

Matthew Kwan, Lisa Sauermann

Consider a quadratic polynomial $Q(\xi_{1},\dots,\xi_{n})$ of independent Rademacher random variables $\xi_{1},\dots,\xi_{n}$. To what extent can $Q(\xi_{1},\dots,\xi_{n})$ concentrate on a single value? This quadratic version of the classical Littlewood--Offord problem was popularised by Costello, Tao and Vu in their study of symmetric random matrices. In t

Ann-Kathrin Elm, Hendrik Heine

One perspective on tree decompositions is that they display (low-order) separations of the underlying graph or matroid. The separations displayed by a tree decomposition are necessarily nested. In 2013, Clark and Whittle proved the existence of tree decompositions with flowers added in which, up to a natural equivalence, all low-order separations are display

Wojciech Florkowski, Radoslaw Ryblewski, Piotr Salabura, Nikodem Witkowski

A recently formulated thermal model for hadron production in heavy-ion collisions in the few-GeV energy regime is combined with the idea that some part of protons and neutrons present in the original thermal system forms deuterons via the coalescence mechanism. Using realistic parametrizations of the freeze-out conditions, which reproduce well the spectra of

Svante Janson

Uncover the vertices of a given graph, deterministic or random, in random order; we consider both a discrete-time and a continuous-time version. We study the evolution of the number of visible edges, and show convergence after normalization to a Gaussian process. This problem was studied by Hackl, Panholzer, and Wagner for the case when the graph is a random

Yixuan Wang, Shuangyin Li, Shimin DI, Lei Chen

The single-cell RNA sequencing (scRNA-seq) technology enables researchers to study complex biological systems and diseases with high resolution. The central challenge is synthesizing enough scRNA-seq samples; insufficient samples can impede downstream analysis and reproducibility. While various methods have been attempted in past research, the resulting scRN

Kwangrok Ryoo, Yeonsik Jo, Seungjun Lee, Mira Kim

For object detection task with noisy labels, it is important to consider not only categorization noise, as in image classification, but also localization noise, missing annotations, and bogus bounding boxes. However, previous studies have only addressed certain types of noise (e.g., localization or categorization). In this paper, we propose Universal-Noise A

Basabendu Barman, Arghyajit Datta

Assuming axions are potential dark matter (DM) candidate that make up all of the DM abundance, we discuss production of axions via (i) standard misalignment mechanism during the period of reheating and (ii) graviton-mediated 2-to-2 scattering of the inflaton and bath particles, where the inflaton $\phi$ oscillates in a monomial potential $V(\phi)\propto\phi^

Marina Ljubenovic, Alessia Artesani, Stefano Bonetti, Arianna Traviglia

Terahertz time-domain spectroscopy (THz-TDS) employs sub-picosecond pulses to probe dielectric properties of materials giving as a result a 3-dimensional hyperspectral data cube. The spatial resolution of THz images is primarily limited by two sources: a non-zero THz beam waist and the acquisition step size. Acquisition with a small step size allows for the

Inmaculada Baldomá, Mar Giralt, Marcel Guardia

The description of unstable motions in the Restricted Planar Circular 3-Body Problem, modeling the dynamics of a Sun-Planet-Asteriod system, is one of the fundamental problems in Celestial Mechanics. The goal of this paper is to analyze homoclinic and instability phenomena at coorbital motions, that is when the negligible mass Asteroid is at 1:1 mean motion

Zheng Zhu, Bernard Hallet, András A. Sipos, Gábor Domokos

On Mars, fields of sand dunes contrast with the general cratered, rocky terrain commonly seen from orbit. Near the equator, in Gale Crater, images from the rover, Curiosity, also reveal order on smaller scales: ripples on dunes, and ground patterns in scattered sites. The patterns include relatively inconspicuous forms: evenly spaced pebble-size rocks (terme

Benoît Corsini

This article studies the limit of binary search trees drawn from Mallows permutations under various topologies. The main result, pertaining to the standard local topology for graphs, requires the introduction of a generalization of binary search trees to two-sided infinite sequences, referred to as \textit{redwood trees}. We then show that the almost-sure lo

Ryu Hirai, Shinya Iizuka, Haruhisa Iseno, Ao Guo

At the Dialogue Robot Competition 2023 (DRC2023), which was held to improve the capability of dialogue robots, our team developed a system that could build common ground and take more natural turns based on user utterance texts. Our system generated queries for sightseeing spot searches using the common ground and engaged in dialogue while waiting for user c

Naihuan Jing, Ming Liu, Alexander Molev

We consider the quantum Gelfand invariants which first appeared in a landmark paper by Reshetikhin, Takhtadzhyan and Faddeev (1989). We calculate the eigenvalues of the invariants acting in irreducible highest weight representations of the quantized enveloping algebra for ${\mathfrak {gl}}_n$. The calculation is based on Liouville-type formulas relating two

Pauli Jokinen, Sophie Egelhaaf, Juha-Pekka Pellonpää, Roope Uola

We generalize the notion of joint measurability to continuous variable systems by extending a recently introduced compression algorithm of quantum measurements to this realm. The extension results in a property that asks for the minimal dimensional quantum system required for representing a given set of quantum measurements. To illustrate the concept, we sho

Florian M. Farke, David G. Balash, Maximilian Golla, Adam J. Aviv

Data dashboards are designed to help users manage data collected about them. However, prior work showed that exposure to some dashboards, notably Google's My Activity dashboard, results in significant decreases in perceived concern and increases in perceived benefit from data collection, contrary to expectations. We theorize that this result is due to the fa

Ashod Aradian, Andres Cathey, Karen Caicedo, Milena Mora

We study theoretically the emission and lasing properties of a single nanoshell spaser nanoparticle, or plasmonic nanolaser, made of an active core (gain material) and a plasmonic metal shell. Based on an analytical framework coupling together time-dependent equations for the gain and the metal, we calculate the lasing threshold with the help of an instabili

Shaohan Sha, YaFeng Sun

Federated learning is a decentralized learning paradigm wherein a central server trains a global model iteratively by utilizing clients who possess a certain amount of private datasets. The challenge lies in the fact that the client side private data may not be identically and independently distributed, significantly impacting the accuracy of the global mode

Benjamin Bonnefont, Vincent Vargas

We obtain in this work a sharp estimate on the left tail of the distribution of the so-called derivative martingale in the $L^4$ phase, answering a conjecture by H. Lacoin, R. Rhodes & V. Vargas in the framework of the Gaussian branching random walk.

Lara Löhken, Michael Stiglmayr

The cable-trench problem is defined as a linear combination of the shortest path and the minimum spanning tree problem. In particular, the goal is to find a spanning tree that simultaneously minimizes its total length and the total path length from a pre-defined root to all other vertices. Both, the minimum spanning tree and the shortest path problem are kno

Tobias Jawecki, Pranav Singh

Rational best approximations (in a Chebyshev sense) to real functions are characterized by an equioscillating approximation error. Similar results do not hold true for rational best approximations to complex functions in general. In the present work, we consider unitary rational approximations to the exponential function on the imaginary axis, which map the

Carolina Medina, Santino Ramirez, Jorge L. Ramirez-Alfonsin, Gelasio Salazar

An arrangement of pseudocircles $\mathcal{A}$ is a collection of Jordan curves in the plane that pairwise intersect (transversally) at exactly two points. How many non-equivalent links have $\mathcal{A}$ as their shadow? Motivated by this question, we study the number of non-equivalent positive oriented links that have an arrangement of pseudocircles as thei

Antonio Álvarez-López, Rafael Orive-Illera, Enrique Zuazua

We address binary classification using neural ordinary differential equations from the perspective of simultaneous control of $N$ data points. We consider a single-neuron architecture with parameters fixed as piecewise constant functions of time. In this setting, the model complexity can be quantified by the number of control switches. Previous work has show

Petr Beneš, Filip Blaschke

We discuss a class of effective extensions of the $SU(2)$ Georgi-Glashow model and discuss its Bogomol'nyi-Prasad-Sommerfield (BPS) limit. We identify a specific subclass of these models that admit analytical solutions of the monopole type. We present some concrete examples and find that the resulting monopoles tend to have their energy concentrated not in t

Dongdong Hu, Linglong Yuan, Minzhi Zhao

The ratio of Laplace transforms of powers of a function arises in the context of auction theory. The question whether a function is uniquely identified by this ratio has been answered affirmatively, if the function is non-negative, non-decreasing and right analytic.This paper extends the result to a larger class of functions without monotonicity.A conjecture

Matei Hanu, Simon Weissmann

The ensemble Kalman inversion (EKI), a recently introduced optimisation method for solving inverse problems, is widely employed for the efficient and derivative-free estimation of unknown parameters. Specifically in cases involving ill-posed inverse problems and high-dimensional parameter spaces, the scheme has shown promising success. However, in its genera

Chandramouli Chowdhury, Arthur Lipstein, Jiajie Mei, Ivo Sachs

We investigate cosmological correlators for conformally coupled $\phi^4$ theory in four-dimensional de Sitter space. These \textit{in-in} correlators differ from scattering amplitudes for massless particles in flat space due to the spacelike structure of future infinity in de Sitter. They also require a regularization which preserves de Sitter-invariance, wh

Haobo Lu, Xin Liu, Kun He

Deep Neural Networks (DNNs) are widely acknowledged to be susceptible to adversarial examples, wherein imperceptible perturbations are added to clean examples through diverse input transformation attacks. However, these methods originally designed for non-targeted attacks exhibit low success rates in targeted attacks. Recent targeted adversarial attacks main

Jun Zhang, Yiping Xie, Li Ling, John Folkesson

Side-scan sonar (SSS) is a lightweight acoustic sensor that is commonly deployed on autonomous underwater vehicles (AUVs) to provide high-resolution seafloor images. However, leveraging side-scan images for simultaneous localization and mapping (SLAM) presents a notable challenge, primarily due to the difficulty of establishing sufficient amount of accurate

Ya-Wen Pan, Ming-Zhu Liu, Jun-Xu Lu, Li-Sheng Geng

Assuming that $D_{s0}^{*}(2317)$ is a $DK$ molecular state with a binding energy of 45 MeV, we investigate the existence of four-hadron molecules, $DDKK$ and $D\Bar{D}K\Bar{K}$, with the Gaussian expansion method. Their binding energies are $138\sim155$ MeV and $123\sim163$ MeV below the mass thresholds of $DDKK$ and $D\Bar{D}K\Bar{K}$. The $D\Bar{D}K\Bar{K}

Peter Kern, Leonard Pleschberger

We explicitly calculate the Hausdorff dimension of the graph and range of an isotropic stable L\'{e}vy process $X$ plus deterministic drift function $f$. For that purpose we use a restricted version of the genuine Hausdorff dimension which is called the parabolic Hausdorff dimension. It turns out that covers by parabolic cylinders are optimal for treating se

Jun Kong, Kaiyuan Shi, Xingbang Dong, Xiao Dong

The Gr\"uneisen parameter ({\gamma}) is crucial for determining many thermal properties, including the anharmonic effect, thermostatistics, and equation of state (EOS) of materials. However, the isentropic adiabatic compression conditions required to measure the Gr\"uneisen parameter under high pressure are difficult to achieve. Thus, direct experimental Gr\

Georg Kruse, Theodora-Augustina Dragan, Robert Wille, Jeanette Miriam Lorenz

Quantum Reinforcement Learning (QRL) emerged as a branch of reinforcement learning (RL) that uses quantum submodules in the architecture of the algorithm. One branch of QRL focuses on the replacement of neural networks (NN) by variational quantum circuits (VQC) as function approximators. Initial works have shown promising results on classical environments wi

Kaiyue Hou, Shuowen Zhang

In this paper, we study a secure integrated sensing and communication (ISAC) system where one multi-antenna base station (BS) simultaneously communicates with one single-antenna user and senses the location parameter of a target which serves as a potential eavesdropper via its reflected echo signals. In particular, we consider a challenging scenario where th

Samuel Hannah, Ana Ros Camacho, with an appendix with Devi Young

In this article we study the possible Morita equivalence classes of algebras in three families of fusion categories (pointed, near-group and $A \left( 1,l \right)_{\frac{1}{2}}$) by studying the Non-negative Integer Matrix representations (NIM-reps) of their underlying fusion ring, and compare these results with existing classification results of algebra obj

Ran Greidi, Kobi Cohen

Federated Learning (FL) has attracted much interest due to the significant advantages it brings to training deep neural network (DNN) models. However, since communications and computation resources are limited, training DNN models in FL systems face challenges such as elevated computational and communication costs in complex tasks. Sparse training schemes ga

Ertugrul Basar

Instead of treating the noise as a detrimental effect, can we use it as an information carrier? In this letter, we provide the conceptual and mathematical foundations of wireless communication utilizing noise and random signals in general. Mainly, the concept of noise modulation (NoiseMod) is introduced to cover information transmission by both thermal noise

TP John, M Mowbray, A Alalwyat, M Vousvoukis

Identification and parameterisation of constitutive models can be a challenging task in rheology. We investigate the use of Random Forest (RF) regression to estimate viscoelastic constitutive model parameters using Large Amplitude Oscillatory Shear (LAOS) data. Specifically, we deploy the RF to predict constitutive model parameters using the spectra of Cheby

Marvin Kahra, Michael Breuß, Andreas Kleefeld, Martin Welk

Mathematical morphology is a part of image processing that has proven to be fruitful for numerous applications. Two main operations in mathematical morphology are dilation and erosion. These are based on the construction of a supremum or infimum with respect to an order over the tonal range in a certain section of the image. The tonal ordering can easily be