May 2023 arXiv papers — page 174

P. Drmota, D. P. Nadlinger, D. Main, B. C. Nichol

We report the first hybrid matter-photon implementation of verifiable blind quantum computing. We use a trapped-ion quantum server and a client-side photonic detection system networked via a fibre-optic quantum link. The availability of memory qubits and deterministic entangling gates enables interactive protocols without post-selection - key requirements fo

Leatile Marata, Onel Luis Alcaraz López, Andreas Hauptmann, Hamza Djelouat

Compressed sensing multi-user detection (CS-MUD) algorithms play a key role in optimizing grant-free (GF) non-orthogonal multiple access (NOMA) for massive machine-type communications (mMTC). However, current CS-MUD algorithms cannot be efficiently parallelized, leading to computationally expensive implementations of joint activity detection and channel esti

Davide Zorzenon, Jan Komenda, Jörg Raisch

P-time event graphs are discrete event systems suitable for modeling processes in which tasks must be executed in predefined time windows. Their dynamics can be represented by max-plus linear-dual inequalities (LDIs), i.e., systems of linear dynamical inequalities in the primal and dual operations of the max-plus algebra. We define a new class of models call

Hanbin Yang, Noah Rhodes, Haoxiang Yang, Line Roald

Natural wildfire becomes increasingly frequent as climate change evolves, posing a growing threat to power systems, while grid failures simultaneously fuel the most destructive wildfires. Preemptive de-energization of grid equipment is effective in mitigating grid-induced wildfires but may cause significant power outages during natural wildfires. This paper

Honori Udo, Takafumi Koshinaka

Image captioning, a.k.a. "image-to-text," which generates descriptive text from given images, has been rapidly developing throughout the era of deep learning. To what extent is the information in the original image preserved in the descriptive text generated by an image captioner? To answer that question, we have performed experiments involving the c

Harry Bevins, Will Handley, Thomas Gessey-Jones

Normalizing flows are an established approach for modelling complex probability densities through invertible transformations from a base distribution. However, the accuracy with which the target distribution can be captured by the normalizing flow is strongly influenced by the topology of the base distribution. A mismatch between the topology of the target a

William Huie, Lintao Li, Neville Chen, Xiye Hu

We demonstrate high fidelity repetitive projective measurements of nuclear spin qubits in an array of neutral ytterbium-171 ($^{171}$Yb) atoms. We show that the qubit state can be measured with a fidelity of 0.995(4) under a condition that leaves it in the state corresponding to the measurement outcome with a probability of 0.993(6) for a single tweezer and

Milan Bašić

A set of novel vertex-degree-based invariants was introduced by Gutman, denoted by \newline $SO_1, SO_2, \ldots,SO_6$. These invariants were constructed through geometric reasoning based on a new graph invariant framework. Motivated by proposed open problems in [Z. Tang, Q. Li, H. Deng, \textit{Trees with Extremal Values of the Sombor-Index-Like Graph Invari

Felix Klingelhoefer, Alantha Newman

A $k$-coloring of a tournament is a partition of its vertices into $k$ acyclic sets. Deciding if a tournament is 2-colorable is NP-hard. A natural problem, akin to that of coloring a 3-colorable graph with few colors, is to color a 2-colorable tournament with few colors. This problem does not seem to have been addressed before, although it is a special case

Sean Mandrick, Vincent Vatter

Lettericity measures the minimum size of an alphabet needed to represent a graph as a letter graph, where vertices are encoded by letters, and edges are determined by an underlying decoder. We prove that all graphs on~$n$ vertices have lettericity at most approximately $n - \tfrac{1}{2} \log_2 n$ and that almost all graphs on $n$ vertices have lettericity at

Gustav Zetterqvist, Fredrik Gustafsson, Gustaf Hendeby

Conventional direction of arrival (DOA) estimators are based on array processing using either time differences or beamforming. The proposed approach is based on the received power at each microphone, which enables simple hardware, low sampling frequency and small arrays. The problem is recast into a linear regression framework where the least squares method

Hui Hong, Huiyuan Wang, H. J. Mo, Ziwen Zhang

A stellar system is dynamically hot when its kinetic energy is dominated by random motion represented by the velocity dispersion $\sigma_{\rm hot} (M_*)$. We use MaNGA data to obtain inner and outer dispersion of a galaxy, $\sigma_{\rm in}$ and $\sigma_{\rm out}$, to characterize its dynamical status and study its connection with star formation quenching and

Carolin P. Bauer, Zofia A. Bejm, Michelle K. Bollier, Justinas Pupeikis

Coherent dual-comb spectroscopy (DCS) enables high-resolution measurements at high speeds without the trade-off between resolution and update rate inherent to mechanical delay scanning approaches. However, high system complexity and limited measurement sensitivity remain major challenges for DCS. Here, we address these challenges via a wavelength-tunable dua

Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee

Large Language Models (LLMs) have shown impressive performance as general purpose agents, but their abilities remain highly dependent on prompts which are hand written with onerous trial-and-error effort. We propose a simple and nonparametric solution to this problem, Automatic Prompt Optimization (APO), which is inspired by numerical gradient descent to aut

X. Y. Jin, K. Cicak, Z. Parrott, S. Kotler

Future quantum information processors require tunable coupling architectures that can produce high fidelity logical gates between two or more qubits. Parametric coupling is a powerful technique for generating tunable interactions between many qubits. Here, we present a highly flexible parametric coupling scheme with superconducting qubits that provides compl

James Hefford, Mario Román

We further the theory of optics or "circuits-with-holes" to encompass premonoidal categories: monoidal categories without the interchange law. Every premonoidal category gives rise to an effectful category (i.e. a generalised Freyd-category) given by the embedding of the monoidal subcategory of central morphisms. We introduce "pro-effectful" categories and s

Animesh Biswas, Trinh Huynh, Balaram Desai, Max Moss

We investigate the dynamics of a magnetoelastic robot with a dipolar magnetic head and a slender elastic body as it performs undulatory strokes and burrows through water-saturated granular beds. The robot is actuated by an oscillating magnetic field and moves forward when the stroke amplitude increases above a critical threshold. By visualizing the medium, w

Javier Aguilar, Jose J. Ramasco, Raúl Toral

Approximate numerical methods are one of the most used strategies to extract information from many-interacting-agents systems. In particular, numerical approximations are of extended use to deal with epidemic, ecological and biological models, since unbiased methods like the Gillespie algorithm can become unpractical due to high CPU time usage required. Howe

Andrii Kuibarov, Oleksandr Suvorov, Riccardo Vocaturo, Alexander Fedorov

An essential ingredient for the production of Majorana fermions that can be used for quantum computing is the presence of topological superconductivity. As bulk topological superconductors remain elusive, the most promising approaches exploit proximity-induced superconductivity making systems fragile and difficult to realize. Weyl semimetals due to their int

Etienne Batori, Alan Bregazzi, Ben Lewis, Paul Griffin

We present an additive-manufactured microwave cavity for a Ramsey-type, double resonance, compact cold-atom clock. Atoms can be laser cooled inside the cavity using a grating magneto-optic trap (GMOT) with the cavity providing an excellent TE011-like mode while maintaining sufficient optical access for atomic detection. The cavity features a low Q-factor of

Konstantin Hebenstreit, Robert Praas, Louis P Kiesewetter, Matthias Samwald

Emergent chain-of-thought (CoT) reasoning capabilities promise to improve performance and explainability of large language models (LLMs). However, uncertainties remain about how reasoning strategies formulated for previous model generations generalize to new model generations and different datasets. In this small-scale study, we compare different reasoning s

Susana Furtado, Charles Johnson

The Analytic Hierarchy Process (AHP) is a much discussed method in ranking business alternatives based on empirical and judgemental information. We focus here upon the key component of deducing efficient vectors for a reciprocal matrix of pair-wise comparisons. It is not yet known how to produce all efficient vectors. It has been shown that the entry-wise ge

Quan Liu, Yunsong Zhou, Hongzi Zhu, Shan Chang

For many driving safety applications, it is of great importance to accurately register LiDAR point clouds generated on distant moving vehicles. However, such point clouds have extremely different point density and sensor perspective on the same object, making registration on such point clouds very hard. In this paper, we propose a novel feature extraction fr

M. Ilyas, A. R. Athar, F. Khan, Asma Anfal

The present study provides an in-depth analysis of the anisotropic matter distribution and various physical aspects of compact stars in the context of a $f(R,G)$-gravity framework. In order to gain an exhaustive understanding of these aspects, our study focuses on three particular compact stars: VELA X-1 (CS1), SAXJ1808.4-3658 (CS2), and 4U1820-30 (CS3). We

O. Pezzi, P. Blasi

Galactic cosmic ray transport relies on the existence of turbulence on scales comparable with the gyration radius of the particles and with wavenumber vector oriented along the local magnetic field. In the standard picture, in which turbulence is injected at large scales and cascades down to smaller scales, it is all but guaranteed that the turbulent fluctua

Jianing Liu, Ruiwen Xie, Alex Aubert, Lukas Schäfer

The understanding of coercivity mechanism in high performance Nd-Fe-B permanent magnets relies on the analysis of the magnetic properties of all phases present in the magnets. By adding Cu in such compounds, a new Nd6Fe13Cu grain boundary phase is formed, however, the magnetic properties of this phase and its role in the magnetic decoupling of the matrix Nd2

Bogar Díaz, Diego González, Marcos J. Hernández, J. David Vergara

It has recently been proposed classical analogs of the purity, linear quantum entropy, and von Neumann entropy for classical integrable systems, when the corresponding quantum system is in a Gaussian state. We generalized these results by providing classical analogs of the generalized purities, Bastiaans-Tsallis entropies, R\'enyi entropies, and logarithmic

Juan Altmayer Pizzorno, Emery D Berger

Coverage analysis is widely used but can suffer from high overhead. This overhead is especially acute in the context of Python, which is already notoriously slow (a recent study observes a roughly 30x slowdown vs. native code). We find that the state-of-the-art coverage tool for Python, coverage$.$py, introduces a median overhead of 180% with the standard Py

Kevin Nguyen, Peter West

The null conformal boundary $\mathscr{I}$ of Minkowski spacetime $\mathbb{M}$ plays a special role in scattering theory, as it is the locus where massless particle states are most naturally defined. We construct quantum fields on $\mathscr{I}$ which create these massless states from the vacuum and transform covariantly under Poincar\'e symmetries. Since the

Serhii Kryhin, Leonid Levitov

Two-dimensional electron systems offer an appealing platform to explore long-lived excitations arising due to collinear carrier scattering enabled by phase-space constraints at the Fermi surface. Recently it was found that these effects can boost excitation lifetimes over the fundamental bound set by Landau's Fermi-liquid theory by a factor as large as $(T_F

Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss

Quantum generative models provide inherently efficient sampling strategies and thus show promise for achieving an advantage using quantum hardware. In this work, we investigate the barriers to the trainability of quantum generative models posed by barren plateaus and exponential loss concentration. We explore the interplay between explicit and implicit model

Ashish Kumar Meena

This work studies microlensing effects in strongly lensed gravitational wave (GW) signals corresponding to global minima images in galaxy-scale lenses. We find that stellar microlenses alone are unable to introduce noticeable wave effects in the global minima GW signals at strong lensing magnification $(\mu)<50$ with match value between unlensed and lensed G

Richard Aoun, Cagri Sert

In a previous article, given a finite-dimensional real vector space $V$ and a probability measure $μ$ on $\operatorname{PGL}(V)$ with finite first moment, we gave a description of all $μ$-stationary probability measures on the projective space $\operatorname{P}(V)$ in the non-critical (or Lyapunov dominated) case. In the current article, we complete the anal

Max Wakefield

The Tutte polynomial and Derksen's $\mathcal{G}$-invariant are the universal deletion-contraction and valuative matroid and polymatroid invariants, respectively. There are only a handful of well known invariants (like the matroid Kazhdan-Lusztig polynomials) between (in terms of fineness) the Tutte polynomial and Derksen's $\mathcal{G}$-invariant. The aim of

Amazigh Amrane, Hugo Bazille, Uli Fahrenberg, Krzysztof Ziemiański

We report some further developments regarding the language theory of higher-dimensional automata (HDAs). Regular languages of HDAs are sets of finite interval partially ordered multisets (pomsets) with interfaces. We show a pumping lemma which allows us to expose a class of non-regular languages. Concerning decision and closure properties, we show that inclu

Pêdra D. S. Andrade, Ederson Moreira dos Santos, Makson S. Santos, Hugo Tavares

In this paper, we discuss a class of spectral partition problems with a measure constraint, for partitions of a given bounded connected open set. We establish the existence of an optimal open partition, showing that the corresponding eigenfunctions are locally Lipschitz continuous, and obtain some qualitative properties for the partition. The proof uses an e

Yiqun Yao, Zheng Zhang, Jing Li, Yequan Wang

Accelerating large language model pre-training is a critical issue in present research. In this paper, we focus on speeding up pre-training by progressively growing from a small Transformer structure to a large one. There are two main research problems associated with progressive growth: determining the optimal growth schedule, and designing efficient growth

Kilian Schäfer, Rafael Gitti Tortoretto Fim, Fernando Maccari, Tobias Braun

Nd-Fe-B bonded magnets are an important class of permanent magnets, employed in many technological sectors. The Additive Manufacturing (AM) processes enables the fabrication of net-shape bonded magnets with complex geometries, allowing to tailor their magnetic stray field specifically for a given application. A crucial challenge to be addressed concerning AM

Wenhao Zhu, Tianyu Wen, Guojie Song, Xiaojun Ma

Graph Transformer is gaining increasing attention in the field of machine learning and has demonstrated state-of-the-art performance on benchmarks for graph representation learning. However, as current implementations of Graph Transformer primarily focus on learning representations of small-scale graphs, the quadratic complexity of the global self-attention

Thomas van der Jagt, Geurt Jongbloed, Martina Vittorietti

In various stereological problems an $n$-dimensional convex body is intersected with an $(n-1)$-dimensional Isotropic Uniformly Random (IUR) hyperplane. In this paper the cumulative distribution function associated with the $(n-1)$-dimensional volume of such a random section is studied. This distribution is also known as chord length distribution and cross s

Ziad Sakr

The matter fluctuation parameter $\sigma_8$ is, by model construction, degenerate with the growth index $\gamma$. Here, we study the effect on the cosmological parameter constraints by treating each independently from one another, considering $\sigma_8$ as a free and non-derived parameter along with a free $\gamma$. We then try to constrain all parameters us

Jun-Ling Chen, Wei-Xi Li, Chao-Jiang Xu

For the Maxwellian molecules or hard potentials case, we verify the smoothing effect for the spatially inhomogeneous Boltzmann equation without angular cutoff. Given initial data with low regularity, we prove its solutions at any positive time are analytic for strong angular singularity, and in Gevrey class with optimal index for mild angular singularity. To

Atreya Acharyya, Colin Adams, Avery Archer, Priyadarshini Bangale

We report the detection of very high energy gamma-ray emission from the blazar S3 1227+25 (VER J1230+253) with the Very Energetic Radiation Imaging Telescope Array System (VERITAS). VERITAS observations of the source were triggered by the detection of a hard-spectrum GeV flare on May 15, 2015 with the Fermi-Large Area Telescope (LAT). A combined five-hour VE

Timur Akhtyamov, Aleksandr Kashirin, Aleksey Postnikov, Gonzalo Ferrer

This work is dedicated to the study of how uncertainty estimation of the human motion prediction can be embedded into constrained optimization techniques, such as Model Predictive Control (MPC) for the social robot navigation. We propose several cost objectives and constraint functions obtained from the uncertainty of predicting pedestrian positions and rela

Thomas van der Jagt, Geurt Jongbloed, Martina Vittorietti

Consider an opaque medium which contains 3D particles. All particles are convex bodies of the same shape, but they vary in size. The particles are randomly positioned and oriented within the medium and cannot be observed directly. Taking a planar section of the medium we obtain a sample of observed 2D section profile areas of the intersected particles. In th

Vincent Giraud, Guillaume Bouffard

Private and public actors increasingly encounter use cases where they need to implement sensitive operations on mass-market peripherals for which they have little or no control. They are sometimes inclined to attempt this without using hardware-assisted equipment, such as secure elements. In this case, the white-box attack model is particularly relevant and

Jinfeng Dou, Thorsten Götte, Henning Hillebrandt, Christian Scheideler

We consider the problem of computing compact routing tables for a (weighted) planar graph $G:= (V, E,w)$ in the PRAM, CONGEST, and the novel HYBRID communication model. We present algorithms with polylogarithmic work and communication that are almost optimal in all relevant parameters, i.e., computation time, table sizes, and stretch. All algorithms are heav

Francesco Costa

The document discusses a proposed extension to the Standard Model that aims to explain the presence of neutrino masses and the existence of dark matter. The model includes two potential candidates for dark matter, a vector WIMP and a fermion FIMP, and their combined presence accounts for the total amount of observed dark matter. This study examines the vario

Chengyuan Deng, Surya Teja Gavva, Karthik C. S., Parth Patel

Over the last few years Explainable Clustering has gathered a lot of attention. Dasgupta et al. [ICML'20] initiated the study of explainable $k$-means and $k$-median clustering problems where the explanation is captured by a threshold decision tree which partitions the space at each node using axis parallel hyperplanes. Recently, Laber et al. [Pattern Recogn

Luciano M. Abreu, Natsumi Ikeno, Eulogio Oset

In this work we study the role of the $f_0(980)$ and $a_0(980)$ resonances in the low $ K ^{+} K^{-} $ and $K^0 \bar K^0 $ invariant-mass region of the $B^- \to \pi ^- K^+ K^- $ and $B^- \to \pi ^- K^0 \bar K^0 $ reactions. The amplitudes are calculated by using the chiral unitary $\rm SU(3)$ formalism, in which these two resonances are dynamically generated

Ziad Sakr

We investigate whether the two cosmological discrepancies on the Hubble constant ($H_0$) and the matter fluctuation parameter ($\sigma_8$) are suggesting and compatible with the existence of an additional one on the matter density. Knowing that the latter effects on observables is degenerate with those coming from $H_0$ and $\sigma_8$, we combined different

Carlo Maccaferri, Alberto Ruffino, Jakub Vošmera

We use the new nilpotent formulation of open-closed string field theory to explore the limit where the number $N$ of identical D-branes of the starting background is large. By reformulating the theory in terms of the 't Hooft coupling $\lambda=\kappa N$, where $\kappa$ is the string coupling constant, we explicitly see that at large $N$ only genus zero verti

Carlo Maccaferri, Alberto Ruffino, Jakub Vošmera

In this note we revisit the homotopy-algebraic structure of oriented bosonic open-closed string field theory and we give a new compact formulation in terms of a single cyclic open-closed coderivation which defines a single nilpotent structure describing the consistency of generic open-closed color-ordered off-shell amplitudes with arbitrary number of boundar

Alaa Akkoush, Yair Litman, Mariana Rossi

Defects can strongly influence the electronic, optical and mechanical properties of 2D materials, making defect stability under different thermodynamic conditions crucial for material-property engineering. In this paper, we present an account of the structural and electronic characteristics of point defects in monolayer transition metal dichalcogenides $MX_2

Ezio Bartocci, Thomas A. Henzinger, Dejan Nickovic, Ana Oliveira da Costa

We introduce hypernode automata as a new specification formalism for hyperproperties of concurrent systems. They are finite automata with nodes labeled with hypernode logic formulas and transitions labeled with actions. A hypernode logic formula specifies relations between sequences of variable values in different system executions. Unlike HyperLTL, hypernod

Francisco Borges, Sung-Sik Lee

We show that anisotropic quantum corrections can dynamically give rise to curved momentum-spacetimes for quasiparticles in metals. In the (2+1)-dimensional antiferromagnetic quantum critical metal, a curved momentum-spacetime arises as the critical spin fluctuations generate red shift that dilates frequency of electron unevenly on the Fermi surface. As the d

Danilo A. Jesus, Eric F. Thee, Tim Doekemeijer, Daniel Luttikhuizen

To study whether it is possible to differentiate intermediate age-related macular degeneration (AMD) from healthy controls using partial optical coherence tomography (OCT) data, that is, restricting the input B-scans to certain pre-defined regions of interest (ROIs). A total of 15744 B-scans from 269 intermediate AMD patients and 115 normal subjects were use

Jitendra Dhakar, Ram Prakash Bharti

The electroviscous effects in the pressure-driven flow of electrolyte liquid through an asymmetrically charged contraction-expansion (4:1:4) slit microfluidic device have been investigated numerically. The mathematical model (i.e., Poisson's, Navier-Stokes, and Nernst-Planck equations) is solved using the finite element method to obtain the electrical potent

Ása Skúladóttir, Irene Vanni, Stefania Salvadori, Romain Lucchesi

The Sculptor dwarf spheroidal galaxy is old and metal-poor, making it ideal to study the earliest chemical enrichment in the Local Group. We followed up the most metal-poor star known in this (or any external) galaxy, AS0039, with high-resolution ESO VLT/UVES spectra. Our new analysis confirmed its low metallicity, [Fe/H]=-3.90, and that it is extremely C-po

Simon Blouin, Antoine Bédard, Pier-Emmanuel Tremblay

The Gaia colour--magnitude diagram reveals a striking separation between hydrogen-atmosphere white dwarfs and their helium-atmosphere counterparts throughout a significant portion of the white dwarf cooling track. However, pure-helium atmospheres have Gaia magnitudes that are too close to the pure-hydrogen case to explain this bifurcation. To reproduce the o

Nathaniel Virgo

We elucidate the mathematical structure of Bayesian filtering, and Bayesian inference more broadly, by applying recent work on category theoretical probability, specifically the concept of a strongly representable Markov category. We show that filtering, along with related concepts such as conjugate priors, arise from an adjunction: the process of taking a h

Gregory Moille, Jordan Stone, Michal Chojnacky, Rahul Shrestha

The phase-coherent frequency division of a stabilized optical reference laser to the microwave domain is made possible by optical frequency combs (OFCs). Fundamentally, OFC-based clockworks rely on the ability to lock one comb tooth to this reference laser, which probes a stable atomic transition. The active feedback process associated with locking the comb

Leland Bybee

I introduce a survey of economic expectations formed by querying a large language model (LLM)&#39;s expectations of various financial and macroeconomic variables based on a sample of news articles from the Wall Street Journal between 1984 and 2021. I find the resulting expectations closely match existing surveys including the Survey of Professional Forecaste

Zhiling Zhang, Mengyue Wu, Kenny Q. Zhu

Controlling chatbot utterance generation with multiple attributes such as personalities, emotions and dialogue acts is a practically useful but under-studied problem. We propose a novel framework called DASC that possesses strong controllability with a weighted decoding paradigm, while improving generation quality with the grounding in an attribute semantics

Holger Boche, Andrea Grigorescu, Rafael F. Schaefer, H. Vincent Poor

Designing capacity-achieving coding schemes for the band-limited additive colored Gaussian noise (ACGN) channel has been and is still a challenge. In this paper, the capacity of the band-limited ACGN channel is studied from a fundamental algorithmic point of view by addressing the question of whether or not the capacity can be algorithmically computed. To th

Sharon-Lise Normand, Katya Zelevinsky, Marcela Horvitz-Lennon

Healthcare quality metrics refer to a variety of measures used to characterize what should have been done or not done for a patient or the health consequences of what was or was not done. When estimating healthcare quality, many metrics are measured and combined to provide an overall estimate either at the patient level or at higher levels, such as the provi

Ziad Sakr

We performed a Bayesian study on three beyond LCDM phenomenological triggering parameters, the growth index $\gamma$, the dark energy equation of state parameter $w$ and the lensing deviation from the GR prediction parameter $\Sigma$, using the latest cosmological geometric, growth and lensing probes, all in a consistent implementation within the modified gr

David Rasmussen Lolck, Rasmus Pagh

Integer data is typically made differentially private by adding noise from a Discrete Laplace (or Discrete Gaussian) distribution. We study the setting where differential privacy of a counting query is achieved using bit-wise randomized response, i.e., independent, random bit flips on the encoding of the query answer. Binary error-correcting codes transmitte

Tasneem Watad, Netanel H. Lindner

We introduce a variational hybrid classical-quantum algorithm to simulate the Lindblad master equation and its adjoint for time-evolving Markovian open quantum systems and quantum observables. Our method is based on a direct representation of density matrices and quantum observables as quantum superstates. We design and optimize low-depth variational quantum

Si-Hong Zhou, Xin-Xia Hai, Run-Hui Li, Cai-Dian Lu

We analyze quasi-two-body charmless $B$ decays $B_{(s)} \to P_1 V \to P_1 P_2 P_3$ with $V$ representing a vector resonant, and $P_{1,2,3}$ as a light pseudo-scalar meson, pion, kaon or $\eta^{(\prime)}$. The intermediate processes $B_{(s)} \to P_1 V $ are calculated in the factorization-assisted topological-amplitude approach and the vector resonant effects

Chenzhan Shang, Yupeng Hou, Wayne Xin Zhao, Yaliang Li

Conversational recommender system (CRS) interacts with users through multi-turn dialogues in natural language, which aims to provide high-quality recommendations for user's instant information need. Although great efforts have been made to develop effective CRS, most of them still focus on the contextual information from the current dialogue, usually sufferi

Darian Onchis, Gilbert-Rainer Gillich, Eduard Hogea, Cristian Tufisi

In the last decade, damage detection approaches swiftly changed from advanced signal processing methods to machine learning and especially deep learning models, to accurately and non-intrusively estimate the state of the beam structures. But as the deep learning models reached their peak performances, also their limitations in applicability and vulnerabiliti

Kiran Kumar A. S, Shambhu Nath Maurya, Koushik Saha

This article focuses on the fluctuations of linear eigenvalue statistics of $T_{n\times p}T'_{n\times p}$, where $T_{n\times p}$ is an $n\times p$ Toeplitz matrix with real, complex or time-dependent entries. We show that as $n \rightarrow \infty$ and $p/n \rightarrow \lambda \in (0, \infty)$, the linear eigenvalue statistics of these matrices for polynomial

Minwoo Lee, Kyu Tae Kim, Jongho Park

Self-sustained oscillations are ubiquitous in nature and engineering. In this paper, we propose a novel output-only system-identification framework for identifying the system parameters of a self-sustained oscillator affected by Gaussian white noise. A Langevin model that characterizes the self-sustained oscillator is postulated, and the corresponding Fokker

Jorke M. de Vlas

This paper categorizes the parameterized complexity of the algorithmic problems Perfect Phylogeny and Triangulating Colored Graphs when parameterized by the number of genes and colors, respectively. We show that they are complete for the parameterized complexity class XALP using a reduction from Tree-chained Multicolor Independent Set and a proof of membersh

H. D. Etea, K. N. Nigussa

Studies of the structural, electronic, and optical characteristics of the interfaces between graphene and ZnO polar surfaces is carried out using first-principles simulations. At the interface, a strong van der Waals force is present, and because of the different work functions of graphene and ZnO, charge transfer takes place. Graphene&#39;s superior conduct

Mohamed Abdalla, Jan Philip Wahle, Terry Ruas, Aurélie Névéol

Recent advances in deep learning methods for natural language processing (NLP) have created new business opportunities and made NLP research critical for industry development. As one of the big players in the field of NLP, together with governments and universities, it is important to track the influence of industry on research. In this study, we seek to qua

Ming-Kun Xie, Jia-Hao Xiao, Hao-Zhe Liu, Gang Niu

Pseudo-labeling has emerged as a popular and effective approach for utilizing unlabeled data. However, in the context of semi-supervised multi-label learning (SSMLL), conventional pseudo-labeling methods encounter difficulties when dealing with instances associated with multiple labels and an unknown label count. These limitations often result in the introdu

Daniel Hausmann, Mathieu Lehaut, Nir Pitermann

Emerson-Lei conditions have recently attracted attention due to their succinctness and compositionality properties. In the current work, we show how infinite-duration games with Emerson-Lei objectives can be analyzed in two different ways. First, we show that the Zielonka tree of the Emerson-Lei condition gives rise naturally to a new reduction to parity gam

Pavel Krupskii, Bouchra R Nasri, Bruno N Remillard

In this article, a copula-based method for mixed regression models is proposed, where the conditional distribution of the response variable, given covariates, is modelled by a parametric family of continuous or discrete distributions, and the effect of a common latent variable pertaining to a cluster is modelled with a factor copula. We show how to estimate

Stefano Galanda, Albert Much, Rainer Verch

The relative entropy of certain states on the algebra of canonical anticommutation relations (CAR) is studied in the present work. The CAR algebra is used to describe fermionic degrees of freedom in quantum mechanics and quantum field theory. The states for which the relative entropy is investigated are multi-excitation states (similar to multi-particle stat

Matthias Rempel, Tanayveer Bhatia, Luis Bellot Rubio, Maarit J. Korpi-Lagg

In this article we review small-scale dynamo processes that are responsible for magnetic field generation on scales comparable to and smaller than the energy carrying scales of turbulence. We provide a review of critical observation of quiet Sun magnetism, which have provided strong support for the operation of a small-scale dynamo in the solar photosphere a

Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann

This work introduces interpretable regional descriptors, or IRDs, for local, model-agnostic interpretations. IRDs are hyperboxes that describe how an observation's feature values can be changed without affecting its prediction. They justify a prediction by providing a set of "even if" arguments (semi-factual explanations), and they indicate which features af

Yunlong Liang, Fandong Meng, Jinan Xu, Jiaan Wang

Existing neural machine translation (NMT) studies mainly focus on developing dataset-specific models based on data from different tasks (e.g., document translation and chat translation). Although the dataset-specific models have achieved impressive performance, it is cumbersome as each dataset demands a model to be designed, trained, and stored. In this work

Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding

Federated Learning (FL) aims to train machine learning models for multiple clients without sharing their own private data. Due to the heterogeneity of clients' local data distribution, recent studies explore the personalized FL that learns and deploys distinct local models with the help of auxiliary global models. However, the clients can be heterogeneous in

Qi Wang, Zhijie Wen, Jun Shi, Qian Wang

Multi-modal magnetic resonance imaging (MRI) plays a crucial role in comprehensive disease diagnosis in clinical medicine. However, acquiring certain modalities, such as T2-weighted images (T2WIs), is time-consuming and prone to be with motion artifacts. It negatively impacts subsequent multi-modal image analysis. To address this issue, we propose an end-to-

Jürgen Fuchs, Christoph Schweigert, Simon Wood, Yang Yang

This is an invited contribution to the 2nd edition of the Encyclopedia of Mathematical Physics. We review the following algebraic structures which appear in two-dimensional conformal field theory (CFT): The symmetries of two-dimensional conformal field theories (CFTs) can be formalised as chiral algebras, vertex operator algebras or nets of observable algebr

Daniel Racek, Brittany I. Davidson, Paul W. Thurner, Xiao Xiang Zhu

The use of language is innately political and often a vehicle of cultural identity as well as the basis for nation building. Here, we examine language choice and tweeting activity of Ukrainian citizens based on more than 4 million geo-tagged tweets from over 62,000 users before and during the Russian-Ukrainian War, from January 2020 to October 2022. Using st

Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki

Table detection is the task of classifying and localizing table objects within document images. With the recent development in deep learning methods, we observe remarkable success in table detection. However, a significant amount of labeled data is required to train these models effectively. Many semi-supervised approaches are introduced to mitigate the need

Christian Pedersen, Timur Aslyamov, Mathijs Janssen

Batteries, supercapacitors, and several other electrochemical devices charge by accumulating ions in the pores of electrolyte-immersed porous electrodes. The charging of such devices has long been interpreted using equivalent circuits and the partial differential equations these give rise to. Here, we discuss the validity of the transmission line (TL) circui

Dongchao Yang, Songxiang Liu, Rongjie Huang, Jinchuan Tian

Audio codec models are widely used in audio communication as a crucial technique for compressing audio into discrete representations. Nowadays, audio codec models are increasingly utilized in generation fields as intermediate representations. For instance, AudioLM is an audio generation model that uses the discrete representation of SoundStream as a training

Vageesh Saxena, Nils Rethmeier, Gijs Van Dijck, Gerasimos Spanakis

The anonymity on the Darknet allows vendors to stay undetected by using multiple vendor aliases or frequently migrating between markets. Consequently, illegal markets and their connections are challenging to uncover on the Darknet. To identify relationships between illegal markets and their vendors, we propose VendorLink, an NLP-based approach that examines

Xiaoli Yuan, Yuejian Peng

Erd\H{o}s and Simonovits asked the following question: For an integer $r\geq 2$ and a family of non-bipartite graphs $\mathcal{H}$, determine the infimum of $\alpha$ such that any $\mathcal{H}$-free $n$-vertex graph with minimum degree at least $\alpha n$ has chromatic number at most $r$. We answer this question for $r=2$ and any family consisting of odd cyc

Souradeep Bhattacharya, Magda Arnaboldi, Ortwin Gerhard, Nelson Caldwell

The Andromeda galaxy (M 31) has experienced a tumultuous merger history as evidenced by the many substructures present in its inner halo. We use planetary nebulae (PNe) as chemodynamic tracers to shed light on the recent merger history of M 31. We identify the older dynamically hotter thicker disc in M 31 and a distinct younger dynamically colder thin disc.

Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin

Recent studies show that graph neural networks (GNNs) are prevalent to model high-order relationships for collaborative filtering (CF). Towards this research line, graph contrastive learning (GCL) has exhibited powerful performance in addressing the supervision label shortage issue by learning augmented user and item representations. While many of them show

Gabor Facsko, Gergely Koban, Nikolett Biro, Munkhjargal Lkhagvadorj

Gas pipelines, transmission lines, overhead wires, transformers, GNSS navigation, and telecommunication systems are part of critical infrastructure. Industry, transportation, service operations, farming, and everyday life highly depend on this infrastructure. However, these systems are very sensitive to solar activity. Therefore, all activities above are vul

Rui He, Shengcai Liu, Jiahao Wu, Shan He

Multi-domain learning (MDL) refers to simultaneously constructing a model or a set of models on datasets collected from different domains. Conventional approaches emphasize domain-shared information extraction and domain-private information preservation, following the shared-private framework (SP models), which offers significant advantages over single-domai

Julien Philip, Valentin Deschaintre

NeRF acquisition typically requires careful choice of near planes for the different cameras or suffers from background collapse, creating floating artifacts on the edges of the captured scene. The key insight of this work is that background collapse is caused by a higher density of samples in regions near cameras. As a result of this sampling imbalance, near

Sung-Soo Byun, Leslie Molag, Nick Simm

We study real eigenvalues of $N\times N$ real elliptic Ginibre matrices indexed by a non-Hermiticity parameter $0\leq \tau<1$, in both the strong and weak non-Hermiticity regime. Here $N$ is assumed to be an even number. In both regimes, we prove a central limit theorem for the number of real eigenvalues. We also find the asymptotic behaviour of the probabil

Maxim Wenzel, Alexander A. Tsirlin, Francesco Capitani, Yuk T. Chan

The coexistence of the charge-density wave (CDW) and superconducting phases and their tunability under external pressure remains one of the key points in understanding the electronic structure of $A$V$_3$Sb$_5$ ($A$ = K, Rb, Cs) kagome metals. Here, we employ synchrotron-based infrared spectroscopy assisted by density-functional calculations to study the pre