May 2023 arXiv papers — page 135

Nicholas W. Landry, Ilya Amburg, Mirah Shi, Sinan G. Aksoy

Many complex systems often contain interactions between more than two nodes, known as higher-order interactions, which can change the structure of these systems in significant ways. Researchers often assume that all interactions paint a consistent picture of a higher-order dataset's structure. In contrast, the connection patterns of individuals or entities i

Daniel Friedrich, Jin Qin, Benedikt Schurr, Tommaso Tufarelli

Room-temperature strong coupling of a single quantum emitter and a single resonant plasmonic mode is a key resource for quantum information processing and quantum sensing at ambient conditions. To beat dephasing, ultrafast energy transfer is achieved by coupling single emitters to a plasmonic nanoresonator with an extremely small mode volume and optimal spec

Felisia Angela Chiarello, Simone Göttlich, Thomas Schilliger, Andrea Tosin

We present a formal kinetic derivation of a second order macroscopic traffic model from a stochastic particle model. The macroscopic model is given by a system of hyperbolic partial differential equations (PDEs) with a discontinuous flux function, in which the traffic density and the headway are the averaged quantities. A numerical study illustrates the perf

Zhen Ye, Wei Xue, Xu Tan, Jie Chen

Denoising diffusion probabilistic models (DDPMs) have shown promising performance for speech synthesis. However, a large number of iterative steps are required to achieve high sample quality, which restricts the inference speed. Maintaining sample quality while increasing sampling speed has become a challenging task. In this paper, we propose a "Co"nsistency

Sajid Ali, Dibyendu Bala, Olaf Kaczmarek, Hai-Tao Shu

This paper discusses the charmonium and bottomonium correlators in the pseudoscalar channel and the corresponding spectral reconstruction on the lattice. The absence of a transport peak in the pseudoscalar channel spectral function allows for an easier study of the in-medium modification of bound states. However, extracting spectral information from Euclidea

Andrea Lacava, Matteo Bordin, Michele Polese, Rajarajan Sivaraj

O-RAN is radically shifting how cellular networks are designed, deployed and optimized through network programmability, disaggregation, and virtualization. Specifically, RAN Intelligent Controllers (RICs) can orchestrate and optimize the Radio Access Network (RAN) operations, allowing fine-grained control over the network. RICs provide new approaches and sol

Andrew A. Voitiv, Mark T. Lusk, Mark E. Siemens

We present and implement a method for the experimental measurement of geometric phase of non-geodesic (small) circles on any SU(2) parameter space. This phase is measured by subtracting the dynamic phase contribution from the total phase accumulated. Our design does not require theoretical anticipation of this dynamic phase value and the methods are generall

Alexander Berglund

The purpose of this note is to give a concise account of some fundamental properties of the exponential group and the Maurer-Cartan space associated to a complete dg Lie algebra. In particular, we give a direct elementary proof that the Maurer-Cartan space is a delooping of the exponential group. This leads to a short proof that the Maurer-Cartan space funct

André Beauducel, Norbert Hilger, Anneke Weide

The relevance of determinacy coefficients as indicators for the validity of factor score predictors has regularly been emphasized. Previous simulation studies revealed biased determinacy coefficients for factor score predictors based on categorical variables. Therefore, and because there are different possibilities to compute determinacy coefficients, the pr

Meet Udeshi, Prashanth Krishnamurthy, Hammond Pearce, Ramesh Karri

Cybersecurity attacks on embedded devices for industrial control systems and cyber-physical systems may cause catastrophic physical damage as well as economic loss. This could be achieved by infecting device binaries with malware that modifies the physical characteristics of the system operation. Mitigating such attacks benefits from reverse engineering tool

Marcell Szakály, Sebastian Köhler, Martin Strohmeier, Ivan Martinovic

Many modern devices, including critical infrastructures, depend on the reliable operation of electrical power conversion systems. The small size and versatility of switched-mode power converters has resulted in their widespread adoption. Whereas transformer-based systems passively convert voltage, switched-mode converters feature an actively regulated feedba

Huzaifa Mustafa Unjhawala, Ruochun Zhang, Wei Hu, Jinlong Wu

In robotics, simulation has the potential to reduce design time and costs, and lead to a more robust engineered solution and a safer development process. However, the use of simulators is predicated on the availability of good models. This contribution is concerned with improving the quality of these models via calibration, which is cast herein in a Bayesian

Feng Ji, Xingchao Jian, Wee Peng Tay, Maosheng Yang

Topological signal processing (TSP) over simplicial complexes typically assumes observations associated with the simplicial complexes are real scalars. In this paper, we develop TSP theories for the case where observations belong to general abelian groups, including function spaces that are commonly used to represent time-varying signals. Our approach genera

Yujie Zeng, Yiming Huang, Xiao-Long Ren, Linyuan Lü

Empirical networks possess considerable heterogeneity of node connections, resulting in a small portion of nodes playing crucial roles in network structure and function. Yet, how to characterize nodes' influence and identify vital nodes is by far still unclear in the study of networks with higher-order interactions. In this paper, we introduce a multi-order

Odunayo Ogundepo, Tajuddeen R. Gwadabe, Clara E. Rivera, Jonathan H. Clark

African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems -- those that retrieve answer content from other languages while serving people in their native language -- offer a means of f

Victor S. L'vov, Anna Pomyalov, Dmytro A. Bozhko, Burkard Hillebrands

Nonlinear interactions are crucial in science and engineering. Here, we investigate wave interactions in a highly nonlinear magnetic system driven by parametric pumping leading to Bose--Einstein condensation of spin-wave quanta -- magnons. Using Brillouin light scattering spectroscopy in yttrium-iron garnet films, we found and identified a set of nonlinear p

K. Abdukayumov, M. Mičica, F. Ibrahim, C. Vergnaud

Terahertz (THz) Spintronic emitters based on ferromagnetic/metal junctions have become an important technology for the THz range, offering powerful and ultra-large spectral bandwidths. These developments have driven recent investigations of two-dimensional (2D) materials for new THz spintronic concepts. 2D materials, such as transition metal dichalcogenides

Dominik Janzing, Philipp M. Faller, Leena Chennuru Vankadara

If $X,Y,Z$ denote sets of random variables, two different data sources may contain samples from $P_{X,Y}$ and $P_{Y,Z}$, respectively. We argue that causal discovery can help inferring properties of the `unobserved joint distributions' $P_{X,Y,Z}$ or $P_{X,Z}$. The properties may be conditional independences (as in `integrative causal inference') or also qua

Alena Erchenko, Thibault Lefeuvre

Let $\Sigma$ be a smooth compact connected oriented surface with boundary. A metric on $\Sigma$ is said to be of Anosov type if it has strictly convex boundary, no conjugate points, and a hyperbolic trapped set. We prove that two metrics of Anosov type with the same marked boundary distance are isometric (via a boundary-preserving isometry isotopic to the id

Hadiseh Mahmoudi

This paper describes our system on SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). This work aims to design an automatic system for detecting and classifying sexist content in online spaces. We propose a set of transformer-based pre-trained models with task-adaptive pretraining and ensemble learning. The main contributions of our system

Ivan Baburin, Jonas Ballani, John W. Peterson, David Knezevic

In this paper we examine the use of low-rank approximations for the handling of radiation boundary conditions in a transient heat equation given a cavity radiation setting. The finite element discretization that arises from cavity radiation is well known to be dense, which poses difficulties for efficiency and scalability of solvers. Here we consider a speci

Renyu Wang, Hsiang-Ku Lin, Leonid P. Pryadko

We discuss quantum two-block codes, a large class of CSS codes constructed from two commuting square matrices.Interesting families of such codes are generalized-bicycle (GB) codes and two-block group-algebra (2BGA) codes, where a cyclic group is replaced with an arbitrary finite group, generally non-abelian. We present code construction and give several expr

Saiyad Ashanujjaman, Siddharth P. Maharathy

Despite a great deal of effort in searching for the triplet-like Higgses in the type-II seesaw model, evidence for their production is yet to be found at the LHC. As such, one might be in the balance regarding this model's relevance at the electroweak scale. In this work, we peruse a scenario, akin to compressed mass spectra in Supersymmetry, which might hav

Lorenzo Lucchini, Ollin Langle-Chimal, Lorenzo Candeago, Lucio Melito

Mobile phone data have played a key role in quantifying human mobility during the COVID-19 pandemic. Existing studies on mobility patterns have primarily focused on regional aggregates in high-income countries, obfuscating the accentuated impact of the pandemic on the most vulnerable populations. Leveraging geolocation data from mobile-phone users and popula

Ismaila Salihou Adamou, Elsa Dupraz, Tad Matsumoto

This paper investigates Distributed Hypothesis testing (DHT), in which a source $\mathbf{X}$ is encoded given that side information $\mathbf{Y}$ is available at the decoder only. Based on the received coded data, the receiver aims to decide on the two hypotheses $H_0$ or $H_1$ related to the joint distribution of $\mathbf{X}$ and $\mathbf{Y}$. While most exi

Yivan Zhang, Masashi Sugiyama

Disentangling the factors of variation in data is a fundamental concept in machine learning and has been studied in various ways by different researchers, leading to a multitude of definitions. Despite the numerous empirical studies, more theoretical research is needed to fully understand the defining properties of disentanglement and how different definitio

Maria Hellgren, Lucas Baguet

We investigate the adiabatic approximation to the exact-exchange kernel for calculating correlation energies within the adiabatic-connection fluctuation-dissipation framework of time-dependent density functional theory. A numerical study is performed on a set of systems having bonds of different character (H$_2$ and N$_2$ molecules, H-chain, H$_2$-dimer, sol

Anwesha Maharana, Camilla Scolini, Brigitte Schmieder, Stefaan Poedts

Solar coronal mass ejections (CMEs) can catch up and interact with preceding CMEs and solar wind structures to undergo rotation and deflection during their propagation. We aim to show how interactions undergone by a CME in the corona and heliosphere can play a significant role in altering its geoeffectiveness predicted at the time of its eruption. We conside

Liyao Hao, Wenyi Tian

In this paper, we propose and analyze a second-order time-stepping numerical scheme for the inhomogeneous backward fractional Feynman-Kac equation with nonsmooth initial data. The complex parameters and time-space coupled Riemann-Liouville fractional substantial integral and derivative in the equation bring challenges on numerical analysis and computations.

Yinfei Li, Sanjib Ghosh, Jiangwei Shang, Qihua Xiong

Estimating properties of a quantum state is an indispensable task in various applications of quantum information processing. To predict properties in the post-processing stage, it is inherent to first perceive the quantum state with a measurement protocol and store the information acquired. In this work, we propose a general framework for constructing classi

Manpreet Kaur, Marc Walker, Steven Hindmarsh, Charlotte Bolt

Efficient artificial photosynthesis systems are currently realized as catalyst- and surfacefunctionalized photovoltaic tandem- and triple-junction devices, enabling photoelectrochemical (PEC) water oxidation while simultaneously recycling CO2 and generating hydrogen as a solar fuel for storable renewable energy. Although PEC systems also bear advantages for

Marc Hoffmann, Yating Liu

We prove optimal convergence results of a stochastic particle method for computing the classical solution of a multivariate McKean-Vlasov equation, when the measure variable is in the drift, following the classical approach of [BT97, AKH02]. Our method builds upon adaptive nonparametric results in statistics that enable us to obtain a data-driven selection o

I. Ceresa-Dussel, J. Fernández Bonder, A. Silva

In this work we study a priori bounds for weak solution to elliptic problems with nonstandard growth that involves the so-called $g-$Laplace operator. The $g-$Laplacian is a generalization of the $p-$Laplace operator that takes into account different behaviors than pure powers. The method to obtain this a priori estimates is the so called ``blow-up'' argumen

A. Hahlin, O. Kochukhov, A. D. Rains, A. Lavail

We aim to characterise the small-scale magnetic fields for a sample of 16 Sun-like stars and investigate the capabilities of the newly upgraded near-infrared (NIR) instrument CRIRES$^+$ at the VLT in the context of small-scale magnetic field studies. Our targets also had their magnetic fields studied in the optical, which allows us to compare magnetic field

Yacine Barhoumi-Andréani, Marius Butzek, Peter Eichelsbacher

We introduce a new general concept of surrogate random variable, the ``surrogate by exchangeability'' that allows to study the class of random variables that can be decomposed by means of an independent randomisation. As an example, we treat the case of the Curie-Weiss model using the explicit construction of its De Finetti measure of exchangeability. Writin

Roman Kozlov

Mean field games equations are examined for conservation laws. The system of mean field games equations consists of two partial differential equations: the Hamilton-Jacobi-Bellman equation for the value function and the forward Kolmogorov equation for the probability density. For separable Hamiltonians, this system has a variational structure, i.e., the equa

Henrik Garde, Michael Vogelius

We derive exact reconstruction methods for cracks consisting of unions of Lipschitz hypersurfaces in the context of Calder\'on's inverse conductivity problem. Our first method obtains upper bounds for the unknown cracks, bounds that can be shrunk to obtain the exact crack locations upon verifying certain operator inequalities for differences of the local Neu

Kyungmin Jung, Thomas Hitchcox, James Richard Forbes

Many problems in robotics, such as estimating the state from noisy sensor data or aligning two point clouds, can be posed and solved as least-squares problems. Unfortunately, vanilla nonminimal solvers for least-squares problems are notoriously sensitive to outliers. As such, various robust loss functions have been proposed to reduce the sensitivity to outli

Yuriy Pischalnikov, Crispin Contreras-Martinez

Modern particle accelerators and high-energy physics experiments that deployed up to several hundred of accelerating superconducting RF cavities require accurate frequency control. This is achieved by using cavity tuners typically actuated with the piezoelectric ceramic actuators. Piezoelectric ceramic actuators have become "standard" components of the SRF c

Warren Cattani

We construct a minimal Lefschetz decomposition of the bounded derived category of the odd isotropic Grassmannian $\mathsf{IGr}(3,9)$. The exceptional objects are $\mathsf{Sp}_9$-equivariant vector bundles. This provides further evidence of the Kuznetsov-Smirnov version of Dubrovin conjecture.

Muhammad Waqas Khaliq, José M. Álvarez, Antonio Camps, Nahikari González

We describe a setup that is used for high-frequency electrical sample excitation in a cathode lens electron microscope with the sample stage at high voltage as used in many synchrotron light sources. Electrical signals are transmitted by dedicated high-frequency components to the printed circuit board supporting the sample. Sub-miniature push-on connectors (

Yulan Gao, Yansong Zhao, Han Yu

Federated learning (FL), which addresses data privacy issues by training models on resource-constrained mobile devices in a distributed manner, has attracted significant research attention. However, the problem of optimizing FL client selection in mobile federated learning networks (MFLNs), where devices move in and out of each others' coverage and no FL ser

Jayakrishnan Madathil

We study the computational complexity of fair division of indivisible items in an enriched model: there is an underlying graph on the set of items. And we have to allocate the items (i.e., the vertices of the graph) to a set of agents in such a way that (a) the allocation is fair (for appropriate notions of fairness) and (b) each agent receives a bundle of i

Peter Zhang

A growing literature studies how humans incorporate advice from algorithms. This study examines an algorithm with millions of daily users: ChatGPT. In a preregistered study, 118 student participants answer 2,828 multiple-choice questions across 25 academic subjects. Participants receive advice from a GPT model and can update their initial responses. The advi

Jianhuan Cen, Qingsong Zou

In this paper, we introduce the Deep Finite Volume Method (DFVM), an innovative deep learning framework tailored for solving high-order (order \(\geq 2\)) partial differential equations (PDEs). Our approach centers on a novel loss function crafted from local conservation laws derived from the original PDE, distinguishing DFVM from traditional deep learning m

George H. Chen

We propose a general framework for visualizing any intermediate embedding representation used by any neural survival analysis model. Our framework is based on so-called anchor directions in an embedding space. We show how to estimate these anchor directions using clustering or, alternatively, using user-supplied "concepts" defined by collections of raw input

Mahmoud M. Asmar, Wang-Kong Tse

The interplay between light-matter, spin-orbit, and magnetic interactions allows the investigation of light-induced magnetic phenomena that are otherwise absent without irradiation. We present our analysis of light-driving effects on the interlayer exchange coupling mediated by a bulk Rashba semiconductor in a magnetic multilayer. The collinear magnetic exch

Alexander Taveira Blomenhofer

We consider simultaneous Waring decompositions: Given forms $ f_d $ of degrees $ kd $, $ (d = 2,3 )$, which admit a representation as $ d $-th power sums of $ k $-forms $ q_1,\ldots,q_m $, when is it possible to reconstruct the addends $ q_1,\ldots,q_m $ from the power sums $ f_d $? Such powers-of-forms decompositions model the moment problem for mixtures of

Aurélien Drezet

We assess the analysis made by Bohr in 1935 of the Einstein Podolsky Rosen paradox/theorem. We explicitly describe Bohr's gedanken experiment involving a double-slit moving diaphragm interacting with two independent particles and show that the analysis provided by Bohr was flawed. We propose a different protocol correcting Bohr's version that confirms EPR di

Hamidreza Bakhshzad Mahmoodi, MohammadJavad Salehi, Antti Tolli

A location-aware multi-antenna coded caching scheme is proposed for applications with location-dependent data requests, such as wireless immersive experience, where users are immersed in a three-dimensional virtual world. The wireless connectivity conditions vary as the users move within the application area motivating the use of a non-uniform cache memory a

Alireza Dehlaghi-Ghadim, Mahshid Helali Moghadam, Ali Balador, Hans Hansson

Over the past few decades, Industrial Control Systems (ICSs) have been targeted by cyberattacks and are becoming increasingly vulnerable as more ICSs are connected to the internet. Using Machine Learning (ML) for Intrusion Detection Systems (IDS) is a promising approach for ICS cyber protection, but the lack of suitable datasets for evaluating ML algorithms

Sarah A. Obead, Hsuan-Yin Lin, Eirik Rosnes

We study the problem of pliable private information retrieval with side information (PPIR-SI) for the single server case. In PPIR, the messages are partitioned into nonoverlapping classes and stored in a number of noncolluding databases. The user wishes to retrieve any one message from a desired class while revealing no information about the desired class id

Timothy J. Callow, Jan Nikl, Eli Kraisler, Attila Cangi

Rapid access to accurate equation-of-state (EOS) data is crucial in the warm-dense matter regime, as it is employed in various applications, such as providing input for hydrodynamic codes to model inertial confinement fusion processes. In this study, we develop neural network models for predicting the EOS based on first-principles data. The first model utili

Hamza Fawzi, Omar Fawzi, Samuel O. Scalet

We study the use of von Neumann entropy constraints for obtaining lower bounds on the ground energy of quantum many-body systems. Known methods for obtaining certificates on the ground energy typically use consistency of local observables and are expressed as semidefinite programming relaxations. The local marginals defined by such a relaxation do not necess

Xinyue Zhang, Pan Hu, Yavor Nenov, Ian Horrocks

Datalog reasoning based on the semina\"ive evaluation strategy evaluates rules using traditional join plans, which often leads to redundancy and inefficiency in practice, especially when the rules are complex. Hypertree decompositions help identify efficient query plans and reduce similar redundancy in query answering. However, it is unclear how this can be

Xiaotian Dai, Zhenyun Qin

The elementary and systematic binary Bell polynomial approach is applied to the good Boussinesq equation. The bilinear representation, $n$-soliton solutions, bilinear B\"acklund transformation, Lax pair and infinite conservation laws of the good Boussinesq equation are obtained directly. In addition, from the reduction conditions of the obtained Lax pairs, t

Hyeon-Jin Kim, Ji-Hyeok Jung, Kyung-Jun Lee, Young-Sik Ra

Entanglement is a crucial quantum resource with broad applications in quantum information science. For harnessing entanglement in practice, it is a prerequisite to certify the entanglement of a given quantum state. However, the certification process itself destroys the entanglement, thereby precluding further exploitation of the entanglement. Resolving this

Adrien Bolland, Gilles Louppe, Damien Ernst

Direct policy optimization in reinforcement learning is usually solved with policy-gradient algorithms, which optimize policy parameters via stochastic gradient ascent. This paper provides a new theoretical interpretation and justification of these algorithms. First, we formulate direct policy optimization in the optimization by continuation framework. The l

Lauren E Dang, Susan Gruber, Hana Lee, Issa Dahabreh

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized controlled

Yujia Qin, Zihan Cai, Dian Jin, Lan Yan

Long-form question answering (LFQA) aims at answering complex, open-ended questions with detailed, paragraph-length responses. The de facto paradigm of LFQA necessitates two procedures: information retrieval, which searches for relevant supporting facts, and information synthesis, which integrates these facts into a coherent answer. In this paper, we introdu

Duy-Nhat Phan, Sedi Bartz, Nilabja Guha, Hung M. Phan

We study a class of nonconvex nonsmooth optimization problems in which the objective is a sum of two functions: One function is the average of a large number of differentiable functions, while the other function is proper, lower semicontinuous and has a surrogate function that satisfies standard assumptions. Such problems arise in machine learning and regula

Benedikt Steinar Magnússon, Álfheiður Edda Sigurðardóttir, Ragnar Sigurðsson, Bergur Snorrason

The main result of this paper is that an entire function $f$ that is in $L^2(\mathbb C^n,\psi)$ with respect to the weight $\psi(z)=2mH_S(z)+\gamma\log(1+|z|^2)$ is a polynomial with exponents in $m\widehat S_\Gamma$. Here $H_S$ is the logarithmic supporting function of a compact convex set $S\subset \mathbb R^n_+$ with $0\in S$, $\gamma\geq 0$ is small enou

S. Huczynska, L. M. Johnson

Recently, new combinatorial structures called disjoint partial difference families (DPDFs) and external partial difference families (EPDFs) were introduced, which simultaneously generalize partial difference sets, disjoint difference families and external difference families, and have applications in information security. So far, all known construction metho

P. Deivendran, S. Selvakanmani, S. Jegadeesan, V. Vinoth Kumar

Liver infection is a common disease, which poses a great threat to human health, but there is still able to identify an optimal technique that can be used on large-level screening. This paper deals with ML algorithms using different data sets and predictive analyses. Therefore, machine ML can be utilized in different diseases for integrating a piece of patte

Sun Yifei, Li Dingrui, Ye Minying, Tanaka Kanji

In 3D point cloud-based visual self-localization, pole landmarks have a great potential as landmarks for accurate and reliable localization due to their long-term stability under seasonal and weather changes. In this study, we aim to explore the use of recently developed deep learning models for pole classification in the context of pole landmark-based self-

Daniel Reyes, Piergiulio Tempesta, Giorgio Tondo

A theory of partial separability for classical Hamiltonian systems is proposed in the context of Haantjes geometry. As a general result, we show that the knowledge of a non-semisimple symplectic-Haantjes manifold for a given Hamiltonian system is sufficient to construct sets of coordinates (called Darboux-Haantjes coordinates) which allow both the partial se

Takanobu Kirihara, Hajime Susa, Takashi Hosokawa, Tomoya Kinugawa

Massive close binary stars with extremely small separations have been observed, and they are possible progenitors of gravitational-wave sources. The evolution of massive binaries in the protostellar accretion stage is key to understanding their formation process. We, therefore, investigate how close the protostars, consisting of a high-density core and a vas

P. Deivendran, P. Suresh Babu, G. Malathi, K. Anbazhagan

Human communication is the vocal and non verbal signal to communicate with others. Human expression is a significant biometric object in picture and record databases of surveillance systems. Face appreciation has a serious role in biometric methods and is good-looking for plentiful applications, including visual scrutiny and security. Facial expressions are

Lukáš Mikula, Michal Štefánik, Marek Petrovič, Petr Sojka

While the Large Language Models (LLMs) dominate a majority of language understanding tasks, previous work shows that some of these results are supported by modelling spurious correlations of training datasets. Authors commonly assess model robustness by evaluating their models on out-of-distribution (OOD) datasets of the same task, but these datasets might s

Nazmuddoha Ansary, Quazi Adibur Rahman Adib, Tahsin Reasat, Asif Shahriyar Sushmit

Writing systems of Indic languages have orthographic syllables, also known as complex graphemes, as unique horizontal units. A prominent feature of these languages is these complex grapheme units that comprise consonants/consonant conjuncts, vowel diacritics, and consonant diacritics, which, together make a unique Language. Unicode-based writing schemes of t

Yoshiki Hatta

To decipher complex patterns of gravity-mode period spacings observed for intermediate-mass main-sequence stars is an important step toward the better understanding of the structure and dynamics in the deep radiative region of the stars. In this study, we apply JWKB approximation to derive a semi-analytical expression of the g-mode period spacing pattern, fo

Mathias J. R. Staunstrup, Alexey Tiranov, Ying Wang, Sven Scholz

Realizing a sensitive photon-number-dependent phase shift on a light beam is required both in classical and quantum photonics. It may lead to new applications for classical and quantum photonics machine learning or pave the way for realizing photon-photon gate operations. Non-linear phase-shifts require efficient light-matter interaction, and recently quantu

N. Heidari, H. Hassanabadi, A. A. Araújo Filho, J. Kriz

This work investigates several key aspects of a non--commutative theory with mass deformation. We calculate thermodynamic properties of the system and compare our results with recent literature. We examine the \textit{quasinormal} modes of massless scalar perturbations using two approaches: the WKB approximation and the P\"oschl--Teller fitting method. Our r

Sankar Das Sarma, Haining Pan

Motivated by a recent breakthrough transport experiment [Phys. Rev. B.107.245423 (2023)] in Majorana nanowires, we theoretically investigate local and nonlocal transport in Majorana nanowires in various disorder regimes, correlating the transport properties with the corresponding local and total density of states as well as various topological diagnostics. W

Luis Álvarez-Cónsul, Andoni De Arriba de La Hera, Mario Garcia-Fernandez

Motivated by the programme on mirror symmetry for non-K\"ahler manifolds, we construct representations of the $N=2$ superconformal vertex algebra associated to solutions of the Hull-Strominger system. The construction is via embeddings of the $N=2$ superconformal vertex algebra in the chiral de Rham complex of a string Courant algebroid. Our results require

Filip Jonsson Kling, Samuel Lundqvist, Lisa Nicklasson

We consider homogeneous binomial ideals $I=(f_1,\ldots,f_n)$ in $K[x_1, \ldots, x_n]$, where $f_i = a_i x_i^{d_i} - b_i m_i$ and $a_i \neq 0$. When such an ideal is a complete intersection, we show that the monomials which are not divisible by $x_i^{d_i}$ for $i=1,\ldots,n$ form a vector space basis for the corresponding quotient, and we describe the Macaula

Jens Boos

The entropy of a Schwarzschild black hole, as computed via the semiclassical Euclidean path integral in a stationary phase approximation, is determined not by the on-shell value of the action (which vanishes), but by the Gibbons--Hawking--York boundary term evaluated on a suitable hypersurface, which can be chosen arbitrarily far away from the horizon. For t

Rongwu Xu, Sen Yang, Fan Zhang, Zhixuan Fang

Single sign-on (SSO) allows users to authenticate to third-party applications through a central identity provider. Despite their wide adoption, deployed SSO systems suffer from privacy problems such as user tracking by the identity provider. While numerous solutions have been proposed by academic papers, none were adopted because they require modifying ident

R. V. Harlander, T. Kempkens, M. C. Schaaf

We present a complete and non-redundant basis of effective operators for the Standard Model Effective Field Theory up to mass dimension 12 with three generations of fermions. We also include operators coupling to gravity via the Weyl tensor. The results are obtained by implementing the algorithm of Li et al., and provided in the form of ancillary files.

Shaina Raza, Parisa Osivand Pour, Syed Raza Bashir

With the growing utilization of machine learning in healthcare, there is increasing potential to enhance healthcare outcomes. However, this also brings the risk of perpetuating biases in data and model design that can harm certain demographic groups based on factors such as age, gender, and race. This study proposes an artificial intelligence framework, grou

Alexandr Karpenko, Mikhail Korobko, Sergey P. Vyatchanin

Quantum optomechanical systems enable the study of fundamental questions on quantum nature of massive objects. For that a strong coupling between light and mechanical motion is required, which presents a challenge for massive objects. In particular large interferometric sensors with low frequency oscillators are difficult to bring into quantum regime. Here w

Chan Xu, Shuowen Zhang

In this paper, we consider a multiple-input multiple-output (MIMO) radar system for localizing a target based on its reflected echo signals. Specifically, we aim to estimate the random and unknown angle information of the target, by exploiting its prior distribution information. First, we characterize the estimation performance by deriving the posterior Cram

Joao Luís Rosa, Rui André, José P. S. Lemos

In quadratic gravity, the junction conditions are six and permit the appearance of double layer thin shells. Double layers arise typically in theories with dipoles, i.e., two opposite charges, such as electromagnetic theories, and appear exceptionally in gravitational theories, which are theories with a single charge. We explore this property of the existenc

Joakim Brorsson, Ivana Staničić, Jonatan Gastaldi, Tobias Mattison

In this study, an efficient first-principles approach for calculating the thermodynamic properties of mixed metal oxides at high temperatures is demonstrated. More precisely, this procedure combines density functional theory and harmonic phonon calculations with tabulated thermochemical data to predict the heat capacity, formation energy, and entropy of impo

Minh-Thanh Bui, Duc-Thinh Ngo, Demin Lu, Zonghua Zhang

Self-awareness is the key capability of autonomous systems, e.g., autonomous driving network, which relies on highly efficient time series forecasting algorithm to enable the system to reason about the future state of the environment, as well as its effect on the system behavior as time progresses. Recently, a large number of forecasting algorithms using eit

Xiaobao Jia, Qing Jia, Rui Yan, Jian Zheng

Recently, the verification of stimulated Raman side-scattering (SRSS) in different laser inertial confinement fusion ignition schemes poses an underlying risk of SRSS on ignition. In this paper, we propose a method to use the non-uniform polarization nature of vector light to suppress SRSS and give an additional threshold condition determined by the paramete

Anna Rodriguez Rasmussen

Given an algebra and a finite group acting on it via automorphisms, a natural object of study is the associated skew group algebra. In this article, we study the relationship between quasi-hereditary structures on the original algebra and on the corresponding skew group algebra. Assuming a natural compatibility condition on the partial order, we show that th

Taniya Khatun, Tanmoy Banerjee

Noise induced order in excitable systems has diverse manifestations, such as coherence resonance (CR) and stochastic resonance. In this context a less explored phenomenon is self-induced stochastic resonance (SISR). Unlike CR, SISR may arise away from the bifurcation threshold and the properties of the induced oscillations depend upon both the noise intensit

M. Shahid, S. P. MacLachlan, H. bin Zubair Syed

Boundary value problems based on the convection-diffusion equation arise naturally in models of fluid flow across a variety of engineering applications and design feasibility studies. Naturally, their efficient numerical solution has continued to be an interesting and active topic of research for decades. In the context of finite-element discretization of th

Johannes F. Kunz, Stefan Ruschke, Reinhard Heckel

Cardiac magnetic resonance imaging (MRI) requires reconstructing a real-time video of a beating heart from continuous highly under-sampled measurements. This task is challenging since the object to be reconstructed (the heart) is continuously changing during signal acquisition. In this paper, we propose a reconstruction approach based on representing the bea

Bruno P. Cavalar, Igor C. Oliveira

We establish new separations between the power of monotone and general (non-monotone) Boolean circuits: - For every $k \geq 1$, there is a monotone function in ${\sf AC^0}$ that requires monotone circuits of depth $\Omega(\log^k n)$. This significantly extends a classical result of Okol'nishnikova (1982) and Ajtai and Gurevich (1987). In addition, our separa

Sebastian Huch, Florian Sauerbeck, Johannes Betz

Autonomous vehicles demand high accuracy and robustness of perception algorithms. To develop efficient and scalable perception algorithms, the maximum information should be extracted from the available sensor data. In this work, we present our concept for an end-to-end perception architecture, named DeepSTEP. The deep learning-based architecture processes ra

Davide Bilò, Vittorio Bilò, Michelle Döring, Pascal Lenzner

In most major cities and urban areas, residents form homogeneous neighborhoods along ethnic or socioeconomic lines. This phenomenon is widely known as residential segregation and has been studied extensively. Fifty years ago, Schelling proposed a landmark model that explains residential segregation in an elegant agent-based way. A recent stream of papers ana

Albin Zehe, Julian Schröter, Andreas Hotho

Suspense is an important tool in storytelling to keep readers engaged and wanting to read more. However, it has so far not been studied extensively in Computational Literary Studies. In this paper, we focus on one of the elements authors can use to build up suspense: dangerous situations. We introduce a corpus of texts annotated with dangerous situations, di

Haitao Li, Changyue Wang, Weihang Su, Yueyue Wu

This paper describes the approach of the THUIR team at the COLIEE 2023 Legal Case Entailment task. This task requires the participant to identify a specific paragraph from a given supporting case that entails the decision for the query case. We try traditional lexical matching methods and pre-trained language models with different sizes. Furthermore, learnin

Bart Eggen, Stéphanie L. van der Pas, Aad W. van der Vaart

In causal inference, sensitivity analysis is important to assess the robustness of study conclusions to key assumptions. We perform sensitivity analysis of the assumption that missing outcomes are missing completely at random. We follow a Bayesian approach, which is nonparametric for the outcome distribution and can be combined with an informative prior on t

Wout Merbis, Clélia de Mulatier, Philippe Corboz

The contact process is an emblematic model of a non-equilibrium system, containing a phase transition between inactive and active dynamical regimes. In the epidemiological context, the model is known as the susceptible-infected-susceptible (SIS) model, and widely used to describe contagious spreading. In this work, we demonstrate how accurate and efficient r

Hasan B. Al Ba'ba'a

Brillouin-zone (BZ) definition in a class of non-reciprocal Willis monatomic lattices (WMLs) is analytically quantified. It is shown that BZ boundaries only shift in response to non-reciprocity in one-dimensional WMLs, implying a constant BZ width, with asymmetric dispersion diagrams exhibiting unequal wavenumber ranges for forward and backward going waves.

Sojung Go, Younghoon Ji, Sang Jun Park, Soochahn Lee

We introduce a new technique for generating retinal fundus images that have anatomically accurate vascular structures, using diffusion models. We generate artery/vein masks to create the vascular structure, which we then condition to produce retinal fundus images. The proposed method can generate high-quality images with more realistic vascular structures an

Haitao Li, Weihang Su, Changyue Wang, Yueyue Wu

Legal case retrieval techniques play an essential role in modern intelligent legal systems. As an annually well-known international competition, COLIEE is aiming to achieve the state-of-the-art retrieval model for legal texts. This paper summarizes the approach of the championship team THUIR in COLIEE 2023. To be specific, we design structure-aware pre-train