April 2023 arXiv papers — page 45

Alana C. L. Santos, Célio R. Muniz, Roberto V. Maluf

This work presents new three-dimensional traversable wormhole solutions sourced by the Casimir density and pressures related to the quantum vacuum fluctuations in Yang-Mills (Y-M) theory. We begin by analyzing the noninteracting Y-M Casimir wormholes, initially considering an arbitrary state parameter $\omega$ and determine a simple constant wormhole shape f

Nick Edelen, Luca Spolaor, Bozhidar Velichkov

We introduce a symmetric (log-)epiperimetric inequality, generalizing the standard epiperimetric inequality, and we show that it implies a growth-decay for the associated energy: as the radius increases energy decays while negative and grows while positive. One can view the symmetric epiperimetric inequality as giving a log-convexity of energy, analogous to

James B. R. Battat, Eric Adelberger, Nicholas R. Colmenares, Megan Farrah

We present data from the Apache Point Observatory Lunar Laser-ranging Operation (APOLLO) covering the 15-year span from April 2006 through the end of 2020. APOLLO measures the earth-moon separation by recording the round-trip travel time of photons from the Apache Point Observatory to five retro-reflector arrays on the moon. The APOLLO data set, combined wit

Nicholas R. Colmenares, James B. R. Battat, Daniel P. Gonzales, Thomas W. Murphy

The Apache Point Lunar Laser-ranging Operation (APOLLO) has been collecting lunar range measurements for 15 years at millimeter accuracy. The median nightly range uncertainty since 2006 is 1.7 mm. A recently added Absolute Calibration System (ACS), providing an independent assessment of APOLLO system accuracy and the capability to correct lunar range data, r

Richard Schoen

We show that an odd dimensional closed manifold with positive curvature cannot contain an incompressible real projective plane in the sense that there is no map of the projective plane into the manifold which is nontrivial on both first and second homotopy groups. Another way to say this is that no element of the fundamental group reverses the orientation of

Joshua Groen, Salvatore DOro, Utku Demir, Leonardo Bonati

The Open Radio Access Network (RAN) is a networking paradigm that builds on top of cloud-based, multi-vendor, open and intelligent architectures to shape the next generation of cellular networks for 5G and beyond. While this new paradigm comes with many advantages in terms of observatibility and reconfigurability of the network, it inevitably expands the thr

Giancarlo Guizzardi, Nicola Guarino

The terms 'semantics' and 'ontology' are increasingly appearing together with 'explanation', not only in the scientific literature, but also in organizational communication. However, all of these terms are also being significantly overloaded. In this paper, we discuss their strong relation under particular interpretations. Specifically, we discuss a notion o

Bedoor AlShebli, Shahan Ali Memon, James A. Evans, Talal Rahwan

Artificial Intelligence (AI) has become a disruptive technology, promising to grant a significant economic and strategic advantage to nations that harness its power. China, with its recent push towards AI adoption, is challenging the U.S.'s position as the global leader in this field. Given AI's massive potential, as well as the fierce geopolitical tensions

W. Pepper Marts, Matthew G. F. Dosanjh, Whit Schonbein, Scott Levy

Early-bird communication is a communication/computation overlap technique that combines fine-grained communication with partitioned communication to improve application run-time. Communication is divided among the compute threads such that each individual thread can initiate transmission of its portion of the data as soon as it is complete rather than waitin

Pankaj K Mishra, Pushpak Jagtap

Motivated by the concept of Quasi-Sliding Mode (QSM) in discrete-time systems, this paper presents a novel approach that relaxes the requirement of ubiquitous exact sliding motion in continuous-time systems, aiming to achieve an approximation- and chattering-free quasi-sliding mode controller (QSMC). The proposed QSMC provides robust and chattering-free cont

Min Young Lee

This work aims to create a multimodal AI system that chats with humans and shares relevant photos. While earlier works were limited to dialogues about specific objects or scenes within images, recent works have incorporated images into open-domain dialogues. However, their response generators are unimodal, accepting text input but no image input, thus prone

Phillip M. Maffettone, Pascal Friederich, Sterling G. Baird, Ben Blaiszik

Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. The promise of this field has given rise to a rich community of passionate scientists, engineers, and social scientists, as evidenced by the development of the Acceleration Consortium and recent Accelerate Conferen

A. Morvan, B. Villalonga, X. Mi, S. Mandrà

Undesired coupling to the surrounding environment destroys long-range correlations on quantum processors and hinders the coherent evolution in the nominally available computational space. This incoherent noise is an outstanding challenge to fully leverage the computation power of near-term quantum processors. It has been shown that benchmarking Random Circui

Zihao Li

With the launch of ChatGPT, Large Language Models (LLMs) are shaking up our whole society, rapidly altering the way we think, create and live. For instance, the GPT integration in Bing has altered our approach to online searching. While nascent LLMs have many advantages, new legal and ethical risks are also emerging, stemming in particular from stochastic pa

Angela Castillo, Maria Escobar, Guillaume Jeanneret, Albert Pumarola

Mixed reality applications require tracking the user's full-body motion to enable an immersive experience. However, typical head-mounted devices can only track head and hand movements, leading to a limited reconstruction of full-body motion due to variability in lower body configurations. We propose BoDiffusion -- a generative diffusion model for motion synt

Jacob Mallet, Natalie Krueger, Mounika Vanamala, Rushit Dave

The growing reliance of society on social media for authentic information has done nothing but increase over the past years. This has only raised the potential consequences of the spread of misinformation. One of the growing methods in popularity is to deceive users using a deepfake. A deepfake is an invention that has come with the latest technological adva

Samir Sadok, Simon Leglaive, Renaud Séguier

Recent years have seen remarkable progress in speech emotion recognition (SER), thanks to advances in deep learning techniques. However, the limited availability of labeled data remains a significant challenge in the field. Self-supervised learning has recently emerged as a promising solution to address this challenge. In this paper, we propose the vector qu

Pierluigi Colli, Gianni Gilardi, Gabriela Marinoschi, Elisabetta Rocca

This paper is concerned with the well-posedness and optimal control problem of a reaction-diffusion system for an epidemic Susceptible-Infected-Recovered-Susceptible (SIRS) mathematical model in which the dynamics develops in a spatially heterogeneous environment. Using as control variables the transmission rates $u_{i}$ and $u_{e}$ of contagion resulting fr

Chuhan Chen, Matthew O'Toole, Gaurav Bharaj, Pablo Garrido

High-quality reconstruction of controllable 3D head avatars from 2D videos is highly desirable for virtual human applications in movies, games, and telepresence. Neural implicit fields provide a powerful representation to model 3D head avatars with personalized shape, expressions, and facial parts, e.g., hair and mouth interior, that go beyond the linear 3D

Julian Coda-Forno, Kristin Witte, Akshay K. Jagadish, Marcel Binz

Large language models (LLMs) are transforming research on machine learning while galvanizing public debates. Understanding not only when these models work well and succeed but also why they fail and misbehave is of great societal relevance. We propose to turn the lens of psychiatry, a framework used to describe and modify maladaptive behavior, to the outputs

Vuthea Chheang, Rakshith Lokesh, Amit Chaudhari, Qile Wang

Stroke patients often experience upper limb impairments that restrict their mobility and daily activities. Physical therapy (PT) is the most effective method to improve impairments, but low patient adherence and participation in PT exercises pose significant challenges. To overcome these barriers, a combination of virtual reality (VR) and robotics in PT is p

Manish Kumar

We establish factoriality and non-injectivity in full generality for the mixed $q$-Araki-Woods von Neumann algebra associated to a separable real Hilbert space $\mathsf{H}_{\mathbf{R}}$ with $\dim\mathsf{H}_{\mathbf{R}}\geq 2$, a strongly continuous one parameter group of orthogonal transformations on $\mathsf{H}_\mathbb{R}$, a direct sum decomposition $\mat

Tianyang Zhong, Yaonai Wei, Li Yang, Zihao Wu

Large language models (LLMs) such as ChatGPT have recently demonstrated significant potential in mathematical abilities, providing valuable reasoning paradigm consistent with human natural language. However, LLMs currently have difficulty in bridging perception, language understanding and reasoning capabilities due to incompatibility of the underlying inform

Yiming Ai, Bipin Rajendran

Brain-computer interfaces are being explored for a wide variety of therapeutic applications. Typically, this involves measuring and analyzing continuous-time electrical brain activity via techniques such as electrocorticogram (ECoG) or electroencephalography (EEG) to drive external devices. However, due to the inherent noise and variability in the measuremen

Hanyuan Liu, Jinbo Xing, Minshan Xie, Chengze Li

Image colorization has been attracting the research interests of the community for decades. However, existing methods still struggle to provide satisfactory colorized results given grayscale images due to a lack of human-like global understanding of colors. Recently, large-scale Text-to-Image (T2I) models have been exploited to transfer the semantic informat

Alexander W. Goodall, Francesco Belardinelli

Balancing exploration and conservatism in the constrained setting is an important problem if we are to use reinforcement learning for meaningful tasks in the real world. In this paper, we propose a principled algorithm for safe exploration based on the concept of shielding. Previous approaches to shielding assume access to a safety-relevant abstraction of th

Rongzhen Hu, JunYan Luo, Yiying Yan

We study the emission spectrum of two distant qubits strongly coupled to a waveguide by using the numerical and analytical approaches, which are beyond the Markovian approximation and the rotating-wave approximation (RWA). The numerical approach combines the Dirac-Frenkel time-dependent variational principle with the multiple Davydov $D_{1}$ ansatz. A transf

Allison Fitisone, Yuan Zhou

This paper addresses the computation of normalized solid angle measure of polyhedral cones. This is well understood in dimensions two and three. For higher dimensions, assuming that a positive-definite criterion is met, the measure can be computed via a multivariable hypergeometric series. We present two decompositions of full-dimensional simplicial cones in

Viktorija Pruckovskaja, Axel Weissenfeld, Clemens Heistracher, Anita Graser

Data-driven machine learning is playing a crucial role in the advancements of Industry 4.0, specifically in enhancing predictive maintenance and quality inspection. Federated learning (FL) enables multiple participants to develop a machine learning model without compromising the privacy and confidentiality of their data. In this paper, we evaluate the perfor

Patrick Charbonneau, Peter K. Morse

Real structural glasses form through various out-of-equilibrium processes, including temperature quenches, rapid compression, shear, and aging. Each of these processes should be formally understandable within the recently formulated dynamical mean-field theory of glasses, but many of the numerical tools needed to solve the relevant equations for sufficiently

Marcus Nóbrega Gomes, César Ambrogi Ferreira do Lago, Luis Miguel Castillo Rápalo, Paulo Tarso S. Oliveira

Floods are one of the deadliest natural hazards and are fueled by excessive urbanization. Urban development decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry weather. During wet weather events, there is an increase in the levels of pollution concentrations and stormwater runoff that eventually reach cre

Ruichen Zhang, Ke Xiong, Hongyang Du, Dusit Niyato

Recognizing the tremendous improvements that the integration of generative AI can bring to intelligent transportation systems, this article explores the integration of generative AI technologies in vehicular networks, focusing on their potential applications and challenges. Generative AI, with its capabilities of generating realistic data and facilitating ad

Wenshan Chen, Kingsley Egbo, Hans Tornatzky, Manfred Ramsteiner

Rutile GeO2 has been predicted to be an ultra-wide bandgap semiconductor suitable for future power electronics devices while quartz-like GeO2 shows piezoelectric properties. To explore these crystalline phases for application and fundamental materials investigations, molecular beam epitaxy (MBE) is a well-suited thin film growth technique. In this study, we

Yousef Bisabr

We investigate a cosmological model in which dark energy, represented by a quintessential scalar field, is coupled to a dark-matter perfect fluid in the spatially flat Friedmann-Robertson-Walker Universe. This allows an energy exchange in the dark sector which could happen both at early times before recombination era or at late times. We use the coupling fun

Yury Solyaev

In this paper, we propose a generalized variant of Kr\"oner's self-consistent scheme for evaluation of the effective standard and gradient elastic moduli of polycrystalline materials within Mindlin-Toupin second-gradient elasticity theory. Assuming random orientation of crystallites (grains) we use an extended Eshelby's equivalent inclusion method and mappin

Luis Morales-Navarro, Yasmin B. Kafai

As several critical issues in computing such as algorithmic bias, discriminatory practices, and techno-solutionism have become more visible, numerous efforts are being proposed to integrate criticality in K-16 computing education. Yet, how exactly these efforts address criticality and translate it into classroom practice is not clear. In this conceptual pape

Francesco Esposito, Rafael López-Soriano, Berardino Sciunzi

This work deals with a family of Hardy-Sobolev doubly critical system defined in $\mathbb{R}^n$. More precisely, we provide a classification of the positive solutions, whose expressions comprise multiplies of solutions of the decoupled scalar equation. Our strategy is based on the symmetry of the solutions, deduced via a suitable version of the moving planes

Charles-Edouard Bréhier, David Cohen, Johan Ulander

We introduce a positivity-preserving numerical scheme for a class of nonlinear stochastic heat equations driven by a purely time-dependent Brownian motion. The construction is inspired by a recent preprint by the authors where one-dimensional equations driven by space-time white noise are considered. The objective of this paper is to illustrate the propertie

Peter L. Bartlett, Philip M. Long

We present a new general-purpose algorithm for learning classes of $[0,1]$-valued functions in a generalization of the prediction model, and prove a general upper bound on the expected absolute error of this algorithm in terms of a scale-sensitive generalization of the Vapnik dimension proposed by Alon, Ben-David, Cesa-Bianchi and Haussler. We give lower bou

Christopher Beem, Andrea E. V. Ferrari

We study the boundary vertex algebras of $A$-twisted $\mathcal{N}=4$ Abelian gauge theories in three dimensions. These are identified with the BRST quotient (semi-infinite cohomology) of collections of symplectic bosons and free fermions that reflect the matter content of the corresponding gauge theory. We develop various free field realisations for these ve

Valeria Banica, Renato Lucà, Nikolay Tzvetkov, Luis Vega

We consider the 1D cubic NLS on $\mathbb R$ and prove a blow-up result for functions that are of borderline regularity, i.e. $H^s$ for any $s<-\frac 12$ for the Sobolev scale and $\mathcal F L^\infty$ for the Fourier-Lebesgue scale. This is done by identifying at this regularity a certain functional framework from which solutions exit in finite time. This fu

Arijit Mannna, Sabyasachi Pal

The amide-related molecules are essential for the formation of the other complex bio-molecules and an understanding of the prebiotic chemistry in the interstellar medium (ISM). We presented the first detection of the rotational emission lines of the amide-like molecule cyanamide (NH$_{2}$CN) towards the hot molecular core G358.93$-$0.03 MM1 using the Atacama

E. P. van den Ban

We study Whittaker vectors (and Jacquet integrals) in the generalized principal series for a real reductive group. A functional equation for them is obtained. This allows to establish uniform estimates for their holomorphic extensions with respect to the continuous induction parameter. Finally, we link the Whittaker vectors to Harish-Chandra's Whittaker inte

Victor Chardès, Andrea Mazzolini, Thierry Mora, Aleksandra M. Walczak

Antigenic variation is the main immune escape mechanism for RNA viruses like influenza or SARS-CoV-2. While high mutation rates promote antigenic escape, they also induce large mutational loads and reduced fitness. It remains unclear how this cost-benefit trade-off selects the mutation rate of viruses. Using a traveling wave model for the co-evolution of vir

Ali Maatouk, Fadhel Ayed, Wenjie Li, Yu Wang

This paper considers an anomaly detection problem in which a detection algorithm assigns anomaly scores to multi-dimensional data points, such as cellular networks' Key Performance Indicators (KPIs). We propose an optimization framework to refine these anomaly scores by leveraging side information in the form of a causality graph between the various features

Gang Lü, Xi-Liang Yuan, Na-Wang, Xin-Heng Guo

We introduce the new resonance of $V\rightarrow K^{+}K^{-}$ $(V=\phi, \rho, \omega)$, which produces some new strong phase associated with vector meson resonance and thus can cause relatively large CP asymmetry at the range of interferences. There are the resonances of $\phi \rightarrow K^{+}K^{-}$, $\rho \rightarrow K^{+}K^{-}$ and $\omega \rightarrow K^{+}

Bo Yang, Xinyuan Zhao, Xudong Li, Defeng Sun

To ensure the system stability of the $\bf{\mathcal{H}_{2}}$-guaranteed cost optimal decentralized control problem (ODC), an approximate semidefinite programming (SDP) problem is formulated based on the sparsity of the gain matrix of the decentralized controller. To reduce data storage and improve computational efficiency, the SDP problem is vectorized into

Moira Chas, Arpan Kabiraj

In this note we develop a tool box of non-Euclidean plane geometry methods that yield a constructive way to define in terms of closed geodesics the Goldman bracket on deformation classes of closed, directed curves. We use this construction to algebraically characterize closed geodesics without self-intersection on hyperbolic surfaces.

Zhi-Hui Xu, Qiang Yuan, Zhi-Cheng Tang, Xiao-Jun Bi

Precise measurements of the spectra of secondary and primary cosmic rays are crucial for understanding the origin and propagation of those energetic particles. The High Energy cosmic-Radiation Detection (HERD) facility onboard China`s Space Station, which is expected to operate in 2027, will push the direct measurements of cosmic ray fluxes precisely up to P

Sanghyuk Lee, Seunghyun Lee, Byung Cheol Song

Meta-learning performs adaptation through a limited amount of support set, which may cause a sample bias problem. To solve this problem, transductive meta-learning is getting more and more attention, going beyond the conventional inductive learning perspective. This paper proposes so-called task-adaptive pseudo labeling for transductive meta-learning. Specif

Guillem Domènech, Alexander Ganz

Symmetries play an important role in fundamental physics. In gravity and field theories, particular attention has been paid to Weyl (or conformal) symmetry. However, once the theory contains a scalar field, conformal transformations of the metric can be considered a subclass of a more general type of transformation, so-called disformal transformation. Here,

Pascal Bergsträßer, Moses Ganardi

We revisit the membership problem for subclasses of rational relations over finite and infinite words: Given a relation R in a class C_2, does R belong to a smaller class C_1? The subclasses of rational relations that we consider are formed by the deterministic rational relations, synchronous (also called automatic or regular) relations, and recognizable rel

Valentin Zieglmeier, Gabriel Loyola Daiqui, Alexander Pretschner

Employee data can be used to facilitate work, but their misusage may pose risks for individuals. Inverse transparency therefore aims to track all usages of personal data, allowing individuals to monitor them to ensure accountability for potential misusage. This necessitates a trusted log to establish an agreed-upon and non-repudiable timeline of events. The

Antonio A. Valido, Alejandro J. Castro

Despite the prospect of next-generation electronic technologies has spurred the investigation of the remarkable topological magnetoelectric response, it remains largely unexplored its potential in the application of basic electronic devices. In this paper, we undertake this task at the theoretical level by addressing the $\theta$-electrodynamics and examine

Rico Pohle, Ludovic D. C. Jaubert

The Curie-Weiss law is widely used to estimate the strength of frustration in frustrated magnets. However, the Curie-Weiss law was originally derived as an estimate of magnetic correlations close to a mean-field phase transition, which -- by definition -- is absent in spin liquids. Instead, the susceptibility of spin liquids is known to undergo a Curie-law c

Jiaao Yu, Paul-Philipp Manea, Sara Ameli, Mohammad Hizzani

Recent breakthroughs in associative memories suggest that silicon memories are coming closer to human memories, especially for memristive Content Addressable Memories (CAMs) which are capable to read and write in analog values. However, the Program-Verify algorithm, the state-of-the-art memristor programming algorithm, requires frequent switching between ver

Shangda Wu, Dingyao Yu, Xu Tan, Maosong Sun

We introduce CLaMP: Contrastive Language-Music Pre-training, which learns cross-modal representations between natural language and symbolic music using a music encoder and a text encoder trained jointly with a contrastive loss. To pre-train CLaMP, we collected a large dataset of 1.4 million music-text pairs. It employed text dropout as a data augmentation te

Ramón Christen, Luca Mazzola, Alexander Denzler, Edy Portmann

Evaluating the relevance of an exogenous data series is the first step in improving the prediction capabilities of a forecast algorithm. Inspired by existing metrics for time series similarity, we introduce a new approach named FARM - Forward Aligned Relevance Metric. Our forward method relies on an angular measure that compares changes in subsequent data po

Angelo Pasquale, Sebastian Rodriguez, Khanh Nguyen, Amine Ammar

For the numerical simulation of time-dependent problems, recent works suggest the use of a time marching scheme based on a tensorial decomposition of the time axis. This time-separated representation is straightforwardly introduced in the framework of the Proper Generalized Decomposition (PGD). The time coordinate is transformed into a multi-dimensional time

Filippo Bracci

In this paper we give a characterization in terms of ``quasi-geodesics frames' of visibility and existence of geodesic loops for bounded domains in $\mathbb C^d$ which are Kobayashi complete hyperbolic and Gromov hyperbolic.

Maciej Borodzik, Marcin Mielniczuk

In 2015, Borodzik, N\'emethi and Ranicki proved that an interior critical point can be pushed to the boundary, where it splits into two boundary critical points. In this paper, we show that two critical points at the boundary can be, under specific assumptions, merged into a single critical point in the interior. That is, we reverse the original construction

Ethan Lau, Vaibhav Srivastava, Shaunak D. Bopardikar

Safely controlling unknown dynamical systems is one of the biggest challenges in the field of control. Oftentimes, an approximate model of a system's dynamics exists which provides beneficial information for the selection of controls. However, differences between the approximate and true systems present challenges as well as safety concerns. We propose an al

H. M. Cegla, N. Roguet-Kern, M. Lendl, B. Akinsanmi

We analyse spectroscopic and photometric transits of the hot Jupiters WASP-52b and HAT-P30b obtained with ESPRESSO, Eulercam and NGTS for both targets, and additional TESS data for HAT-P-30. Our goal is to update the system parameters and refine our knowledge of the host star surfaces. For WASP-52, the companion planet has occulted starspots in the past, and

Jake Stuchbury-Wass, Erika Bondareva, Kayla-Jade Butkow, Sanja Scepanovic

Abdominal sounds (ABS) have been traditionally used for assessing gastrointestinal (GI) disorders. However, the assessment requires a trained medical professional to perform multiple abdominal auscultation sessions, which is resource-intense and may fail to provide an accurate picture of patients' continuous GI wellbeing. This has generated a technological i

Karel Houfek, Jakub Benda, Zdeněk Mašín, Alex Harvey

UKRmol-scripts is a set of Perl scripts to automatically run the UKRmol+ codes, a complex software suite based on the R-matrix method to calculate fixed-nuclei photoionization and electron- and positron-scattering for polyatomic molecules. Starting with several basic parameters, the scripts operatively produce all necessary input files and run all codes for

Hengxu You, Yang Ye, Tianyu Zhou, Qi Zhu

Robot-based assembly in construction has emerged as a promising solution to address numerous challenges such as increasing costs, labor shortages, and the demand for safe and efficient construction processes. One of the main obstacles in realizing the full potential of these robotic systems is the need for effective and efficient sequence planning for constr

Kevin Scaman

Let $\mathcal{A}$ be a Las Vegas algorithm, i.e. an algorithm whose running time $T$ is a random variable drawn according to a certain probability distribution $p$. In 1993, Luby, Sinclair and Zuckerman [LSZ93] proved that a simple universal restart strategy can, for any probability distribution $p$, provide an algorithm executing $\mathcal{A}$ and whose exp

Joe Skeens, Johnathan York, Leonid Petrov, David Munton

We describe the design of a radio interferometer composed of a Global Navigation Satellite Systems (GNSS) antenna and a Very Long Baseline Interferometry (VLBI) radio telescope. Our eventual goal is to use this interferometer for geodetic applications including local tie measurements. The GNSS element of the interferometer uses a unique software-defined rece

Mohammadreza Pourreza, Davood Rafiei

There is currently a significant gap between the performance of fine-tuned models and prompting approaches using Large Language Models (LLMs) on the challenging task of text-to-SQL, as evaluated on datasets such as Spider. To improve the performance of LLMs in the reasoning process, we study how decomposing the task into smaller sub-tasks can be effective. I

Hugo Paquet, Philip Saville

We develop the theory of strong and commutative monads in the 2-dimensional setting of bicategories. This provides a framework for the analysis of effects in many recent models which form bicategories and not categories, such as those based on profunctors, spans, or strategies over games. We then show how the 2-dimensional setting provides new insights into

Guoying Chen, Xinyu Wang, Min Hua, Wei Liu

With the rapid development of autonomous driving, the attention of academia has increasingly focused on the development of anti-collision systems in emergency scenarios, which have a crucial impact on driving safety. While numerous anti-collision strategies have emerged in recent years, most of them only consider steering or braking. The dynamic and complex

Paolo Ferragina, Hans-Peter Lehmann, Peter Sanders, Giorgio Vinciguerra

A Monotone Minimal Perfect Hash Function (MMPHF) constructed on a set S of keys is a function that maps each key in S to its rank. On keys not in S, the function returns an arbitrary value. Applications range from databases, search engines, data encryption, to pattern-matching algorithms. In this paper, we describe LeMonHash, a new technique for constructing

Paweł Ordyna, Carsten Bähtz, Erik Brambrink, Michael Bussmann

Ultra-intense lasers that ionize and accelerate electrons in solids to near the speed of light can lead to kinetic instabilities that alter the laser absorption and subsequent electron transport, isochoric heating, and ion acceleration. These instabilities can be difficult to characterize, but a novel approach using X-ray scattering at keV energies allows fo

Alan Guo

We develop a formalism for reasoning about trading on decentralized exchanges on blockchains and a formulation of a particular form of maximal extractable value (MEV) that represents the total arbitrage opportunity extractable from on-chain liquidity. We use this formalism to prove that for blockchains with deterministic block times whose liquidity pools sat

Hannes Lagemann

In this thesis we study aspects of Hamiltonian models which can affect the time evolution of transmon systems. We model the time evolution of various systems as a unitary real-time process by numerically solving the time-dependent Schr\"odinger equation (TDSE). We denote the corresponding computer models as non-ideal gate-based quantum computer (NIGQC) model

Xieping Wang

The celebrated Ohsawa--Takegoshi extension theorem for $L^2$ holomorphic functions on bounded pseudoconvex domains in $\mathbb C^n$ is a fundamental result in several complex variables and complex geometry. Ohsawa conjectured in 1995 that the same theorem still holds for more general bounded complete K\"ahler domains in $\mathbb C^n$. Recently, Chen--Wu--Wan

Giuseppe Gaetano Luciano, Ahmad Sheykhi

We analyze geometrothermodynamics of charged anti-de Sitter (AdS) black holes with a global monopole in the framework of Tsallis statistics. The latter arises from a non-additive generalization of Boltzmann-Gibbs entropy, which is still recovered as a particular sub-case. We examine the effects of Tsallis entropy on small-large black holes phase-transitions

Carl Hvarfner, Erik Hellsten, Frank Hutter, Luigi Nardi

Gaussian processes are the model of choice in Bayesian optimization and active learning. Yet, they are highly dependent on cleverly chosen hyperparameters to reach their full potential, and little effort is devoted to finding good hyperparameters in the literature. We demonstrate the impact of selecting good hyperparameters for GPs and present two acquisitio

Andrea Conti, Yolanda Lozano, Niall T. Macpherson

We present general results on generating $\text{AdS}_2$ solutions to Type II supergravity from $\text{AdS}_3$ solutions via U(1) and SL(2) T-dualities. We focus on a class of Type IIB solutions with small $\mathcal{N}=4$ supersymmetry, that we show can be embedded into a more general class of solutions obtained by double analytical continuation from $\text{A

Andrew Ballin, Thomas Creutzig, Tudor Dimofte, Wenjun Niu

We study the braided tensor structure of line operators in the topological A and B twists of abelian 3d $\mathcal{N}=4$ gauge theories, as accessed via boundary vertex operator algebras (VOA's). We focus exclusively on abelian theories. We first find a non-perturbative completion of boundary VOA's in the B twist, which start out as certain affine Lie superal

Cristian Vega, Stanislav Boldyrev, Vadim Roytershteyn

Relativistic magnetically dominated turbulence is an efficient engine for particle acceleration in a collisionless plasma. Ultrarelativistic particles accelerated by interactions with turbulent fluctuations form non-thermal power-law distribution functions in the momentum (or energy) space, $f(\gamma)d\gamma\propto \gamma^{-\alpha}d\gamma$, where $\gamma$ is

Ricardo Salinas, Steve B. Howell

We present Gemini-N/'Alopeke speckle observations of KIC 9832227, a system originally predicted to become a red nova. The diffraction limited observations do not find an outer companion between 11 and 678 AU that could be responsible for the period changes of the system.

Chiara Ricca, Tristan Blandenier, Valérie Werner, Xing Wang

Perovskite oxynitrides are, due to their reduced band gap compared to oxides, promising materials for photocatalytic applications. They are most commonly synthesized from {110} layered Carpy-Galy (A$_2$B$_2$O$_7$}) perovskites via thermal ammonolysis, i.e. the exposure to a flow of ammonia at elevated temperature. The conversion of the layered oxide to the n

Nikita Tsegelnik, Evgeni Kolomeitsev, Vadym Voronyuk

The gold--gold collisions at $\sqrt{s_{NN}}=7.7$ and $11.5$GeV are simulated within the PHSD transport model. In each collision event, the spectator nucleons are separated and the fluidization procedure for the participants is performed. The local velocities are determined in the Landau frame and the kinematic and thermal vorticity fields are evaluated. We a

Matheus M. A. Paixão, Olesya Galkina, Nelson Pinto-Neto

We investigate the Minkowski ground state associated with a real massless scalar field as seen by an accelerated observer under the perspective of the de Broglie-Bohm quantum theory. We use the Schr\"odinger picture to obtain the wave functional associated with the Minkowski vacuum in Rindler coordinates, and we calculate the field trajectories through the B

Ayoub Harnoune, Maryem Rhanoui, Mounia Mikram, Siham Yousfi

Background : Knowledge is evolving over time, often as a result of new discoveries or changes in the adopted methods of reasoning. Also, new facts or evidence may become available, leading to new understandings of complex phenomena. This is particularly true in the biomedical field, where scientists and physicians are constantly striving to find new methods

Mauro Lucci, Daniel Severin, Graciela Nasini

In this work, we present a branch-and-price algorithm to solve the weighted version of the List Coloring Problem, based on a vertex cover formulation by stable sets. This problem is interesting for its applications and also for the many other problems that it generalizes, including the well-known Graph Coloring Problem. With the introduction of the concept o

Laurent Lam, Pirashanth Ratnamogan, Joël Tang, William Vanhuffel

Research in Document Intelligence and especially in Document Key Information Extraction (DocKIE) has been mainly solved as Token Classification problem. Recent breakthroughs in both natural language processing (NLP) and computer vision helped building document-focused pre-training methods, leveraging a multimodal understanding of the document text, layout an

STAR Collaboration, M. I. Abdulhamid, B. E. Aboona, J. Adam

We report the first measurements of cumulants, up to $4^{th}$ order, of deuteron number distributions and proton-deuteron correlations in Au+Au collisions recorded by the STAR experiment in phase-I of Beam Energy Scan (BES) program at the Relativistic Heavy Ion Collider. Deuteron cumulants, their ratios, and proton-deuteron mixed cumulants are presented for

Enrico Catalano

Cartilage is a connective tissue that covers the surfaces of bones in joints and provides a smooth gliding surface for movement. It is characterized by specific biophysical properties that allow it to withstand compressive loads, distribute mechanical forces, and maintain tissue integrity. The bi-ophysical properties of cartilage are primarily determined by

Minh N. Bui, Stefan Rost, Manuel Auge, Lanqing Zhou

The paper explores the optical properties of an exfoliated MoSe$_2$ monolayer implanted with Cr$^+$ ions, accelerated to 25 eV. Photoluminescence of the implanted MoSe$_2$ reveals an emission line from Cr-related defects that is present only under weak electron doping. Unlike band-to-band transition, the Cr-introduced emission is characterised by non-zero ac

Mikhail Astashenkov

According to Einstein-Maxwell-Dilaton theory, the dilaton field $\psi$ can be produced by electromagnetic fields with non-zero Maxwell invariant. So electromagnetic wave propagating in an external electromagnetic field is a typical source of dilaton radiation. For study dilaton photoproduction in astrophysical conditions it's interesting to consider plane el

Iris Andrussow, Huanbo Sun, Katherine J. Kuchenbecker, Georg Martius

Intelligent interaction with the physical world requires perceptual abilities beyond vision and hearing; vibrant tactile sensing is essential for autonomous robots to dexterously manipulate unfamiliar objects or safely contact humans. Therefore, robotic manipulators need high-resolution touch sensors that are compact, robust, inexpensive, and efficient. The

Philippe Gimenez, Mario González-Sánchez

Let $A=\{a_0,\ldots,a_{n-1}\}$ be a finite set of $n\geq 4$ non-negative relatively prime integers such that $0=a_0<a_1<\cdots<a_{n-1}=d$. The $s$-fold sumset of $A$ is the set $sA$ of integers that contains all the sums of $s$ elements in $A$. On the other hand, given an infinite field $k$, one can associate to $A$ the projective monomial curve $\mathcal{C}

Koustubh Phalak, Swaroop Ghosh

In this paper, we propose shot optimization method for QML models at the expense of minimal impact on model performance. We use classification task as a test case for MNIST and FMNIST datasets using a hybrid quantum-classical QML model. First, we sweep the number of shots for short and full versions of the dataset. We observe that training the full version p

Denis Bernard, Ludwig Hruza

Entanglement properties of driven quantum systems can potentially differ from the equilibrium situation due to long range coherences. We confirm this observation by studying a suitable toy model for mesoscopic transport~: the open quantum symmetric simple exclusion process (QSSEP). We derive exact formulae for its mutual information between different subsyst

Jianheng Liu, Xuanfu Li, Yueqian Liu, Haoyao Chen

Current simultaneous localization and mapping (SLAM) algorithms perform well in static environments but easily fail in dynamic environments. Recent works introduce deep learning-based semantic information to SLAM systems to reduce the influence of dynamic objects. However, it is still challenging to apply a robust localization in dynamic environments for res

Xiaolei Liu, Ming Yi, Kangyi Ding, Bangzhou Xin

Deep learning models are vulnerable to backdoor attacks, where attackers inject malicious behavior through data poisoning and later exploit triggers to manipulate deployed models. To improve the stealth and effectiveness of backdoors, prior studies have introduced various imperceptible attack methods targeting both defense mechanisms and manual inspection. H

Dongliang Zheng, Panagiotis Tsiotras

In this work, we propose the Informed Batch Belief Trees (IBBT) algorithm for motion planning under motion and sensing uncertainties. The original stochastic motion planning problem is divided into a deterministic motion planning problem and a graph search problem. We solve the deterministic planning problem using sampling-based methods such as PRM or RRG to

Alexander Agroskin, Elena Lyulina, Sergey Titov, Vladimir Kovalenko

One of the primary factors that encourage developers to contribute to open source software (OSS) projects is the collaborative nature of OSS development. However, the collaborative structure of these communities largely remains unclear, partly due to the enormous scale of data to be gathered, processed, and analyzed. In this work, we utilize the World Of Cod