November 2024 arXiv papers — page 60

Aaron Zheng, Mansi Rana, Andreas Stolcke

With the recent proliferation of large language models (LLMs), enterprises have been able to rapidly develop proof-of-concepts and prototypes. As a result, there is a growing need to implement robust guardrails that monitor, quantize and control an LLM's behavior, ensuring that the use is reliable, safe, accurate and also aligned with the users' expectations

M. Akramov, C. Trunk, J. Yusupov, D. Matrasulov

We propose an approach to quantize discrete networks (graphs with discrete edges). We introduce a new exact solution of discrete Schrodinger equation that is used to write the solution for quantum graphs. Formulation of the problem and derivation of secular equation for arbitrary quantum graphs is presented. Application of the approach for the star graph is

Gregory W. Moore, Vivek Saxena, Ranveer Kumar Singh

We discuss what topological data must be provided to define topologically twisted partition functions of four-dimensional $\mathcal{N}=2$ supersymmetric field theories. The original example of Donaldson-Witten theory depends only on the diffeomorphism type of the spacetime and 't Hooft fluxes (characteristic classes of background gerbe connections, a.k.a. "o

A. Y. Potekhin, A. I. Chugunov, N. N. Shchechilin, M. E. Gusakov

Thermal radiation of neutron stars in soft X-ray transients (SXTs) in a quiescent state is believed to be powered by the heat deposited in the stellar crust due to nuclear reactions during accretion. Confronting observations of this radiation with simulations helps to verify theoretical models of the dense matter in neutron stars. We simulate the thermal evo

Alessandro Lotto, Alessandro Brighente, Mauro Conti

The increasing integration of modern IT technologies into OT technologies and industrial systems is expanding the vulnerability surface of legacy infrastructures, which often rely on outdated protocols and resource-constrained devices. Recent security incidents in safety-critical industries exposed how the lack of proper message authentication enables attack

Grigorii Churakov

This study presents the development of a part-of-speech (POS) tagging model to extract the skeletal structure of sentences using transfer learning with the BERT architecture for token classification. The model, fine-tuned on Russian text, demonstrating its effectiveness. The approach offers potential applications in enhancing natural language processing task

Yash Gondhalekar, Kana Moriwaki

Parameter inference is a crucial task in modern cosmology that requires accurate and fast computational methods to handle the high precision and volume of observational datasets. In this study, we explore a hybrid vision transformer, the Convolution vision Transformer (CvT), which combines the benefits of vision transformers (ViTs) and convolutional neural n

Maurice de Gosson

Bopp shifts, introduced in 1956, played a pivotal role in the statistical interpretation of quantum mechanics. As demonstrated in our previous work, Bopp's construction provides a phase-space perspective of quantum mechanics that is closely connected to the Moyal star product and its role in deformation quantization. In this paper, we both review and expand

An Wang, Li Zou

We propose a unified framework based on persistent homology (PH) to characterize both local and global structures in disordered systems. It can simultaneously generate local and global descriptors using the same algorithm and data structure, and has shown to be highly effective and interpretable in predicting particle rearrangements and classifying global ph

Guy Gabrieli, Yair Shokef, Izhar Neder

We derive an Ito-Langevin stochastic process that captures the time-dependent deviation from Poisson behavior of the noise detected from a general heterogeneous sub-critical neutron system. Using the probability generating function for the actual physical process, we deduce the super-Poisson deviation of the covariance matrix of counts at the detector due to

Shunhua Jiang, Victor Lecomte, Omri Weinstein, Sorrachai Yingchareonthawornchai

We prove direct-sum theorems for Wilber's two lower bounds [Wilber, FOCS'86] on the cost of access sequences in the binary search tree (BST) model. These bounds are central to the question of dynamic optimality [Sleator and Tarjan, JACM'85]: the Alternation bound is the only bound to have yielded online BST algorithms beating $\log n$ competitive ratio, whil

Junfeng Long, Junli Ren, Moji Shi, Zirui Wang

In contrast to quadruped robots that can navigate diverse terrains using a "blind" policy, humanoid robots require accurate perception for stable locomotion due to their high degrees of freedom and inherently unstable morphology. However, incorporating perceptual signals often introduces additional disturbances to the system, potentially reducing its robustn

Xian-Xian Liu, Mingkun Xu, Yuanyuan Wei, Huafeng Qin

Timely and precise classification and segmentation of gastric bleeding in endoscopic imagery are pivotal for the rapid diagnosis and intervention of gastric complications, which is critical in life-saving medical procedures. Traditional methods grapple with the challenge posed by the indistinguishable intensity values of bleeding tissues adjacent to other ga

Yuanhao Cai, He Zhang, Kai Zhang, Yixun Liang

Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt view direction and mainly handle object-centric cases. In this paper, we propose a novel single-stage 3D diffusion model, DiffusionGS, for object generation and scene reconstructio

P. Rinaldi, N. Bonaventura, G. H. Rieke, S. Alberts

We analyze 99 photometrically selected Little Red Dots (LRDs) at $z \approx 4-8$ in the GOODS fields, leveraging ultra-deep JADES NIRCam short-wavelength (SW) data. We examine the morphology of 30 LRDs, while the remaining 69 appear predominantly compact, with sizes $\leq 400$ pc and no extended components even in stacked SW images. However, their unresolved

Lingying Ma, Gengsheng Wang, Yubiao Zhang

This paper studies the sampling observability for the heat equations with memory in the lower-order term, where the observation is conducted at a finite number of time instants and on a small open subset at each time instant. We present a two-sided sampling observability inequality and give a sharp sufficient condition to ensure the aforementioned inequality

Yucheng Tang, Xi Huang, Yongzhou Zhang, Tao Chen

This paper presents ETA-IK, a novel Execution-Time-Aware Inverse Kinematics method tailored for dual-arm robotic systems. The primary goal is to optimize motion execution time by leveraging the redundancy of both arms, specifically in tasks where only the relative pose of the robots is constrained, such as dual-arm scanning of unknown objects. Unlike traditi

Gerasimos Kouniatalis, Emmanuel N. Saridakis

We use Weyl connection and Weyl geometry in order to construct novel modified gravitational theories. In the simplest case where one uses only the Weyl-connection Ricci scalar as a Lagrangian, the theory recovers general relativity. However, by upgrading the Weyl field to a dynamical field with a general potential and/or general couplings constructed from it

Ivan Cheltsov, Yuri Tschinkel, Zhijia Zhang

We study rationality properties of real singular cubic threefolds.

Xin-Yang Liu, Meet Hemant Parikh, Xiantao Fan, Pan Du

Eddy-resolving turbulence simulations require stochastic inflow conditions that accurately replicate the complex, multi-scale structures of turbulence. Traditional recycling-based methods rely on computationally expensive precursor simulations, while existing synthetic inflow generators often fail to reproduce realistic coherent structures of turbulence. Rec

Marco Marinucci, Gabriel Jung, Michele Liguori, Andrea Ravenni

The marked power spectrum - a two-point correlation function of a transformed density field - has emerged as a promising tool for extracting cosmological information from the large-scale structure of the Universe. In this work, we present the first comprehensive analytical study of the marked power spectrum's sensitivity to primordial non-Gaussianity (PNG) o

Connor Mooney, Ovidiu Savin

Lawson and Osserman proved that the Dirichlet problem for the minimal surface system is not always solvable in the class of Lipschitz maps. However, it is known that minimizing sequences (for area) of Lipschitz graphs converge to objects called Cartesian currents. Essentially nothing is known about these limits. We show that such limits can have surprisingly

Paolo Burgio, Angelo Ferrando, Marco Villani

In the realm of autonomous driving, the development and integration of highly complex and heterogeneous systems are standard practice. Modern vehicles are not monolithic systems; instead, they are composed of diverse hardware components, each running its own software systems. An autonomous vehicle comprises numerous independent components, often developed by

Rong Gu

Most reinforcement learning (RL) platforms use high-level programming languages, such as OpenAI Gymnasium using Python. These frameworks provide various API and benchmarks for testing RL algorithms in different domains, such as autonomous driving (AD) and robotics. These platforms often emphasise the design of RL algorithms and the training performance but n

Jan Gruteser, Jan Roßbach, Fabian Vu, Michael Leuschel

The certification of autonomous systems is an important concern in science and industry. The KI-LOK project explores new methods for certifying and safely integrating AI components into autonomous trains. We pursued a two-layered approach: (1) ensuring the safety of the steering system by formal analysis using the B method, and (2) improving the reliability

Sylvain Raïs, Julien Brunel, David Doose, Frédéric Herbreteau

Robotic systems are widely used to interact with humans or to perform critical tasks. As a result, it is imperative to provide guarantees about their behavior. Due to the modularity and complexity of robotic systems, their design and verification are often divided into several layers. However, some system properties can only be investigated by considering mu

Grégoire Boussu, Nikolai Kosmatov, Franck Védrine

Lack of numerical precision in control software -- in particular, related to trajectory computation -- can lead to incorrect results with costly or even catastrophic consequences. Various tools have been proposed to analyze the precision of program computations. This paper presents a case study on numerical analysis of an industrial implementation of the fas

Till Schnittka, Mario Gleirscher

When designing correct-by-construction controllers for autonomous collectives, three key challenges are the task specification, the modelling, and its use at practical scale. In this paper, we focus on a simple yet useful abstraction for high-level controller synthesis for robot collectives with optimisation goals (e.g., maximum cleanliness, minimum energy c

Luz A. Alvarez, Diego F. de Bernardini, Christophe Gallesco

Model Predictive Control (MPC) is a popular technology to operate industrial systems. It refers to a class of control algorithms that use an explicit model of the system to obtain the control action by minimizing a cost function. At each time step, MPC solves an optimization problem that minimizes the future deviation of the outputs which are calculated from

Yvonne Murray, Henrik Nordlie, David A. Anisi, Pedro Ribeiro

This paper describes use of model checking to verify synchronisation properties of an industrial welding system consisting of a cobot arm and an external turntable. The robots must move synchronously, but sometimes get out of synchronisation, giving rise to unsatisfactory weld qualities in problem areas, such as around corners. These mistakes are costly, sin

Andrea Gatti, Viviana Mascardi, Angelo Ferrando

Chatbots have become integral to various application domains, including those with safety-critical considerations. As a result, there is a pressing need for methods that ensure chatbots consistently adhere to expected, safe behaviours. In this paper, we introduce RV4Chatbot, a Runtime Verification framework designed to monitor deviations in chatbot behaviour

Maryam Ghaffari Saadat, Angelo Ferrando, Louise A. Dennis, Michael Fisher

Formal verification of robotic applications presents challenges due to their hybrid nature and distributed architecture. This paper introduces ROSMonitoring 2.0, an extension of ROSMonitoring designed to facilitate the monitoring of both topics and services while considering the order in which messages are published and received. The framework has been enhan

ALICE Collaboration

In this letter, we present the first measurement of direct photons at the transverse momentum of $ 1 < p_{\rm T} < 6$ GeV/$c$ at midrapidity $|\eta| < 0.8$ in inelastic and high-multiplicity proton--proton collisions at a centre-of-mass energy of $\sqrt{s} =$ 13 TeV. The fraction of virtual direct photons in the inclusive virtual photon spectrum is obtained

Pedro Mendes, Ricardo Correia, Renato Neves, José Proença

The design and analysis of systems that combine computational behaviour with physical processes' continuous dynamics - such as movement, velocity, and voltage - is a famous, challenging task. Several theoretical results from programming theory emerged in the last decades to tackle the issue; some of which are the basis of a proof-of-concept tool, called Linc

Vladislav Taranchuk

In this short note, we provide a new infinite family of $K_{2, t+1}$-free graphs for each prime power $t$. Using these graphs, we show that it is possible to partition the edges of $K_n$ into parts, such that each part is isomorphic to our $K_{2, t+1}$-free graph. This yields an improved lower bound to the multicolor Ramsey number $r_k(K_{2, t+1})$ when $k$

Yating Zhang, Narayanan Menon

We report measurements of the mean settling velocities for suspensions of discs and rods in the stokes regime for a number of particle aspect ratios. All these shapes display ''hindered settling'', namely, a decrease in settling speed as the solid volume fraction is increased. A comparison of our data to spheres reveals that discs and rods show less hinderin

Noémie. C. Combe

The purpose of this article is to show that flat compact K\"ahler manifolds exhibit the structure of a Frobenius manifold, a structure originating in 2D Topological Quantum Field Theory and closely related to Joyce structure. As a result, we classify all such manifolds. It can be deduced that K\"ahler--Frobenius manifolds include certain Calabi--Yau manifold

Arpon Basu, Jun-Ting Hsieh, Pravesh K. Kothari, Andrew D. Lin

We prove that for every odd $q\geq 3$, any $q$-query binary, possibly non-linear locally decodable code ($q$-LDC) $E:\{\pm1\}^k \rightarrow \{\pm1\}^n$ must satisfy $k \leq \tilde{O}(n^{1-2/q})$. For even $q$, this bound was established in a sequence of prior works. For $q=3$, the above bound was achieved in a recent work of Alrabiah, Guruswami, Kothari and

Jie Ma, Pinjun Zheng, Xing Liu, Yuchen Zhang

Low Earth orbit (LEO) satellites, as a prominent technology in the 6G non-terrestrial network, offer both positioning and communication capabilities. While these two applications have each been extensively studied and have achieved substantial progress in recent years, the potential synergistic benefits of integrating them remain an underexplored yet promisi

Leonard Logaric, John Goold, Shane Dooley

Ergodicity has been one of the fundamental concepts underpinning our understanding of thermalization in isolated systems since the first developments in classical statistical mechanics. Recently, a similar notion has been introduced for quantum systems, termed complete Hilbert space ergodicity (CHSE), in which the evolving quantum state explores all of the a

Marziyeh Bamdad, Hans-Peter Hutter, Alireza Darvishy

Simultaneous localization and mapping (SLAM) techniques can be used to navigate the visually impaired, but the development of robust SLAM solutions for crowded spaces is limited by the lack of realistic datasets. To address this, we introduce InCrowd-VI, a novel visual-inertial dataset specifically designed for human navigation in indoor pedestrian-rich envi

Jun Xiang, Jun Chen

Identifying the obstacle space is crucial for path planning. However, generating an accurate obstacle space remains a significant challenge due to various sources of uncertainty, including motion, behavior, and perception limitations. Even though an autonomous system can operate with an inaccurate obstacle space by being over-conservative and using redundant

PandaX Collaboration, Zihao Bo, Wei Chen, Xun Chen

Detailed studies of two-neutrino double electron capture (2$\nu$DEC) is a crucial step towards searching for the neutrino-less mode to explore the Majorana nature of neutrinos. We have measured precisely the half-life of the 2$\nu$DEC process in $^{124}$Xe, utilizing a total exposure of 1.73 tonne$\cdot$year from the commissioning run and the first science r

Esther Rolf, Lucia Gordon, Milind Tambe, Andrew Davies

While advances in machine learning with satellite imagery (SatML) are facilitating environmental monitoring at a global scale, developing SatML models that are accurate and useful for local regions remains critical to understanding and acting on an ever-changing planet. As increasing attention and resources are being devoted to training SatML models with glo

Houze Liu, Tong Zhou, Yanlin Xiang, Aoran Shen

Medical image segmentation is crucial for accurate clinical diagnoses, yet it faces challenges such as low contrast between lesions and normal tissues, unclear boundaries, and high variability across patients. Deep learning has improved segmentation accuracy and efficiency, but it still relies heavily on expert annotations and struggles with the complexities

Mateus Marra, Pedro Morelli, Daniel Smania

We define distributions on an abstract measure space endowed with a sequence of partitions, and introduce analogues of Besov spaces with negative smoothness in this setting. In particular, we describe these spaces of distributions using unconditional Schauder bases consisting either of Haar wavelets or of pairs of Dirac masses (dipoles). This framework allow

William N. Caballero, Matthew LaRosa, Alexander Fisher, Vahid Tarokh

The multivariate Gaussian distribution underpins myriad operations-research, decision-analytic, and machine-learning models (e.g., Bayesian optimization, Gaussian influence diagrams, and variational autoencoders). However, despite recent advances in adversarial machine learning (AML), inference for Gaussian models in the presence of an adversary is notably u

Luzie Kupffer, Mahan Mj, Chiranjib Mukherjee

Motivated by Gromov's geodesic flow problem on hyperbolic groups $G$, we develop in this paper an analog using random walks. This leads to a notion of a harmonic analog $\Theta$ of the Bowen-Margulis-Sullivan measure on $\partial^2 G$. We provide three different but related constructions of $\Theta$: 1) by moving the base-point along a quasigeodesic ray 2) b

Anxin Guo, Aravindan Vijayaraghavan

We consider the problem of learning an arbitrarily-biased ReLU activation (or neuron) over Gaussian marginals with the squared loss objective. Despite the ReLU neuron being the basic building block of modern neural networks, we still do not understand the basic algorithmic question of whether one arbitrary ReLU neuron is learnable in the non-realizable setti

Markku Oksanen, Nico Stirling, Anca Tureanu

We propose a theory for neutrino oscillations, in which the flavour neutrinos are treated as waves of massless particles propagating in a "refractive quantum vacuum" and obeying a relativistically covariant equation of motion. The difference in strength between weak interactions and mass-generating interactions is argued to allow for the production and detec

Tianhe Ren, Yihao Chen, Qing Jiang, Zhaoyang Zeng

In this paper, we introduce DINO-X, which is a unified object-centric vision model developed by IDEA Research with the best open-world object detection performance to date. DINO-X employs the same Transformer-based encoder-decoder architecture as Grounding DINO 1.5 to pursue an object-level representation for open-world object understanding. To make long-tai

Edgar Mauricio Salazar Duque, Bart van der Holst, Pedro P. Vergara, Juan S. Giraldo

This paper presents the spherical lower dimensional representation for daily medium voltage load profiles, based on principal component analysis. The objective is to unify and simplify the tasks for (i) clustering visualisation, (ii) outlier detection and (iii) generative profile modelling under one concept. The lower dimensional projection of standardised l

Leandro Giusti Mugnaini, Carolina Tavares Duarte, Anna H. Reali Costa, Artur Jordao

Layer pruning offers a promising alternative to standard structured pruning, effectively reducing computational costs, latency, and memory footprint. While notable layer-pruning approaches aim to detect unimportant layers for removal, they often rely on single criteria that may not fully capture the complex, underlying properties of layers. We propose a nove

Pravesh K. Kothari, Ankur Moitra, Alexander S. Wein

Motivated by connections between algebraic complexity lower bounds and tensor decompositions, we investigate Koszul-Young flattenings, which are the main ingredient in recent lower bounds for matrix multiplication. Based on this tool we give a new algorithm for decomposing an $n_1 \times n_2 \times n_3$ tensor as the sum of a minimal number of rank-1 terms,

Bethel Melesse Tessema, Akhil Kedia, Tae-Sun Chung

Large language models (LLMs) under-perform on low-resource languages due to limited training data. We present a method to efficiently collect text data for low-resource languages from the entire Common Crawl corpus. Our approach, UnifiedCrawl, filters and extracts common crawl using minimal compute resources, yielding mono-lingual datasets much larger than p

Yao Yao, Qihang Lin, Tianbao Yang

This note studies numerical methods for solving compositional optimization problems, where the inner function is smooth, and the outer function is Lipschitz continuous, non-smooth, and non-convex but exhibits one of two special structures that enable the design of efficient first-order methods. In the first structure, the outer function allows for an easily

Andrew Lesniewski, Giulio Trigila

We propose a highly efficient and accurate methodology for generating synthetic financial market data using a diffusion model approach. The synthetic data produced by our methodology align closely with observed market data in several key aspects: (i) they pass the two-sample Cramer - von Mises test for portfolios of assets, and (ii) Q - Q plots demonstrate c

Ojash Neopane, Aaditya Ramdas, Aarti Singh

Estimation of the Average Treatment Effect (ATE) is a core problem in causal inference with strong connections to Off-Policy Evaluation in Reinforcement Learning. This paper considers the problem of adaptively selecting the treatment allocation probability in order to improve estimation of the ATE. The majority of prior work on adaptive ATE estimation focus

Jean Lagacé, Stephen Lynch

We introduce a new curvature condition for high-codimension submanifolds of a Riemannian ambient space, called quasi-parallel mean curvature (QPMC). The class of submanifolds with QPMC includes all CMC hypersurfaces and submanifolds with parallel mean curvature. We use our notion of QPMC to prove that certain kinds of high-curvature regions which appear in g

Hibiki Gyotoku, Tsuyoshi Yuno, Yoshio Ebihara, Victor Magron

This study investigates the absolute stability criteria based on the framework of integral quadratic constraint (IQC) for feedback systems with slope-restricted nonlinearities. In existing works, well-known absolute stability certificates expressed in the IQC-based linear matrix inequalities (LMIs) were derived, in which the input-to-output characteristics o

Delilah E. A. Gates, Chau Truong, Amrita Sahu, Alejandro Cárdenas-Avendaño

Single-frequency emission from an accretion disk around a black hole is broadened into a line profile due to gravitational redshift and the motion of the disk's particles relative to the observer. The ensemble of relativistically broadened emission frequencies from the disk elements forms the spectrum viewed by an observer. Over the past decades, the broaden

Rachid Nouicer

Recent results on the identified charged-hadron ($\pi^\pm$, $K^\pm$, $p$, $\bar{p}$) production at midrapidity region ($|\eta|<$ 0.35) have been measured by the PHENIX experiment in ${\rm {\it p}+Al}$, ${\rm ^{3}He+Au}$, ${\rm Cu+Au}$ collisions at $\sqrt{s_{_{NN} }}$ = 200 GeV and ${\rm U+U}$ collisions at $\sqrt{s_{_{NN} }}$ = 193 GeV. These measurements a

Anna Brandenberger, Cassandra Marcussen, Elchanan Mossel, Madhu Sudan

We study the inference of network archaeology in growing random geometric graphs. We consider the root finding problem for a random nearest neighbor tree in dimension $d \in \mathbb{N}$, generated by sequentially embedding vertices uniformly at random in the $d$-dimensional torus and connecting each new vertex to the nearest existing vertex. More precisely,

Zih-En Tseng, Yue Wu, Dimitris Menemenlis, Guangyao Wang

We develop a 3D Eulerian model to study the transport and distribution of microplastics in the global ocean. Among other benefits that will be discussed in the paper, one unique feature of our model is that it takes into consideration the effect of properties of particles (size and density, the former for the first time) to their vertical terminal velocity.

Fenna Müller, Max von Renesse, Johannes Zimmer

We consider systems of interacting particles which are described by a second order Langevin equation. The class of equations considered includes the situation where the particle evolution is governed by Hamiltonian dynamics with additional damping and noise satisfying a fluctuation-dissipation relation. Also covered are systems of two equations describing an

Faezeh Nassajian Mojarrad

Stochastic diffusion equations are crucial for modeling a range of physical phenomena influenced by uncertainties. We introduce the generalized finite difference method for solving these equations. Then, we examine its consistency, stability and convergence in mean-square, showing that the proposed method preserves stability and demonstrates favorable conver

Ruhui Jin, Qin Li, Stephen O. Mussmann, Stephen J. Wright

In computational inverse problems, the optimal experimental design (OED) problem seeks the best locations in time and space at which to take measurements. We investigate the nonlinear OED problem in the context of continuously-indexed design space for the measurements. In contrast to traditional approaches that select experiments from a finite measurement se

Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes

This paper evaluates the suitability of Apache Arrow, Parquet, and ORC as formats for subsumption in an analytical DBMS. We systematically identify and explore the high-level features that are important to support efficient querying in modern OLAP DBMSs and evaluate the ability of each format to support these features. We find that each format has trade-offs

Thomas Gilray, Arash Sahebolamri, Yihao Sun, Sowmith Kunapaneni

Datalog is a popular logic programming language for deductive reasoning tasks in a wide array of applications, including business analytics, program analysis, and ontological reasoning. However, Datalog's restriction to flat facts over atomic constants leads to challenges in working with tree-structured data, such as derivation trees or abstract syntax trees

H. -X. Zeng, Q. -L. Zhao, P. -M. Zhang, P. A. Horvathy

The particle with first-order dynamics proposed by Dunne, Jackiw and Trugenberger (DJT) to justify the ``Peierls substitution" is obtained by reduction from both of the planar two-parameter centrally extended Galilean and Carroll systems. In the latter case the extension parameters $\kappa_{exo}$ and $\kappa_{mag}$ generate non-commutativity of the coordinat

A Niveth, S Karthiga, M Senthilvelan

This article studies a non-Hermitian Su-Schrieffer-Heeger (SSH) model which has periodically staggered Hermitian and non-Hermitian dimers. The changes in topological phases of the considered chiral symmetric model with respect to the introduced non-Hermiticity are studied where we find that the system supports only complex eigenspectra for all values of $u \

E. Vitte, A. Verhamme, P. Hibon, F. Leclercq

The Hydrogen Lyman-alpha (Lya) line shows a large variety of shapes which is caused by factors at different scales, from the interstellar medium to the intergalactic medium. This work aims to provide a systematic inventory and classification of the spectral shapes of Lya emission lines to understand the general population of high-redshift Lya emitting galaxi

Evangelos Papapetros

We prove that if the unital $C^*$-algebras $\cl A$ and $\cl B$ satisfy Kadison's similarity property and the length $L=L\left(\cl A\tens\limits_{max}\cl B\right)$ of their maximal tensor product is finite, then $\cl A\tens\limits_{max}\cl \cl B$ satisfies Kadison's similarity property with similarity length $\ell\left(\cl A\tens\limits_{max}\cl B\right)\leq

Gautam Venugopalan, Giorgio Gratta

Microscopic devices are widely used in optomechanical experiments at the cutting-edge of precision experimental physics. Such devices often need to have high electrical conductivity but low reflectivity at optical wavelengths, which can be competing requirements for many commonly available coatings. In this manuscript, we present a technique to electroplate

Rebecca K. Metcalfe, Antonio Remiro-Azócar, Quang Vuong, Anders Gorst-Rasmussen

The ICH E9(R1) addendum provides guidelines on accounting for intercurrent events in clinical trials using the estimands framework. However, there has been limited attention to the estimands framework for meta-analysis. Using treatment switching, a well-known intercurrent event that occurs frequently in oncology, we conducted a simulation study to explore th

Arjun P S, Andrew Melnik, Gora Chand Nandi

Experience Goal Visual Rearrangement task stands as a foundational challenge within Embodied AI, requiring an agent to construct a robust world model that accurately captures the goal state. The agent uses this world model to restore a shuffled scene to its original configuration, making an accurate representation of the world essential for successfully comp

Feihan Li, Abulikemu Abuduweili, Yifan Sun, Rui Chen

The control of legged robots, particularly humanoid and quadruped robots, presents significant challenges due to their high-dimensional and nonlinear dynamics. While linear systems can be effectively controlled using methods like Model Predictive Control (MPC), the control of nonlinear systems remains complex. One promising solution is the Koopman Operator,

Moritz Wedemeyer, Eike Cramer, Alexander Mitsos, Manuel Dahmen

Time-series information needs to be incorporated into energy system optimization to account for the uncertainty of renewable energy sources. Typically, time-series aggregation methods are used to reduce historical data to a few representative scenarios but they may neglect extreme scenarios, which disproportionally drive the costs in energy system design. We

Radhe S. T. Saini, Parth R. Brahmbhatt, Styliani Avraamidou, Hari S. Ganesh

Cooperative Distributed Model Predictive Control (DiMPC) architecture employs local MPC controllers to control different subsystems, exchanging information with each other through an iterative procedure to enhance overall control performance compared to the decentralized architecture. However, this method can result in high communication between the controll

Zheheng Luo, Xin Zhang, Xiao Liu, Haoling Li

It is well-known that a diverse corpus is critical for training large language models, which are typically constructed from a mixture of various domains. In general, previous efforts resort to sampling training data from different domains with static proportions, as well as adjusting data proportions during training. However, few methods have addressed the c

Nicholas M. Boffi, Eric Vanden-Eijnden

Active systems comprise a class of nonequilibrium dynamics in which individual components autonomously dissipate energy. Efforts towards understanding the role played by activity have centered on computation of the entropy production rate (EPR), which quantifies the breakdown of time reversal symmetry. A fundamental difficulty in this program is that high di

Ulisse Stefanelli, Andreas Vikelis

We investigate finite-strain elastoplastic evolution in the nonassociative setting. The constitutive material model is formulated in variational terms and coupled with the quasistatic equilibrium system. We introduce measure-valued energetic solutions and prove their existence via a time discretization approach. The existence theory hinges on a suitable regu

Dongjie Jia, Mahdi Esmaily

The adoption of cardiovascular simulations for diagnosis and surgical planning on a patient-specific basis requires the development of faster methods than the existing state-of-the-art techniques. To address this need, we leverage the periodic nature of these flows to accurately capture their time-dependence using spectral discretization. Owing to the reduce

Jeff Xu

In this work, we give novel spectral norm bounds for graph matrix on inputs being random regular graphs. Graph matrix is a family of random matrices with entries given by polynomial functions of the underlying input. These matrices have been known to be the backbone for the analysis of various average-case algorithms and hardness. Previous investigations of

Antoine Laudrain, Ties Behnke, Carl Mikael Berggren, Karsten Buesser

The Hybrid Asymmetric Linear Higgs Factory (HALHF) proposes a shorter and cheaper design for a future Higgs factory. It reaches a $\sqrt{s} = 250$ GeV using a 500 GeV electron beam accelerated by an electron-driven plasma wake-field, and a conventionally-accelerated 31 GeV positron beam. Assuming plasma acceleration R&D challenges are solved in a timely mann

Kostiantyn Drach, Leon Staresinic, Sebastian van Strien

Assume that the interval $I=[0,1)$ is partitioned into finitely many intervals $I_1,\dots,I_r$ and consider a map $T\colon I\to I$ so that $T_{\vert I_s}$ is a translation for each $1 \le s \le r$. We do not assume that the images of these intervals are disjoint. Such maps are called Interval Translation Maps. Let $ITM(r)$ be the space of all such transforma

Igor Mol

We propose a generalisation of the Wess-Zumino-Novikov-Witten (WZNW) model, formulated on a holomorphic extension of supersymmetric three-dimensional Anti-de Sitter $\left(AdS_{3}\right)$ space, which holographically reproduces the tree-level maximally-helicity-violating (MHV) celestial amplitudes for gravitons in $\mathcal{N}=8$ supergravity and gluons in f

B. H. C. Emonts, P. N. Appleton, U. Lisenfeld, P. Guillard

We present the large-scale distribution and kinematics of cold molecular gas across the compact galaxy group Stephan's Quintet, based on CO(2-1) observations performed with the Atacama Compact Array (ACA) and CO(1-0) data from the Combined Array for Research in Millimeter-wave Astronomy (CARMA). We find coherent structures of molecular gas associated with th

Michael J. Probst, Arjun Khurana, Archana Kaushalram, Stephen E. Ralph

Waveguide tapers are critical components for leveraging the benefits of both single-mode and wide waveguides. Adiabatic tapers are typically hundreds of microns in length, dramatically limiting density and scalability. We reenvision the taper design process in an inverse-design paradigm, introducing the novel L-taper. We present a novel approach to inverse-d

Zhi-Wei Sun

In this paper we establish some new results similar to Lagrange's four-square theorem. For example, we prove that any integer $n>1$ can be written as $w(5w+1)/2+x(5x+1)/2+y(5y+1)/2+z(5z+1)/2$ with $w,x,y,z\in\mathbb Z$. Let $a$ and $b$ be integers with $a>0$, $b>-a$ and $\gcd(a,b)=1$. When $2\nmid ab$, we show that any sufficiently large integer can be writt

Gregor Janson, Richard Lopp

Recent proposals suggested quantum clock interferometry for tests of the Einstein equivalence principle. However, atom interferometric models often include relativistic effects only in an ad hoc fashion. Here, instead, we start from the multi-particle nature of quantum-delocalizable atoms in curved spacetime and generalize the special-relativistic center of

Nora Brambilla, Abhishek Mohapatra, Tommaso Scirpa, Antonio Vairo

Two decades ago the $\chi_{c1}\left(3872\right)$ was discovered in the hadron spectrum with two heavy quarks. The discovery fueled a surge in experimental research, uncovering dozens of so called XYZ exotics states lying outside the conventional quark model, as well as theoretical investigations into new forms of matter, such as quark-gluon hybrids, tetraqua

Hongjie Chen, Deepak Narayanan Sridharan, David Steurer

We revisit the problem of estimating the mean of a high-dimensional distribution in the presence of an $\varepsilon$-fraction of adversarial outliers. When $\varepsilon$ is at most some sufficiently small constant, previous works can achieve optimal error rate efficiently \cite{diakonikolas2018robustly, kothari2018robust}. As $\varepsilon$ approaches the bre

Mariana O. Monteiro, Nadja K. Bernardes, Eugene M. Broni, Francisco A. B. F. de Moura

Manipulating the dynamics of open quantum systems is a crucial requirement for large-scale quantum computers. Finding ways to overcome or extend decoherence times is a challenging task. Already at the level of a single two-level atom, its reduced dynamics with respect to a larger environment can be very complex. Structured environments, for instance, can lea

Victor-Alexandru Pădurean, Paul Denny, Adish Singla

Debugging is an essential skill when learning to program, yet its instruction and emphasis often vary widely across introductory courses. In the era of code-generating large language models (LLMs), the ability for students to reason about code and identify errors is increasingly important. However, students frequently resort to trial-and-error methods to res

Seong-Ho Shinn, Adolfo del Campo

In two spatial dimensions, vortex-vortex interactions approximately vary with the logarithm of the inter-vortex distance, making it possible to describe an ensemble of vortices as a Coulomb gas. We introduce a duality between vortices in a quasi-two-dimensional (quasi-2D) scalar Bose-Einstein condensates (BEC) and effective Maxwell's electrodynamics. Specifi

Florian Ahrens, Dawn Geatches, Niall McCarroll, Justin Buck

The UK Research and Innovation Digital Research Infrastructure (DRI) needs to operate sustainably in the future, encompassing its use of energy and resources, and embedded computer hardware carbon emissions. Transition concepts towards less unsustainable operations will inform the future design and operations of DRI. A problem remains that, while the skills

Thomas Blum, William I. Jay, Luchang Jin, Andreas S . Kronfeld

Inclusive hadronic observables are ubiquitous in particle and nuclear physics. Computation of these observables using lattice QCD is challenging due the presence of a difficult inverse problem. As a stepping stone to more complicated observables, we report on progress to compute the smeared $R$~ratio with staggered quarks using the spectral reconstruction al

Marliadi Susanto, Nadihah Wahi, Adem Kilicman

This study is a modification of the McKendrick equation into a growth model with fractional order to predict the abalone length growth. We have shown that the model is a special case of Taylor's series after it was analysed using Adomian decomposition method and Caputo fractional derivative. By simulating the series with some fractional orders, the results i

Jitendra Bhandari, Vineet Bhat, Yuheng He, Hamed Rahmani

Masala-CHAI is a fully automated framework leveraging large language models (LLMs) to generate Simulation Programs with Integrated Circuit Emphasis (SPICE) netlists. It addresses a long-standing challenge in circuit design automation: automating netlist generation for analog circuits. Automating this workflow could accelerate the creation of fine-tuned LLMs