March 2024 arXiv papers — page 56

Taylor Allred, Xinyi Li, Ashton Wiersdorf, Ben Greenman

Reliable numerical computations are central to scientific computing, but the floating-point arithmetic that enables large-scale models is error-prone. Numeric exceptions are a common occurrence and can propagate through code, leading to flawed results. This paper presents FlowFPX, a toolkit for systematically debugging floating-point exceptions by recording

J. Zak, A. Bocchieri, E. Sedaghati, H. M. J. Boffin

One can infer the orbital alignment of exoplanets with respect to the spin of their host stars using the Rossiter-McLaughlin effect, thereby giving us the chance to test planet formation and migration theories and improve our understanding of the currently observed population. We analyze archival HARPS and HARPS-N spectroscopic transit time series of six gas

Mohammad Al-Jarrah, Bamdad Hosseini, Amirhossein Taghvaei

The nonlinear filtering problem is concerned with finding the conditional probability distribution (posterior) of the state of a stochastic dynamical system, given a history of partial and noisy observations. This paper presents a data-driven nonlinear filtering algorithm for the case when the state and observation processes are stationary. The posterior is

Bernhard Fickl, Teresa M. Seifried, Erwin Rait, Jakob Genser

Control of water ice formation on surfaces is of key technological and economic importance, but the fundamental understanding of ice nucleation and growth mechanisms and the design of surfaces for controlling water freezing behaviour remain incomplete. Graphene is a two-dimensional (2D) material that has been extensively studied for its peculiar wetting prop

Youssef Azouzi, Marwa Masmoudi, Bruce Alastair Watson

Recently the Kac formula for the conditional expectation of the first recurrence time of a conditionally ergodic conditional expectation preserving system was established in the measure free setting of vector lattices (Riesz spaces). We now give a formulation of the Kakutani-Rokhlin decomposition for conditionally ergodic systems in terms of components of we

Chang Qian, Ethan Stanifer, Zhan Ma, Binbin Luo

Topologically-engineered mechanical frames are important model constructs for architecture, machine mechanisms, and metamaterials. Despite significant advances in macroscopically fashioned frames, realization and phonon imaging of nanoframes have remained challenging. Here we extend for the first time the principles of topologically-engineered mechanical fra

Eduardo Figueiredo, Andrea Patane, Morteza Lahijanian, Luca Laurenti

Uncertainty propagation in non-linear dynamical systems has become a key problem in various fields including control theory and machine learning. In this work we focus on discrete-time non-linear stochastic dynamical systems. We present a novel approach to approximate the distribution of the system over a given finite time horizon with a mixture of distribut

Pavel Stishenko, Adam McSloy, Berk Onat, Ben Hourahine

Modern software engineering of electronic structure codes has seen a paradigm shift from monolithic workflows towards object-based modularity. Software objectivity allows for greater flexibility in the application of electronic structure calculations, with particular benefits when integrated with approaches for data-driven analysis. Here, we discuss differen

Marcin Kolakowski

Bluetooth Low Energy systems are one of the most popular solutions used for indoor localization. Unfortunately their accuracy might not be sufficient for some of the applications. One way to reduce localization errors is hybrid positioning, which combines measurement results obtained with different techniques. The paper describes a concept of a hybrid locali

Jun Guo, Xiaojian Ma, Yue Fan, Huaping Liu

Open-vocabulary 3D scene understanding presents a significant challenge in computer vision, with wide-ranging applications in embodied agents and augmented reality systems. Existing methods adopt neurel rendering methods as 3D representations and jointly optimize color and semantic features to achieve rendering and scene understanding simultaneously. In this

Santhini K. A., Kamesh Munagala, Meghana Nasre, Govind S. Sankar

We consider the problem of assigning students to schools, when students have different utilities for schools and schools have capacity. There are additional group fairness considerations over students that can be captured either by concave objectives, or additional constraints on the groups. We present approximation algorithms for this problem via convex pro

Apoorv Singh, Gaurav Raut, Alka Choudhary

Collaborative perception in multi-robot fleets is a way to incorporate the power of unity in robotic fleets. Collaborative perception refers to the collective ability of multiple entities or agents to share and integrate their sensory information for a more comprehensive understanding of their environment. In other words, it involves the collaboration and fu

Bingran Wang, Nicholas C. Orndorff, Mark Sperry, John T. Hwang

The univariate dimension reduction (UDR) method stands as a way to estimate the statistical moments of the output that is effective in a large class of uncertainty quantification (UQ) problems. UDR's fundamental strategy is to approximate the original function using univariate functions so that the UQ cost only scales linearly with the dimension of the probl

Logan E. Beaver

In this article we address the multi-robot task allocation problem, where robots must cooperatively assign themselves to accomplish a set of tasks. We consider the colony maintenance problem as an example, where a team of robots are tasked with continuously maintaining the energy supply of a central colony. We model this as a global game, where each robot me

Guangwen Chen, George J. Bendo, Gary A. Fuller, Hong-Xin Zhang

We analyse the radio-to-submillimetre spectral energy distribution (SED) for the central pseudobulge of NGC~1365 using archival data from the Atacama Large Millimeter/submillimeter Array (ALMA) and the Very Large Array (VLA). This analysis shows that free-free emission dominates the continuum emission at 50--120~GHz and produces about 75 per cent of the 103~

C. Robertson, B. Holwerda, J. Young, W. Keel

The Balmer decrement (H$\alpha$/H$\beta$) provides a constraint on attenuation, the cumulative effects of dust grains in the ISM. The ratio is a reliable spectroscopic tool for deriving the dust properties of galaxies that determine many different quantities such as star formation rate, metallicity, and SED models. Here we measure independently both the atte

Cristian Ciulică, Alexandra Otiman, Miron Stanciu

We investigate the metric and cohomological properties of higher dimensional analogues of Inoue surfaces, that were introduced by Endo and Pajitnov. We provide a solvmanifold structure and show that in the diagonalizable case, they are formal and have invariant de Rham cohomology. Moreover, we obtain an arithmetic and cohomological characterization of pluric

Daniel C. May, Petr Musilek

ALEX (Autonomous Local Energy eXchange) is an economy-driven, transactive local energy market where each participating building is represented by a rational agent. Relying solely on building-level information, this agent minimizes its electricity bill by automating distributed energy resource utilization and trading. This study examines ALEX's capabilities t

Jiayi Li, Matthew Motoki, Baosen Zhang

Bringing fairness to energy resource allocation remains a challenge, due to the complexity of system structures and economic interdependencies among users and system operators' decision-making. The rise of distributed energy resources has introduced more diverse heterogeneous user groups, surpassing the capabilities of traditional efficiency-oriented allocat

Gus Cooney, Andrew Reece

Conversation is a subject of increasing interest in the social, cognitive, and computational sciences. Yet as conversational datasets continue to increase in size and complexity, researchers lack scalable methods to segment speech-to-text transcripts into conversational "turns"-the basic building blocks of social interaction. We discuss this challenge and th

Marcin Kolakowski, Bartosz Blachucki

With the aging of our populations, dementia will become a problem which would directly or indirectly affect a large number of people. One of the most dangerous dementia symptoms is wandering. It consists in aimless walking and spatial disorientation, which might lead to various unpleasant situations like falling down accidents at home to leaving the living p

Bingran Wang, Nicholas C. Orndorff, John T. Hwang

Recently, the graph-accelerated non-intrusive polynomial chaos (NIPC) method has been proposed for solving uncertainty quantification (UQ) problems. This method leverages the full-grid integration-based NIPC method to address UQ problems while employing the computational graph transformation approach, AMTC, to accelerate the tensor-grid evaluations. This met

Ricardo J. Alonso, Pierre Gervais, Bertrand Lods

We introduce a practical criterion that justifies the propagation and appearance of $L^{p}$-norms for the solutions to the spatially homogeneous Boltzmann equation with very soft potentials without cutoff. Such criterion also provides a new conditional stability result for classical solutions to the equation. All results are quantitative. Our approach is ins

Sisi Dai, Wenhao Li, Haowen Sun, Haibin Huang

In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner. We identify and address two key challenges: the unsatisfactory outcomes of direct text-to-3D methods in HOI, largely due to the lack of paired text-interaction data, and the inherent difficulties in simultaneo

Yuqing Zhu, Ziyi Song, Rodrigo Becerra Silva, Bob Minyu Wang

We investigate the circular photogalvanic effect (CPGE) in single-crystalline methylammonium lead iodide microcrystals under a static electric field. The external electric field can enhance the magnitude of the helicity dependent photocurrent (HDPC) by two orders of magnitude and flip its sign, which we attribute to magnetic shift currents induced by the Ras

William Clark, Maria Oprea

Optimal control is ubiquitous in many fields of engineering. A common technique to find candidate solutions is via Pontryagin's maximum principle. An unfortunate aspect of this method is that the dimension of system doubles. When the system evolves on a Lie group and the system is invariant under left (or right) translations, Lie-Poisson reduction can be app

Cosmin Ciausu, Deepa Krishnaswamy, Benjamin Billot, Steve Pieper

Deep learning has shown great promise in the ability to automatically annotate organs in magnetic resonance imaging (MRI) scans, for example, of the brain. However, despite advancements in the field, the ability to accurately segment abdominal organs remains difficult across MR. In part, this may be explained by the much greater variability in image appearan

Elizabeth Sattler

In this paper, we consider subsets of an attractor of an iterated function system in which each point is associated with an allowable word from an $S$-gap shift. The main result shows that bounds for the box dimension and Hausdorff dimension of a subfractal induced by an $S$-gap shift are given by the zeros of the upper and lower topological pressure functio

Enrico Bacis, Igor Bilogrevic, Robert Busa-Fekete, Asanka Herath

Modern Web APIs allow developers to provide extensively customized experiences for website visitors, but the richness of the device information they provide also make them vulnerable to being abused to construct browser fingerprints, device-specific identifiers that enable covert tracking of users even when cookies are disabled. Previous research has establi

Sanghyo Park, Milica Notaros, Aseema Mohanty, Donggyu Kim

Control over the amplitude, phase, and spatial distribution of visible-spectrum light underlies many technologies, but commercial solutions remain bulky, require high control power, and are often too slow. Active integrated photonics for visible light promises a solution, especially with recent materials and fabrication advances. In this review, we discuss t

Khiem Le, Long Ho, Cuong Do, Danh Le-Phuoc

Domain shift is a formidable issue in Machine Learning that causes a model to suffer from performance degradation when tested on unseen domains. Federated Domain Generalization (FedDG) attempts to train a global model using collaborative clients in a privacy-preserving manner that can generalize well to unseen clients possibly with domain shift. However, mos

Ricardo Gonzalez, Jazmin Collins, Shiri Azenkot, Cynthia Bennett

"Scene description" applications that describe visual content in a photo are useful daily tools for blind and low vision (BLV) people. Researchers have studied their use, but they have only explored those that leverage remote sighted assistants; little is known about applications that use AI to generate their descriptions. Thus, to investigate their use case

Zeliang Zhang, Mingqian Feng, Jinyang Jiang, Rongyi Zhu

Gradient-based saliency maps are widely used to explain deep neural network decisions. However, as models become deeper and more black-box, such as in closed-source APIs like ChatGPT, computing gradients become challenging, hindering conventional explanation methods. In this work, we introduce a novel unified framework for estimating gradients in black-box s

Anastasia Halfpap, Bernard Lidický, Tomáš Masařík

We say that an edge-coloring of a graph $G$ is proper if every pair of incident edges receive distinct colors, and is rainbow if no two edges of $G$ receive the same color. Furthermore, given a fixed graph $F$, we say that $G$ is rainbow $F$-saturated if $G$ admits a proper edge-coloring which does not contain any rainbow subgraph isomorphic to $F$, but the

Aashish Ghimire, John Edwards

Emerging technologies like generative AI tools, including ChatGPT, are increasingly utilized in educational settings, offering innovative approaches to learning while simultaneously posing new challenges. This study employs a survey methodology to examine the policy landscape concerning these technologies, drawing insights from 102 high school principals and

Sivana Hamer, Marcelo d'Amorim, Laurie Williams

Sonatype's 2023 report found that 97% of developers and security leads integrate generative Artificial Intelligence (AI), particularly Large Language Models (LLMs), into their development process. Concerns about the security implications of this trend have been raised. Developers are now weighing the benefits and risks of LLMs against other relied-upon infor

Raphael Yuster

For integers $k,n$ with $1 \le k \le n/2$, let $f(k,n)$ be the smallest integer $t$ such that every $t$-connected $n$-vertex graph has a spanning bipartite $k$-connected subgraph. A conjecture of Thomassen asserts that $f(k,n)$ is upper bounded by some function of $k$. The best upper bound for $f(k,n)$ is by Delcourt and Ferber who proved that $f(k,n) \le 10

Jonathan A. Weyn, Divya Kumar, Jeremy Berman, Najeeb Kazmi

We present an operations-ready multi-model ensemble weather forecasting system which uses hybrid data-driven weather prediction models coupled with the European Centre for Medium-range Weather Forecasts (ECMWF) ocean model to predict global weather at 1-degree resolution for 4 weeks of lead time. For predictions of 2-meter temperature, our ensemble on averag

Clément Rieutord, Carlos Gustavo Moreira, Harold Erazo

Let $M$ and $L$ be the Markov and Lagrange spectra, respectively. It is known that $L$ is contained in $M$ and Freiman showed in 1968 that $M\setminus L\neq \emptyset$. In 2018 the first region of $M\setminus L$ above $\sqrt{12}$ was discovered by C. Matheus and C. G. Moreira, thus disproving a conjecture of Cusick of 1975. In 2022, the same authors together

Harish S. Bhat, Hardeep Bassi, Karnamohit Ranka, Christine M. Isborn

For any linear system with unreduced dynamics governed by invertible propagators, we derive a closed, time-delayed, linear system for a reduced-dimensional quantity of interest. This method does not target dimensionality reduction: rather, this method helps shed light on the memory-dependence of $1$-electron reduced density matrices in time-dependent configu

Mauricio Chacón-Tirado, César Piceno

In the literature, various types of points and meager sets whose complements are connected have been studied, such as colocally connected points, non-weak cut points/sets, non-block points/sets, shore points/sets, etc. We extend that study, in the following way: considering a continuum $X$ and a natural number $n$, we investigate sets $A \in 2^X$ meeting the

Md Abrar Jahin, Saleh Akram Naife, Fatema Tuj Johora Lima, M. F. Mridha

Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. This study presents a novel, data-driven analysis of male domestic violence (MDV) in Bangladesh, highlighting the factors that influence it and addressing the challenges posed by a significant categorical imbalance of 5

Sepehr Dehdashtian, Lan Wang, Vishnu Naresh Boddeti

Large pre-trained vision-language models such as CLIP provide compact and general-purpose representations of text and images that are demonstrably effective across multiple downstream zero-shot prediction tasks. However, owing to the nature of their training process, these models have the potential to 1) propagate or amplify societal biases in the training d

Conrad Gstöttner, Bernd Kolar, Markus Schöberl

This paper is devoted to normal forms for x-flat control-affine systems with two inputs. We propose a general triangular normal form which contains several other normal forms discussed in the literature as special cases. We derive conditions under which a system with given x-flat output can be transformed into the proposed triangular form. Based on the trian

Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques

We consider fair network topology inference from nodal observations. Real-world networks often exhibit biased connections based on sensitive nodal attributes. Hence, different subpopulations of nodes may not share or receive information equitably. We thus propose an optimization-based approach to accurately infer networks while discouraging biased edges. To

Jacob W. Knaup, Panagiotis Tsiotras

This work examines the optimal covariance steering problem for systems subject to unknown parameters that enter multiplicatively with the state and control, in addition to additive disturbances. In contrast to existing works, the unknown parameters are modeled as random variables and are estimated online. This work proposes the utilization of recursive least

James Beyer, Greg Muller

We initiate a systematic study of the deep points of a cluster algebra; that is, the points in the associated variety which are not in any cluster torus. We describe the deep points of cluster algebras of type A, rank 2, Markov, and unpunctured surface type.

Jianxin Dai, Jin Ge, Kangda Zhi, Cunhua Pan

Integrating the reconfigurable intelligent surface (RIS) into a cell-free massive multiple-input multiple-output (CF-mMIMO) system is an effective solution to achieve high system capacity with low cost and power consumption. However, existing works of RIS-assisted systems mostly assumed perfect hardware, while the impact of hardware impairments (HWIs) is gen

David Herrera-Poyatos, Cristina Zuheros, Rosana Montes, Francisco Herrera

Social Media and Internet have the potential to be exploited as a source of opinion to enrich Decision Making solutions. Crowd Decision Making (CDM) is a methodology able to infer opinions and decisions from plain texts, such as reviews published in social media platforms, by means of Sentiment Analysis. Currently, the emergence and potential of Large Langua

Aashish Ghimire, James Prather, John Edwards

The rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. This study delves into university instructors' experiences and attitudes toward AI language models, filling a gap in the literature by analyzing educators' perspectives on AI's role in

Mai A. Shaaban, Adnan Khan, Mohammad Yaqub

Chest X-ray images are commonly used for predicting acute and chronic cardiopulmonary conditions, but efforts to integrate them with structured clinical data face challenges due to incomplete electronic health records (EHR). This paper introduces MedPromptX, the first clinical decision support system that integrates multimodal large language models (MLLMs),

Juan Zurita, Andrés Agustí Casado, Charles E. Creffield, Gloria Platero

In the ongoing effort towards a scalable quantum computer, multiple technologies have been proposed. Some of them exploit topological materials to process quantum information. In this work, we propose a lattice of photonic cavities with alternating hoppings to create a modified multidomain SSH chain, that is, a sequence of topological insulators made from ch

Aalok Patwardhan, Callum Rhodes, Gwangbin Bae, Andrew J. Davison

Camera rotation estimation from a single image is a challenging task, often requiring depth data and/or camera intrinsics, which are generally not available for in-the-wild videos. Although external sensors such as inertial measurement units (IMUs) can help, they often suffer from drift and are not applicable in non-inertial reference frames. We present U-AR

Juntian Tu, Sarthak Subhankar

Real-time arbitrary waveform generation (AWG) is essential in various engineering and research applications. This paper introduces a novel AWG architecture using an NVIDIA graphics processing unit (GPU) and a commercially available high-speed digital-to-analog converter (DAC) card, both running on a desktop personal computer (PC). The GPU accelerates the "em

Carlos Rocha

We consider the characterization of global attractors $A_f$ for semiflows generated by scalar one-dimensional semilinear parabolic equations of the form $u_t = u_{xx} + f(u,u_x)$, defined on the circle $x\in S^1$, for a class of reversible nonlinearities. Given two reversible nonlinearities, $f_0$ and $f_1$, with the same lap signature, we prove the existenc

Anna Rodriguez Rasmussen

K\"ulshammer, K\"onig and Ovsienko proved that for any quasi-hereditary algebra $(A,\leq_A)$ there exists a Morita equivalent quasi-hereditary algebra $(R, \leq_R)$ containing a basic exact Borel subalgebra $B$. The obtained Borel subalgebra is in fact a regular exact Borel subalgebra. Later, Conde showed that given a quasi-hereditary algebra $(R,\leq_R)$ wi

Kangming Li, Kamal Choudhary, Brian DeCost, Michael Greenwood

High-entropy materials (HEMs) have recently emerged as a significant category of materials, offering highly tunable properties. However, the scarcity of HEM data in existing density functional theory (DFT) databases, primarily due to computational expense, hinders the development of effective modeling strategies for computational materials discovery. In this

Agustina Victoria Ledezma, Adrián Pastine, Mario Valencia-Pabon

For any graph $G = (V,E)$ and positive integer $d$, the exact distance-$d$ graph $G_{=d}$ is the graph with vertex set $V$, where two vertices are adjacent if and only if the distance between them in $G$ is $d$. We study the exact distance-$d$ Kneser graphs. For these graphs, we characterize the adjacency of vertices in terms of the cardinality of the inters

Xiao Li, H. Eric Tseng, Anouck Girard, Ilya Kolmanovsky

Autonomous driving depends on perception systems to understand the environment and to inform downstream decision-making. While advanced perception systems utilizing black-box Deep Neural Networks (DNNs) demonstrate human-like comprehension, their unpredictable behavior and lack of interpretability may hinder their deployment in safety critical scenarios. In

Mahtab Sarvmaili, Hassan Sajjad, Ga Wu

Existing example-based prediction explanation methods often bridge test and training data points through the model's parameters or latent representations. While these methods offer clues to the causes of model predictions, they often exhibit innate shortcomings, such as incurring significant computational overhead or producing coarse-grained explanations. Th

Vigneshwaran Krishnamurthy, Nicolas B. Cowan

Searches for helium in the exospheres of exoplanets via the metastable near-infrared triplet have yielded 17 detections and 40 non-detections. We performed a comprehensive re-analysis of published studies to investigate the influence of stellar XUV flux and orbital parameters on the detectability of helium in exoplanetary atmospheres. We identified a distinc

Yuhan Xia, Qingqing Zhao, Yunfei Long, Ge Xu

In traditional research approaches, sensory perception and emotion classification have traditionally been considered separate domains. Yet, the significant influence of sensory experiences on emotional responses is undeniable. The natural language processing (NLP) community has often missed the opportunity to merge sensory knowledge with emotion classificati

Vladimir I. Bogachev

We prove pseudocompactness of a Tychonoff space $X$ and the space $\mathcal{P}(X)$ of Radon probability measures on it with the weak topology under the condition that the Stone-\v{C}ech compactification of the space $\mathcal{P}(X)$ is homeomorphic to the space $\mathcal{P}(\beta X)$ of Radon probability measures on the Stone-\v{C}ech compactification of the

Irina Bobkova, Andrea Lachmann, Ang Li, Alicia Lima

In this paper, we bound the descent filtration of the exotic Picard group $\kappa_n$, for a prime number p>3 and n=p-1. Our method involves a detailed comparison of the Picard spectral sequence, the homotopy fixed point spectral sequence, and an auxiliary $\beta$-inverted homotopy fixed point spectral sequence whose input is the Farrell-Tate cohomology of th

Sepehr Sabeti, Fatemeh Banani Ardecani, Omidreza Shoghli

Given the aging highway infrastructure requiring extensive rebuilding and enhancements, and the consequent rise in the number of work zones, there is an urgent need to develop advanced safety systems to protect workers. While Augmented Reality (AR) holds significant potential for delivering warnings to workers, its integration into roadway work zones remains

Radha Jagadeesan

We study the desiderata on a model for statistical probabilistic programming languages. We argue that they can be met by a combination of traditional tools, namely open bisimulation and probabilistic simulation.

André Correia, Luís A. Alexandre

Synthesising appropriate choreographies from music remains an open problem. We introduce MDLT, a novel approach that frames the choreography generation problem as a translation task. Our method leverages an existing data set to learn to translate sequences of audio into corresponding dance poses. We present two variants of MDLT: one utilising the Transformer

Ibrahim Sadiek, Alexander Puth, Grzegorz Kowzan, Akiko Nishiyama

Non-thermal molecular plasmas play a crucial role in numerous industrial processes and hold significant potential for driving essential chemical transformations. Accurate information about the molecular composition of the plasmas and the distribution of populations among quantum states is essential for understanding and optimizing plasma processes. Here, we

Shambhavi Mishra, Balamurali Murugesan, Ismail Ben Ayed, Marco Pedersoli

State-of-the-art semi-supervised learning (SSL) approaches rely on highly confident predictions to serve as pseudo-labels that guide the training on unlabeled samples. An inherent drawback of this strategy stems from the quality of the uncertainty estimates, as pseudo-labels are filtered only based on their degree of uncertainty, regardless of the correctnes

Srikanth B. Iyengar, Linquan Ma, Mark E. Walker, Ziquan Zhuang

Over a Cohen-Macaulay local ring, the minimal number of generators of a maximal Cohen-Macaulay module is bounded above by its multiplicity. In 1984 Ulrich asked whether there always exist modules for which equality holds; such modules are known nowadays as Ulrich modules. We answer this question in the negative by constructing families of two dimensional Coh

Asma Fallah, Nader Engheta

Here, we theoretically investigate the nonreciprocal response of an electrically biased graphene-coated dielectric fiber. By electrically biasing the graphene coating along the fiber axis, the dynamic conductivity of graphene exhibits a nonsymmetric response with respect to the longitudinal component of guided-mode wave vectors. Consequently, the guided wave

Ludovic Ducobu, Nicoleta Voicu

The method of variational completion allows one to transform an (in principle, arbitrary) system of partial differential equations -- based on an intuitive ``educated guess'' -- into the Euler-Lagrange one attached to a Lagrangian, by adding a canonical correction term. Here, we extend this technique to theories that involve at least two sets of dynamical va

Fatima Antarou Ba, Oleh Melnyk, Christian Wald, Gabriele Steidl

High-dimensional real-world systems can often be well characterized by a small number of simultaneous low-complexity interactions. The analysis of variance (ANOVA) decomposition and the anchored decomposition are typical techniques to find sparse additive decompositions of functions. In this paper, we are interested in a setting, where these decompositions a

J. R. Peterson, G. Sembroski, A. Dutta, C. Remacaldo

We present a self-consistent representation of the atmosphere and implement the interactions of light with the atmosphere using a photon Monte Carlo approach. We compile global climate distributions based on historical data, self-consistent vertical profiles of thermodynamic quantities, spatial models of cloud variation and cover, and global distributions of

Jean-Pierre Tignol

A $3$-fold and a $5$-fold quadratic Pfister forms are canonically associated to every symplectic involution on a central simple algebra of degree $8$ over a field of characteristic $2$. The same construction on central simple algebras of degree $4$ associates to every unitary involution a $2$-fold and a $4$-fold Pfister quadratic forms, and to every orthogon

Kyle Lucke, Aleksandar Vakanski, Min Xian

In recent years, convolutional neural networks for semantic segmentation of breast ultrasound (BUS) images have shown great success; however, two major challenges still exist. 1) Most current approaches inherently lack the ability to utilize tissue anatomy, resulting in misclassified image regions. 2) They struggle to produce accurate boundaries due to the r

Zhengyi Zhao, Chen Song, Xiaodong Gu, Yuan Dong

A fundamental problem in the texturing of 3D meshes using pre-trained text-to-image models is to ensure multi-view consistency. State-of-the-art approaches typically use diffusion models to aggregate multi-view inputs, where common issues are the blurriness caused by the averaging operation in the aggregation step or inconsistencies in local features. This p

C. W. F. Freeman, H. Youel, A. K. Budniak, Z. Xue

Antiferromagnetic (AFM) magnons in van der Waals (vdW) materials offer substantial potential for applications in magnonics and spintronics. In this study, we demonstrate ultra-strong magnon-magnon coupling in the GHz regime within a vdW AFM, achieving a maximum coupling rate of 0.91. Our investigation shows the tunability of coupling strength through tempera

Jean Sternberg, Julien Voisin, Charline Roux, Yannick Chassagneux

In this paper, we introduce a secure optical communication protocol that harnesses quantum correlation within entangled photon pairs. A message written by acting on one of the photons can be read by exclusive measurements of the other photon of the pair. In this scheme a bright, meaningless optical beam hides the message rendering it inaccessible to potentia

Sanaa Agarwal, Edwin Chaparro, Diego Barberena, A. Piñeiro Orioli

Ultra-cold atomic systems are among the most promising platforms that have the potential to shed light on the complex behavior of many-body quantum systems. One prominent example is the case of a dense ensemble illuminated by a strong coherent drive while interacting via dipole-dipole interactions. Despite being subjected to intense investigations, this syst

Gustavo Rigolin

We show that the Schr\"odinger equation can be derived assuming the Galilean covariance of a generic wave equation and the validity of the de Broglie's wave-particle duality hypothesis. We also obtain from this set of assumptions the transformation law for the wave function under a Galilean boost and prove that complex wave functions are unavoidable for a co

S. Wojciechowski, J. Krajewska Spiewak, R. W. Maruda, G. M. Krolczyk

Ploughing phenomena occurring during precise machining processes affect the formation of surface finish and progress of tool wear. Therefore, this study presents an evaluation of ploughing phenomenon by studying the ploughing forces in tool flank face workpiece interface during precise ball end milling of AISI L6 alloy steel. Developed original model of plou

Aécio Santos, Flip Korn, Juliana Freire

Relational data augmentation is a powerful technique for enhancing data analytics and improving machine learning models by incorporating columns from external datasets. However, it is challenging to efficiently discover relevant external tables to join with a given input table. Existing approaches rely on data discovery systems to identify joinable tables fr

Rodrigo Hernández-Gutiérrez, Santi Spadaro

A space is functionally countable if every real-valued continuous function has countable image. A stronger property recently defined by Tkachuk is exponentially separability. We start by studying these properties in GO spaces, where we extend results by Tkachuk and Wilson, and prove a conjecture by Dow. We also study some subspaces of products that are funct

Dylan Auty, Krystian Mikolajczyk

Monocular depth estimation (MDE) is inherently ambiguous, as a given image may result from many different 3D scenes and vice versa. To resolve this ambiguity, an MDE system must make assumptions about the most likely 3D scenes for a given input. These assumptions can be either explicit or implicit. In this work, we demonstrate the use of natural language as

John J. Tobin, Patrick D. Sheehan

The envelopes and disks that surround protostars reflect the initial conditions of star and planet formation and govern the assembly of stellar masses. Characterizing these structures requires observations that span the near-infrared to centimeter wavelengths. Consequently, the past two decades have seen progress driven by numerous advances in observational

Vladislav Cherepanov, Sebastian W. Ertel, Zhongmin Qian, Jiang-Lun Wu

Functional integral representations for solutions of the motion equations for wall-bounded incompressible viscous flows, expressed (implicitly) in terms of distributions of solutions to stochastic differential equations of McKean-Vlasov type, are established by using a perturbation technique. These representations are used to obtain exact random vortex dynam

Pierre Bousseyroux, Marc Potters

We explore a spectral initialization method that plays a central role in contemporary research on signal estimation in nonconvex scenarios. In a noiseless phase retrieval framework, we precisely analyze the method's performance in the high-dimensional limit when sensing vectors follow a multivariate Gaussian distribution for two rotationally invariant models

Chandra Chekuri, Rhea Jain

The Survivable Network Design problem (SNDP) is a well-studied problem, motivated by the design of networks that are robust to faults under the assumption that any subset of edges up to a specific number can fail. We consider non-uniform fault models where the subset of edges that fail can be specified in different ways. Our primary interest is in the flexib

Valentin Crépel, Andrew Millis

Many of the important phases observed in twisted transition metal dichalcogenide homobilayers are driven by short-range interactions, which should be captured by a local tight binding description since no Wannier obstruction exists for these systems. Yet, published theoretical descriptions have been mutually inconsistent, with honeycomb lattice tight binding

Nora Brambilla, Tom Magorsch, Michael Strickland, Antonio Vairo

We compute the suppression of bottomonium in the quark-gluon plasma using the three-loop QCD static potential. The potential describes the spin-averaged bottomonium spectrum below threshold with a less than 1% error. Within potential nonrelativistic quantum chromodynamics and an open quantum systems framework, we compute the evolution of the bottomonium dens

Evan Vienneau, Addy J. Evans, Odelia V. Hartl, Nassim Bozorgnia

We examine the gamma-ray signal from dark matter (DM) annihilation from analogues of the Sagittarius (Sgr) dwarf spheroidal galaxy in the Auriga cosmological simulations. For velocity-dependent annihilation cross sections, we compute emissions from simulated Sgr subhalos and from the Milky Way (MW) foreground. In addition to the annihilation signals from DM

Lea Fuß, Mathias Garny, Alejandro Ibarra

The invisible decay of cold dark matter into a slightly lighter dark sector particle on cosmological time-scales has been proposed as a solution to the $S_8$ tension. In this work we discuss the possible embedding of this scenario within a particle physics framework, and we investigate its phenomenology. We identify a minimal dark matter decay setup that add

Antony Susmitha, Anohita Mallick, Bacham E. Reddy

The presence of a large amount of Li in giants is still a mystery. Most of the super Li-rich giants reported in recent studies are in the solar metallicity regime. Here, we study the five metal-poor super Li-rich giants (SLRs) from GALAH Data Release 3 with their [Fe/H] ranging from -1.35 to -2.38 with lithium abundance of A(Li) $\geq$ 3.4~dex. The asterosei

Subrata Pachhal, Adhip Agarwala

Entanglement measures have emerged as one of the versatile probes to diagnose quantum phases and their transitions. Universal features in them expand their applicability to a range of systems, including those with quenched disorder. In this work, we show that when the underlying lattice has percolation disorder, free fermions at a finite density show interes

Ernesto Campos, Daniil Rabinovich, Alexey Uvarov

Variational quantum algorithms have become the de facto model for current quantum computations. A prominent example of such algorithms -- the quantum approximate optimization algorithm (QAOA) -- was originally designed for combinatorial optimization tasks, but has been shown to be successful for a variety of other problems. However, for most of these problem

L. A. Heuser, G. Chanturia, F. -K. Guo, C. Hanhart

Resonances are uniquely characterized by their complex pole locations and the corresponding residues. In practice, however, resonances are typically identified experimentally as structures in invariant mass distributions, with branching fractions of resonances determined as ratios of count rates. To make contact between these quantities it is necessary to co

Yohei Ema, Ting Gao, Wenqi Ke, Zhen Liu

We construct tree-level amplitude for massive particles using on-shell recursion relations based on two classes of momentum shifts: an all-line transverse shift that deforms momentum by its transverse polarization vector, and a massive BCFW-type shift. We illustrate that these shifts allow us to correctly calculate four-point and five-point amplitudes in mas

Eugeny Babichev, Ignacy Sawicki, Leonardo G. Trombetta

Static black holes in general relativity modified by a linear scalar coupling to the Gauss-Bonnet invariant always carry hair. We show that the same mechanism that creates the hair makes it incompatible with a cosmological horizon. Other scalar-tensor models do not have this problem when time dependence of the scalar provides a natural matching to cosmology.

Christian Capanelli, Leah Jenks, Edward W. Kolb, Evan McDonough

We demonstrate that gravitational particle production (GPP) of a massive, Abelian, vector (Proca) field during inflation in the presence of nonminimal coupling to gravity may suffer from an instability which leads to runaway production of high-momentum modes. This is untenable unless there is some mechanism to regulate the runaway. We discuss the parameter s