April 2024 arXiv papers — page 75

Miguel Landeros, Christopher O'Neill, Roberto Pelayo, Karina Peña

The Huneke-Wiegand conjecture is a decades-long open question in commutative algebra. Garc\'ia-S\'anchez and Leamer showed that a special case of this conjecture concerning numerical semigroup rings $\Bbbk[\Gamma]$ can be answered in the affirmative by locating certain arithmetic sequences within the numerical semigroup $\Gamma$. In this paper, we use their

Benjamin Bruce, Izabella Laba

Keller's conjecture on cube tilings asserted that, in any tiling of $\mathbb{R}^d$ by unit cubes, there must exist two cubes that share a $(d-1)$-dimensional face. This is now known to be true in dimensions $d\leq 7$ and false for $d\geq 8$. In this article, we investigate analogues of Keller's conjecture for integer tilings.

Swadha Pandey, Evan D. Hall, Matthew Evans

Axions and axion-like particles are strongly motivated dark matter candidates that are the subject of many current ground based dark matter searches. We present first results from the Axion Dark-Matter Birefringent Cavity (ADBC) experiment, which is an optical bow-tie cavity probing the axion-induced birefringence of electromagnetic waves. Our experiment is

Brian Punsly

Jets are endemic to both Galactic solar mass and extragalactic supermassive black holes. A recent 86 GHz image of M\,87 shows a jet emerging from the accretion ring around a black hole, providing the first direct observational constraint on the kinematics of the jet-launching region in any black hole jetted system. The very wide ($\sim280\mu\rm{as}$), highly

Nadzieja Hodur, Monika Pilśniak, Magdalena Prorok, Ingo Schiermeyer

The $3$-colourability problem is a well-known NP-complete problem and it remains NP-complete for $bull$-free graphs, where $bull$ is the graph consisting of $K_3$ with two pendant edges attached to two of its vertices. In this paper we study $3$-colourability of $(bull,H)$-free graphs for several graphs $H$. We show that these graphs are $3$-colourable or co

Tommaso Roscilde, Filippo Caleca, Adriano Angelone, Fabio Mezzacapo

Long-range spin-spin interactions are known to generate non-equilibrium dynamics which can squeeze the collective spin of a quantum spin ensemble in a scalable manner, leading to states whose metrologically useful entanglement grows with system size. Here we show theoretically that scalable squeezing can be produced in 2d U(1)-symmetric systems even by short

Maurizio Verde, Ansgar Schaefer, Benjamin Zenz, Zyad Shehata

We study coherent light scattering from linear crystals with up to twelve $^{40}\text{Ca}^+$ ions, acting as single photon emitters. Light-scattering is induced by two-photon laser excitation, starting from the S$_{1/2}\rightarrow$ D$_{5/2}$ quadrupole transition at 729~nm followed by the D$_{5/2}\rightarrow$ P$_{3/2}$ dipole transition at 854~nm, from where

Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu

Deep learning (DL) models have revolutionized numerous domains, yet optimizing them for computational efficiency remains a challenging endeavor. Development of new DL models typically involves two parties: the model developers and performance optimizers. The collaboration between the parties often necessitates the model developers exposing the model architec

Olga Cherednichenko, Dmytro Chernyshov, Dmytro Sytnikov, Polina Sytnikova

This research paper delves into the innovative integration of Shannon entropy and rough set theory, presenting a novel approach to generalize the evaluation approach in machine learning. The conventional application of entropy, primarily focused on information uncertainty, is extended through its combination with rough set theory to offer a deeper insight in

Blas Fernández, Roghayeh Maleki, Štefko Miklavič, Giusy Monzillo

The $Q$-polynomial property is an algebraic property of distance-regular graphs, that was introduced by Delsarte in his study of coding theory. Many distance-regular graphs admit the $Q$-polynomial property. Only recently the $Q$-polynomial property has been generalized to graphs that are not necessarily distance-regular. In [ J. Combin. Theory Ser. A, 205:1

Peihan Tu, Li-Yi Wei, Matthias Zwicker

Texture plays a vital role in enhancing visual richness in both real photographs and computer-generated imagery. However, the process of editing textures often involves laborious and repetitive manual adjustments of textons, which are the recurring local patterns that characterize textures. This work introduces a fully unsupervised approach for representing

Leopoldo Mejía, Sandeep Sharma, Roi Baer, Garnet Kin-Lic Chan

Stochastic orbital techniques offer reduced computational scaling and memory requirements to describe ground and excited states at the cost of introducing controlled statistical errors. Such techniques often rely on two basic operations, stochastic trace estimation and stochastic resolution of identity, both of which lead to statistical errors that scale wit

Yizhuo Wu, Ang Li, Mohammadreza Beikmirza, Gagan Deep Singh

Digital Pre-Distortion (DPD) enhances signal quality in wideband RF power amplifiers (PAs). As signal bandwidths expand in modern radio systems, DPD's energy consumption increasingly impacts overall system efficiency. Deep Neural Networks (DNNs) offer promising advancements in DPD, yet their high complexity hinders their practical deployment. This paper intr

Nicholas J. C. Papadopoulos, Kirby Linvill

Quantum key distribution (QKD) and quantum message encryption protocols promise a secure way to distribute information while detecting eavesdropping. However, current protocols may suffer from significantly reduced eavesdropping protection when only a subset of qubits are observed by an attacker. In this paper, we present two quantum cryptographic protocols

Yuanfang Ren, Chirayu Tripathi, Ziyuan Guan, Ruilin Zhu

Given the sheer volume of surgical procedures and the significant rate of postoperative fatalities, assessing and managing surgical complications has become a critical public health concern. Existing artificial intelligence (AI) tools for risk surveillance and diagnosis often lack adequate interpretability, fairness, and reproducibility. To address this, we

V. M. Pergamenshchik

The one-body free volume, which determines the entropy of a hard disk system, has extensive (cavity) and intensive (cell) contributions. So far these contributions have not been unified and considered separately. The presented theory incorporates both contributions, and their sum is shown to determine the free volume and partition function. The approach is b

Rania Mkhinini Gahar, Olfa Arfaoui, Minyar Sassi Hidri

The new age of digital growth has marked all fields. This technological evolution has impacted data flows which have witnessed a rapid expansion over the last decade that makes the data traditional processing unable to catch up with the rapid flow of massive data. In this context, the implementation of a big data analytics system becomes crucial to make big

Christian Lourido, Zaid Waghoo, Hassam Khan Wazir, Nishtha Bhagat

Many neurological conditions, e.g., a stroke, can cause patients to experience upper limb (UL) motor impairments that hinder their daily activities. For such patients, while rehabilitation therapy is key for regaining autonomy and restoring mobility, its long-term nature entails ongoing time commitment and it is often not sufficiently engaging. Virtual reali

Daniel Vazquez, Jose Miranda, Alfonso Rodriguez, Andres Otero

Reconfigurable computing offers a good balance between flexibility and energy efficiency. When combined with software-programmable devices such as CPUs, it is possible to obtain higher performance by spatially distributing the parallelizable sections of an application throughout the reconfigurable device while the CPU is in charge of control-intensive sectio

Jingjing Zhang, Ulisses Braga-Neto, Eduardo Gildin

Physics-Informed Neural Networks (PINNs) integrate physical principles into machine learning, finding wide applications in various science and engineering fields. However, solving nonlinear hyperbolic partial differential equations (PDEs) with PINNs presents challenges due to inherent discontinuities in the solutions. This is particularly true for the Buckle

Mykola Lavreniuk

Self-supervised monocular depth estimation has garnered considerable attention for its applications in autonomous driving and robotics. While recent methods have made strides in leveraging techniques like the Self Query Layer (SQL) to infer depth from motion, they often overlook the potential of strengthening pose information. In this paper, we introduce SPI

Jason Wu, Yi-Hao Peng, Amanda Li, Amanda Swearngin

User interface (UI) design is a difficult yet important task for ensuring the usability, accessibility, and aesthetic qualities of applications. In our paper, we develop a machine-learned model, UIClip, for assessing the design quality and visual relevance of a UI given its screenshot and natural language description. To train UIClip, we used a combination o

Nina Deliu, Brunero Liseo

Doping control is an essential component of anti-doping organizations for protecting clean sports competitions. Since 2009, this mission has been complemented worldwide by the Athlete Biological Passport (ABP), used to monitor athletes' individual profiles over time. The practical implementation of the ABP is based on a Bayesian framework, called ADAPTIVE, i

Avisek Naug, Antonio Guillen, Ricardo Luna Gutierrez, Vineet Gundecha

There have been growing discussions on estimating and subsequently reducing the operational carbon footprint of enterprise data centers. The design and intelligent control for data centers have an important impact on data center carbon footprint. In this paper, we showcase PyDCM, a Python library that enables extremely fast prototyping of data center design

Sungjoon Kim, Manoj B. Jadhav, Vikas Berry, Jessica E. Metcalfe

Thin film detectors which incorporate semiconductor materials other than silicon have the potential to build upon their unique material properties and offer advantages such as faster response times, operation at room temperature, and radiation hardness. To explore the possibility, promising candidate materials were selected, and particle tracking detectors w

J. M. Rocha, F. Dahia

We discuss the quantum-bouncer experiment involving ultracold neutrons in a braneworld scenario. Extra-dimensional theories typically predict the strengthening of gravitational interactions over short distances. In this paper, we specifically study the anomalous gravitational interaction between the bouncing neutron and the reflecting mirror, resulting from

Connor Roncaioli, Connor Hart, Ronald Walsworth, Donald P. Fahey

Nitrogen-vacancy (NV) centers in diamond are a leading modality for magnetic sensing and imaging under ambient conditions. However, these sensors suffer from degraded performance due to paramagnetic impurities and regions of stress in the diamond crystal lattice. This work demonstrates a quantum diamond microscope (QDM) for simultaneous mapping and spatial c

Yu Feng, Ben Zhou, Weidong Lin, Dan Roth

Predictive models often need to work with incomplete information in real-world tasks. Consequently, they must provide reliable probability or confidence estimation, especially in large-scale decision-making and planning tasks. Current large language models (LLMs) are insufficient for accurate estimations, but they can generate relevant factors that may affec

Urchade Zaratiana, Nadi Tomeh, Yann Dauxais, Pierre Holat

Joint entity and relation extraction plays a pivotal role in various applications, notably in the construction of knowledge graphs. Despite recent progress, existing approaches often fall short in two key aspects: richness of representation and coherence in output structure. These models often rely on handcrafted heuristics for computing entity and relation

Yuan Quan, Shahram Shahsavari, Catherine Rosenberg

This paper investigates downlink radio resource management (RRM) in millimeter-wave systems with codebook-based hybrid beamforming in a single cell. We consider a practical but often overlooked multi-channel scenario where the base station is equipped with fewer radio frequency chains than there are user equipment (UEs) in the cell. In this case, analog beam

Urchade Zaratiana, Nadi Tomeh, Niama El Khbir, Pierre Holat

Information extraction (IE) is an important task in Natural Language Processing (NLP), involving the extraction of named entities and their relationships from unstructured text. In this paper, we propose a novel approach to this task by formulating it as graph structure learning (GSL). By formulating IE as GSL, we enhance the model's ability to dynamically r

Jaehong Choi, Kevin J. Crust, Lizhong Li, Kihong Lee

We demonstrate the integration of a thin BaTiO$_3$ (BTO) membrane with monolayer MoSe$_2$ in a dual gate device that enables in-situ manipulation of the BTO ferroelectric polarization with a voltage pulse. While two-dimensional (2D) transition metal dichalcogenides (TMDs) offer remarkable adaptability, their hybrid integration with other families of function

Kelvin Wey Han Chan, Christopher Bryant, Li Nguyen, Andrew Caines

Code-switching (CSW) is a common phenomenon among multilingual speakers where multiple languages are used in a single discourse or utterance. Mixed language utterances may still contain grammatical errors however, yet most existing Grammar Error Correction (GEC) systems have been trained on monolingual data and not developed with CSW in mind. In this work, w

Bartlomiej Sobieski, Przemysław Biecek

Despite increasing progress in development of methods for generating visual counterfactual explanations, especially with the recent rise of Denoising Diffusion Probabilistic Models, previous works consider them as an entirely local technique. In this work, we take the first step at globalizing them. Specifically, we discover that the latent space of Diffusio

Shengxi Gui

With the development of remote sensing technology in recent decades, spaceborne sensors with sub-meter and meter spatial resolution (Worldview and PlanetScope) have achieved a considerable image quality to generate 3D geospatial data via a stereo matching pipeline. These achievements have significantly increased the data accessibility in 3D, necessitating ad

Alaa Saleh, Praveen Kumar Donta, Roberto Morabito, Naser Hossein Motlagh

This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by these environments. Through AI agents that accompany users, Follow-Me AI negotiates data management based on user consent, aligns environmental controls as well as user communicat

Spyros Angelopoulos, Marcin Bienkowski, Christoph Dürr, Bertrand Simon

Contract scheduling is a widely studied framework for designing real-time systems with interruptible capabilities. Previous work has showed that a prediction on the interruption time can help improve the performance of contract-based systems, however it has relied on a single prediction that is provided by a deterministic oracle. In this work, we introduce a

Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser

Simulation-based methods for statistical inference have evolved dramatically over the past 50 years, keeping pace with technological advancements. The field is undergoing a new revolution as it embraces the representational capacity of neural networks, optimization libraries and graphics processing units for learning complex mappings between data and inferen

Long-Hao Xu, Tobias Mütze, Frank Konietschke, Tim Friede

In group sequential designs, where several data looks are conducted for early stopping, we generally assume the vector of test statistics from the sequential analyses follows (at least approximately or asymptotially) a multivariate normal distribution. However, it is well-known that test statistics for which an asymptotic distribution is derived may suffer f

Haylee N. Archer, Deidre A. Hunter, Bruce G. Elmegreen, Monica Rubio

Wolf-Lundmark-Melotte (WLM) is a Local Group dwarf irregular (dIrr) galaxy with a metallicity 13% of solar. At 1 Mpc, the relative isolation of WLM provides a unique opportunity to investigate the internal mechanisms of star formation at low metallicities. The earliest stages of star formation in larger spirals occur in embedded clusters within molecular clo

Abdul Wahab Ziaullah, Ferda Ofli, Muhammad Imran

Critical Infrastructure Facilities (CIFs), such as healthcare and transportation facilities, are vital for the functioning of a community, especially during large-scale emergencies. In this paper, we explore a potential application of Large Language Models (LLMs) to monitor the status of CIFs affected by natural disasters through information disseminated in

Yufan Li, Subhabrata Sen, Ben Adlam

In the transfer learning paradigm models learn useful representations (or features) during a data-rich pretraining stage, and then use the pretrained representation to improve model performance on data-scarce downstream tasks. In this work, we explore transfer learning with the goal of optimizing downstream performance. We introduce a simple linear model tha

Jan Giesselmann, Attila Karsai, Tabea Tscherpel

For a general class of nonlinear port-Hamiltonian systems we develop a high-order time discretization scheme with certain structure preservation properties. The finite or infinite-dimensional system under consideration possesses a Hamiltonian function, which represents an energy in the system and is conserved or dissipated along solutions. For infinite-dimen

Rahul Bhardwaj, Rohit Kumar Mishra, Manmohan Vashisth

This article studies the inverse problem of recovering a vector field supported in $\mathbb{D}_R$, the disk of radius $R$ centered at the origin, through a set of generalized broken ray/V-line transforms, namely longitudinal and transverse V-line transforms. Geometrically, we work with broken lines that start from the boundary of a disk and break at a fixed

Gargi Roy, Dalia Chakrabarty

We present a new strategy for learning the functional relation between a pair of variables, while addressing inhomogeneities in the correlation structure of the available data, by modelling the sought function as a sample function of a non-stationary Gaussian Process (GP), that nests within itself multiple other GPs, each of which we prove can be stationary,

Wadim Strielkowski, Oxana Mukhoryanova, Oxana Kuznetsova, Yury Syrov

This paper analyzes sustainable regional economic development and land use employing a case study of Russia. The economics of land management in Russia which is shaped by both historical legacies and contemporary policies represents an interesting conundrum. Following the dissolution of the Soviet Union, Russia embarked on a thorny and complex path towards t

Pablo M. Candela, Valentina De Romeri, Pantelis Melas, Dimitrios K. Papoulias

We investigate the possible production of a MeV-scale sterile fermion through the up-scattering of neutrinos on nuclei and atomic electrons at different facilities. We consider a phenomenological model that adds a new fermion to the particle content of the Standard Model and we allow for all possible Lorentz-invariant non-derivative interactions (scalar, pse

Haocheng Zhang, Markus Böttcher, Ioannis Liodakis

X-ray and MeV polarization can be powerful diagnostics for leptonic and hadronic blazar models. Previous predictions are mostly based on a one-zone framework. However, recent IXPE observations of Mrk~421 and 501 strongly favor a multi-zone framework. Thus, the leptonic and hadronic polarization predictions need to be revisited. Here we identify two generic r

Sion Kim, Ezra Kissel, Karel Matous

The high computational demands of multiscale modeling necessitate advanced parallel and adaptive strategies. To address this challenge, we introduce an adaptive method that utilizes two microscale models based on an offline database for multiscale modeling of curved interfaces (e.g., adhesive layers). This database employs nonlinear classifiers, developed us

Michael H. Shaham, Taskin Padir

Platooning of autonomous vehicles has the potential to increase safety and fuel efficiency on highways. The goal of platooning is to have each vehicle drive at a specified speed (set by the leader) while maintaining a safe distance from its neighbors. Many prior works have analyzed various controllers for platooning, most commonly linear feedback and distrib

Quincy Card, Daniel Simpson, Kshitiz Aryal, Maanak Gupta

In recent years, there has been a significant surge in malware attacks, necessitating more advanced preventive measures and remedial strategies. While several successful AI-based malware classification approaches exist categorized into static, dynamic, or online analysis, most successful AI models lack easily interpretable decisions and explanations for thei

André Galligo, Joseph Najnudel, Truong Vu

Let $(Z^{(n)}_k)_{1 \leq k \leq n}$ be a random set of points and let $\mu_n$ be its \emph{empirical measure}: $$\mu_n = \frac{1}{n} \sum_{k=1}^n \delta_{Z^{(n)}_k}. $$ Let $$P_n(z) := (z - Z^{(n)}_1)\cdots (z - Z^{(n)}_n)\quad \text{and}\quad Q_n (z) := \sum_{k=1}^n \gamma^{(n)}_k \prod_{1 \leq j \leq n, j \neq k} (z- Z^{(n)}_j), $$ where $(\gamma^{(n)}_k)_

Thiago Holleben

The theory of Rees algebras of monomial ideals has been extensively studied, and as a consequence, many (sometimes partial) equivalences between algebraic properties of monomial ideals, and combinatorial properties of simplicial complexes and hypergraphs are known. In this paper we show how this theory can be used to find interesting examples in the theory o

P. Malgaretti, E. Locatelli, C. Valeriani

We derive an effective Rouse model for tangentially active polymers, characterized by a constant active force tangent to their backbone. In particular, we show that, once extended to account for finite bending rigidity, such active Rouse model captures the reduction in the gyration radius, or coil-to-globule-like transition, that has been observed numericall

Ilya D. Shkredov

The paper obtains the optimal form of the uncertainty principle in the special case of convolution of sets.

Ankita Koley, Chandramani Singh

We consider a dynamic content caching problem wherein the contents get updated at a central server, and local copies of a subset of contents are cached at a local cache associated with a Base station (BS). When a content request arrives, based on whether the content is in the local cache, the BS can decide whether to fetch the content from the central server

Guangyu Sun, Matias Mendieta, Aritra Dutta, Xin Li

Multi-modal transformers mark significant progress in different domains, but siloed high-quality data hinders their further improvement. To remedy this, federated learning (FL) has emerged as a promising privacy-preserving paradigm for training models without direct access to the raw data held by different clients. Despite its potential, a considerable resea

Alina Carmen Cojocaru, Auden Hinz, Tian Wang

For $E_1$ and $E_2$ elliptic curves defined over a number field $K$, without complex multiplication, we consider the function ${\mathcal{F}}_{E_1, E_2}(x)$ counting non-zero prime ideals $\mathfrak{p}$ of the ring of integers of $K$, of good reduction for $E_1$ and $E_2$, of norm at most $x$, and for which the Frobenius fields $\mathbb{Q}(\pi_{\mathfrak{p}}(

Benjamin Blakely, Joaquin Chung, Alec Poczatek, Ryan Syed

Any human-designed system can potentially be exploited in ways that its designers did not envision, and information systems or networks using quantum components do not escape this reality. We are presented with a unique but quickly waning opportunity to bring cybersecurity concerns to the forefront for quantum information systems before they become widely de

Abhinav Rao, Akhila Yerukola, Vishwa Shah, Katharina Reinecke

To be effectively and safely deployed to global user populations, large language models (LLMs) may need to adapt outputs to user values and cultures, not just know about them. We introduce NormAd, an evaluation framework to assess LLMs' cultural adaptability, specifically measuring their ability to judge social acceptability across varying levels of cultural

Haodong Yao

In this article, we prove a Kudla-Rapoport conjecture for $\mathcal{Y}$-cycles on exotic smooth unitary Rapoport-Zink spaces of odd arithmetic dimension, i.e. the arithmetic intersection numbers for $\mathcal{Y}$-cycles equals the derivatives of local representation density. We also compare $\mathcal{Z}$-cycles and $\mathcal{Y}$-cycles on these RZ spaces. Th

Edis Mekić, Mihailo Jovanović, Kristijan Kuk, Bojan Prlinčević

This research paper will bring forth the innovative pedagogical approach in computer science education, which uses a combination of methodologies borrowed from Artificial Intelligence (AI) and DevOps to enhance the learning experience in Content Management Systems (CMS) Development. It has been done over three academic years, comparing the traditional way of

Xun Zhou, Timo Kuosmanen

Understanding input substitution and output transformation possibilities is critical for efficient resource allocation and firm strategy. There are important examples of fixed proportion technologies where certain inputs are non-substitutable and/or certain outputs are non-transformable. However, there is widespread confusion about the appropriate modeling o

Mohsen Shirali, Zahra Ahmadi, Carlos Fernández-Llatas, Jose-Luis Bayo-Monton

Internet of Things (IoT) systems are vulnerable to data collection errors and these errors can significantly degrade the quality of collected data, impact data analysis and lead to inaccurate or distorted results. This article emphasizes the importance of evaluating data quality and errors before proceeding with analysis and considering the effectiveness of

Jeonghwan Ahn, Seoung-Hun Kang, Mina Yoon, Jaron T. Krogel

We have investigated interlayer interactions in the bilayer PtTe$_{2}$ system, which influence the electronic energy bands near the Fermi levels. Our diffusion Monte Carlo (DMC) calculations for the high-symmetry bilayer stackings (AA, AB, AC) manifest distinct interlayer binding characteristics among the stacking modes by revealing significantly different i

Sevin Mohammadi, Andrew W. Smyth

Vehicular trajectory data from geolocation telematics is vital for analyzing urban mobility patterns. Map-matching aligns noisy, sparsely sampled GPS trajectories with digital road maps to reconstruct accurate vehicle paths. Traditional methods rely on geometric proximity, topology, and shortest-path heuristics, but they overlook two key factors: (1) drivers

Detlef Schmicker

We construct a three dimensional toy systems with two types of fermions forming a composite boson. They are hold in a harmonic potential. The basis functions are constructed from an internal and an external Gauss function. All integrals have analytical solutions. The high symmetry reduces the number of integrals to be calculated for the symmetrized wave func

Mohammad Ali Abbassi

We investigate the recoil heating phenomenon experienced by a dielectric spherical particle when it interacts with a linearly polarized plane wave within the Rayleigh regime. We derive the fluctuating force acted upon the particle arising from the fluctuations of the electromagnetic fields. Our derivations reveal that the spectral density of the fluctuating

Rongqian Ma, Meredith Dedema, Andrew Cox

The advent of generative artificial intelligence (GenAI) technologies has been changing the research landscape and potentially has significant implications for Digital Humanities (DH), a field inherently intertwined with technologies. This article investigates how DH scholars adopt and critically evaluate GenAI technologies for research. Drawing on 76 respon

Chao Jin, Zili Zhang, Xuanlin Jiang, Fangyue Liu

Retrieval-Augmented Generation (RAG) has shown significant improvements in various natural language processing tasks by integrating the strengths of large language models (LLMs) and external knowledge databases. However, RAG introduces long sequence generation and leads to high computation and memory costs. We propose RAGCache, a novel multilevel dynamic cac

Arne Mertens

We follow the work of Aguiar on internal categories and introduce simplicial objects internal to a monoidal category as certain colax monoidal functors. Then we compare three approaches to equipping them with a discrete set of vertices. We introduce based colax monoidal functors and show that under suitable conditions they are equivalent to the templicial ob

Kuo Chen, Xinyan Huang, Xunjie Chen, Jingang Yi

Gait control of legged robotic walkers on dynamically moving surfaces (e.g., ships and vehicles) is challenging due to the limited balance control actuation and unknown surface motion. We present a contingent model predictive control (CMPC) for bipedal walker locomotion on moving surfaces with a linear inverted pendulum (LIP) model. The CMPC is a robust desi

Jaren N. Ashcraft, Ewan S. Douglas, Ramya Anche, Brandon D. Dube

Paraxial diffraction modeling based on the Fourier transform has seen widespread implementation for simulating the response of a diffraction-limited optical system. For systems where the paraxial assumption is not sufficient, a class of algorithms has been developed that employs hybrid propagation physics to compute the propagation of an elementary beamlet a

Mohamed Boujoudar, Abdelaziz Beljadid, Ahmed Taik

In this paper, we first propose a coupled numerical model of unsaturated flow in soils and plant root water uptake. The Richards equation and different formulations are used in the developed numerical model to describe infiltration in root zone and to investigate the impact of the plant root on the distribution of soil moisture. The Kirchhoff transformed Ric

Bingbing Wen, Bill Howe, Lucy Lu Wang

The correct model response in the face of uncertainty is to abstain from answering a question so as not to mislead the user. In this work, we study the ability of LLMs to abstain from answering context-dependent science questions when provided insufficient or incorrect context. We probe model sensitivity in several settings: removing gold context, replacing

J. L. Ball, E. E. Peterson, R. S. Kemp, S. E. Ferry

Construction of a nuclear weapon requires access to kilogram-scale quantities of fissile material, which can be bred from fertile material like U-238 and Th-232 via neutron capture. Future fusion power plants, with total neutron source rates in excess of $10^{20}$ n/s, could breed weapons-relevant quantities of fissile material on short timescales, posing a

Ting-Ruen Wei, Michele Hell, Dang Bich Thuy Le, Aren Vierra

This study presents an unsupervised domain adaptation method aimed at autonomously generating image masks outlining regions of interest (ROIs) for differentiating breast lesions in breast ultrasound (US) imaging. Our semi-supervised learning approach utilizes a primitive model trained on a small public breast US dataset with true annotations. This model is t

I. J. Hamad, C. S. Helman, L. O. Manuel, A. E. Feiguin

Light-matter interactions can be used as a tool to realize novel many-body states of matter and to study the interplay between electronic and magnetic degrees of freedom. In particular, tightly bound many-body states that behave as coherent quasi-particles are rare, and may lead to unconventional technological applications beyond the semi-conductor paradigm,

Qin-He Yang, Di Guo, Ming-Yan Li, Ling-Yun Dai

The electromagnetic form factors $G_{\rm E}$ and $G_{\rm M}$ of the proton and neutron in the timelike region are extracted in a study of the processes $e^+ e^-\to \bar{p}p$ and $e^+ e^-\to \bar{n}n$. The reaction amplitude is evaluated within the distorted wave Born approximation, with the interaction of the antinucleon-nucleon ($\bar{N}N$) pair taken into

Yoonsang Lee, Xi Ye, Eunsol Choi

Different entities with the same name can be difficult to distinguish. Handling confusing entity mentions is a crucial skill for language models (LMs). For example, given the question "Where was Michael Jordan educated?" and a set of documents discussing different people named Michael Jordan, can LMs distinguish entity mentions to generate a cohesive answer

Emil Albrychiewicz, Andrés Franco Valiente, Ori J. Ganor, Chao Ju

In radial quantization, the ground states of a gauge theory on ADE singularities $\mathbb{R}^4/\Gamma$ are characterized by flat connections that are maps from $\Gamma$ to the gauge group. We study Class $\mathcal{S}$ theory of type $\mathfrak{a}_1=\mathfrak{su}(2)$ on a Riemann surface of genus $g>1$, without punctures. The fundamental building block of Cla

Jie Chen, Pengfei Ou, Yuxin Chang, Hengrui Zhang

High-performance catalysts are crucial for sustainable energy conversion and human health. However, the discovery of catalysts faces challenges due to the absence of efficient approaches to navigating vast and high-dimensional structure and composition spaces. In this study, we propose a high-throughput computational catalyst screening approach integrating d

Tianze Hua, Tian Yun, Ellie Pavlick

Many pretrained multilingual models exhibit cross-lingual transfer ability, which is often attributed to a learned language-neutral representation during pretraining. However, it remains unclear what factors contribute to the learning of a language-neutral representation, and whether the learned language-neutral representation suffices to facilitate cross-li

Manuela Bischetti, Hyunseop Choi, Fabrizio Fiore, Chiara Feruglio

Although the mass growth of supermassive black holes during the Epoch of Reionisation is expected to play a role in shaping the concurrent growth of their host-galaxies, observational evidence of feedback at z$\gtrsim$6 is still sparse. We perform the first multi-scale and multi-phase characterisation of black-hole driven outflows in the $z\sim6.6$ quasar J0

Mario Fernández Navarro, Stephen F. King, Avelino Vicente

The tri-hypercharge proposal introduces a separate gauged weak hypercharge assigned to each fermion family as the origin of flavour. This is arguably one of the simplest setups for building "gauge non-universal theories of flavour" or "flavour deconstructed theories". In this paper we propose and study two minimal but ultraviolet complete and renormalisable

Michael H. Shaham, Taskin Padir

This paper presents a distributed model predictive control (DMPC) algorithm for a heterogeneous platoon using arbitrary communication topologies, provided each vehicle can communicate with a preceding vehicle in the platoon. The proposed DMPC algorithm can accommodate any spacing policy that is affine in a vehicle's velocity, which includes constant distance

Oliver Lemke, Zuria Bauer, René Zurbrügg, Marc Pollefeys

In recent years, modern techniques in deep learning and large-scale datasets have led to impressive progress in 3D instance segmentation, grasp pose estimation, and robotics. This allows for accurate detection directly in 3D scenes, object- and environment-aware grasp prediction, as well as robust and repeatable robotic manipulation. This work aims to integr

Henning Bahl, Marcela Carena, Aurora Ireland, Carlos E. M. Wagner

The resummation of large thermal corrections to the effective potential is mandatory for the accurate prediction of phase transitions. We discuss the accuracy of different prescriptions to perform this resummation at the one- and two-loop level and point out conceptual issues that appear when using a high-temperature expansion at the two-loop level. Moreover

Ivan A. Bocanegra-Garay, Miguel Castillo-Celeita, J. Negro, L. M. Nieto

The supersymmetric connection that exists between the Jaynes-Cummings (JC) and anti-Jaynes Cummings (AJC) models in quantum optics is unraveled entirely. A new method is proposed to obtain the temporal evolution of observables in the AJC model using supersymmetric techniques, providing an overview of its dynamics and extending the calculation to full photon

Ricardo Z. Ferreira, Ángel Gil Muyor

In this work, we study the luminosity that results from the conversion of QCD axion particles into photons in the magnetic field of the plasma accreting onto black holes (BHs). For the luminosities to be large two conditions need to be met: i) there are large numbers of axions in the PBH surroundings as a result of the so-called superradiant instability; ii)

Aman Khalid, Sarah Brough, Garreth Martin, Lucas C. Kimmig

Tidal features provide signatures of recent mergers and offer a unique insight into the assembly history of galaxies. The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will enable an unprecedentedly large survey of tidal features around millions of galaxies. To decipher the contributions of mergers to galaxy evolution it will be necessar

S. Andreon, G. Trinchieri, A. Moretti

The comparison of the properties of galaxy cluster samples selected using observations in different wavebands may shed light on potential biases of the way in which the samples are assembled. For this comparison, we introduce a new observable that does not require previous knowledge of the cluster mass: the X-ray mean surface brightness within the central 30

Daniel Faraco, Luis Guijarro, Yaroslav Kurylev, Alberto Ruiz

We consider the problem of finding the homogenization limit of oscillating linear elliptic equations on an arbitrary parallelizable manifold $(M,g,\Gamma)$. We replicate the concept of two-scale convergence by pulling back tensors $T$ defined on the torus bundle $\mathbb{T}M$ to $M$. The process consist of two steps: localization in the slow variable through

Nils Quetschlich, Florian J. Kiwit, Maximilian A. Wolf, Carlos A. Riofrio

Quantum computing has made tremendous improvements in both software and hardware that have sparked interest in academia and industry to realize quantum computing applications. To this end, several steps are necessary: The underlying problem must be encoded in a quantum circuit, a suitable device must be selected to execute it, and it must be compiled accordi

Martje Slob, Mariska Kriek, Aliza G. Beverage, Katherine A. Suess

We present an overview and first results from the Spectroscopic Ultradeep Survey Probing Extragalactic Near-infrared Stellar Emission (SUSPENSE), executed with NIRSpec on JWST. The primary goal of the SUSPENSE program is to characterize the stellar, chemical, and kinematic properties of massive quiescent galaxies at cosmic noon. In a single deep NIRSpec/MSA

Collin T. Christy, Kate D. Alexander, Yvette Cendes, Ryan Chornock

We present detailed radio observations of the tidal disruption event (TDE) ASASSN-19bt/AT2019ahk, obtained with the Australia Telescope Compact Array (ATCA), the Atacama Large Millimeter/submillimeter Array (ALMA), and the MeerKAT radio telescopes, spanning 40 to 1464 days after the onset of the optical flare. We find that ASASSN-19bt displays unusual radio

Peter D. Johannsen, Constantin Schrade

Arrays of superconducting qubits and cavities offer a promising route for realizing highly controllable artificial materials. However, many analog simulations of superconducting circuit hardware have focused on bosonic systems. Fermionic simulations, on the other hand, have largely relied on digital approaches that require non-local qubit couplings, which co

Domantas Burba, Hubert Dunikowski, Martin Robert-de-Saint-Vincent, Emilia Witkowska

Ultra-cold fermionic atoms, having two valence electrons, exhibit a distinctive internal state structure, wherein the nuclear spin becomes decoupled from the electronic degrees of freedom in the ground electronic state. Consequently, the nuclear spin states are well isolated from the environment, rendering these atomic systems an opportune platform for quant

Jan Heisig

The phenomena of dark matter and the baryon asymmetry pose two of the most pressing questions in today's fundamental physics. Conversion-driven freeze-out has emerged as a successful mechanism to generate the observed dark matter relic density. It supports thermalization of dark matter despite its very weak couplings aligning with the null results from direc

Laura Andrianopoli, Ruggero Noris, Mario Trigiante, Jorge Zanelli

In this letter, we construct a supersymmetric model, obtained by deforming $\mathcal N=2$ AdS$_3$ supergravity through a chiral vector component of the torsion. Moreover, we study the existence of BPS states of such theory, by inspecting the presence of Killing spinors on a specific bosonic solution.