December 2023 arXiv papers — page 68

Zhenhao He, Dario Korolija, Yu Zhu, Benjamin Ramhorst

FPGAs are increasingly prevalent in cloud deployments, serving as Smart NICs or network-attached accelerators. Despite their potential, developing distributed FPGA-accelerated applications remains cumbersome due to the lack of appropriate infrastructure and communication abstractions. To facilitate the development of distributed applications with FPGAs, in t

Fayçal Hammad, Nicolas Fleury, Parvaneh Sadeghi

We study, using the Mathisson-Papapetrou-Dixon equations, the spin oscillation of neutrinos when the latter are coupled to the scalar field of screening models of dark energy. First, we derive the transition probability formula for a left-handed neutrino to become a right-handed neutrino within a general static and spherically symmetric metric. We then apply

Akash Dhruv

Multiphysics incompressible fluid dynamics simulations play a crucial role in understanding intricate behaviors of many complex engineering systems that involve interactions between solids, fluids, and various phases like liquid and gas. Numerical modeling of these interactions has generated significant research interest in recent decades and has led to the

Niloofar Gholipour, Marcos Dias de Assuncao, Pranav Agarwal, julien gascon-samson

Emerging applications in healthcare, autonomous vehicles, and wearable assistance require interactive and low-latency data analysis services. Unfortunately, cloud-centric architectures cannot fulfill the low-latency demands of these applications, as user devices are often distant from cloud data centers. Edge computing aims to reduce the latency by enabling

Robert Brignall

The juxtaposition of permutation classes $\mathcal{C}$ and $\mathcal{D}$ is the class of all permutations formed by concatenations $\sigma\tau$, such that $\sigma$ is order isomorphic to a permutation in $\mathcal{C}$, and $\tau$ to a permutation in $\mathcal{D}$. We give simple necessary and sufficient conditions on the classes $\mathcal{C}$ and $\mathcal{D

Dario Trevisan

We establish novel rates for the Gaussian approximation of random deep neural networks with Gaussian parameters (weights and biases) and Lipschitz activation functions, in the wide limit. Our bounds apply for the joint output of a network evaluated any finite input set, provided a certain non-degeneracy condition of the infinite-width covariances holds. We d

Leonid Pekker, David Pekker, James Myrick

In this work, we extend the model of contact angles that we have previously developed for sessile drops on a wetted surface to the case of a meniscus in a capillary. The underlying physics of our model describe the intermolecular forces between the fluid and the surface of the capillary that result in the formation of a thin, non-removable fluid layer that c

David D. Nguyen, David Liebowitz, Surya Nepal, Salil S. Kanhere

In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios. Current deep learning techniques to address multiple-output problems are based on two main methodologies: (1) mixture density networks, which suffer from poor stability at high d

A. Collado Hernández, F. Marroquín, B. M. Rodríguez-Lara

We report electromagnetic field modes solving the inhomogeneous Maxwell equations for parabolic gradient index fibers in the low refractive index contrast approximation. The first family comprises accelerating fields characterized by an intensity distribution center tracing a circular trajectory transverse to the fiber optical axis. These fields maintain an

Silvia Bertoluzza, Erik Burman

We consider heterogeneous coupling problems on an abstract level, establishing fundamental principles of domain decomposition agnostic to the solvers of the local subproblems. Introducing a coupling framework reminiscent of FETI methods, but here on abstract form, we establish conditions for stability and minimal requirements for well-posedness on the contin

Han Wu, Jian-Xin Zhu, Lebing Chen, Matthew W Butcher

The two-dimensional (2D) material Cr$_2$Ge$_2$Te$_6$ is a member of the class of insulating van der Waals magnets. Here, using high resolution angle-resolved photoemission spectroscopy in a detailed temperature dependence study, we identify a clear response of the electronic structure to a dimensional crossover in the form of two distinct temperature scales

Jacopo Ghiglieri, Philipp Schicho, Niels Schlusser, Eamonn Weitz

High-energy particles traversing the Quark-Gluon plasma experience modified (massive) dispersion, although their vacuum mass is negligible compared to the kinetic energy. Due to poor convergence of the perturbative series in the regime of soft loop momenta, a more precise determination of this effective mass is needed. This paper continues our investigation

Eugene Ku

Graph Neural Networks are notorious for its memory consumption. A recent Transformer-based GNN called Graph Transformer is shown to obtain superior performances when long range dependencies exist. However, combining graph data and Transformer architecture led to a combinationally worse memory issue. We propose a novel version of "edge regularization techniqu

Ciril Bohak, Dmytro Kovalskyi, Sergey Linev, Alja Mrak Tadel

ROOT-Eve (REve), the new generation of the ROOT event-display module, uses a web server-client model to guarantee exact data translation from the experiments' data analysis frameworks to users' browsers. Data is then displayed in various views, including high-precision 2D and 3D graphics views, currently driven by THREE.js rendering engine based on WebGL tec

Giuseppe Cerati, Peter Elmer, Patrick Gartung, Leonardo Giannini

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of

Dmitry A. Zimin, Ihor Cherniukh, Simon C. Böhme, Gabriele Rainò

We present a novel electric-field-resolved approach for probing ultrafast dynamics of localized surface plasmons in metallic nanoparticles. The electric field of the broadband carrier-envelope-phase stable few-cycle light pulse employed in the experiment provides access to time-domain signatures of plasmonic dynamics that are imprinted on the pulse waveform.

Sureni Wickramasooriya, Jonathan Martin, Aniket Banerjee, Rana D. Parshad

The provision of additional food (AF) sources to an introduced predator has been identified as a mechanism to improve pest control. However, AF models with prey dependent functional responses can cause unbounded growth of the predator \cite{S27}. To avoid such dynamics, an AF model with mutual interference effect has been proposed \cite{S02}. The analysis th

Mehran Tarif, Babak Nouri Moghadam

Oceans, covering 70% of Earth's surface, arelargely unexplored, with about 95% remaining a mystery.Underwater wireless communication is pivotal in various domains,such as real-time aquatic data collection, marine surveillance,disaster prevention, archaeological exploration, andenvironmental monitoring. The Internet of Things has openednew avenues in underwat

Mohammad Hassan Naddaf, Bozena Czerny

The origin of the broad-line region (BLR) clouds in active galactic nuclei is still under discussion. We develop a scenario in which the clouds in the outer, less ionized part of the BLR are launched by the radiation pressure acting on dust. Most of the outflow forms a failed wind, so we refer to it as failed radiatively accelerated dusty outflow (FRADO), bu

József Balogh, The Nguyen, Patric R. J. Ostergard, Ethan Patrick White

We present a general method to modify existing uniquely decodable codes in the $T$-user binary adder channel. If at least one of the original constituent codes does not have average weight exactly half of the dimension, then our method produces a new set of constituent codes in a higher dimension, with a strictly higher rate. Using our method we improve the

Robinson Paniagua, Rdawa Sultan, Ahmed Refaey

With the current nations struggling to track the pandemic's trajectories. There has been a lack of transparency or real-live data streaming for pandemic cases and symptoms. This phenomenon has led to a rapid and uncontrolled spread of these deadly pandemics. One of the main issues in creating a global pandemic tracking system is the lack of standardization o

Weiguo Yin

In a previous paper [Weiguo Yin, Phys. Rev. Res. 6, 013331 (2024)], the forbidden spontaneous phase transition in the one-dimensional Ising model was found to be approachable arbitrarily closely in decorated ladders by ultranarrow phase crossover (UNPC) at a given finite temperature $T_0$ with the crossover width $2\delta T$ reduced exponentially, which rese

Ángeles Carmona, Andrés M. Encinas, María José Jiménez, Álvaro Samperio

We address the discrete inverse conductance problem for well-connected spider networks; that is, to recover the conductance function on a well-connected spider network from the Dirichlet-to-Neumann map. It is well-known that this inverse problem is exponentially ill-posed, requiring the implementation of a regularization strategy for numerical solutions. Our

Paulo Pirozelli, Marcos M. José, Paulo de Tarso P. Filho, Anarosa A. F. Brandão

Logical reasoning is central to complex human activities, such as thinking, debating, and planning; it is also a central component of many AI systems as well. In this paper, we investigate the extent to which encoder-only transformer language models (LMs) can reason according to logical rules. We ask whether those LMs can deduce theorems in propositional cal

Rudrajit Choudhuri, Dylan Liu, Igor Steinmacher, Marco Gerosa

Conversational Generative AI (convo-genAI) is revolutionizing Software Engineering (SE) as engineers and academics embrace this technology in their work. However, there is a gap in understanding the current potential and pitfalls of this technology, specifically in supporting students in SE tasks. In this work, we evaluate through a between-subjects study (N

Laila El Moujtahid, Sai Krishna Gottipati, Clodéric Mars, Matthew E. Taylor

Full automation is often not achievable or desirable in critical systems with high-stakes decisions. Instead, human-AI teams can achieve better results. To research, develop, evaluate, and validate algorithms suited for such teaming, lightweight experimentation platforms that enable interactions between humans and multiple AI agents are necessary. However, t

Geraldo Botelho, Vinícius C. C. Miranda, Pilar Rueda

First we develop a technique to construct Banach lattices of homogeneous polynomials. We obtain, in particular, conditions for the linear spans of all positive compact and weakly compact $n$-homogeneous polynomials between the Banach lattices $E$ and $F$, denoted by ${\cal P}_{\cal K}^r(^n E; F)$ and $\mathcal{P}_{\mathcal{W}}^r(^n E; F)$, to be Banach latti

Edward Humes, Mozhgan Navardi, Tinoosh Mohsenin

Demand for efficient onboard object detection is increasing due to its key role in autonomous navigation. However, deploying object detection models such as YOLO on resource constrained edge devices is challenging due to the high computational requirements of such models. In this paper, an compressed object detection model named Squeezed Edge YOLO is examine

Irma Avdic, David A. Mazziotti

Classical shadow tomography provides a randomized scheme for approximating the quantum state and its properties at reduced computational cost with applications in quantum computing. In this Letter we present an algorithm for realizing fewer measurements in the shadow tomography of many-body systems by imposing $N$-representability constraints. Accelerated to

Yuansan Liu, Sudanthi Wijewickrema, Ang Li, Christofer Bester

Generating time series data is a promising approach to address data deficiency problems. However, it is also challenging due to the complex temporal properties of time series data, including local correlations as well as global dependencies. Most existing generative models have failed to effectively learn both the local and global properties of time series d

Jared Strader, Nathan Hughes, William Chen, Alberto Speranzon

This paper proposes an approach to build 3D scene graphs in arbitrary indoor and outdoor environments. Such extension is challenging; the hierarchy of concepts that describe an outdoor environment is more complex than for indoors, and manually defining such hierarchy is time-consuming and does not scale. Furthermore, the lack of training data prevents the st

Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco

Differentially private (DP) mechanisms have been deployed in a variety of high-impact social settings (perhaps most notably by the U.S. Census). Since all DP mechanisms involve adding noise to results of statistical queries, they are expected to impact our ability to accurately analyze and learn from data, in effect trading off privacy with utility. Alarming

Wadim Strielkowski, Larisa Gorina, Elena Korneeva, Olga Kovaleva

This paper explores the role of energy-saving technologies and energy efficiency in the post-COVID era. The pandemic meant major rethinking of the entrenched patterns in energy saving and efficiency. It also provided opportunities for reevaluating energy consumption for households and industries. In addition, it highlighted the importance of employing digita

Sukriti Jaitly, Tanay Shah, Ashish Shugani, Razik Singh Grewal

We present a study on the integration of Large Language Models (LLMs) in tabular data classification, emphasizing an efficient framework. Building upon existing work done in TabLLM (arXiv:2210.10723), we introduce three novel serialization techniques, including the standout LaTeX serialization method. This method significantly boosts the performance of LLMs

Snorre H. Christiansen, Kaibo Hu, Ting Lin

We show that the cohomology of the Regge complex in three dimensions is isomorphic to $\mathcal{H}^{{\scriptscriptstyle \bullet}}_{dR}(\Omega)\otimes\mathcal{RM}$, the infinitesimal-rigid-body-motion-valued de~Rham cohomology. Based on an observation that the twisted de~Rham complex extends the elasticity (Riemannian deformation) complex to the linearized ve

Kyle Noordhoek, Christopher J. Bartel

The surface properties of solid-state materials often dictate their functionality, especially for applications where nanoscale effects become important. The relevant surface(s) and their properties are determined, in large part, by the materials synthesis or operating conditions. These conditions dictate thermodynamic driving forces and kinetic rates respons

Yesukhei Jagvaral, Francois Lanusse, Rachel Mandelbaum

Diffusion-based generative models represent the current state-of-the-art for image generation. However, standard diffusion models are based on Euclidean geometry and do not translate directly to manifold-valued data. In this work, we develop extensions of both score-based generative models (SGMs) and Denoising Diffusion Probabilistic Models (DDPMs) to the Li

Benoit Cloitre, Jeffrey Shallit

We discuss an interesting sequence defined recursively; namely, sequence A105774 from the On-Line Encyclopedia of Integer Sequences, and study some of its properties. Our main tools are Fibonacci representation, finite automata, and the Walnut theorem-prover. We also prove two new results about synchronized sequences.

M. Grundner, P. Westhoff, F. B. Kugler, O. Parcollet

Real-time calculations in tensor networks are strongly limited in time by entanglement growth, restricting the achievable frequency resolution of Green's functions, spectral functions, self-energies, and other related quantities. By extending the time evolution to contours in the complex plane, entanglement growth is curtailed, enabling numerically efficient

Charles Rajan, Nishit Asnani, Shreya Singh

Multi-document summarization is the process of automatically generating a concise summary of multiple documents related to the same topic. This summary can help users quickly understand the key information from a large collection of documents. Multi-document summarization systems are more complex than single-document summarization systems due to the need to

Roger Van Peski

We prove dynamical local limits for the singular numbers of $p$-adic random matrix products at both the bulk and edge. The limit object which we construct, the reflecting Poisson sea, may thus be viewed as a $p$-adic analogue of line ensembles appearing in classical random matrix theory. However, in contrast to those it is a discrete space Poisson-type parti

Liang Zhang, Zhelun Chen

In recent years, the rapid advancement and impressive capabilities of Large Language Models (LLMs) have been evident across various domains. This paper explores the application, implications, and potential of LLMs in building energy efficiency and decarbonization studies. The wide-ranging capabilities of LLMs are examined in the context of the building energ

Seongwon Kim, Parisa Mollaei, Amir Barati Farimani, Anne Skaja Robinson

Alzheimer's Disease (AD), a neurodegenerative disorder, is reported as one of the most severe health and socioeconomic problems in current public health. Tau proteins are assumed to be a crucial driving factor of AD that detach from microtubules (MT) and accumulate as neurotoxic aggregates in the brains of AD patients. Extensive experimental and computationa

Sushanta C. Tripathy, Kiran Jain, Shukurijon Kholikov, Rudolf Komm

We have measured zonal and meridional components of subsurface flows up to a depth of 30 Mm below the solar surface by applying the technique of ring diagram on Dopplergrams which are constructed from the spherical harmonic (SH) coefficients. The SH coefficients are obtained from the Helioseismic and Magnetic Imager (HMI) full-disk Dopplergrams. We find a go

Giulia Zheng, Elías Portolés, Alexandra Mestre-Torá, Marta Perego

Magic-angle twisted bilayer graphene (MATBG) combines in one single material different phases like insulating, metallic and superconducting. These phases and their in-situ tunability make MATBG an important platform for the fabrication of superconducting devices. We realize a split gate-defined geometry which enables us to tune the width of a superconducting

Joel Mabillard, Pierre Gaspard

The elastic and transport coefficients of a perfect face-centered cubic crystal of hard spheres are computed from the poles of the dynamic structure factor and of the spectral functions of transverse momentum density fluctuations. For such crystals, the relevant coefficients are the three isothermal elastic constants $(C_{11}^T,C_{12}^T,C_{44}^T)$, the heat

Nathan Kirk, Christiane Lemieux, Jaspar Wiart

In this paper we introduce and study nets and sequences constructed in an irrational base, focusing on the case of a base given by the golden ratio $\phi$. We provide a complete framework to study equidistribution properties of nets in base $\phi$, which among other things requires the introduction of a new concept of prime elementary intervals which differ

Abdallah Ammar, Arnaud Leclerc, Lorenzo Ugo Ancarani

The ionization by photon or electron impact of the inner (2a1) and outer (1t2) valence orbitals of the CH4 molecule is investigated theoretically. In spite of a number of approximations, including a monocentric approach and a rather simple distorting molecular potential, the calculated cross sections are overall similar to those of other theoretical methods,

Amaris V. McCarver, Thomas J. Maccarone, Scott M. Ransom, Tracy E. Clarke

We present results from a search for pulsars in globular clusters, including the discovery of a new millisecond pulsar in the stellar cluster GLIMPSE-C01. We searched for low frequency radio sources within 97 globular clusters using images from the VLA Low-band Ionosphere and Transient Experiment (VLITE) and epochs 1 and 2 of the VLITE Commensal Sky Survey (

Anqi Mu, Zhiyuan Sun, Andrew J. Millis

The qualitative reliability of the dynamical mean field theory (DMFT) is investigated for systems in which either the actual carrier density or the effective carrier density is low, by comparing the exact perturbative and dynamical mean field expressions of electron scattering rates and optical conductivities. We study two interacting systems: tight binding

R. Oubagha, B. Hamil, M. Merad, B. C. Lütfüoğlu

Recently, Rajagapol et al presented an asymptotically AdS black hole metric whose thermodynamics qualitatively mimics the behavior of the Van der Waals fluid by treating the cosmological constant as a thermodynamic pressure. In some studies in the literature, authors have discussed the effects of deformed algebras such as generalized and extended uncertainty

João Paulo S. Melo, Wagno Cesar e Silva, José A. Helayël-Neto

This contribution sets out to pursue the investigation of a supersymmetric electrodynamics model with Lorentz-symmetry violation (LSV) manifested by a space-time unbalance in the propagation of the fermionic charged matter. Despite violation of Lorentz symmetry, the supersymmetry algebra is kept untouched. A superspace approach is then adopted to build up an

Mehrad Ansari, Seyed Mohamad Moosavi

Advancements in machine learning and artificial intelligence are transforming materials discovery. Yet, the availability of structured experimental data remains a bottleneck. The vast corpus of scientific literature presents a valuable and rich resource of such data. However, manual dataset creation from these resources is challenging due to issues in mainta

Christophe Andrieu, Anthony Lee, Sam Power, Andi Q. Wang

We investigate the application of Weak Poincar\'e Inequalities (WPI) to Markov chains to study their rates of convergence and to derive complexity bounds. At a theoretical level we investigate the necessity of the existence of WPIs to ensure \mathrm{L}^{2}-convergence, in particular by establishing equivalence with the Resolvent Uniform Positivity-Improving

Alexander Karataev, Christian Forsch, Laura Cottatellucci

We consider a cell-free massive multiple-input multiple-output (CF-MaMIMO) communication system in the uplink transmission and propose a novel algorithm for blind or semi-blind joint channel estimation and data detection (JCD). We formulate the problem in the framework of bilinear inference and develop a solution based on the expectation propagation (EP) met

Konstantin Gaul, Nicholas R. Hutzler, Phelan Yu, Andrew M. Jayich

Closed-shell atoms and molecules such as Hg or TlF provide some of the best low-energy tests of hadronic $\mathcal{CP}$-violation which is considered to be a necessary ingredient to explain the observed excess of matter over antimatter in our universe. $\mathcal{CP}$-violation is, however, expected to be strongly enhanced in octupole deformed nuclei such as

Demid V. Sychev, Peigang Chen, Yuheng Chen, Morris Yang

The distinctive characteristics of light, such as high-speed and low-loss propagation, low cross-talk and low power consumption, along with photons unique quantum properties, make it most suitable for various applications in communication, high-resolution imaging, optical computing, and emerging quantum information technologies. One limiting factor, though,

Saheli Mukherjee, Bivas Mallick, Sravani Yanamandra, Samyadeb Bhattacharya

Several recent studies have demonstrated the utility of the quantum SWITCH as an important resource for enhancing the performance of various information processing tasks. In a quantum SWITCH, the advantages appear significantly due to the coherent superposition of alternative configurations of the quantum components which are controlled by an additional cont

Rémi Coulon, Francesco Fournier-Facio

We construct continuum many infinite, simple, characteristic quotients of non-abelian free groups, answering a 1978 question of James Wiegold. The method is very flexible, allowing to impose certain properties on the quotients, to generalize the construction to large classes of groups with hyperbolic features, and to produce quasi-isometrically diverse examp

Sadjad Arzash, Indrajit Tah, Andrea J. Liu, M. Lisa Manning

How do cells tune emergent properties at the scale of tissues? One class of such emergent behaviors are rigidity transitions, in which a tissue changes from a solid-like to a fluid-like state or vice versa. Here, we introduce a new way for a tissue described by a vertex model to tune its rigidity, by using ``tunable degrees of freedom." We use the vertex mod

Vishnu V. Ratnam, Jianhua Mo, Ahmad AlAmmouri, Boon L. Ng

Hybrid beamforming is an attractive solution to build cost-effective and energy-efficient transceivers for millimeter-wave and terahertz systems. However, conventional hybrid beamforming techniques rely on analog components that generate a frequency flat response such as phase-shifters and switches, which limits the flexibility of the achievable beam pattern

Madeleine Grunde-McLaughlin, Michelle S. Lam, Ranjay Krishna, Daniel S. Weld

LLM chains enable complex tasks by decomposing work into a sequence of subtasks. Similarly, the more established techniques of crowdsourcing workflows decompose complex tasks into smaller tasks for human crowdworkers. Chains address LLM errors analogously to the way crowdsourcing workflows address human error. To characterize opportunities for LLM chaining,

Mahshid Pournajar, Paolo Moretti, Seyyed Ahmad Hosseini, Michael Zaiser

Creep failure of hierarchical materials is investigated by simulation of beam network models. Such models are idealizations of hierarchical fibrous materials where bundles of load-carrying fibers are held together by multi-level (hierarchical) cross-links. Failure of individual beams is assumed to be governed by stress-assisted thermal activation over local

Asaph Lee, Mikhail Shekhirev, Mark Anayee, Yury Gogotsi

MXenes are a family of two-dimensional (2D) carbides and nitrides that display extraordinary electrical, optical, chemical, and electrochemical properties. There is a perception that MXenes are unstable and degrade quickly, limiting potential applications and requiring specific storage conditions to last for a long time. This was true for delaminated MXenes

Connie Moon Sehat, Ryan Li, Peipei Nie, Tarunima Prabhakar

In this work, we examine how fact-checkers prioritize which claims to fact-check and what tools may assist them in their efforts. Through a series of interviews with 23 professional fact-checkers from around the world, we validate that harm assessment is a central component of how fact-checkers triage their work. We also clarify the processes behind fact-che

Aranya Bhattacharya, Pingal Pratyush Nath, Himanshu Sahu

Building upon recent research in spin systems with non-local interactions, this study investigates operator growth using the Krylov complexity in different non-local versions of the Ising model. We find that the non-locality results in a faster scrambling of the operator to all sites. While the saturation value of Krylov complexity of local integrable and lo

Gage MacLin, Maxwell Hammond, Venanzio Cichella, J. Ezequiel Martin

This work introduces two multi-level control strategies to address the problem of guidance and control of underwater vehicles. An outer-loop path-following algorithm and an outer-loop trajectory tracking algorithm are presented. Both outer-loop algorithms provide reference commands that enable the generic submarine to adhere to a three-dimensional path, and

Jennet Dickinson, Rachel Kovach-Fuentes, Lindsey Gray, Morris Swartz

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector tech

Christian Muise, Sheila A. McIlraith, J. Christopher Beck

Fully Observable Non-Deterministic (FOND) planning is a variant of classical symbolic planning in which actions are nondeterministic, with an action's outcome known only upon execution. It is a popular planning paradigm with applications ranging from robot planning to dialogue-agent design and reactive synthesis. Over the last 20 years, a number of approache

Bernardo Gonçalves

In the wake of the latest trends of artificial intelligence (AI), there has been a resurgence of claims and questions about the Turing test and its value, which are reminiscent of decades of practical "Turing" tests. If AI were quantum physics, by now several "Schr\"odinger's" cats would have been killed. It is time for a historical reconstruction of Turing'

Salwua Aqreerah, Alhaam Alariyibi, Wafa El-Tarhouni

Local Binary Patterns (LBP) are extensively used to analyze local texture features of an image. Several new extensions to LBP-based texture descriptors have been proposed, focusing on improving noise robustness by using different coding or thresholding schemes. In this paper we propose three algorithms (LBP), Shift Local Binary Pattern (SLBP), and Multi Shif

Li An, Sungtak Hong, Maria Ferraris Araneta, Tara Turon

Over the past two decades, magnetic resonance spectroscopy with two-shot difference editing has been widely employed to characterize altered levels of GABA, the primary inhibitory neurotransmitter in the brain, in various neuropsychiatric disorders. This conventional technique detects the GABA H4 resonance, making it unsuitable for investigating GABA metabol

Nils Herrmann, Mariam Akhtar, Daanish Arya, Marcus W. Doherty

We demonstrate - for the first time - the application of a quantum machine learning (QML) algorithm on an on-site room-temperature quantum computer. A two-qubit quantum computer installed at the Pawsey Supercomputing Centre in Perth, Australia, is used to solve multi-class classification problems on unseen, i.e. untrained, 2D data points. The underlying 1-qu

Yanqi Song, Yusen Wu, Shengyao Wu, Dandan Li

Quantum Federated Learning (QFL) enables collaborative training of a Quantum Machine Learning (QML) model among multiple clients possessing quantum computing capabilities, without the need to share their respective local data. However, the limited availability of quantum computing resources poses a challenge for each client to acquire quantum computing capab

Heba Najm, Khirallah Elferjani, Alhaam Alariyibi

For visually impaired people, it is highly difficult to make independent movement and safely move in both indoors and outdoors environment. Furthermore, these physically and visually challenges prevent them from in day-today live activities. Similarly, they have problem perceiving objects of surrounding environment that may pose a risk to them. The proposed

Megan Kinniment, Lucas Jun Koba Sato, Haoxing Du, Brian Goodrich

In this report, we explore the ability of language model agents to acquire resources, create copies of themselves, and adapt to novel challenges they encounter in the wild. We refer to this cluster of capabilities as "autonomous replication and adaptation" or ARA. We believe that systems capable of ARA could have wide-reaching and hard-to-anticipate conseque

Motoko Fujiwara, Gonzalo Herrera

Stars can be tidally disrupted when passing near a black hole, and the debris can induce a flux of high-energy neutrinos. It has been discussed that there are hints in IceCube data of high-energy neutrinos produced in Tidal Disruption Events. The emitting region of neutrinos and photons in these astrophysical events is likely to be located in the vicinity of

Nishanth Anand, Doina Precup

Temporal difference (TD) learning is often used to update the estimate of the value function which is used by RL agents to extract useful policies. In this paper, we focus on value function estimation in continual reinforcement learning. We propose to decompose the value function into two components which update at different timescales: a permanent value fun

CMS Collaboration

The first evidence for the standard model production of a top quark in association with a W boson and a Z boson is reported. The measurement is performed in multilepton final states, where the Z boson is reconstructed via its decays to electron or muon pairs and the W boson decays either to leptons or hadrons. The analysed data were recorded by the CMS exper

Zofia Kaczmarek, Peter McGill, N. Wyn Evans, Leigh C. Smith

We analyze 1602 microlensing events found in the VISTA Variables in the Via Lactea (VVV) near-infrared (NIR) survey data. We obtain spatially-resolved, efficiency-corrected timescale distributions across the Galactic bulge ($|\ell|<10^\circ,$ $|b|<5^\circ$), using a Bayesian hierarchical model. Spatially-resolved peaks and means of the timescale distribution

Vanessa Sklyarova, Egor Zakharov, Otmar Hilliges, Michael J. Black

We present HAAR, a new strand-based generative model for 3D human hairstyles. Specifically, based on textual inputs, HAAR produces 3D hairstyles that could be used as production-level assets in modern computer graphics engines. Current AI-based generative models take advantage of powerful 2D priors to reconstruct 3D content in the form of point clouds, meshe

M. Kachelriess, M. P. Nødtvedt

It has been suggested to use seismic detectors on the Moon as a tool to search for gravitational waves in an intermediate frequency range between mHz and Hz. Employing three different spherically symmetric models for the lunar interior, we investigate the response of the Moon to gravitational waves in Einstein and Jordan-Brans-Dicke gravity. We find that the

Alex Golovin, Sabine Reffert, Akash Vani, Ulrich Bastian

Based on the astrometry and photometry in Gaia DR3, we identified new nearby white dwarfs and validated those that had been missed from recent white dwarf catalogues despite being previously documented. To ensure the reliability of their astrometric solutions, we used a cut on just two parameters from Gaia DR3: the amplitude of the image parameter determinat

Anne-Marie George, Christos Dimitrakakis

We formulate the problem of eliciting agents' preferences with the goal of finding a Kemeny ranking as a Dueling Bandits problem. Here the bandits' arms correspond to alternatives that need to be ranked and the feedback corresponds to a pairwise comparison between alternatives by a randomly sampled agent. We consider both sampling with and without replacemen

Jihang Zhu, Dawei Zhai, Cong Xiao, Wang Yao

The recent constructions of flat moir\'e minibands in specifically twisted multilayer graphene and twisted transition metal dichalcogenides (TMDs) have facilitated the observation of strong correlations with a convenient tunability. These correlations in flat bands result in the band dispersion heavily influenced by carrier densities, leading to filling-depe

Tim McCormack, Joshua Zelinsky

We use the weighted version of the arithmetic-mean-geometric-mean inequality to motivate new results about Zaremba's function, $z(n) = \sum_{d|n} \frac{\log d}{d}$. We investigate record-setting values for $z(n)$ and the related function $v(n) = \frac{z(n)}{\log \tau(n)}$ where $\tau(n)$ is the number of divisors of $n$. We show that $v(n)$ takes on a maximu

António Antunes, Sebastian Harris, Apratim Kaviraj, Volker Schomerus

In this work we initiate a positive semi-definite numerical bootstrap program for multi-point correlators. Considering six-point functions of operators on a line we reformulate the crossing symmetry equation for a pair of comb-channel expansions as a semi-definite programming problem. We provide two alternative formulations of this problem. At least one of t

Justin L. Ripley, Abhishek Hegade K. R., Rohit S. Chandramouli, and Nicolas Yunes

The gravitational waves (GWs) emitted by neutron star binaries probe the physics of matter at supra nuclear densities. During the late inspiral, tidal deformations raised on each star by the gravitational field of its companion depend crucially on the star's internal properties. The misalignment of a star's tidal bulge with its companion's gravitational fiel

Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen

Large language models have gained significant popularity because of their ability to generate human-like text and potential applications in various fields, such as Software Engineering. Large language models for code are commonly trained on large unsanitised corpora of source code scraped from the internet. The content of these datasets is memorised and can

Ben Goodberry, Daniel Orr

We formulate a precise conjecture relating integral form partially-symmetric Macdonald polynomials and the parabolic flag Hilbert schemes of Carlsson, Gorsky, and Mellit. This extends, in an explicit fashion, Haiman's realization of modified Macdonald symmetric functions via Hilbert schemes of points in the plane. As evidence for our conjecture we prove that

Ursula Hamenstädt

Let S be a closed oriented surface of genus $g\geq 0$ with $n\geq 0$ punctures and $3g-3+n\geq 5$. Let $Q$ be a connected component of a stratum in the moduli space Q(S) of area one meromorphic quadratic differentials on S with n simple poles at the punctures or in the moduli space H(S) of abelian differentials on S if n=0. For a compact subset K of Q(S) or

M. Lynne Saade, Philip Kaaret, Andrea Gnarini, Juri Poutanen

We present the first X-ray polarimetric study of the dipping accreting neutron star 4U 1624$-$49 with the Imaging X-ray Polarimetry Explorer (IXPE). We report a detection of polarization in the non-dip time intervals with a confidence level of 99.99%. We find an average polarization degree (PD) of $3.1\pm0.7$% and a polarization angle of $81\pm6$ degrees eas

Jesús Fernández, Fernando Buitrago, Benjamín Sahelices

Galaxy edges or truncations are low-surface-brightness (LSB) features located in the galaxy outskirts that delimit the distance up to where the gas density enables efficient star formation. As such, they could be interpreted as a non-arbitrary means to determine the galaxy size and this is also reinforced by the smaller scatter in the galaxy mass-size relati

Apostolos Thoma, Marius Vladoiu

We describe explicitly all multisets of weights whose defining projective toric varieties are self-dual. In addition, we describe a remarkable and unexpected combinatorial behaviour of the defining ideals of these varieties. The toric ideal of a self-dual projective variety is weakly robust, that means the Graver basis is the union of all minimal binomial ge

Himanshu Raj, Raju Venugopalan

We discuss a quantitative "double copy" between radiation from shockwave collisions in Einstein gravity and in QCD. The correspondence extends to $2\rightarrow N$ amplitudes in Regge asymptotics. The classicalization and unitarization of these amplitudes at maximal occupancy, corresponding to black hole and Color Glass Condensate (CGC) states respectively, a

Fadi Al Machot

Neural-symbolic learning, an intersection of neural networks and symbolic reasoning, aims to blend neural networks' learning capabilities with symbolic AI's interpretability and reasoning. This paper introduces an approach designed to improve the performance of neural models in learning reasoning tasks. It achieves this by integrating Answer Set Programming

Greg Jackson, Stéphane Peigné, Kazuhiro Watanabe

Results are presented for the medium-induced, soft coherent radiation spectrum for all $2\to 2$ partonic channels in QCD, at leading-order in $\alpha_s$ but beyond leading logarithmic accuracy. The general formula is valid in the full kinematic range of the underlying process, and reduces to previous results in special cases. The soft gluon radiation spectru

Shinichiro Akiyama, Raghav G. Jha, Judah Unmuth-Yockey

We study the three-dimensional $SU(2)$ principal chiral model (PCM) using different tensor renormalization group methods based on the triad and anisotropic decomposition of the tensor. The tensor network representation is formulated based on the character expansion of the Boltzmann weight. We compare the average action obtained using these two tensor network

Prakash Thakolkaran, Michael A. Espinal, Somayajulu Dhulipala, Siddhant Kumar

Spinodal metamaterials, with architectures inspired by natural phase-separation processes, have presented a significant alternative to periodic and symmetric morphologies when designing mechanical metamaterials with extreme performance. While their elastic mechanical properties have been systematically determined, their large-deformation, nonlinear responses

M. H. Montgomery, Bart H. Dunlap

Accurate models of cooling white dwarfs must treat the energy released as their cores crystallize. This phase transition slows the cooling by releasing latent heat and also gravitational energy, which results from phase separation: liquid C is released from the solid C/O core, driving an outward carbon flux. The Gaia color-magnitude diagram provides striking