December 2023 arXiv papers — page 35

Andy Buckley, Louie Corpe, Matthew Filipovich, Christian Gutschow

Histogramming is often taken for granted, but the power and compactness of partially aggregated, multidimensional summary statistics, and their fundamental connection to differential and integral calculus make them formidable statistical objects, especially when very large data volumes are involved. But expressing these concepts robustly and efficiently in h

Rahul N. Chacko, François P. Landes, Giulio Biroli, Olivier Dauchot

Convincing evidence of domain growth in the heating of ultrastable glasses suggests that the equilibration dynamics of super-cooled liquids could be driven by a nucleation and growth mechanism. We investigate this possibility by simulating the equilibration dynamics of a model glass during both heating and cooling between poorly and well-annealed states. Tho

Xingfang Wu, Heng Li, Nobukazu Yoshioka, Hironori Washizaki

One goal of technical online communities is to help developers find the right answer in one place. A single question can be asked in different ways with different wordings, leading to the existence of duplicate posts on technical forums. The question of how to discover and link duplicate posts has garnered the attention of both developer communities and rese

Anindita Samanta, Subir Majumder, Hasan Ibrahim, Prasad Enjeti

In this paper, we developed an Electromagnetic Transient (EMT) model tailored for large cryptocurrency mining loads to understand the cross-interaction of these loads with the electric grid. The load model has been built using Electromagnetic Transients Program (EMTP) software. We have cross-validated the performance of the EMT model of the load with commerc

Tobias Becker, André Eckardt

Time-local quantum master equations that describe open quantum systems beyond the limit of ultraweak system-bath coupling are often not of Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) form. Prominent examples are the Redfield equation approximating general open quantum systems and the Hu-Paz-Zhang equation exactly describing a damped harmonic oscillator. Her

Gianmichele Blasi, Shishir Khandelwal, Géraldine Haack

Transport in open quantum systems can be explored through various theoretical frameworks, including the quantum master equation, scattering matrix, and Heisenberg equation of motion. The choice of framework depends on factors such as the presence of interactions, the coupling strength between the system and environment, and whether the focus is on steady-sta

Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman

The integration of different imaging modalities, such as structural, diffusion tensor, and functional magnetic resonance imaging, with deep learning models has yielded promising outcomes in discerning phenotypic characteristics and enhancing disease diagnosis. The development of such a technique hinges on the efficient fusion of heterogeneous multimodal feat

Benjamin Scellier, Siddhartha Mishra

Resistor networks have recently been studied as analog computing platforms for machine learning, particularly due to their compatibility with the Equilibrium Propagation training framework. In this work, we explore the computational capabilities of these networks. We prove that electrical networks consisting of voltage sources, linear resistors, diodes, and

Yifan Lu, Zachary S. C. Picker, Alexander Kusenko

Recent observations of the high-redshift universe have uncovered a significant number of active galactic nuclei, implying that supermassive black holes (SMBHs) would have to have been formed at much earlier times than expected. Direct collapse of metal-free gas clouds to SMBHs after recombination could help explain the early formation of SMBHs, but this scen

Walter H. Baron, Nahuel A. Yazbek

A non geometric sector of the duality group emerging in Kaluza-Klein reductions is realized as an effective symmetry in the low energy action of uncompactified type II theories. This is achieved by extending the so called $\beta$ symmetry of the universal NS-NS sector to the R-R sector of type IIA, IIB and massive type IIA.

Hung T. Diep, Miron Kaufman, Sanda Kaufman

In this paper, using Monte Carlo simulations we show that the Blume-Capel model gives rise to the social depolarization. This model borrowed from statistical physics uses the continuous Ising spin varying from -1 to 1 passing by zero to express the political stance of an individual going from ultra-left (-1) to ultra-right (+1). The particularity of the Blum

HyunJun Jung, Nikolas Brasch, Jifei Song, Eduardo Perez-Pellitero

Recent advances in neural radiance fields enable novel view synthesis of photo-realistic images in dynamic settings, which can be applied to scenarios with human animation. Commonly used implicit backbones to establish accurate models, however, require many input views and additional annotations such as human masks, UV maps and depth maps. In this work, we p

Ernesto Lang Oreamuno, Rohan Faiyaz Khan, Abdul Ali Bangash, Catherine Stinson

Model stores offer third-party ML models and datasets for easy project integration, minimizing coding efforts. One might hope to find detailed specifications of these models and datasets in the documentation, leveraging documentation standards such as model and dataset cards. In this study, we use statistical analysis and hybrid card sorting to assess the st

A. Santos, C. D. Kilpatrick, C. R. Bom, P. Darc

We present the S-PLUS Transient Extension Program (STEP): a supernova and fast transient survey conducted in the southern hemisphere using data from the Southern Photometric Local Universe Survey (S-PLUS) Main Survey and the T80-South telescope. Transient astrophysical phenomena have a range of interest that goes through different fields of astrophysics and

Daniel G. Figueroa, Adrien Florio, Francisco Torrenti

We discuss the present state and planned updates of CosmoLattice, a cutting-edge code for lattice simulations of non-linear dynamics of scalar-gauge field theories in an expanding background. We first review current capabilities of the code, including the simulation of interacting singlet scalars and of Abelian and non-Abelian scalar-gauge theories. We also

Kexuan Li

Genome-Wide Association Studies (GWAS) face unique challenges in the era of big genomics data, particularly when dealing with ultra-high-dimensional datasets where the number of genetic features significantly exceeds the available samples. This paper introduces an extension to the feature selection methodology proposed by Mirzaei et al. (2020), specifically

M. C. Rahn, M. N. Wilson, T. J. Hicken, F. L. Pratt

Eu$_5$In$_2$Sb$_6$ is a member of a family of orthorhombic nonsymmorphic rare-earth intermetallics that combines large localized magnetic moments and itinerant exchange with a low carrier density and perpendicular glide planes. This may result in special topological crystalline (wallpaper fermion) or axion insulating phases. Recent studies of Eu$_5$In$_2$Sb$

Subhaditya Bhattacharya, Niloy Mondal, Rishav Roshan, Drona Vatsyayan

We analyse a model that connects the neutrino sector and the dark sector of the universe via a mediator $\Phi$, stabilised by a discrete $Z_4$ symmetry that breaks to a remnant $Z_2$ upon $\Phi$ acquiring a non-zero vacuum expectation value ($v_\phi$). The model accounts for the observed baryon asymmetry of the universe via additional contributions to the ca

Tatyana A. Kozlovskaya

In the present paper we define homogeneous algebraic systems. Particular cases of these systems are: semigroup (monoid, group) system. These algebraic systems were studied by J. Loday, A. Zhuchok, T. Pirashvili, N. Koreshkov. Quandle systems were introduced and studied by V. Bardakov, D. Fedoseev, V. Turaev. We construct some group systems on the set of squa

Emmet P. Byrne

We analyse the real part of one-loop five-parton amplitudes in the next-to-multi-Regge kinematic (NMRK) limit, to leading power, and to finite order in the dimensional regularisation parameter. To leading logarithmic (LL) accuracy, it is known that five-parton amplitudes in this limit are given to all-orders by a single factorised expression, in which the pa

Miki Nakajima, Hidenori Genda, Erik Asphaug, Shigeru Ida

One of the unique aspects of Earth is that it has a fractionally large Moon, which is thought to have formed from a Moon-forming disk generated by a giant impact. The Moon stabilizes the Earth's spin axis at least by several degrees and contributes to Earth's stable climate. Given that impacts are common during planet formation, exomoons, which are moons aro

Juliano Pinto, Georg Hess, Yuxuan Xia, Henk Wymeersch

Multi-object tracking (MOT) is the task of estimating the state trajectories of an unknown and time-varying number of objects over a certain time window. Several algorithms have been proposed to tackle the multi-object smoothing task, where object detections can be conditioned on all the measurements in the time window. However, the best-performing methods s

Erin Lipman, Scott Moser, Abel Rodriguez

Spatial voting models of legislators' preferences are used in political science to test theories about their voting behavior. These models posit that legislators' ideologies as well as the ideologies reflected in votes for and against a bill or measure exist as points in some low dimensional space, and that legislators vote for positions that are close to th

Christo Meriwether Keller, Stephan Eidenbenz, Andreas Bärtschi, Daniel O'Malley

Quantum computing is an emerging topic in engineering that promises to enhance supercomputing using fundamental physics. In the near term, the best candidate algorithms for achieving this advantage are variational quantum algorithms (VQAs). We design and numerically evaluate a novel ansatz for VQAs, focusing in particular on the variational quantum eigensolv

Pengcheng Liao, Quntao Zhuang

Given a quantum system $S$ entangled with another system $I$, the entanglement testing problem arises, prompting the identification of the system $S$ within a set of $m \ge 2$ identical systems. This scenario serves as a model for the measurement task encountered in quantum ranging and entanglement-assisted communication [Phys. Rev. Lett. 126, 240501, (2021)

Wouter M. Kouw

We propose an adaptive model-predictive controller that balances driving the system to a goal state and seeking system observations that are informative with respect to the parameters of a nonlinear autoregressive exogenous model. The controller's objective function is derived from an expected free energy functional and contains information-theoretic terms e

Yuxin Chang, Alex Boyd, Padhraic Smyth

Neural marked temporal point processes have been a valuable addition to the existing toolbox of statistical parametric models for continuous-time event data. These models are useful for sequences where each event is associated with a single item (a single type of event or a "mark") -- but such models are not suited for the practical situation where each even

Manuel De León, Víctor M. Jiménez

In this paper we study contact nonholonomic mechanical sys\-tems. We construct a general framework for non-holonomic constraints in contact geometry and, in this framework, we define different nonholonomic brackets using con\-venient \linebreak decompositions of the tangent bundle of the phase space. \linebreak Furthermore, we prove that all of them coincide

Haozhan Shen, Tiancheng Zhao, Mingwei Zhu, Jianwei Yin

Visual grounding, a crucial vision-language task involving the understanding of the visual context based on the query expression, necessitates the model to capture the interactions between objects, as well as various spatial and attribute information. However, the annotation data of visual grounding task is limited due to its time-consuming and labor-intensi

Robin Marzucca, Andrew J. McLeod, Ben Page, Sebastian Pögel

This talk reviews recent developments in the field of analytical Feynman integral calculations. The central theme is the geometry associated to a given Feynman integral. In the simplest case this is a complex curve of genus zero (aka the Riemann sphere). In this talk we discuss Feynman integrals related to more complicated geometries like curves of higher ge

Rogers Kaliisa, Kamila Misiejuk, Sonsoles López-Pernas, Mohammad Khalil

While learning analytics dashboards (LADs) are the most common form of LA intervention, there is limited evidence regarding their impact on students learning outcomes. This systematic review synthesizes the findings of 38 research studies to investigate the impact of LADs on students' learning outcomes, encompassing achievement, participation, motivation, an

Akanksha Atrey, Camellia Zakaria, Rajesh Balan, Prashant Shenoy

Human social interactions occur in group settings of varying sizes and locations, depending on the type of social activity. The ability to distinguish group formations based on their purposes transforms how group detection mechanisms function. Not only should such tools support the effective detection of serendipitous encounters, but they can derive categori

Libby Tiderman, Juan Sanchez Mercedes, Fiona Romanoschi, Fabricio Murai

Social media may disseminate medical claims that highlight misleading correlations between social identifiers and diseases due to not accounting for structural determinants of health. Our research aims to identify biased medical claims on Twitter and measure their spread. We propose a machine learning framework that uses two models in tandem: RoBERTa to dete

David Frenklakh, Dmitri E. Kharzeev, Wenliang Li

Local gauge invariance of the baryon wave function leads to the emergence of a baryon junction, where three (or $N$, in $SU(N)$ gauge theory) string operators merge. The existence of baryon junction dramatically affects the dynamics of baryon stopping at high energies, and the corresponding predictions are supported by the recent data from STAR Collaboration

Charuhas Shiveshwarkar, Thejs Brinckmann, Marilena Loverde

We investigate how well the SPHEREx all-sky survey can constrain local primordial non-Gaussianity beyond the parameter $f_{\text{NL}}$ using galaxy power spectra. We forecast joint constraints on the parameters $f_{\text{NL}}$, $g_{\text{NL}}$ and $\tau_{\text{NL}}$ obtained assuming a simple two-field curvaton model of inflation. The parameters $f_{\text{NL

Snehal Singh Tomar, A. N. Rajagopalan

With the metaverse slowly becoming a reality and given the rapid pace of developments toward the creation of digital humans, the need for a principled style editing pipeline for human faces is bound to increase manifold. We cater to this need by introducing the Latents2Semantics Autoencoder (L2SAE), a Generative Autoencoder model that facilitates highly loca

Marcelo S. Tedesco, Francisco Javier Ramos Soria

This study offers an examination of grassroots innovation actors and their integration within larger economic ecosystems. Through a comparative analysis in Oaxaca, Mexico; La Plata, Argentina; and Araucania, Chile, this research sheds light on the vital role that grassroots innovation plays in broader economic ecosystems. Using Complex Network Analysis and t

Akanksha Atrey, Ritwik Sinha, Saayan Mitra, Prashant Shenoy

The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications. These applications gather contextual information about users and provide some services, such as personalized offers, through a machine learning (ML) model. A growing practice has been to deploy such ML models on the user's device to reduce laten

Andy Ray, Benjamin Devlin, Fu Yong Quah, Rahul Yesantharao

This paper introduces Hardcaml, an embedded hardware design domain specific language (DSL) implemented in the OCaml programming language. Unlike high level synthesis (HLS), Hardcaml allows for low level control of the underlying hardware for maximum productivity, while abstracting away many of the tedious aspects of traditional hardware definition languages

Erik Schroedter, Michael Bonitz

Correlated quantum many-particle systems out of equilibrium are of high interest in many fields, including correlated solids, ultracold atoms or dense plasmas. Accurate theoretical description of these systems is challenging both, conceptionally and with respect to computational resources. We have recently presented a quantum fluctuations approach which is e

Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu

Large Language Models (LLMs) have achieved unprecedented breakthroughs in various natural language processing domains. However, the enigmatic ``black-box'' nature of LLMs remains a significant challenge for interpretability, hampering transparent and accountable applications. While past approaches, such as attention visualization, pivotal subnetwork extracti

Thom Benjamin Volker, Irene Klugkist

Scientific claims gain credibility by replicability, especially if replication under different circumstances and varying designs yields equivalent results. Aggregating results over multiple studies is, however, not straightforward, and when the heterogeneity between studies increases, conventional methods such as (Bayesian) meta-analysis and Bayesian sequent

Kostas D. Housiadas, Antony N. Beris

We investigate theoretically the steady incompressible viscoelastic flow in a rigid axisymmetric tube (cylindrical pipe) with varying cross-section. We use the Oldroyd-B viscoelastic constitutive equation to model the fluid viscoelasticity. First, we derive new exact results expressed in the form of general formulas: for the average pressure-drop through the

Michael Bonitz, Jan-Philip Joost, Christopher Makait, Erik Schroedter

The theory of Nonequilibrium Green functions (NEGF) has seen a rapid development over the recent three decades. Applications include diverse correlated many-body systems in and out of equilibrium. Very good agreement with experiments and available exact theoretical results could be demonstrated if the proper selfenergy approximations were used. However, full

Ivan R. Slootweg

Proprioception is crucial in intuitive control of prosthetic limbs and therefor contributes to intuitive prosthetic use. The agonist-antagonist myoneural interface (AMI) is an prosthetic innovation with enhanced control, reduced pain, and heightened proprioceptive sensation in clinical experiments. Furthermore, studies have addressed surgical techniques to m

Mohammed Sardar, Alex Skillen, Małgorzata J. Zimoń, Samuel Draycott

We investigate the statistical recovery of missing physics and turbulent phenomena in fluid flows using generative machine learning. Here we develop a two-stage super-resolution method using spectral filtering to restore the high-wavenumber components of a Kolmogorov flow. We include a rigorous examination of generated samples through the lens of statistical

Yunbo Ou, Murod Mirzhalilov, Norbert M. Nemes, Jose L. Martinez

Exchange-coupled interfaces are pivotal in exploiting two-dimensional (2D) ferromagnetism. Due to the extraordinary correlations among charge, spin, orbital and lattice degrees of freedom, layered magnetic transition metal chalcogenides (TMCs) bode well for exotic topological phenomena. Here we report the realization of wafer-scale Cr2Te3 down to monolayer (

Felix Ulrich-Pur, Thomas Bergauer, Tetyana Galatyuk, Albert Hirtl

Ion computed tomography (iCT) is an imaging modality for the direct determination of the relative stopping power (RSP) distribution within a patient's body. Usually, this is done by estimating the path and energy loss of ions traversing the scanned volume via a tracking system and a separate residual energy detector. This study, on the other hand, introduces

Apostolos Chalkis, Thomas Kleinert, Boro Sofranac

In this paper, we present a new method to solve a certain type of Semidefinite Programming (SDP) problems. These types of SDPs naturally arise in the Quadratic Convex Reformulation (QCR) method and can be used to obtain dual bounds of Quadratic Unconstrained Binary Optimization (QUBO) problems. QUBO problems have recently become the focus of attention in the

Laura Baldelli, Jarosław Mederski, Alessio Pomponio

The paper concerns the existence of normalized solutions to a large class of quasilinear problems, including the well-known Born-Infeld operator. In the mass subcritical cases, we study a global minimization problem and obtain a ground state solution for a $(2,q)$-type operator which implies the existence of solutions to the Born-Infeld problem. We also deal

Rajlaxmi Pandey, Charul Rajput, B. Sundar Rajan

We examine a two-layered hierarchical coded caching problem, a configuration addressed in existing research. This involves a server connected to $K_1$ mirrors, each of which serves $K_2$ users. The mirrors and the users are equipped with caches of size $M_1$ and $M_2$, respectively. We propose a hierarchical coded caching scheme with coded placements that ou

Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang

In this paper, we consider federated reinforcement learning for tabular episodic Markov Decision Processes (MDP) where, under the coordination of a central server, multiple agents collaboratively explore the environment and learn an optimal policy without sharing their raw data. While linear speedup in the number of agents has been achieved for some metrics,

Mark Embree

If the numerical range of a matrix is contained in the right half of the complex plane, the GMRES algorithm for solving linear systems will reduce the norm of the residual at every iteration. In his Ph.D. dissertation, Howard Elman derived a bound that guarantees convergence. When the numerical range contains the origin, GMRES need not make progress at every

Abhinav Arun, Dipendra Singh Mal, Mehul Soni, Tomohiro Sawada

Recent advancements in deep learning have led to the development of powerful language models (LMs) that excel in various tasks. Despite these achievements, there is still room for improvement, particularly in enhancing reasoning abilities and incorporating multimodal data. This report investigates the potential impact of combining Chain-of-Thought (CoT) reas

Travis S. J. Gabriel, Saverio Cambioni

Planets are expected to conclude their growth through a series of giant impacts: energetic, global events that significantly alter planetary composition and evolution. Computer models and theory have elucidated the diverse outcomes of giant impacts in detail, improving our ability to interpret collision conditions from observations of their remnants. However

Tomohiro Oishi, Masaaki Kimura

We investigate the two-proton ($2p$) emission from $^{16}$Ne with the time-dependent $^{14}$O$+p+p$ three-body calculations. Two $0^+$ resonances are suggested to participate. For the $0^+_1$ resonance, the true emission of the spatially localized two protons is dominant, if the single-particle $s_{1/2}$ resonance locates above the $2p$ energy. By evaluating

Lukáš Gráf, Sudip Jana, Oliver Scholer, Nele Volmer

We present a proof-of-concept extension to the Standard Model that can generate a non-vanishing neutrinoless double beta decay ($0\nu\beta\beta$) signal without the existence of Majorana neutrinos or lepton number violation in the zero-density vacuum-ground-state Lagrangian. We propose that the $0\nu\beta\beta$ can be induced by the capture of an ultralight

Martin Hoferichter, Jacobo Ruiz de Elvira, Bastian Kubis, Ulf-G. Meißner

A reliable determination of the pole parameters and residues of nucleon resonances is notoriously challenging, given the required analytic continuation into the complex plane. We provide a comprehensive analysis of such resonance parameters accessible with Roy-Steiner equations for pion-nucleon scattering - a set of partial-wave dispersion relations that com

Philip C. Argyres, Mario Martone, Zekai Yu

We determine new genus 2 Seiberg-Witten curves for four dimensional rank 2 absolute N=4 superYang-Mills theories using the automorphism twist approach. The conformal manifolds of these curves agree with those predicted by S-duality orbits of global structures, and we use this to identify which of the two S-duality orbits of the $so(5) \simeq sp(4)$ superYang

Jan Albert, Johan Henriksson, Leonardo Rastelli, Alessandro Vichi

We continue the investigation of large $N$ QCD from a modern bootstrap perspective, focusing on the mesons. We make the natural spectral assumption that the $2 \to 2$ pion amplitude must contain, above the spin-one rho meson, a massive resonance of spin two. By maximizing its coupling we find a very interesting extremal solution of the dual bootstrap problem

Sam E. Cutler, Katherine E. Whitaker, John R. Weaver, Bingjie Wang

We present a measurement of the low-mass quiescent size-mass relation at Cosmic Noon (1<z<3) from the JWST PRIMER and UNCOVER treasury surveys, which highlights two distinct classes of quiescent galaxies. While the massive population is well studied at these redshifts, the low-mass end has been previously under-explored due to a lack of observing facilities

Zhangyang Qi, Ye Fang, Mengchen Zhang, Zeyi Sun

The rapidly evolving sector of Multi-modal Large Language Models (MLLMs) is at the forefront of integrating linguistic and visual processing in artificial intelligence. This paper presents an in-depth comparative study of two pioneering models: Google's Gemini and OpenAI's GPT-4V(ision). Our study involves a multi-faceted evaluation of both models across key

Soshi Shimada, Franziska Mueller, Jan Bednarik, Bardia Doosti

The physical properties of an object, such as mass, significantly affect how we manipulate it with our hands. Surprisingly, this aspect has so far been neglected in prior work on 3D motion synthesis. To improve the naturalness of the synthesized 3D hand object motions, this work proposes MACS the first MAss Conditioned 3D hand and object motion Synthesis app

Juven Wang

Family Puzzle or Generation Problem demands an explanation of why there are 3 families or generations of quarks and leptons in the Standard Model of particle physics. Here we propose a novel solution -- the multiple of 3 families of 16 Weyl fermions (namely $(N_f=3) \times 16$) in the 3+1d spacetime dimensions are topologically robust due to constraints root

Leonardo Bettini, Mattia Cenedese, George Haller

We develop a model reduction technique for non-smooth dynamical systems using spectral submanifolds. Specifically, we construct low-dimensional, sparse, nonlinear and non-smooth models on unions of slow and attracting spectral submanifolds (SSMs) for each smooth subregion of the phase space and then properly match them. We apply this methodology to both equa

Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang

Introducing interpretability and reasoning into Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) analysis is challenging, given the complexity of gigapixel slides. Traditionally, MIL interpretability is limited to identifying salient regions deemed pertinent for downstream tasks, offering little insight to the end-user (pathologist) regar

Steffen Bollmann, Chandan Setty, Urban F. P. Seifert, Elio J. König

The interplay of topological electronic band structures and strong interparticle interactions provides a promising path towards the constructive design of robust, long-range entangled many-body systems. As a prototype for such systems, we here study an exactly integrable, local model for a fractionalized topological insulator. Using a controlled perturbation

Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier

Reinforcement learning from human feedback (RLHF) is a variant of reinforcement learning (RL) that learns from human feedback instead of relying on an engineered reward function. Building on prior work on the related setting of preference-based reinforcement learning (PbRL), it stands at the intersection of artificial intelligence and human-computer interact

Riccardo Scodellaro, Ajinkya Kulkarni, Frauke Alves, Matthias Schröter

Recent successes in image analysis with deep neural networks are achieved almost exclusively with Convolutional Neural Networks (CNNs), typically trained using the backpropagation (BP) algorithm. In a 2022 preprint, Geoffrey Hinton proposed the Forward-Forward (FF) algorithm as a biologically inspired alternative, where positive and negative examples are joi

Guihong Li, Hsiang Hsu, Chun-Fu Chen, Radu Marculescu

The rapid growth of machine learning has spurred legislative initiatives such as ``the Right to be Forgotten,'' allowing users to request data removal. In response, ``machine unlearning'' proposes the selective removal of unwanted data without the need for retraining from scratch. While the Neural-Tangent-Kernel-based (NTK-based) unlearning method excels in

Eszter Székely, Lorenzo Bardone, Federica Gerace, Sebastian Goldt

Neural networks excel at discovering statistical patterns in high-dimensional data sets. In practice, higher-order cumulants, which quantify the non-Gaussian correlations between three or more variables, are particularly important for the performance of neural networks. But how efficient are neural networks at extracting features from higher-order cumulants?

Giorgos Eleftheriou, Sameer Murthy, Martí Rosselló

The superconformal index of $\frac12$-BPS states of $N=4$ U(N) super Yang-Mills theory has a known infinite $q$-series expression with successive terms suppressed by $q^N$. We derive a holographic bulk interpretation of this series by evaluating the corresponding functional integral in the dual $AdS_5 \times S^5$. The integral localizes to a product of small

Kapil Ahuja, Mithun Singh, Kuldeep Pathak, Milind B. Ratnaparkhe

Clustering species of the same plant into different groups is an important step in developing new species of the concerned plant. Phenotypic (or physical) characteristics of plant species are commonly used to perform clustering. Hierarchical Clustering (HC) is popularly used for this task, and this algorithm suffers from low accuracy. In one of the recent wo

James Gunn, Zygmunt Lenyk, Anuj Sharma, Andrea Donati

Combining complementary sensor modalities is crucial to providing robust perception for safety-critical robotics applications such as autonomous driving (AD). Recent state-of-the-art camera-lidar fusion methods for AD rely on monocular depth estimation which is a notoriously difficult task compared to using depth information from the lidar directly. Here, we

I. D. Avdeev, M. O. Nestoklon

We put forward a generalized procedure which allows to restore the bulk-like electron and hole wave functions localized in certain valleys from the wave functions of quantum confined electron/hole states obtained in atomistic calculations of nanostructures. As a demonstration, the procedure is applied to the lead chalcogenide quantum dots to extract the effe

Milos Indjin, I-Kang Liu, Nick P. Proukakis, Gerasimos Rigopoulos

We investigate the effect of self-interactions on the shape and oscillations of the solitonic core profile of condensed fuzzy dark matter systems without the backdrop of a halo, revealing universal features in terms of an appropriately scaled interaction strength characterizing the crossover between the weakly- and strongly-interacting regimes. Our semi-anal

Bodo Manthey, Nils Morawietz, Jesse van Rhijn, Frank Sommer

We show that the simplest local search heuristics for two natural Euclidean clustering problems are PLS-complete. First, we show that the Hartigan--Wong method for $k$-Means clustering is PLS-complete, even when $k = 2$. Second, we show the same result for the Flip heuristic for Max Cut, even when the edge weights are given by the (squared) Euclidean distanc

Mohsen Gholami, Rabab Ward, Z. Jane Wang

This paper proposes an end-to-end framework for generating 3D human pose datasets using Neural Radiance Fields (NeRF). Public datasets generally have limited diversity in terms of human poses and camera viewpoints, largely due to the resource-intensive nature of collecting 3D human pose data. As a result, pose estimators trained on public datasets significan

Johann Ostmeyer, Tahereh Nematiaram, Alessandro Troisi, Pavel Buividovich

We present a first-principle numerical study of charge transport in a realistic two-dimensional tight-binding model of organic molecular semiconductors. We use the Hybrid Monte Carlo (HMC) algorithm to simulate the full quantum dynamics of phonons and either a single or multiple charge carriers without any tunable parameters. We introduce a number of algorit

Lucile Cangemi, Marco Chiodaroli, Henrik Johansson, Alexander Ochirov

We construct a candidate tree-level gravitational Compton amplitude for a rotating Kerr black hole, for any quantum spin s=0,1/2,1,...,$\infty$, from which we extract the corresponding classical amplitude to all orders in the spin vector $S^\mu$. We use multiple insights from massive higher-spin quantum field theory, such as massive gauge invariance and impr

Ryan Martin

That science and other domains are now largely data-driven means virtually unlimited opportunities for statisticians. With great power comes responsibility, so it's imperative that statisticians ensure that the methods being developing to solve these problems are reliable. But reliable in what sense? This question is problematic because different notions of

Giancarlo Ferrera, Wan-Li Ju, Marek Schoenherr

In this paper, we present an algorithm to construct the qT distribution at NLO accuracy to arbitrary power precision, including the assembly of suitable zero-bin subtrahends, in a mathematically well-defined way for a generic choice of rapidity-divergence regularisation prescription. In its derivation, we divide the phase space into two sectors, the interior

Andrii Dmytryshyn

Versal deformation of a matrix A is a normal form to which all matrices A + E, close to A, can be reduced by similarity transformation smoothly depending on the entries of A + E. In this paper we discuss versal deformations and their use in codimension computations, in investigation of closure relations of orbits and bundles, in studying changes of canonical

Maximilian Balthasar Mansky, Santiago Londoño Castillo, Victor Ramos Puigvert, Claudia Linnhoff-Popien

The implementation of physical symmetries into problem descriptions allows for the reduction of parameters and computational complexity. We show the integration of the permutation symmetry as the most restrictive discrete symmetry into quantum circuits. The permutation symmetry is the supergroup of all other discrete groups. We identify the permutation with

Giorgio Trentinaglia

We extend the standard construction of the adjoint representation of a Lie groupoid to the case of an arbitrary higher Lie groupoid. As for a Lie groupoid, the adjoint representation of a higher Lie groupoid turns out to be a representation up to homotopy which is well defined up to isomorphism. Its existence and uniqueness are immediate consequences of a mo

Saugat Kandel, Siddharth Maddali, Marc Allain, Xiaojing Huang

We describe a phase-retrieval-based imaging method to directly spatially resolve the vector lattice distortions in an extended crystalline sample by explicit coupling of independent Bragg ptychography data sets into the reconstruction process. Our method addresses this multi-peak Bragg ptychography (MPBP) inverse problem by explicit gradient descent optimiza

M. C. Baldiotti, R. Fresneda

This work is a generalization of \cite{baldiotti2021} to Grassmann algebras of arbitrary dimensions. Here we present a covariant quantization scheme for pseudoclassical theories focused on non-hermitian quantum mechanics. The quantization maps canonically related pseudoclassical theories to equivalent quantum realizations in arbitrary dimensions. We apply th

Piotr Kucharski, Hélder Larraguível, Dmitry Noshchenko, Piotr Sułkowski

We analyse the structure of equivalence classes of symmetric quivers whose generating series are equal. We consider such classes constructed using the basic operation of unlinking, which increases a size of a quiver. The existence and features of such classes do not depend on a particular quiver but follow from the properties of unlinking. We show that such

R. Au-Yeung, B. Camino, O. Rathore, V. Kendon

Quantum computing promises to provide the next step up in computational power for diverse application areas. In this review, we examine the science behind the quantum hype, and the breakthroughs required to achieve true quantum advantage in real world applications. Areas that are likely to have the greatest impact on high performance computing (HPC) include

Aaron Wheeler, Jeffrey D. Varner

In this study, we developed a computational framework for simulating large-scale agent-based financial markets. Our platform supports trading multiple simultaneous assets and leverages distributed computing to scale the number and complexity of simulated agents. Heterogeneous agents make decisions in parallel, and their orders are processed through a realist

Sharath S. Girimaji

Turbulence closure modeling using machine learning is at an early crossroads. The extraordinary success of machine learning (ML) in a variety of challenging fields has given rise to justifiable optimism regarding similar transformative advances in the area of turbulence closure modeling. However, by most accounts, the current rate of progress toward accurate

Sylvian Kahane, Raymond Moreh

Mono-energetic $\gamma$-beams ($\Delata \approx$ 10 eV) based on thermal neutron capture, in a nuclear reactor, using the Mn(n, $\gamma$) reaction were utilized for generating a fast neutron source from Zinc, via the ${67}^Zn(\gamma, n)$ reaction. One of the incident $\gamma$-lines of the Mn source at $E_\gamma$ = 7244 keV, photoexcites by chance a resonance

Zhuoran Bao, Daniel F. V. James

It has been shown that the entanglement between the system and ancillary states is not a strict requirement for performing ancilla-assisted process tomography(AAPT). Instead, from a theoretical point of view, it only requires that the system-ancilla state be faithful, which, in the qubit case, is the invertibility of a certain matrix representing the state.

M. Malnou, T. F. Q. Larson, J. D. Teufel, F. Lecocq

Parametric amplifiers have become a workhorse in superconducting quantum computing, however research and development of these devices has been hampered by inconsistent, and sometimes misleading noise performance characterization methodologies. The concepts behind noise characterization are deceptively simple, and there are many places where one can make mist

F. A. Brito, C. H. A. B. Borges, J. A. V. Campos, F. G. Costa

We consider $f(R,T)$ modified theories of gravity in the context of string theory inspired dilaton gravity. We deal with a specific model that under certain conditions describes the late time Universe in accord with observational data in modern cosmology and addresses the $H_0$ tension. This is done by exploring the space of parameters made out of those comi

Wendkûuni C. Ouédraogo, Laura Plein, Kader Kaboré, Andrew Habib

The quality of software is closely tied to the effectiveness of the tests it undergoes. Manual test writing, though crucial for bug detection, is time-consuming, which has driven significant research into automated test case generation. However, current methods often struggle to generate relevant inputs, limiting the effectiveness of the tests produced. To a

Emerson A. da Silva, Leonardo A. Mozelli, Armando A. Neto, Fernando O. Souza

This paper addresses the problem of longitudinal platooning control of homogeneous vehicles subject to external disturbances, such as wind gusts, road slopes, and parametric uncertainties. Our control objective is to maintain the relative distance of the cars regarding their nearby teammates in a decentralized manner. Therefore, we proposed a novel control l

Lulu Gong, Xudong Chen, ShiNung Ching

In this paper, we study recurrent neural networks in the presence of pairwise learning rules. We are specifically interested in how the attractor landscapes of such networks become altered as a function of the strength and nature (Hebbian vs. anti-Hebbian) of learning, which may have a bearing on the ability of such rules to mediate large-scale optimization

Subhodip Panda, Prathosh AP

The heightened emphasis on the regulation of deep generative models, propelled by escalating concerns pertaining to privacy and compliance with regulatory frameworks, underscores the imperative need for precise control mechanisms over these models. This urgency is particularly underscored by instances in which generative models generate outputs that encompas

G. Alguero, G. Belanger, F. Boudjema, S. Chakraborti

micrOMEGAs is a numerical code to compute dark matter (DM) observables in generic extensions of the Standard Model of particle physics. We present a new version of micrOMEGAs that includes a generalization of the Boltzmann equations governing the DM cosmic abundance evolution which can be solved to compute the relic density of N-component DM. The direct and