arXiv papers from July 2023

Andy Vidan, Lars H. Fiedler

This paper introduces a computing framework that combines Flow-Based Programming (FBP) and Large Language Models (LLMs) to enable Just-In-Time Programming (JITP). JITP empowers users, regardless of their programming expertise, to actively participate in the development and automation process by leveraging their task-time algorithmic insights. By seamlessly i

Juan M. Z. Pretel, Sergio E. Jorás, Ribamar R. R. Reis, Sergio B. Duarte

The macroscopic properties of compact stars in modified gravity theories can be significantly different from the general relativistic (GR) predictions. Within the gravitational context of scalar-tensor theories, with a scalar field $\phi$ and coupling function $\Phi(\phi)= \exp[2\phi/\sqrt{3}]$, we investigate the hydrostatic equilibrium structure of neutron

Julius Owusu

We develop randomization-based tests for heterogeneous treatment effects in the presence of network interference. Leveraging the exposure mapping framework, we study a broad class of null hypotheses that represent various forms of constant treatment effects in networked populations. These null hypotheses, unlike the classical Fisher sharp null, are not sharp

Niraj K. Nepal, Paul C. Canfield, Lin-Lin Wang

For Y$_2$C$_3$ with a superconducting critical temperature (T$_c$) $\sim$18 K, zone-center imaginary optical phonon modes have been found for the high-symmetry $I$-$43d$ structure due to C dimer wobbling motion and electronic instability from a flat band near Fermi energy. After lattice distortion to the more stable lowest symmetry $P1$ structure, these stab

Linsey K. Rodenbach, Jason M. Underwood, Ngoc Thanh Mai Tran, Alireza R. Panna

In the revised International System of Units (SI), the ohm and the volt are realized from the von Klitzing constant and the Josephson constant, and a practical realization of the ampere is possible by applying Ohm's law directly to the quantum Hall and Josephson effects. As a result, it is possible to create an instrument capable of realizing all three prima

Ali Ayub, Alan R. Wagner

For most real-world applications, robots need to adapt and learn continually with limited data in their environments. In this paper, we consider the problem of Few-Shot class Incremental Learning (FSIL), in which an AI agent is required to learn incrementally from a few data samples without forgetting the data it has previously learned. To solve this problem

Vincent Moreau, Lê Thành Dũng Nguyên

A fundamental theme in automata theory is regular languages of words and trees, and their many equivalent definitions. Salvati has proposed a generalization to regular languages of simply typed $\lambda$-terms, defined using denotational semantics in finite sets. We provide here some evidence for its robustness. First, we give an equivalent syntactic charact

Sanad Aburass, Osama Dorgham

Vision Transformers (ViTs) have emerged as a promising approach for visual recognition tasks, revolutionizing the field by leveraging the power of transformer-based architectures. Among the various ViT models, Swin Transformers have gained considerable attention due to their hierarchical design and ability to capture both local and global visual features eff

Cristina Gavazzoni, Carolina Brito, Matthieu Wyart

We study the glass transition by exploring a broad class of kinetic rules that can significantly modify the normal dynamics of super-cooled liquids, while maintaining thermal equilibrium. Beyond the usual dynamics of liquids, this class includes dynamics in which a fraction $(1-f_R)$ of the particles can perform pairwise exchange or 'swap moves', while a fra

Han Liu, Changhao Qin, Georgios Papangelakis, Meng Lon Iu

Entanglement and correlation of quantum light can enhance LiDAR sensitivity in the presence of strong background noise. However, the power of such quantum sources is fundamentally limited to a stream of single photons and cannot compete with the detection range of high-power classical LiDAR transmitters. To circumvent this, we develop and demonstrate a quant

Sebastian Brandhofer, Ilia Polian, Kevin Krsulich

Near-term quantum computations are limited by high error rates, the scarcity of qubits and low qubit connectivity. Increasing support for mid-circuit measurements and qubit reset in near-term quantum computers enables qubit reuse that may yield quantum computations with fewer qubits and lower errors. In this work, we introduce a formal model for qubit reuse

Boah Kim, Yujin Oh, Bradford J. Wood, Ronald M. Summers

Blood vessel segmentation in medical imaging is one of the essential steps for vascular disease diagnosis and interventional planning in a broad spectrum of clinical scenarios in image-based medicine and interventional medicine. Unfortunately, manual annotation of the vessel masks is challenging and resource-intensive due to subtle branches and complex struc

Joseph Sklenar, Soho Shim, Hilal Saglam, Junseok Oh

The confluence between high-energy physics and condensed matter has produced groundbreaking results via unexpected connections between the two traditionally disparate areas. In this work, we elucidate additional connectivity between high-energy and condensed matter physics by examining the interplay between spin-orbit interactions and local symmetry-breaking

Richard Naab, Erik Ganster, Zelong Zhang

The IceCube Neutrino Observatory has discovered a diffuse neutrino flux of astrophysical origin and measures its properties in various detection channels. With more than 10 years of data, we use multiple data samples from different detection channels for a combined fit of the diffuse astrophysical neutrino spectrum. This leverages the complementary informati

Matthew Streeter

Majorization-minimization (MM) is a family of optimization methods that iteratively reduce a loss by minimizing a locally-tight upper bound, called a majorizer. Traditionally, majorizers were derived by hand, and MM was only applicable to a small number of well-studied problems. We present optimizers that instead derive majorizers automatically, using a rece

Robert L Burdett, Paul corry, David Cook, Prasad Yarlagadda

This article introduces analytical techniques and a decision support tool to support capacity assessment and case mix planning (CMP) approaches previously created for hospitals. First, an optimization model is proposed to analyse the impact of making a change to an existing case mix. This model identifies how other patient types should be altered proportiona

Ari Holtzman, Peter West, Luke Zettlemoyer

Coaxing out desired behavior from pretrained models, while avoiding undesirable ones, has redefined NLP and is reshaping how we interact with computers. What was once a scientific engineering discipline-in which building blocks are stacked one on top of the other-is arguably already a complex systems science, in which emergent behaviors are sought out to sup

Tomas Basile, Carlos Pineda

Pauli channels are fundamental in the context of quantum computing as they model the simplest kind of noise in quantum devices. We propose a quantum algorithm for simulating Pauli channels and extend it to encompass Pauli dynamical maps (parametrized Pauli channels). A parametrized quantum circuit is employed to accommodate for dynamical maps. We also establ

Robert L Burdett, Paul Corry, Prasad Yarlagadda, David Cook

Various medical and surgical units operate in a typical hospital and to treat their patients these units compete for infrastructure like operating rooms (OR) and ward beds. How that competition is regulated affects the capacity and output of a hospital. This article considers the impact of treating different patient case mix (PCM) in a hospital. As each case

Chiyu Zhang, Ji Han, Yao Zou, Kexin Dong

LiDAR sensors play an important role in the perception stack of modern autonomous driving systems. Adverse weather conditions such as rain, fog and dust, as well as some (occasional) LiDAR hardware fault may cause the LiDAR to produce pointcloud with abnormal patterns such as scattered noise points and uncommon intensity values. In this paper, we propose a n

Robert L Burdett, Paul Corry, David Cook, Prasad Yarlagadda

This article showcases a personal decision support tool (PDST) called HOPLITE, for performing insightful and actionable quantitative assessments of hospital capacity, to support hospital planners and health care managers. The tool is user-friendly and intuitive, automates tasks, provides instant reporting, and is extensible. It has been developed as an Excel

Farhad Nawaz, Tianyu Li, Nikolai Matni, Nadia Figueroa

We propose a Dynamical System (DS) approach to learn complex, possibly periodic motion plans from kinesthetic demonstrations using Neural Ordinary Differential Equations (NODE). To ensure reactivity and robustness to disturbances, we propose a novel approach that selects a target point at each time step for the robot to follow, by combining tools from contro

Robert L Burdett, Paul Corry, Prasad Yarlagadda, David Cook

A new approach to perform hospital case-mix planning (CMP) is introduced in this article. Our multi-criteria approach utilises utility functions (UF) to articulate the preferences and standpoint of independent decision makers regarding outputs. The primary aim of this article is to test whether a utility functions method (UFM) based upon the scalarization of

Mark Pollicott, Julia Slipantschuk

We estabish rigorous estimates for the Hausdorff dimension of the spectra of Laplacians associated to Sierpi\'nski lattices and infinite Sierpi\'nski gaskets and other post-critically finite self-similar sets.

Leopoldo Bertossi

We describe recent research on the use of actual causality in the definition of responsibility scores as explanations for query answers in databases, and for outcomes from classification models in machine learning. In the case of databases, useful connections with database repairs are illustrated and exploited. Repairs are also used to give a quantitative me

Aniket Dhole, Bibek Gupta, Adarsh Salagame, Xuejian Niu

This work briefly covers our efforts to stabilize the flight dynamics of Northeastern's tailless bat-inspired micro aerial vehicle, Aerobat. Flapping robots are not new. A plethora of examples is mainly dominated by insect-style design paradigms that are passively stable. However, Aerobat, in addition for being tailless, possesses morphing wings that add to

Amílcar Branquinho, Juan EF Díaz, Ana Foulquié-Moreno, Manuel Mañas

This paper investigates stochastic finite matrices and the corresponding finite Markov chains constructed using recurrence matrices for general families of orthogonal polynomials and multiple orthogonal polynomials. The paper explores the spectral theory of transition matrices, utilizing both orthogonal and multiple orthogonal polynomials. Several properties

Lucas Soster Moriggi, Érison dos Santos Rocha, Magno Valério Trindade Machado

In the present work we investigate the source of azimuthal asymmetry for nuclear collision using a model that contemplates particles produced in the initial hard collisions and the collective effects described by a Blast-Wave like expansion. The latter is described by the relaxation time approximation of the Boltzmann transport equation. The parameters regar

Ruochu Yang, Chad Lembke, Fumin Zhang, Catherine Edwards

Underwater gliders have been widely used in oceanography for a range of applications. However, unpredictable events like shark strikes or remora attachments can lead to abnormal glider behavior or even loss of the instrument. This paper employs an anomaly detection algorithm to assess operational conditions of underwater gliders in the real-world ocean envir

Chowdhury Mohammad Sakib Anwar, Konstantinos Georgalos

Gallice and Monz\'on (2019) present a natural environment that sustains full co-operation in one-shot social dilemmas among a finite number of self-interested agents. They demonstrate that in a sequential public goods game, where agents lack knowledge of their position in the sequence but can observe some predecessors' actions, full contribution emerges in e

Jacek Gosciniak, Jacob B. Khurgin

Fully CMOS-compatible photonic memory holding devices hold a potential in a development of ultrafast artificial neural networks. Leveraging the benefits of photonics such as high-bandwidth, low latencies, low-energy interconnect and high speed they can overcome the existing limits of the electronic processing. To satisfy all these requirements a new photonic

Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti

On tabular data, a significant body of literature has shown that current deep learning (DL) models perform at best similarly to Gradient Boosted Decision Trees (GBDTs), while significantly underperforming them on outlier data. However, these works often study idealized problem settings which may fail to capture complexities of real-world scenarios. We identi

Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen

We consider the problem of embedding point cloud data sampled from an underlying manifold with an associated flow or velocity. Such data arises in many contexts where static snapshots of dynamic entities are measured, including in high-throughput biology such as single-cell transcriptomics. Existing embedding techniques either do not utilize velocity informa

Artur Jeż, Anthony W. Lin, Oliver Markgraf, Philipp Rümmer

Sequence theories are an extension of theories of strings with an infinite alphabet of letters, together with a corresponding alphabet theory (e.g. linear integer arithmetic). Sequences are natural abstractions of extendable arrays, which permit a wealth of operations including append, map, split, and concatenation. In spite of the growing amount of tool sup

Bohan Zhang, Yashaswini Shivalingaiah, Ankit Agrawal

Rigorous testing of small Uncrewed Aerial Systems (sUAS) is crucial to ensure their safe and reliable deployment in the real world. sUAS developers aim to validate the reliability and safety of their applications through simulation testing. However, the dynamic nature of the real-world environment, including factors such as challenging weather conditions and

Nacira Agram, Bernt Øksendal, Frank Proske, Olena Tymoshenko

In this paper we study a Pontryagin type stochastic maximum principle for the optimal control of a system, where the state dynamics satisfy a stochastic partial differential equation (SPDE) driven by a two-parameter (time-space) Brownian motion (also called Brownian sheet). We first discuss some properties of a Brownian sheet driven linear SPDE which models

Zhichao Wang, Xin Zhou

We prove the $C^{1,1}$-regularity for stationary $C^{1,\alpha}$ ($\alpha\in(0,1)$) solutions to the multiple membrane problem. This regularity estimate was essentially used in our recent work on Yau's four minimal spheres conjecture.

Pierre J. Walker, Simon Mueller, Irina Smirnova

Thermodynamic models and, in particular, SAFT-type equations are vital in characterizing complex systems. This paper presents a framework for sampling parameter distributions in PC-SAFT and SAFT-VR Mie equations of state to understand parameter confidence intervals and correlations. We identify conserved quantities contributing to significant correlations. C

Andrea Jiménez, Kolja Knauer, Carla Negri Lintzmayer, Martín Matamala

The proper conflict-free chromatic number, $\chi_{pcf}(G)$, of a graph $G$ is the least $k$ such that $G$ has a proper $k$-coloring in which for each non-isolated vertex there is a color appearing exactly once among its neighbors. The proper odd chromatic number, $\chi_{o}(G)$, of $G$ is the least $k$ such that $G$ has a proper coloring in which for every no

Maksym Radziwiłł, Kannan Soundararajan

We establish a general principle that any lower bound on the non-vanishing of central $L$-values obtained through studying the one-level density of low-lying zeros can be refined to show that most such $L$-values have the typical size conjectured by Keating and Snaith. We illustrate this technique in the case of quadratic twists of a given elliptic curve, an

Tornike Shubitidze, Wesley A. Britton, Luca Dal Negro

Recently, materials with vanishingly small permittivity, known as epsilon-near-zero (ENZ) media, emerged as promising candidates to achieve nonlinear optical effects of unprecedented magnitude on a solid-state platform. In particular, the ENZ behavior of Indium Tin Oxide (ITO) thin films resulted in Kerr-type nonlinearity with non-perturbative refractive ind

Brendon McConnell

The log transformation of the dependent variable is not innocuous when using a difference-in-differences (DD) model. With a dependent variable in logs, the DD term captures an approximation of the proportional difference in growth rates across groups. As I show with both simulations and two empirical examples, if the baseline outcome distributions are suffic

XIn Zhang, Yuqi Song, Fei Zuo, Xiaofeng Wang

Multi-label classification is a widely encountered problem in daily life, where an instance can be associated with multiple classes. In theory, this is a supervised learning method that requires a large amount of labeling. However, annotating data is time-consuming and may be infeasible for huge labeling spaces. In addition, label imbalance can limit the per

Rohit Raj, V Susheela Devi

Legal judgment prediction is the task of predicting the outcome of court cases on a given text description of facts of cases. These tasks apply Natural Language Processing (NLP) techniques to predict legal judgment results based on facts. Recently, large-scale public datasets and NLP models have increased research in areas related to legal judgment predictio

Nils Heyer, Christian Glaser, Thorsten Glüsenkamp

The planned in-ice radio array of IceCube-Gen2 at the South Pole will provide unprecedented sensitivity to ultra-high-energy (UHE) neutrinos in the EeV range. The ability of the detector to measure the neutrino's energy and direction is of crucial importance. This contribution presents an end-to-end reconstruction of both of these quantities for both detecto

Anne Voigtländer, Morgane Houssais, Karol A. Bacik, Ian C. Bourg

Inspired by presentations by the authors during a workshop organized at the Princeton Center for Theoretical Science (PCTS) in January 2022, we present a perspective on some of the outstanding questions related to the "physics of the ground beneath our feet." These identified challenges are intrinsically shared with the field of Soft Matter but also have uni

Mohammad Jalilpour Monesi, Jonas Vanthornhout, Hugo Van hamme, Tom Francart

To investigate how the auditory system processes natural speech, models have been created to relate the electroencephalography (EEG) signal of a person listening to speech to various representations of the speech. Mainly the speech envelope has been used, but also phonetic representations. We investigated to which degree of granularity phonetic representatio

Seyed Samie Alizadeh Darbandi, Alex Fornito, Abdorasoul Ghasemi

Network control theory can be used to model how one should steer the brain between different states by driving a specific region with an input. The needed energy to control a network is often used to quantify its controllability, and controlling brain networks requires diverse energy depending on the selected input region. We use the theory of how input node

Nuno Cunha, Tiago Barros, Mário Reis, Tiago Marta

Multispectral imagery is frequently incorporated into agricultural tasks, providing valuable support for applications such as image segmentation, crop monitoring, field robotics, and yield estimation. From an image segmentation perspective, multispectral cameras can provide rich spectral information, helping with noise reduction and feature extraction. As su

Zhili Yuan, Jialin Lin, Dandan Zhang

Segmenting and recognizing surgical operation trajectories into distinct, meaningful gestures is a critical preliminary step in surgical workflow analysis for robot-assisted surgery. This step is necessary for facilitating learning from demonstrations for autonomous robotic surgery, evaluating surgical skills, and so on. In this work, we develop a hierarchic

Serge Gladkoff, Lifeng Han, Gleb Erofeev, Irina Sorokina

Translation Quality Evaluation (TQE) is an essential step of the modern translation production process. TQE is critical in assessing both machine translation (MT) and human translation (HT) quality without reference translations. The ability to evaluate or even simply estimate the quality of translation automatically may open significant efficiency gains thr

François Remy, Simone Scaboro, Beatrice Portelli

Biomedical entity linking, also known as biomedical concept normalization, has recently witnessed the rise to prominence of zero-shot contrastive models. However, the pre-training material used for these models has, until now, largely consisted of specialist biomedical content such as MIMIC-III clinical notes (Johnson et al., 2016) and PubMed papers (Sayers

Abdurrahman Elmaghbub, Vincent Immler, Bechir Hamdaoui

Deep learning-based RF fingerprinting offers great potential for improving the security robustness of various emerging wireless networks. Although much progress has been done in enhancing fingerprinting methods, the impact of device hardware stabilization and warm-up time on the achievable fingerprinting performances has not received adequate attention. As s

Hussain Ahmad Madni, Rao Muhammad Umer, Gian Luca Foresti

Federated Learning (FL) is an evolving machine learning method in which multiple clients participate in collaborative learning without sharing their data with each other and the central server. In real-world applications such as hospitals and industries, FL counters the challenges of data heterogeneity and model heterogeneity as an inevitable part of the col

Vikram Jain, Matheus Cavalcante, Nazareno Bruschi, Michael Rogenmoser

Emerging deep neural network (DNN) applications require high-performance multi-core hardware acceleration with large data bursts. Classical network-on-chips (NoCs) use serial packet-based protocols suffering from significant protocol translation overheads towards the endpoints. This paper proposes PATRONoC, an open-source fully AXI-compliant NoC fabric to be

E. Kun, S. Britzen, S. Frey, K. É. Gabányi

In a previous work, we have identified the spin of the dominant black hole of a binary from its jet properties. Analysing Very Long Baseline Array (VLBA) observations of the quasar S5~1928+738, taken at $15$-GHz during $43$ epochs between $1995.96$ and $2013.06$, we showed that the inclination angle variation of the inner ($<2$~mas) jet symmetry axis natural

Mohammad Panahazari, Matthew Koscak, Jianhua Zhang, Daqing Hou

With the proliferation of distributed energy resources (DERs) in the distribution grid, it is a challenge to effectively control a large number of DERs resilient to the communication and security disruptions, as well as to provide the online grid services, such as voltage regulation and virtual power plant (VPP) dispatch. To this end, a hybrid feedback-based

Mário j. de Oliveira

We show that the dynamics of a quantum system can be represented by the dynamics of an underlying classical systems obeying the Hamilton equations of motion. This is achieved by transforming the phase space of dimension $2n$ into a Hilbert space of dimension $n$ which is obtained by a peculiar canonical transformation that changes a pair of real canonical va

Yuta Michimura, Haoyu Wang, Francisco Salces-Carcoba, Christopher Wipf

Crystalline materials are promising candidates as substrates or high-reflective coatings of mirrors to reduce thermal noises in future laser interferometric gravitational wave detectors. However, birefringence of such materials could degrade the sensitivity of gravitational wave detectors, not only because it can introduce optical losses, but also because it

Gregory D. Fleishman, Gelu M. Nita, Galina G. Motorina

Solar flares are driven by release of the free magnetic energy and its conversion to other forms of energy -- kinetic, thermal, and nonthermal. Quantification of partitions between these energy components and their evolution is needed to understand the solar flare phenomenon including nonthermal particle acceleration, transport, and escape and the thermal pl

Martin Büßemeyer, Max Reimann, Benito Buchheim, Amir Semmo

We present a novel method for the interactive control of geometric abstraction and texture in artistic images. Previous example-based stylization methods often entangle shape, texture, and color, while generative methods for image synthesis generally either make assumptions about the input image, such as only allowing faces or do not offer precise editing co

Liran Wang, Xunzhu Tang, Yichen He, Changyu Ren

Commit message generation (CMG) is a challenging task in automated software engineering that aims to generate natural language descriptions of code changes for commits. Previous methods all start from the modified code snippets, outputting commit messages through template-based, retrieval-based, or learning-based models. While these methods can summarize wha

Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M. M. Frey

Node classification is one of the core tasks on attributed graphs, but successful graph learning solutions require sufficiently labeled data. To keep annotation costs low, active graph learning focuses on selecting the most qualitative subset of nodes that maximizes label efficiency. However, deciding which heuristic is best suited for an unlabeled graph to

David Gontier, Adechola E. K. Kouande, Éric Séré

In this paper we consider stationary states of the SSH model for infinite polyacetylene chains that are homoclinic or heteroclinic connections between two-periodic dimerized states. We prove that such connections converge exponentially fast to the corresponding asymptotic periodic states.

Sanjay Lall, Calin Cascaval, Martin Izzard, Tammo Spalink

We introduce logical synchrony, a framework that allows distributed computing to be coordinated as tightly as in synchronous systems without the distribution of a global clock or any reference to universal time. We develop a model of events called a logical synchrony network, in which nodes correspond to processors and every node has an associated local cloc

Shahaf Bassan, Guy Amir, Davide Corsi, Idan Refaeli

Deep neural networks (DNNs) are increasingly being used as controllers in reactive systems. However, DNNs are highly opaque, which renders it difficult to explain and justify their actions. To mitigate this issue, there has been a surge of interest in explainable AI (XAI) techniques, capable of pinpointing the input features that caused the DNN to act as it

Chester Holtz, Pengwen Chen, Alexander Cloninger, Chung-Kuan Cheng

Motivated by the need to address the degeneracy of canonical Laplace learning algorithms in low label rates, we propose to reformulate graph-based semi-supervised learning as a nonconvex generalization of a \emph{Trust-Region Subproblem} (TRS). This reformulation is motivated by the well-posedness of Laplacian eigenvectors in the limit of infinite unlabeled

Sinan Allak

This paper presents a comprehensive X-ray and multi-wavelength study of ultraluminous X-ray sources (ULXs) in NGC 1566 using archival Chandra, Swift/XRT, James Webb Space Telescope, JWST, and Hubble Space Telescope, HST observations. The main results are, first, from the hardness ratio diagram, where spectral state transitions from hard to soft as seen in ty

Zohreh Farmani, Nazanin Ghods, Harkirat Singh, Jing Wang

Slowly sheared particulate media like sand and suspensions flow heterogeneously as they yield via narrow shear bands where most of the strain is accumulated. Understanding shear band localization from microscopics is still a major challenge. One class of so-called non-local theories identified that the width of the shearing zone should depend on the stress f

Qian Qin

This article studies the convergence properties of trans-dimensional MCMC algorithms when the total number of models is finite. It is shown that, for reversible and some non-reversible trans-dimensional Markov chains, under mild conditions, geometric convergence is guaranteed if the Markov chains associated with the within-model moves are geometrically ergod

Cory T. Aitchison, Daniel Bulmash, Arpit Dua, Andrew C. Doherty

Haah's cubic code is the prototypical type-II fracton topological order. It instantiates the no string-like operator property that underlies the favorable scaling of its code distance and logical energy barrier. Previously, the cubic code was only explored in translation-invariant systems on infinite and periodic lattices. In these settings, the code distanc

Hemn Barzan Abdalla, Awder Ahmed, Bahtiyar Mehmed, Mehdi Gheisari

Online reviews play a crucial role in shaping consumer decisions, especially in the context of e-commerce. However, the quality and reliability of these reviews can vary significantly. Some reviews contain misleading or unhelpful information, such as advertisements, fake content, or irrelevant details. These issues pose significant challenges for recommendat

R. Seutin, O. J. Hernandez, T. Miyagi, S. Bacca

Many-body approaches for atomic nuclei generally rely on a basis expansion of the nuclear states, interactions, and current operators. In this work, we derive the representation of the magnetic dipole operator in plane-wave and harmonic-oscillator basis states, as needed for Faddeev calculations of few-body systems or many-body calculations within, e.g., the

Qingyuan Jiang, Volkan Isler

Capturing and reconstructing a human actor's motion is important for filmmaking and gaming. Currently, motion capture systems with static cameras are used for pixel-level high-fidelity reconstructions. Such setups are costly, require installation and calibration and, more importantly, confine the user to a predetermined area. In this work, we present a drone

Martin Hirzel, Michael Feffer

There have been many papers with algorithms for improving fairness of machine-learning classifiers for tabular data. Unfortunately, most use only very few datasets for their experimental evaluation. We introduce a suite of functions for fetching 20 fairness datasets and providing associated fairness metadata. Hopefully, these will lead to more rigorous exper

P. Scicluna, S. Waterval, D. A. Vasquez-Torres, S. Srinivasan

Time-domain observations are increasingly important in astronomy, and are often the only way to study certain objects. The volume of time-series data is increasing dramatically as new surveys come online - for example, the Vera Rubin Observatory will produce 15 terabytes of data per night, and its Legacy Survey of Space and Time (LSST) is expected to produce

S. Ayik, M. Arik, E. Erbayri, O. Yilmaz

Multinucleon transfer mechanism in collision of ${}^{160}\mathrm{Gd}+{}^{186}\mathrm{W}$ system is investigated in the framework of quantal transport description, based on the stochastic mean-field (SMF) theory. The SMF theory provides a microscopic approach for nuclear dynamics beyond the time-dependent Hartree-Fock (TDHF) approach by including mean-field f

Jeffrey W. Johnston

How to make artificial intelligence (AI) systems safe and aligned with human values is an open research question. Proposed solutions tend toward relying on human intervention in uncertain situations, learning human values and intentions through training or observation, providing off-switches, implementing isolation or simulation environments, or extrapolatin

Dženan Lapandić, Christos K. Verginis, Dimos V. Dimarogonas, Bo Wahlberg

We develop an algorithm to control an underactuated unmanned surface vehicle (USV) using kinodynamic motion planning with funnel control (KDF). KDF has two key components: motion planning used to generate trajectories with respect to kinodynamic constraints, and funnel control, also referred to as prescribed performance control, which enables trajectory trac

Lanhong Yao, Zheyuan Zhang, Ulas Bagci

Brain tumor segmentation is an active research area due to the difficulty in delineating highly complex shaped and textured tumors as well as the failure of the commonly used U-Net architectures. The combination of different neural architectures is among the mainstream research recently, particularly the combination of U-Net with Transformers because of thei

Yassine Ghannane, Mohamed S. Abdelfattah

Datacenters are increasingly becoming heterogeneous, and are starting to include specialized hardware for networking, video processing, and especially deep learning. To leverage the heterogeneous compute capability of modern datacenters, we develop an approach for compiler-level partitioning of deep neural networks (DNNs) onto multiple interconnected hardwar

David N. Pham, Fei Ye

Left-invariant Hermitian and Gauduchon connections are studied on an arbitrary Lie group $G$ equipped with an arbitrary left-invariant almost Hermitian structure $(\langle\cdot,\cdot\rangle,J)$. The space of left-invariant Hermitian connections is shown to be in one-to-one correspondence with the space $\wedge^{(1,1)}\mathfrak{g}^\ast\otimes \mathfrak{g}$ of

Chak Shing Lee, François P. Hamon, Nicola Castelletto, Panayot S. Vassilevski

A full approximation scheme (FAS) nonlinear multigrid solver for two-phase flow and transport problems driven by wells with multiple perforations is developed. It is an extension to our previous work on FAS solvers for diffusion and transport problems. The solver is applicable to discrete problems defined on unstructured grids as the coarsening algorithm is

Bruno Ipaves, João F. Justo, Biplab Sanyal, Lucy V. C. Assali

In the present paper, we investigate the structural, thermodynamic, dynamic, elastic, and electronic properties of doped 2D diamond C$_4$X$_2$ (X = B or N) nanosheets in both AA$'$A$''$ and ABC stacking configurations, by first-principles calculations. Those systems are composed of 3 diamond-like graphene sheets, with an undoped graphene layer between two 50

Chao Huang, Susan Liang, Yapeng Tian, Anurag Kumar

We propose DAVIS, a Diffusion-based Audio-VIsual Separation framework that solves the audio-visual sound source separation task through generative learning. Existing methods typically frame sound separation as a mask-based regression problem, achieving significant progress. However, they face limitations in capturing the complex data distribution required fo

Kunal S. Narkhede, Dhruv A. Thanki, Abhijeet M. Kulkarni, Ioannis Poulakakis

Humanoid robots are expected to navigate in changing environments and perform a variety of tasks. Frequently, these tasks require the robot to make decisions online regarding the speed and precision of following a reference path. For example, a robot may want to decide to temporarily deviate from its path to overtake a slowly moving obstacle that shares the

Stewart N. Ethier, Jiyeon Lee

In a previous paper, we considered several models of the parlor game baccara chemin de fer, including Model B2 (a $2\times2^{484}$ matrix game) and Model B3 (a $2^5\times2^{484}$ matrix game), both of which depend on a positive-integer parameter $d$, the number of decks. The key to solving the game under Model B2 was what we called Foster's algorithm, which

A. Irles

The proposed LUXE experiment (LASER Und XFEL Experiment) at DESY, Hamburg, using the 16.5 GeV electron beam from the European XFEL, aims to probe QED in the non-perturbative regime created in collisions between high-intensity laser pulses and high-energy electron or photon beams. In this strong-field regime, where the electromagnetic field of the laser is ab

Rushrukh Rayan, Cogan Shimizu, Heidi Sieverding, Pascal Hitzler

The Metadata Object Description Schema (MODS) was developed to describe bibliographic concepts and metadata and is maintained by the Library of Congress. Its authoritative version is given as an XML schema based on an XML mindset which means that it has significant limitations for use in a knowledge graphs context. We have therefore developed the Modular MOD

Valeri P. Frolov, Jose Pinedo Soto

In the present paper, we discuss a nonlocal modification of the Kerr metric. Our starting point is the Kerr-Schild form of the Kerr metric $g_{\mu\nu}=\eta_{\mu\nu}+\Phi l_{\mu}l_{\mu}$. Using Newman's approach we identify a shear free null congruence $\boldsymbol{l}$ with the generators of the null cone with apex at a point $p$ in the complex space. The Ker

Sergey V. Astashkin, Per G. Nilsson

We investigate connections between upper/lower estimates for Banach lattices and the notion of relative s-decomposability, which has roots in interpolation theory. To get a characterization of relatively s-decomposable Banach lattices in terms of the above estimates, we assign to each Banach lattice X two sequence spaces XU and XL that are largely determined

Tatsuya Daniel, Marcell Howard, Morgane König

Cosmological gravitational wave backgrounds (CGWBs) are the conglomeration of unresolved gravitational wave signals from early Universe sources, which make them a promising tool for cosmologists. Because gravitons decouple from the cosmic plasma early on, one can consider interactions between gravitons and any particle species that were present in the very e

Anne Dattilo, Natalie M. Batalha, Steve Bryson

We present Kepler exoplanet occurrence rates for planets between $0.5-16$ R$_\oplus$ and between $1-400$ days. To measure occurrence, we use a non-parametric method via a kernel density estimator and use bootstrap random sampling for uncertainty estimation. We use a full characterization of completeness and reliability measurements from the Kepler DR25 catal

Julie A. Adams, Joshua Hamell, Phillip Walker

An open research question has been whether a single human can supervise a true heterogeneous swarm of robots completing tasks in real world environments. A general concern is whether or not the human's workload will be taxed to the breaking point. The Defense Advanced Research Projects Agency's OFFsensive Swarm-Enabled Tactics program's field exercises that

Claudio Bonati, Andrea Pelissetto, Ettore Vicari

We study the topological phase transitions occurring in three-dimensional (3D) multicomponent lattice Abelian-Higgs (LAH) models, in which an $N$-component scalar field is minimally coupled with a noncompact Abelian gauge field, with a global SU($N$) symmetry. Their phase diagram presents a high-temperature Coulomb (C) phase, and two low-temperature molecula

Akash Anumarlapudi, Anna Ehlke, Megan L. Jones, David L. Kaplan

We present the detection of 661 known pulsars observed with the Australian SKA Pathfinder (ASKAP) telescope at 888 MHz as a part of the Rapid ASKAP Continuum Survey (RACS). Detections were made through astrometric coincidence and we estimate the false alarm rate of our sample to be ~0.5%. Using archival data at 400 and 1400 MHz, we estimate the power law spe

Juliana Coelho

We study the gonality of curves $C$ over $\mathbb C$ whose normalization is composed of one or two copies of $\mathbb P^1$. In the first case, $C$ is a nodal curve with $g(C)$ nodes, and in the second case $C$ is a so-called binary curve. In any case we show that the usual bound $\mathrm{gon}(C)\leq\lfloor\frac{g(C)+3}{2}\rfloor$ holds if $g(C)\geq 2$, with

Viktor Rakhmatulin, Denis Grankin, Mikhail Konenkov, Sergei Davidenko

The growing use of robots in urban environments has raised concerns about potential safety hazards, especially in public spaces where humans and robots may interact. In this paper, we present a system for safe human-robot interaction that combines an infrared (IR) camera with a wearable marker and airflow potential field. IR cameras enable real-time detectio

Kacper Błachut, Tomasz Kowalczyk

We show that the Pythagoras number of rings of type $\mathbb{R}[x,y, \sqrt{f(x,y)}]$ is infinite, provided that the polynomial $f(x,y)$ satisfies some mild conditions.

Santiago Rojas-Rojas, Daniel Martínez, Kei Sawada, Luciano Pereira

With the advent of quantum technology, the interest in communication tasks assisted by quantum systems has increased both in academia and industry. Nonetheless, the transmission of a quantum state in real-world scenarios is bounded by environmental noise, so that the quantum channel is an open quantum system. In this work, we study a high-dimensional open qu