July 2023 arXiv papers — page 15

Rodrigo Panosso Macedo

This work offers a didactical introduction to the calculations and geometrical properties of a static, spherically symmetric spacetime foliated by hyperboloidal time surfaces. We discuss the various degrees of freedom involved, namely the height function, responsible for introducing the hyperboloidal time coordinate, and a radial compactification function. A

Melissa van Beekveld, Mrinal Dasgupta, Basem Kamal El-Menoufi, Jack Helliwell

Jet calculus offers a unique mathematical technique to bridge the area of QCD resummation with Monte Carlo parton showers. With the ultimate goal of constructing next-to-next-to-leading logarithmic (NNLL) parton showers we study, using the language of generating functionals, the collinear fragmentation of final-state partons. In particular, we focus on the d

Gourab Giri, Bhargav Vaidya, Christian Fendt

X-shaped Radio Galaxies (XRGs) develop when certain extra-galactic jets deviate from their propagation path. An asymmetric ambient medium (Back-flow model) or complex Active Galactic Nuclei activity (Jet-reorientation model) enforcing the jet direction to deviate may cause such structures. In this context, the present investigation focuses on the modeling of

P. Cox, R. Neri, S. Berta, D. Ismail

(Abridged) Using the IRAM NOEMA interferometer, we measures the redshifts of 126 bright galaxies detected in the Herschel H-ATLAS, HeLMS, and HerS surveys. We report reliable spectroscopic redshifts for a total of 124 of the Herschel-selected galaxies. The redshifts are estimated from scans of the 3 and 2-mm bands (and, in one case, the 1-mm band) and are ba

Juanca Carrasco-Martinez, David I. Dunsky, Lawrence J. Hall, Keisuke Harigaya

We study the simplest theories with exact spacetime parity that solve the strong CP problem and successfully generate the cosmological baryon asymmetry via decays of right-handed neutrinos. Lower bounds are derived for the masses of the right-handed neutrinos and for the scale of spontaneous parity breaking, $v_R$. For generic thermal leptogenesis, $v_R \gtr

Daniel Lecoanet, Philipp V. F. Edelmann

The cores of main sequence intermediate- and high-mass stars are convective. Mixing at the radiative-convective boundary, waves excited by the convection, and magnetic fields generated by convective dynamos all influence the main sequence and post-main sequence evolution of these stars. These effects must be understood to accurately model the structure and e

Kareem El-Badry, Kevin B. Burdge, Jan van Roestel, Antonio C. Rodriguez

We report the discovery of ZTF J2020+5033, a high-mass brown dwarf (BD) transiting a low-mass star with an orbital period of 1.90 hours. Phase-resolved spectroscopy, optical and infrared light curves, and precise astrometry from Gaia allow us to constrain the masses, radii, and temperatures of both components with few-percent precision. We infer a BD mass of

Shi-Yuan Ma, Tianyu Wang, Jérémie Laydevant, Logan G. Wright

Energy efficiency in computation is ultimately limited by noise, with quantum limits setting the fundamental noise floor. Analog physical neural networks hold promise for improved energy efficiency compared to digital electronic neural networks. However, they are typically operated in a relatively high-power regime so that the signal-to-noise ratio (SNR) is

Zekun Qi, Muzhou Yu, Runpei Dong, Kaisheng Ma

Conditional 3D generation is undergoing a significant advancement, enabling the free creation of 3D content from inputs such as text or 2D images. However, previous approaches have suffered from low inference efficiency, limited generation categories, and restricted downstream applications. In this work, we revisit the impact of different 3D representations

Viviana Cuozzo, Carmelita Carbone, Matteo Calabrese, Elisabetta Carella

We present an analytical modelling of the angular cross-correlations between the Integrated Sachs Wolfe-Rees Sciama (ISWRS) effect and large-scale structure tracers in the presence of massive neutrinos. Our method has been validated against large N-body simulations with a massive neutrino particle component, namely the DEMNUni suite. We investigate the impac

Garvita Allabadi, Ana Lucic, Siddarth Aananth, Tiffany Yang

Traditional semi-supervised object detection methods assume a fixed set of object classes (in-distribution or ID classes) during training and deployment, which limits performance in real-world scenarios where unseen classes (out-of-distribution or OOD classes) may appear. In such cases, OOD data is often misclassified as ID, thus harming the ID classes accur

Tom Mens, Coen De Roover

This chapter defines and presents different kinds of software ecosystems. The focus is on the development, tooling and analytics aspects of software ecosystems, i.e., communities of software developers and the interconnected software components (e.g., projects, libraries, packages, repositories, plug-ins, apps) they are developing and maintaining. The techni

Shuyang Meng, Fionnuala Curran, Gabriel Senno, Victoria J. Wright

One of the most counterintuitive aspects of quantum theory is its claim that there is 'intrinsic' randomness in the physical world. Quantum information science has greatly progressed in the study of intrinsic, or secret, quantum randomness in the past decade. With much emphasis on device-independent and semi-device-independent bounds, one of the most basic q

Mathieu Dedenon, Claire A. Dessalles, Pau Guillamat, Aurélien Roux

Topological defects in active polar fluids can organise spontaneous flows and influence macroscopic density patterns. Both of them play, for example, an important role during animal development. Yet the influence of density on active flows is poorly understood. Motivated by experiments on cell monolayers confined to discs, we study the coupling between densi

Hanbit Oh, Ya-Hui Zhang

Recently, a 80 K superconductor was discovered in La$_3$Ni$_2$O$_7$ under high pressure. Density function theory (DFT) calculations identify $d_{x^2-y^2}$, $d_{z^2}$ as the active orbitals on the bilayer square lattice with a $d^{8-x}$ configuration of of Ni per site. One naive expectation is to describe this system in terms of a two-orbital t-J model. Howev

Erica Hammerstein, S. Bradley Cenko, Suvi Gezari, Sylvain Veilleux

The host galaxies of tidal disruption events (TDEs) have been shown to possess peculiar properties, including high central light concentrations, unusual star-formation histories, and ``green'' colors. The ubiquity of these large-scale galaxy characteristics among TDE host populations suggests they may serve to boost the TDE rate in such galaxies by influenci

Laura Lenkić, Conor Nally, Olivia C. Jones, Martha L. Boyer

We present an imaging survey of the Spitzer I star-forming region in NGC 6822 conducted with the NIRCam and MIRI instruments onboard JWST. Located at a distance of 490 kpc, NGC 6822 is the nearest non-interacting low-metallicity ($\sim$0.2 $Z_{\odot}$) dwarf galaxy. It hosts some of the brightest known HII regions in the local universe, including recently di

Joris Baan, Nico Daheim, Evgenia Ilia, Dennis Ulmer

Recent advances of powerful Language Models have allowed Natural Language Generation (NLG) to emerge as an important technology that can not only perform traditional tasks like summarisation or translation, but also serve as a natural language interface to a variety of applications. As such, it is crucial that NLG systems are trustworthy and reliable, for ex

Nathan Atkinson, Scott C. Ganz, Dorit S. Hochbaum, James B. Orlin

We present a new optimization-based method for aggregating preferences in settings where each voter expresses preferences over pairs of alternatives. Our approach to identifying a consensus partial order is motivated by the observation that collections of votes that form a cycle can be treated as collective ties. Our approach then removes unions of cycles of

Ali Ghorashi, Sachin Vaidya, Mikael Rechtsman, Wladimir Benalcazar

The topological characteristics of photonic crystals have been the subject of intense research in recent years. Despite this, the basic question of whether photonic band topology is rare or abundant -- i.e., its relative prevalence -- remains unaddressed. Here, we determine the prevalence of stable, fragile, and higher-order photonic topology in the 11 two-d

Ruopeng Gao, Limin Wang

As a video task, Multiple Object Tracking (MOT) is expected to capture temporal information of targets effectively. Unfortunately, most existing methods only explicitly exploit the object features between adjacent frames, while lacking the capacity to model long-term temporal information. In this paper, we propose MeMOTR, a long-term memory-augmented Transfo

Prajwal Bhagwat, Dominic Groß

In this work, we investigate grid-forming (GFM) control for dc/ac voltage source converters (VSC) under unbalanced system conditions and unbalanced faults. To fully leverage the degrees of freedom of VSCs, we introduce the concept of generalized three-phase GFM control that combines individual GFM controls for every phase with a phase balancing feedback. The

Alexander A. Andrianov, Danila Lyozin, Artem Starodubtsev

We perform canonical analysis of an action in which 2+1-dimensional gravity with negative cosmological constant is coupled to cylindrically symmetric dust shell. The resulting phase space is finite dimensional having geometry of SO(2; 2) group manifold. Representing the Poisson brackets by commutators results in the algebra of observables which is a quantum

Ioannis Maniadis Metaxas, Adrian Bulat, Ioannis Patras, Brais Martinez

The unsupervised pretraining of object detectors has recently become a key component of object detector training, as it leads to improved performance and faster convergence during the supervised fine-tuning stage. Existing unsupervised pretraining methods, however, typically rely on low-level information to define proposals that are used to train the detecto

Wei Ren, Xi Zhang, Jaden Ma, Xihe Han

We present a device architecture of hybrid-edge and dual-gated quantum point contact. We demonstrate improved electrostatic control over the separation, position, and coupling of each broken-symmetry compressible strip in graphene. Via low-temperature magneto-transport measurement, we demonstrate selective manipulation over the evolution, hybridization, and

Eric Bersin, Matthew Grein, Madison Sutula, Ryan Murphy

Distributing quantum information between remote systems will necessitate the integration of emerging quantum components with existing communication infrastructure. This requires understanding the channel-induced degradations of the transmitted quantum signals, beyond the typical characterization methods for classical communication systems. Here we report on

T. McBroom-Carroll, A. Schlabes, X. Xu, J. Ku

Superconducting metamaterial transmission lines implemented with lumped circuit elements can exhibit left-handed dispersion, where the group and phase velocity have opposite sign, in a frequency range relevant for superconducting artificial atoms. Forming such a metamaterial transmission line into a ring and coupling it to qubits at different points around t

Ran Dou, Jose Principe

In this paper, we propose a new event memory architecture (MemNet) for recurrent neural networks, which is universal for different types of time series data such as scalar, multivariate or symbolic. Unlike other external neural memory architectures, it stores key-value pairs, which separate the information for addressing and for content to improve the repres

F. Arco, D. Domenech, M. J. Herrero, R. A. Morales

In this work we explore the low energy effects induced from the integration of the heavy Higgs boson modes, $H$, $A$ and $H^\pm$, within the Two Higgs Doublet Model (2HDM) by assuming that the lightest Higgs boson $h$ is the one observed experimentally at $m_h \sim 125$ GeV. We work within the context of Effective Field Theories, focusing on the Higgs Effect

Davide Boscaini, Fabio Poiesi

The recent trend in deep learning methods for 3D point cloud understanding is to propose increasingly sophisticated architectures either to better capture 3D geometries or by introducing possibly undesired inductive biases. Moreover, prior works introducing novel architectures compared their performance on the same domain, devoting less attention to their ge

Patrick Vossler, Nathan Justin, Sina Aghaei, Nathanael Jo

ODTlearn is an open source Python package that provides methods for learning optimal decision trees for high-stakes predictive and prescriptive tasks based on the state-of-the-art mixed-integer optimization (MIO) framework proposed in Aghaei et al. (2025). The current version of the package provides implementations for learning optimal classification trees,

Benjamin Q. Huynh, Mathew V. Kiang

Disaster response agencies have been shifting from a paradigm of climate forecasting towards one of anticipatory action: assessing not just what the climate will be, but how it will impact specific populations, thereby enabling proactive response and resource allocation. Machine learning models are becoming exceptionally powerful at climate forecasting, but

Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier

Learning policies from previously recorded data is a promising direction for real-world robotics tasks, as online learning is often infeasible. Dexterous manipulation in particular remains an open problem in its general form. The combination of offline reinforcement learning with large diverse datasets, however, has the potential to lead to a breakthrough in

Aditya Cowsik, Matteo Ippoliti, Xiao-Liang Qi

We introduce a general approach to realize quantum states with holographic entanglement structure via monitored dynamics. Starting from random unitary circuits in $1+1$ dimensions, we introduce measurements with a spatiotemporally-modulated density. Exploiting the known critical properties of the measurement-induced entanglement transition, this allows us to

Jun Takahashi, Chaithanya Rayudu, Cunlu Zhou, Robbie King

Understanding and approximating extremal energy states of local Hamiltonians is a central problem in quantum physics and complexity theory. Recent work has focused on developing approximation algorithms for local Hamiltonians, and in particular the ``Quantum Max Cut'' (QMax-Cut) problem, which is closely related to the antiferromagnetic Heisenberg model. In

B. Z. Kopeliovich, J. Nemchik, I. K. Potashnikova, Ivan Schmidt

Heavy and light quarks produced in high-$p_T$ partonic collisions radiate differently. Heavy quarks regenerate their color field, stripped-off in the hard reaction, much faster than the light ones and radiate a significantly smaller fraction of the initial quark energy. This peculiar feature of heavy-quark jets leads to a specific shape of the fragmentation

Claudio Fontanari

Let $(X, \Delta)$ be a projective klt pair of dimension $2$ and let $L$ be a nef $\mathbb{Q}$-divisor on $X$ such that $K_X + \Delta + L$ is nef. As a complement to the Generalized Abundance Conjecture by Lazi\'c and Peternell, we prove that if $K_X + \Delta$ and $L$ are not proportional modulo numerical equivalence, then $K_X + \Delta + L$ is semiample. An

Pu Gao, Peter Nelson

Consider a random $n\times m$ matrix $A$ over the finite field of order $q$ where every column has precisely $k$ nonzero elements, and let $M[A]$ be the matroid represented by $A$. In the case that q=2, Cooper, Frieze and Pegden (RS\&A 2019) proved that given a fixed binary matroid $N$, if $k\ge k_N$ and $m/n\ge d_N$ where $k_N$ and $d_N$ are sufficiently la

Romain Taureau, Marco Cherubini, Tommaso Morresi, Michele Casula

We study the structural phase transition, originally associated with the highest superconducting critical temperature $T_c$ measured in high-pressure sulfur hydride. A quantitative description of its pressure dependence has been elusive for any \emph{ab initio} theory attempted so far, raising questions on the actual mechanism leading to the maximum of $T_c$

Paolo Amore, Ulises Zarate

We investigate the classical ground state of a large number of charges confined inside a disk and interacting via the Coulomb potential. By realizing the important role that the peripheral charges play in determining the lowest energy solutions, we have successfully implemented an algorithm that allows us to work with configurations with a desired number of

Ben Elias, Hankyung Ko, Nicolas Libedinsky, Leonardo Patimo

The Bruhat order on a Coxeter group is often described by examining subexpressions of a reduced expression. We prove that an analogous description applies to the Bruhat order on double cosets. This establishes the compatibility of the Bruhat order on double cosets with concatenation, leading to compatibility between the monoidal structure and the ideal of lo

Nathan Haboury, Mo Kordzanganeh, Sebastian Schmitt, Ayush Joshi

Managing the response to natural disasters effectively can considerably mitigate their devastating impact. This work explores the potential of using supervised hybrid quantum machine learning to optimize emergency evacuation plans for cars during natural disasters. The study focuses on earthquake emergencies and models the problem as a dynamic computational

Hoang Viet Pham, Thinh Gia Tran, Chuong Dinh Le, An Dinh Le

Innovative enhancement in embedded system platforms, specifically hardware accelerations, significantly influence the application of deep learning in real-world scenarios. These innovations translate human labor efforts into automated intelligent systems employed in various areas such as autonomous driving, robotics, Internet-of-Things (IoT), and numerous ot

Madeline R. Abbott, Walter H. Dempsey, Inbal Nahum-Shani, Cho Y. Lam

Intensive longitudinal data (ILD) collected in mobile health (mHealth) studies contain rich information on multiple outcomes measured frequently over time that have the potential to capture short-term and long-term dynamics. Motivated by an mHealth study of smoking cessation in which participants self-report the intensity of many emotions multiple times per

Zuodong Yu, Danqing Hu, Jiangfan Wang, Xinloong Han

Motivated by the emergence of higher-order van Hove singularities (VHS) with power-law divergent density of states (DOS) ($\rho_c(\omega)=\rho_0/|\omega|^{r}$, $0<r<1$) in materials, we investigate a multichannel Kondo model involving conduction electrons near the higher-order van Hove filling. This model considers $M$ channel and $N$ spin degrees of freedom

Ran Dou, Jose Principe

In recurrent neural networks, learning long-term dependency is the main difficulty due to the vanishing and exploding gradient problem. Many researchers are dedicated to solving this issue and they proposed many algorithms. Although these algorithms have achieved great success, understanding how the information decays remains an open problem. In this paper,

Ali Aït-Bachir, Charles K. Assaad, Christophe de Bignicourt, Emilie Devijver

Information technology (IT) systems are vital for modern businesses, handling data storage, communication, and process automation. Monitoring these systems is crucial for their proper functioning and efficiency, as it allows collecting extensive observational time series data for analysis. The interest in causal discovery is growing in IT monitoring systems

Tiago Leon Melo, João Bravo, Marco O. P. Sampaio, Paolo Romano

Adversarial attacks are a major concern in security-centered applications, where malicious actors continuously try to mislead Machine Learning (ML) models into wrongly classifying fraudulent activity as legitimate, whereas system maintainers try to stop them. Adversarially training ML models that are robust against such attacks can prevent business losses an

Timo Neumeier, Malte A. Peter, Daniel Peterseim, David Wiedemann

Based on the characterization of the polyconvex envelope of isotropic functions by their signed singular value representations, we propose a simple algorithm for the numerical approximation of the polyconvex envelope. Instead of operating on the $d^2$-dimensional space of matrices, the algorithm requires only the computation of the convex envelope of a funct

Muhammad Faizan, Muhammad Faryad

The quantum phase estimation (QPE) is one of the fundamental algorithms based on the quantum Fourier transform. It has applications in order-finding, factoring, and finding the eigenvalues of unitary operators. The major challenge in running QPE and other quantum algorithms is the noise in quantum computers. In the present work, we study the impact of incohe

Mattia Bruno, Marco Cè, Anthony Francis, Patrick Fritzsch

Because of the mass gap, lattice QCD simulations exhibit stochastic locality: distant regions of the lattice fluctuate independently. There is a long history of exploiting this to increase statistics by obtaining multiple spatially-separated samples from each gauge field; in the extreme case, we arrive at the master-field approach in which a single gauge fie

Benjamin N. Miller, David H. Meyer, Teemu Virtanen, Christopher M. O'Brien

We describe a numerical technique and accompanying open-source Python software package called RydIQule. RydIQule uses a directional graph, relying on adjacency matrices and path-finding to generate a Hamiltonian for multi-level atomic systems. RydIQule then constructs semi-classical equations of motion (Bloch equations) into a tensor which can store an entir

Navid Ziaei, Reza Saadatifard, Ali Yousefi, Behzad Nazari

Understanding how external stimuli are encoded in distributed neural activity is of significant interest in clinical and basic neuroscience. To address this need, it is essential to develop analytical tools capable of handling limited data and the intrinsic stochasticity present in neural data. In this study, we propose a straightforward Bayesian time series

Konstantin Röhrl, Dominik Bauer, Timothy Patten, Markus Vincze

Tracking an object's 6D pose, while either the object itself or the observing camera is moving, is important for many robotics and augmented reality applications. While exploiting temporal priors eases this problem, object-specific knowledge is required to recover when tracking is lost. Under the tight time constraints of the tracking task, RGB(D)-based meth

David Nesvorny, Luke Dones, Mario De Pra, Maria Womack

Previous studies of cometary impacts in the outer Solar System used the spatial distribution of ecliptic comets (ECs) from dynamical models that assumed ECs began on low-inclination orbits (<5 deg) in the Kuiper belt. In reality, the source population of ECs - the trans-Neptunian scattered disk - has orbital inclinations reaching up to ~30 deg. In Nesvorny e

Lutz Sager

Air pollution generates substantial health damages and economic costs worldwide. Pollution exposure varies greatly, both between countries and within them. However, the degree of air quality inequality and its' trajectory over time have not been quantified at a global level. Here I use economic inequality indices to measure global inequality in exposure to a

Jianzhi Xu, Aigen Li, Xiaohu Li, Gao-Lei Hou

Fullerenes, including C60, C70, and C60+, are widespread in space through their characteristic infrared vibrational features (C60+ also reveals its presence in the interstellar medium through its electronic transitions) and offer great insights into the carbon chemistry and stellar evolution. The potential existence of fullerene-related species in space has

Sovan Chakraborty, Poonam Mehta, Prantik Sarmah

Ultra-high energy cosmic rays (UHECRs) beyond the Greisen-Zatsepin-Kuzmin (GZK) cut-off provide us with a unique opportunity to understand the universe at extreme energies. Secondary GZK photons and GZK neutrinos associated with the same interaction are indeed interconnected and render access to multi-messenger analysis of UHECRs. The GZK photon flux is heav

Noam Soker

Under the assumption that jets explode all core collapse supernovae (CCSNe) I classify 14 CCSN remnants (CCSNRs) into five groups according to their morphology as shaped by jets, and attribute the classes to the specific angular momentum of the pre-collapse core. Point-symmetry (1 CCSNR): According to the jittering jets explosion mechanism (JJEM) when the pr

Anthony Brogni, Sebastiaan J. C. Joosten

This paper presents the development of a software tool that enables the translation of first-order predicate logic with at most three variables into relation algebra. The tool was developed using the Z3 theorem prover, leveraging its capabilities to enhance reliability, generate code, and expedite development. The resulting standalone Python program allows u

Rafael Merli, Antolín Martínez-Martínez, Juan José Ródenas, Marc Bosch-Galera

In the current industry, the development of optimized mechanical components able to satisfy the customer requirements evolves quickly. Therefore, companies are asked for efficient solutions to improve their products in terms of stiffness and strength. In this sense, Topology Optimization has been extensively used to determine the best topology of structural

Francesco Vercesi, Quentin Fontaine, Sylvain Ravets, Jacqueline Bloch

We consider a one-dimensional driven-dissipative exciton-polariton condensate under incoherent pump, described by the stochastic generalized Gross-Pitaevskii equation. It was shown that the condensate phase dynamics maps under some assumptions to the Kardar-Parisi-Zhang (KPZ) equation, and the temporal coherence of the condensate follows a stretched exponent

Marco Eckhoff, Markus Reiher

The optimization algorithm and its hyperparameters can significantly affect the training speed and resulting model accuracy in machine learning applications. The wish list for an ideal optimizer includes fast and smooth convergence to low error, low computational demand, and general applicability. Our recently introduced continual resilient (CoRe) optimizer

Yeyson A. Becerra-Mora, José Ángel Acosta

An interlaced method to learn and control nonlinear system dynamics from a set of demonstrations is proposed, under a constrained optimization framework for the unsupervised learning process. The nonlinear system is modelled as a mixture of Gaussians and the Sontag's formula together with its associated Control Lyapunov Function is proposed for learning and

Adam Bene Watts, Anirban Chowdhury, Aidan Epperly, J. William Helton

The Quantum Max Cut (QMC) problem has emerged as a test-problem for designing approximation algorithms for local Hamiltonian problems. In this paper we attack this problem using the algebraic structure of QMC, in particular the relationship between the quantum max cut Hamiltonian and the representation theory of the symmetric group. The first major contribut

Eddie Rohr, Karthik Sellakumaran Latha, Amanda Yin

The Type D asymmetric simple exclusion process (Type D ASEP) is a two-species interacting particle system exhibiting a drift, where two particles may occupy the same site only if they belong to different species. In previous research (arXiv:2011.13473), the Type D ASEP was generated using the quantum Hamiltonian corresponding to central elements from the qua

Subhajit Ghosh, Dinusha Herath Mudiyanselage, Fariborz Kargar, Yuji Zhao

We report on the temperature dependence of the low-frequency electronic noise in NiO$_x$/Ga$_2$O$_3$ p-n heterojunction diodes. The noise spectral density is of the 1/f-type near room temperature but shows signatures of Lorentzian components at elevated temperatures and at higher current levels (f is the frequency). We observed an intriguing non-monotonic de

Avishi Abeywickrama, Douglas H. Adamson, Hannes C. Schniepp

We directly measured the interactions between a hydrophobic solid and a hydrophobic liquid separated by water using force spectroscopy, where colloidal probes were coated with graphene oxide (GO) to interact with immobilized heptane droplets in water. We detected attractions with a long range of ~0.5 microns, which cannot be readily explained by standard Der

Safvan Palathingal, Dominic Vella

The shift in the backbone of the frequency--response curve and the `jump-down' observed at a critical frequency observed in nano-resonators are caused by their nonlinear mechanical response. The shift and jump-down point are therefore often used to infer the mechanical properties that underlie the nonlinear response, particularly the resonator's stretching m

Nicolò Cangiotti, Maicol Caponi, Alberto Maione, Enzo Vitillaro

In this paper we prove existence of solutions to Schr\"odinger-Maxwell type systems involving mixed local-nonlocal operators. Two different models are considered: classical Schr\"odinger-Maxwell equations and Schr\"odinger-Maxwell equations with a coercive potential, and the main novelty is that the nonlocal part of the operator is allowed to be nonpositive

Marta Pita-Vidal, Jaap J. Wesdorp, Lukas J. Splitthoff, Arno Bargerbos

Superconducting (or Andreev) spin qubits have recently emerged as an alternative qubit platform with realizations in semiconductor-superconductor hybrid nanowires. In these qubits, the spin degree of freedom is intrinsically coupled to the supercurrent across a Josephson junction via the spin-orbit interaction, which facilitates fast, high-fidelity spin read

Tomáš Ježo, Jonas M. Lindert, Stefano Pozzorini

The increasingly high accuracy of top-quark studies at the LHC calls for a theoretical description of $t\bar t$ production and decay in terms of exact matrix elements for the full $2\to 6$ process that includes the off-shell production and the chain decays of $t\bar t$ and $tW$ intermediate states, together with their quantum interference. Corresponding NLO

D. Lessnich, C. Gauvin-Ndiaye, Roser Valentí, A. -M. S. Tremblay

The Kane-Mele model is known to show a quantized spin Hall conductivity at zero temperature. Including Hubbard interactions at each site leads to a quantum phase transition to an XY antiferromagnet at sufficiently high interaction strength. Here, we use the two-particle self-consistent approach (TPSC), which we extend to include spin-orbit coupling, to inves

Aleksander Filip Żarnecki

A light Higgs boson, with mass of the order of 100 GeV, is still not excluded by the existing experimental data, provided its coupling to gauge bosons is strongly suppressed compared to a SM-like Higgs boson at the same mass. Also other couplings of such a scalar could be very different from the SM predictions leading to non-standard decay paterns. Considere

Zhaoting Guo, Yutong Li, Yiwen Pan, Yufan Wang

4d $\mathcal{N} = 2$ SCFTs and their invariants can be often enriched by non-local BPS operators. In this paper we study the flavored Schur index of several types of N = 2 SCFTs with and without line operators, using a series of new integration formula of elliptic functions and Eisenstein series. We demonstrate how to evaluate analytically the Schur index fo

Leonardo Supán, Gabriela Castelletti, Anne Lemière

This paper presents a comprehensive analysis of the Galactic SNR Kes 17 (G304.6+0.1) with focus on its radio synchrotron emission, environs, and the factors contributing to the observed gamma rays. The firstly-obtained integrated radio continuum spectrum from 88 to 8800 MHz yields an index alpha = -0.488 +/- 0.023 (S_nu $\propto$ nu^alpha), indicative of a l

James Davis, John Polhill, Ken Smith, Eric Swartz

A $(v,k,\lambda, \mu)$-partial difference set (PDS) is a subset $D$ of a group $G$ such that $|G| = v$, $|D| = k$, and every nonidentity element $x$ of $G$ can be written in either $\lambda$ or $\mu$ different ways as a product $gh^{-1}$, depending on whether or not $x$ is in $D$. Assuming the identity is not in $D$ and $D$ is inverse-closed, the correspondi

Benjamin Lambert, Florence Forbes, Senan Doyle, Michel Dojat

Deep Learning models are easily disturbed by variations in the input images that were not observed during the training stage, resulting in unpredictable predictions. Detecting such Out-of-Distribution (OOD) images is particularly crucial in the context of medical image analysis, where the range of possible abnormalities is extremely wide. Recently, a new cat

Xiaofeng Guo, Hung-Jui Huang, Wenzhen Yuan

Solid particles, such as rice and coffee beans, are commonly stored in containers and are ubiquitous in our daily lives. Understanding those particles' properties could help us make later decisions or perform later manipulation tasks such as pouring. Humans typically interact with the containers to get an understanding of the particles inside them, but it is

Zhihao Li, Jiancheng Yang, Yongchao Xu, Li Zhang

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesions of nodule and mass is still challenging. In this paper, we propose a multi-scale neural network with

Zun Wang, Jialu Li, Yicong Hong, Yi Wang

Recent research in language-guided visual navigation has demonstrated a significant demand for the diversity of traversable environments and the quantity of supervision for training generalizable agents. To tackle the common data scarcity issue in existing vision-and-language navigation datasets, we propose an effective paradigm for generating large-scale da

Andrey Korzin, Esmaeel Zanganeh, Polina Kapitanova

Development of compact wireless power transfer (WPT) systems for charging miniature randomly oriented electronic devices is quite a challenge. Traditionally, WPT systems based on resonant magnetic coupling utilize face-to-face aligned transmitter and receiver coils providing sufficient efficiency at relatively large distances. However, with the presence of a

Mindy Tran, Yasemin Acar, Michel Cucker, William Enck

Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-known examples of software supply chain attacks are the SolarWinds or log4j incidents that have affected thousands of customers and businesses. The US government and industry are equal

Anurudh Peduri, Ina Schaefer, Michael Walter

Thanks to the rapid progress and growing complexity of quantum algorithms, correctness of quantum programs has become a major concern. Pioneering research over the past years has proposed various approaches to formally verify quantum programs using proof systems such as quantum Hoare logic. All these prior approaches are post-hoc: one first implements a prog

Liwu Xu, Jinjin Xu, Yuzhe Yang, Xilu Wang

Image Aesthetics Assessment (IAA) is a challenging task due to its subjective nature and expensive manual annotations. Recent large-scale vision-language models, such as Contrastive Language-Image Pre-training (CLIP), have shown their promising representation capability for various downstream tasks. However, the application of CLIP to resource-constrained an

E. Ghamari, C. Ingalls, D. Kucerovsky

In this paper, we present a captivating construction by Grothendieck, originally formulated for algebraic varieties, and adapt it to the realm of C*-algebras. Our main objective is to investigate the conditions under which this particular class of C*-algebras possesses a nontrivial Grothendieck ring. To achieve this, we explore the existence of nontrivial ch

Benjamin Lambert, Florence Forbes, Senan Doyle, Michel Dojat

The volume of a brain lesion (e.g. infarct or tumor) is a powerful indicator of patient prognosis and can be used to guide the therapeutic strategy. Lesional volume estimation is usually performed by segmentation with deep convolutional neural networks (CNN), currently the state-of-the-art approach. However, to date, few work has been done to equip volume se

Jeffrey Covington, Di Qi, Nan Chen

Control of complex turbulent dynamical systems involving strong nonlinearity and high degrees of internal instability is an important topic in practice. Different from traditional methods for controlling individual trajectories, controlling the statistical features of a turbulent system offers a more robust and efficient approach. Crude first-order linear re

Muni Zhou, Vladimir Zhdankin, Matthew W. Kunz, Nuno F. Loureiro

We report on a first-principles numerical and theoretical study of plasma dynamo in a fully kinetic framework. By applying an external mechanical force to an initially unmagnetized plasma, we develop a self-consistent treatment of the generation of ``seed'' magnetic fields, the formation of turbulence, and the inductive amplification of fields by the fluctua

José Manuel Casas, Emzar Khmaladze, Manuel Ladra

We study the extensibility problem of a pair of derivations associated with an abelian extension of algebras with bracket, and derive an exact sequence of the Wells type. We introduce crossed modules for algebras with bracket and prove their equivalence with internal categories in the category of algebras with bracket. We interpret the set of equivalence cla

Ulrich Einhaus

With the broadening landscape of proposals for future Higgs, top and electroweak physics factories, detector diversity as well as the reach and depth of physics analysis increase. One emerging topic of renewed interest is particle identification (PID). This paper highlights the available technology options and the physics need for dedicated PID. It introduce

Xiao Liu, Xiao-Min Hu, Tian-Xiang Zhu, Chao Zhang

Quantum networks provide a prospective paradigm to connect separated quantum nodes, which relies on the distribution of long-distance entanglement and active feedforward control of qubits between remote nodes. Such approaches can be utilized to construct nonlocal quantum gates, forming building blocks for distributed quantum computing and other novel quantum

José Coutinho, Diana Gomes, Vitor J. B. Torres, Tarek O. Abdul Fattah

The thermodynamics of several reactions involving atomic and molecular hydrogen with group-III acceptors is investigated. The results provide a first-principles-level account of thermally- and carrier-activated processes involving these species. Acceptor-hydrogen pairing is revisited as well. We present a refined physicochemical picture of long-range migrati

Robert Fulsche, Miguel Angel Rodriguez Rodriguez

We discuss the notion of spectral synthesis for the setting of Quantum Harmonic Analysis. Using these concepts, we study subalgebras of the full Toeplitz algebra with certain invariant symbols and their commutators. In particular, we find a new class of commutative Toeplitz C$^\ast$ algebras on the Fock space. In the end, we investigate the Gelfand theory of

Ramtin Ehsani, Rezvaneh Rezapour, Preetha Chatterjee

To foster collaboration and inclusivity in Open Source Software (OSS) projects, it is crucial to understand and detect patterns of toxic language that may drive contributors away, especially those from underrepresented communities. Although machine learning-based toxicity detection tools trained on domain-specific data have shown promise, their design lacks

Ernst Seidel, Pejman Mowlaee, Tim Fingscheidt

The topic of deep acoustic echo control (DAEC) has seen many approaches with various model topologies in recent years. Convolutional recurrent networks (CRNs), consisting of a convolutional encoder and decoder encompassing a recurrent bottleneck, are repeatedly employed due to their ability to preserve nearend speech even in double-talk (DT) condition. Howev

Weizheng Cao, Haifeng Yang, Yongkai Li, Cuiying Pei

The Zintl compound AIn2X2 (A = Ca, Sr, and X = P, As), as a theoretically predicted new non-magnetic topological insulator, requires experiments to understand their electronic structure and topological characteristics. In this paper, we systematically investigate the crystal structures and electronic properties of the Zintl compound SrIn2As2 under both ambie

František Marko

We present rational Schur algebra $S(n,r,s)$ over an arbitrary ground field $K$ as a quotient of the distribution algebra $Dist(G)$ of the general linear group $G=GL(n)$ by an ideal $I(n,r,s)$ and provide an explicit description of the generators of $I(n,r,s)$. Over fields $K$ of characteristic zero, this corrects and completes a presentation of $S(n,r,s)$ i

Nguyen T. V. Hang, Ebrahim Sarabi

Local convergence analysis of the augmented Lagrangian method (ALM) is established for a large class of composite optimization problems with nonunique Lagrange multipliers under a second-order sufficient condition. We present a new second-order variational property, called the semi-stability of second subderivatives, and demonstrate that it is widely satisfi

Sreekar Rayaprolu, Kyle Starkey, Anter El-Azab

Voids develop in crystalline materials under energetic particle irradiation, as in nuclear reactors. Understanding the underlying mechanisms of void nucleation and growth is of utmost importance as it leads to dimensional instability of the metallic materials. In the past two decades, researchers have adopted the phase-field approach to study the phenomena o