March 2024 arXiv papers — page 188

Henny Admoni, Daniel Szafir, Wafa Johal, Anara Sandygulova

Human-robot interaction is now an established discipline. Dozens of HRI courses exist at universities worldwide, and some institutions even offer degrees in HRI. However, although many students are being taught HRI, there is no agreed-upon curriculum for an introductory HRI course. In this workshop, we aimed to reach community consensus on what should be cov

S. Paradiso, G. McGee, W. J. Percival

We employ Bayesian Model Averaging (BMA) as a powerful statistical framework to address key cosmological questions about the universe's fundamental properties. We explore extensions beyond the standard $\Lambda$CDM model, considering a varying curvature density parameter $\Omega_{\rm k}$, a spectral index $\mathrm{n}_{\rm s}=1$ and a varying $n_{\rm run}$, a

Bianca Dittrich, Ted Jacobson, José Padua-Argüelles

The dimension of the Hilbert space of a quantum gravitational system can be written formally as a path integral partition function over Lorentzian metrics. We implement this in a 2+1 dimensional simplicial minisuperspace model in which the system is a spatial topological disc, and recover by contour deformation through a Euclidean saddle the entropy of the d

Yue Yang, Yuqi Lin, Hong Liu, Wenqi Shao

Recent text-to-image (T2I) models have had great success, and many benchmarks have been proposed to evaluate their performance and safety. However, they only consider explicit prompts while neglecting implicit prompts (hint at a target without explicitly mentioning it). These prompts may get rid of safety constraints and pose potential threats to the applica

Tsofar Maniv, Vladimir Zhuravlev

A microscopic theory of Cooper-pair fluctuations (CPFs) in a disordered 2D electron system with spin-orbit scatterings under parallel magnetic field is presented in light of the observation, at low temperatures, of large magnetoresistance (MR) above a crossover field to superconductivity in electron-doped SrTiO$_{3}$/LaAlO$_{3}$ interfaces. It is found that

Sayedeh Leila Noorbakhsh, Binghui Zhang, Yuan Hong, Binghui Wang

Machine learning (ML) is vulnerable to inference (e.g., membership inference, property inference, and data reconstruction) attacks that aim to infer the private information of training data or dataset. Existing defenses are only designed for one specific type of attack and sacrifice significant utility or are soon broken by adaptive attacks. We address these

Chandan G. Nagarajappa, Yin-Zhe Ma

We present a novel approach to estimate the value of primordial non-Gaussianity ($f_{\rm NL}$) parameter directly from the Cosmic Microwave Background (CMB) maps using a convolutional neural network (CNN). While traditional methods rely on complex statistical techniques, this study proposes a simpler approach that employs a neural network to estimate $f_{\rm

Konstantin Herb, Takuya F. Segawa, Laura A. Völker, John M. Abendroth

Optically active spin defects in solids offer promising platforms to investigate nuclear spin clusters with high sensitivity and atomic-site resolution. To leverage near-surface defects for molecular structure analysis in chemical and biological contexts using nuclear magnetic resonance (NMR), further advances in spectroscopic characterization of nuclear env

M. Ahumada, L. Trujillo, J. F. Marín

Static or frozen disorder, characterised by spatial heterogeneities, influences diverse complex systems, encompassing many-body systems, equilibrium and nonequilibrium states of matter, intricate network topologies, biological systems, and wave-matter interactions. While static disorder has been thoroughly examined, delving into evolving disorder brings incr

Hugo Bohy, Kevin El Haddad, Thierry Dutoit

Smiles and laughs detection systems have attracted a lot of attention in the past decade contributing to the improvement of human-agent interaction systems. But very few considered these expressions as distinct, although no prior work clearly proves them to belong to the same category or not. In this work, we present a deep learning-based multimodal smile an

A. Biviano, B. M. Poggianti, Y. Jaffé, A. C. C. Lourenço

We analyse a sample of 244 ram-pressure-stripped candidate galaxy members within the virial radius of 62 nearby clusters, to determine their velocity anisotropy profile $\beta(r)$. We use previously determined mass profiles for the 62 clusters to build an ensemble cluster by stacking the 62 cluster samples in projected phase-space. We solve the Jeans equatio

Y. Dai, J. J. Xiang, M. D. Ding

Recent coronal loop modeling has emphasized the importance of combining both Coulomb collisions and turbulent scattering to characterize field-aligned thermal conduction, which invokes a hybrid loop model. In this work we generalize the hybrid model by incorporating nonuniform heating and cross section that are both formulated by a power-law function of temp

Jan Tułowiecki, Łukasz Czerwiński, Konrad Deka, Jan Gwinner

Various quantum algorithms require usage of arbitrary diagonal operators as subroutines. For their execution on a physical hardware, those operators must be first decomposed into target device's native gateset and its qubit connectivity for entangling gates. Here, we assume that the allowed gates are exactly the CX gate and the parameterized phase gate. We i

Heng-Yu Chen, Yasuaki Hikida, Yusuke Taki, Takahiro Uetoko

We find out the complex geometries corresponding to the semi-classical saddles of threedimensional quantum gravity by making use of the known results of dual conformal field theory (CFT), which is effectively given by Liouville field theory. We examine both the cases with positive and negative cosmological constants. We determine the set of semi-classical sa

Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters

The vast majority of Reinforcement Learning methods is largely impacted by the computation effort and data requirements needed to obtain effective estimates of action-value functions, which in turn determine the quality of the overall performance and the sample-efficiency of the learning procedure. Typically, action-value functions are estimated through an i

Tim Suchan, Volker Schulz, Kathrin Welker

This paper sets up an approach for shape optimization problems constrained by variational inequalities (VI) in an appropriate shape space. In contrast to classical VI, where no explicit dependence on the domain is given, VI constrained shape optimization problems are in particular highly challenging because of two main reasons: Firstly, one needs to operate

Jinzhe Liu, Xiangsheng Huang, Zhuo Chen, Yin Fang

Large Language Models (LLMs) encounter challenges with the unique syntax of specific domains, such as biomolecules. Existing fine-tuning or modality alignment techniques struggle to bridge the domain knowledge gap and understand complex molecular data, limiting LLMs' progress in specialized fields. To overcome these limitations, we propose an expandable and

Haoxu Wang

Claude Sabbah has defined the Fourier transform $G$ of the Gauss-Manin system for a non-degenerate and convenient Laurent polynomial and has shown that there exists a polarized mixed Hodge structure on the vanishing cycle of $G$. In this article, we consider certain non-degenerate and convenient Laurent polynomials $f_{P,\mathbf{a}}$, whose Newton polyhedron

Volker Branding

In this note we prove the existence of two proper biharmonic maps between the Euclidean ball of dimension bigger than four and Euclidean spheres of appropriate dimensions. We will also show that, in low dimensions, both maps are unstable critical points of the bienergy.

Matthew G. Signorelli, Yunhai Cai, Georg H. Hoffstaetter de Torquat

We present a novel method for minimizing the effects of radiative depolarization in electron storage rings by use of vertical orbit bumps in the arcs. Electron polarization is directly characterized by the RMS of the so-called spin orbit coupling function in the bends. In the Electron Storage Ring (ESR) of the Electron-Ion Collider (EIC), as was the case in

Ben A. P. Nel, Anja K. Skrivervik, Mats Gustafsson

This paper presents radiation efficiency and gain bounds for microstrip patch antennas. The presented bounds are shown to be good predictors of antenna performance. Using the bounds, patch miniaturization techniques based on high permittivity substrates and geometrical shaping are compared. Further, a semi-analytic model is developed to approximate the bound

Richard G. Carson, Alexander Leemans

Tractography algorithms are used extensively to delineate white matter structures, by operating on the voxel-wise information generated through the application of diffusion tensor imaging (DTI) or other models to diffusion weighted (DW) magnetic resonance imaging (MRI) data. We demonstrate that these methods commonly yield systematic streamline length depend

Renying Zeng

In this article, we work with set-valued optimization problems in locally convex topological vector spaces. We prove the equivalencies of some definitions of generalized convex maps introduced by Jeyakumar, Yang, Yang & Yang & Chen, as well as Zeng. And then, we discuss the conditions of weakly efficient solutions, proper efficient solutions, and optimal sol

Yu Fan, Shuoguo Zhang, Xiangyu Hu, Nikolaus A. Adams

In this paper, we develop a generalized hybrid method for both two-dimensional (2-D) and three-dimensional (3-D) surfactant dynamics. While the Navier-Stokes equations are solved by the Eulerian method, the surfactant transport is tracked by a Lagrangian particle method, in which the remeshing technique is employed to prevent particle clustering. For the mas

Wei He, De-Shun Zhang, Zhi-Feng Sun

In this study, we reconsider the states $Z_b(10610)$ and $Z_b(10650)$ by investigating the presence of diquark-anti-diquark components as well as the hadronic molecule components in the framework of effective field theory. The different masses of pseudoscalar mesons such as $\pi^{0}$, $\eta_{8}$, and $\eta_{0}$, as well as vector mesons like $\rho^{0}$ and $

Honghuai Fang

To each local field, Garoufalidis and Kashaev recently associate a quantum dilogarithm that satisfies a pentagon identity and some symmetries. By employing an angled version of these quantum dilogarithms, they developed three generalized TQFTs, one given by a face state-integral and others by edge state integrals. These TQFTs produce distributional invariant

Luca Maxia, Feng Yuan

By investigating the soft gluon radiation in the $J/\psi$ plus jet photoproduction at the electron-ion collider (EIC), we demonstrate that the azimuthal angular correlations between the leading jet and heavy quarkonium provide a unique probe to the production mechanism of the latter. In particular, a significant $\cos(\phi)$ asymmetry is found for the color-

Shunsuke Adachi, Tylor Adkins, Carlo Baccigalupi, Yuji Chinone

The Crab Nebula, also known as Tau A, is a polarized astronomical source at millimeter wavelengths. It has been used as a stable light source for polarization angle calibration in millimeter-wave astronomy. However, it is known that its intensity and polarization vary as a function of time at a variety of wavelengths. Thus, it is of interest to verify the st

Andreas Klingler, Tim Netzer

Convex optimization encompasses a wide range of optimization problems that contain many efficiently solvable subclasses. Interior point methods are currently the state-of-the-art approach for solving such problems, particularly effective for classes like semidefinite programming, quadratic programming, and geometric programming. However, their success hinges

Jia-Hui Wang, Zhao-Yu Li, Ming-Yang Zhuang, Luis C. Ho

We perform a comprehensive investigation of the PSF smoothing effect on the measurement of concentration-related parameters ($C$, Gini, $M_{20}$) of high redshift galaxies in the HST and JWST surveys. Our sample contains massive galaxies from the CANDELS/EGS survey (0 < z < 2), and the CEERS survey (1 < z < 3). The non-parametric concentration-related parame

Benjamin J. J. Pfister, Dominik Scheinert, Morgan K. Geldenhuys, Odej Kao

Distributed Stream Processing (DSP) systems are capable of processing large streams of unbounded data, offering high throughput and low latencies. To maintain a stable Quality of Service (QoS), these systems require a sufficient allocation of resources. At the same time, over-provisioning can result in wasted energy and high operating costs. Therefore, to ma

Mike Todd, Boyuan Zhao

We give a set of equivalent conditions for a potential on a Countable Markov Shift to have strong positive recurrence, which is also equivalent to having exponential decay of correlations. A key ingredient of our proofs is quantifying how the shift behaves at its boundary.

Séamus Lankford, Haithem Afli, Andy Way

The advent of Multilingual Language Models (MLLMs) and Large Language Models has spawned innovation in many areas of natural language processing. Despite the exciting potential of this technology, its impact on developing high-quality Machine Translation (MT) outputs for low-resource languages remains relatively under-explored. Furthermore, an open-source ap

Aslan S. Dizaji

Laboratory experiments have shown that communication plays an important role in solving social dilemmas. Here, by extending the AI-Economist, a mixed motive multi-agent reinforcement learning environment, I intend to find an answer to the following descriptive question: which governing system does facilitate the emergence and evolution of communication and t

Tyler LeBlond, Xiao Xiao, Eugene Dumitrescu, Ryan Bennink

In this position paper, we posit that a major Department of Energy (DOE)-funded open-source quantum compilation platform is needed to facilitate: (a) resource optimization at the fault-tolerant layer of the quantum computing software stack, and (b) co-design of that layer of the stack with other layers, and that this platform needs to be extensible and inclu

Sangmin Lee, Bolin Lai, Fiona Ryan, Bikram Boote

Understanding social interactions involving both verbal and non-verbal cues is essential for effectively interpreting social situations. However, most prior works on multimodal social cues focus predominantly on single-person behaviors or rely on holistic visual representations that are not aligned to utterances in multi-party environments. Consequently, the

Guangzhou Guo, Peng Wang, Yupeng Zhang

Recently, ultracompact objects have been found to be susceptible to a new nonlinear instability, known as the light-ring instability, triggered by stable light rings. This discovery raises concerns about the viability of these objects as alternatives to black holes. In this work, we investigate the presence of the light-ring instability in scalarized Reissne

Banabir Pal, Ajesh K. Gopi, Yicheng Guan, Anirban Chakraborty

Recent advances in van der Waals (vdW) materials have sparked renewed interest in the impact of dimensionality on magnetic phase transitions. While ordered magnetic phases have been demonstrated to survive in the two-dimensional (2D) limit, the quest for a spin-glass with quenched magnetic disorder in lower dimensions has proven elusive. Here we show evidenc

Laura Niermann, Luis C. Barbado

Cosmological particle creation is the phenomenon by which the expansion of spacetime results in the production of particles of a given quantum field in that spacetime. In this paper, we study this phenomenon by considering a multi-level quantum particle detector in de Sitter spacetime coupled to a massless real quantum scalar field. Rather than considering a

Harukuni Ikeda

We investigate the scaling behavior of Nambu-Goldstone (NG) modes in the ordered phase of the Vicsek model, introducing a phenomenological equation of motion (EOM) incorporating a previously overlooked non-linear term. This term arises from the interaction between velocity fields and density fluctuations, leading to new scaling behaviors. We derive exact sca

Lukas Halekotte, Anna Vanselow, Ulrike Feudel

We study the phenomenon of multistability in mutualistic networks of plants and pollinators, where one desired state in which all species coexist competes with multiple states in which some species are gone extinct. In this setting, we examine the relation between the endangerment of pollinator species and their position within the mutualistic network. To th

Jiaxiang Cheng, Pan Xie, Xin Xia, Jiashi Li

Recent advancement in text-to-image models (e.g., Stable Diffusion) and corresponding personalized technologies (e.g., DreamBooth and LoRA) enables individuals to generate high-quality and imaginative images. However, they often suffer from limitations when generating images with resolutions outside of their trained domain. To overcome this limitation, we pr

Manuel Drees, Rahul Mehra

Interactions between Dark Matter (DM) and nucleons relevant for direct search experiments can be organised in a model independent manner using a Galiliean invariant, non--relativistic effective field theory (NREFT). Here one expands the interactions in powers of the momentum transfer $\vec{q}$ and DM velocity $\vec{v}$. This approach generates many operators

S. Mohanty, A. Magar, Vikram Singh, S. S. Islam

A detailed study of the magnetic and magnetocaloric properties of a garnet compound Mn$_{3}$Cr$_{2}$Ge$_{3}$O$_{12}$ is carried out using x-ray diffraction, magnetization, heat capacity, and neutron diffraction measurements as well as \textit{ab initio} band-structure calculations. This compound manifests two successive magnetic transitions at $T_{\rm N1} \s

Uri Goldblatt, Nitzan Kahn, Sergey Hazanov, Ofir Milul

Decoherence in qubits, caused by their interaction with a noisy environment, poses a significant challenge to the development of reliable quantum processors. A prominent source of errors arises from noise in coupled ancillas, which can quickly spread to qubits. By actively monitoring these noisy ancillas, it is possible to not only identify qubit decoherence

Aiswariya Sweety Malarvanan

In this paper, we investigate the performance of a Hybrid Quantum Neural Network (HQNN) and a comparable classical Convolution Neural Network (CNN) for detection and classification problem using a radar. Specifically, we take a fairly complex radar time-series model derived from electromagnetic theory, namely the Martin-Mulgrew model, that is used to simulat

P. -A. Absil, Simon Mataigne

We exhibit conjugate points on the Stiefel manifold endowed with any member of the family of Riemannian metrics introduced by H\"uper et al. (2021). This family contains the well-known canonical and Euclidean metrics. An upper bound on the injectivity radius of the Stiefel manifold in the considered metric is then obtained as the minimum between the length o

Qiao Wang, Ralph Rose, Naho Orita, Ayaka Sugawara

A common way of assessing language learners' mastery of vocabulary is via multiple-choice cloze (i.e., fill-in-the-blank) questions. But the creation of test items can be laborious for individual teachers or in large-scale language programs. In this paper, we evaluate a new method for automatically generating these types of questions using large language mod

Michela Egidi, Gerhard Knieper

In this paper we prove a quantitative closing Lemma for manifolds of negative sectional curvature. As an application we study partner and pseudo-partner orbits for self-crossing closed geodesic.

Yifang Xu, Yunzhuo Sun, Zien Xie, Benxiang Zhai

Video temporal grounding (VTG) aims to locate specific temporal segments from an untrimmed video based on a linguistic query. Most existing VTG models are trained on extensive annotated video-text pairs, a process that not only introduces human biases from the queries but also incurs significant computational costs. To tackle these challenges, we propose VTG

Weiyi Lv, Yuhang Huang, Ning Zhang, Ruei-Sung Lin

In Multiple Object Tracking, objects often exhibit non-linear motion of acceleration and deceleration, with irregular direction changes. Tacking-by-detection (TBD) trackers with Kalman Filter motion prediction work well in pedestrian-dominant scenarios but fall short in complex situations when multiple objects perform non-linear and diverse motion simultaneo

Zhongzhen Huang, Linda Wei, Shaoting Zhang, Xiaofan Zhang

Combining images from multi-modalities is beneficial to explore various information in computer vision, especially in the medical domain. As an essential part of clinical diagnosis, multi-modal brain tumor segmentation aims to delineate the malignant entity involving multiple modalities. Although existing methods have shown remarkable performance in the task

Antonio Lechiara, Vito Marino, Luca F. Tocchio

We perform variational Monte Carlo simulations of the single-band Hubbard model on the square lattice with both nearest ($t$) and next-nearest ($t'$) neighbor hoppings. Our work investigates the consequences of increasing hole doping on the instauration of stripes and the behavior of the superconducting order parameter, with a discussion on how the two pheno

Shuai Zha, Bernhard Müller, Jade Powell

Core-collapse supernova (CCSN) explosions powered by rotation and magnetic fields present an interesting astrophysical site for nucleosynthesis that potentially contributes to the production of $r$-process elements. Here we present yields of the innermost ejecta in 3D magnetorotational CCSN models simulated using the CoCoNuT-FMT code. Strong magnetic fields

Zhipeng Ma, Marco Kemmerling, Daniel Buschmann, Chrismarie Enslin

Causal inference is a fundamental research topic for discovering the cause-effect relationships in many disciplines. However, not all algorithms are equally well-suited for a given dataset. For instance, some approaches may only be able to identify linear relationships, while others are applicable for non-linearities. Algorithms further vary in their sensiti

Beniamin Costandin, Marius Costandin

In this paper we study the NP-Hard problem of maximizing the distance over an intersection of balls to a given point. We expand the results found in \cite{funcos1}, where the authors characterize the farthest in an intersection of balls $\mathcal{Q}$ to the given point $C_0$ by constructing some intersection of halfspaces. In this paper, by slightly modifyin

Wei Wan, Changxin Tang, Eric R. Homer

One of the major challenges towards understanding and further utilizing the properties and functional behaviors of grain boundaries (GB) is the complexity of general GBs with mixed tilt and twist characters. Here, we report the correlations between mixed GBs and their tilt and twist components in terms of structure, energy and stress field by computationally

Aisha L. Shuaibu, Ivor J. A. Simpson

Methods for medical image registration infer geometric transformations that align pairs/groups of images by maximising an image similarity metric. This problem is ill-posed as several solutions may have equivalent likelihoods, also optimising purely for image similarity can yield implausible transformations. For these reasons regularization terms are essenti

Mateusz Mrukiewicz, Michał Czerwiński, Natalia Podoliak, Dalibor Repček

The recent discovery of a new ferroelectric nematic (NF) liquid crystalline phase became of utmost interest for the liquid crystal (LC) and the whole soft and condensed matter fields. Contrary to the previously known ferroelectric LC materials, whose ferroelectric characteristics were much weaker, new polar nematics exhibit properties comparable to solid fer

Shuai Zha, Oliver Eggenberger Andersen, Evan P. O'Connor

Gravitational waves (GWs) can provide crucial information about the central engines of core-collapse supernovae (CCSNe). In order to unveil the nature of GW emission in CCSNe, we apply perturbative analyses with the same underlying equations as simulations to diagnose oscillations of the proto-neutron star (PNS) during $\sim$1 s postbounce. In the pseudo-New

D. I. Jones, K. Riles

Rotating and oscillating neutron stars can give rise to long-lived Continuous Gravitational Waves (CGWs). Despite many years of searching, the detection of such a CGW signal remains elusive. In this article we describe the main astrophysical uncertainties regarding such emission, and their relation to the behaviour of matter at extremely high density. We des

Riccardo De Santis, Jelle J. Goeman, Samuel Davenport, Jesse Hemerik

In many applied sciences a popular analysis strategy for high-dimensional data is to fit many multivariate generalized linear models in parallel. This paper presents a novel approach to address the resulting multiple testing problem by combining a recently developed sign-flip test with permutation-based multiple-testing procedures. Our method builds upon the

Chuan-Ming She, Yi-Zheng Fan, Liying Kang

Let $F$ be a graph, and let $\mathcal{B}_r(F)$ be the class of $r$-uniform Berge-$F$ hypergraphs. In this paper, we establish a relationship between the spectral radius of the adjacency tensor of a uniform hypergraph and its local structure through walks. Based on the relationship, we give a spectral asymptotic bound for $\mathcal{B}_{r}(C_3)$-free linear $r

Shuai Guo, Qiuwen Wang, Yijie Gao, Rong Xie

Novel-view synthesis with sparse input views is important for real-world applications like AR/VR and autonomous driving. Recent methods have integrated depth information into NeRFs for sparse input synthesis, leveraging depth prior for geometric and spatial understanding. However, most existing works tend to overlook inaccuracies within depth maps and have l

Gerard Higgins, Andrea Di Biagio, Marios Christodoulou

Experimental proposals for testing quantum gravity-induced entanglement of masses (QGEM) typically involve two interacting masses which are each in a spatial superposition state. Here, we propose instead a QGEM experiment with two particles which are each in a superposition of rotational states, this amounts to a superposition of mass through mass-energy equ

F. Marin, A. Marinucci, M. Laurenti, D. E. Kim

We used the Imaging X-ray Polarimetry Explorer (IXPE) satellite to measure, for the first time, the 2-8 keV polarization of NGC 1068. We pointed IXPE for a net exposure time of 1.15 Ms on the target, in addition to two ~ 10 ks each Chandra snapshots in order to account for the potential impact of several ultraluminous X-ray source (ULXs) within IXPE's field-

Yotam Intrator, Matan Halfon, Roman Goldenberg, Reut Tsarfaty

Large language models hold significant promise in multilingual applications. However, inherent biases stemming from predominantly English-centric pre-training have led to the widespread practice of pre-translation, i.e., translating non-English inputs to English before inference, leading to complexity and information loss. This study re-evaluates the need fo

Tianbo Chen, Ta-Hsin Li, Hanbing Zhu, Wenwu Gao

This paper introduces a novel periodogram-like function, called the expectile periodogram, for modeling spectral features of time series and detecting hidden periodicities. The expectile periodogram is constructed from trigonometric expectile regression, in which a specially designed check function is used to substitute the squared $l_2$ norm that leads to t

Benedikt Blumenstiel, Viktoria Moor, Romeo Kienzler, Thomas Brunschwiler

Image retrieval enables an efficient search through vast amounts of satellite imagery and returns similar images to a query. Deep learning models can identify images across various semantic concepts without the need for annotations. This work proposes to use Geospatial Foundation Models, like Prithvi, for remote sensing image retrieval with multiple benefits

Lukas D Sauer, Alexander Ritz, Meinhard Kieser

Basket trial designs are a type of master protocol in which the same therapy is tested in several strata of the patient cohort. Many basket trial designs implement borrowing mechanisms. These allow sharing information between similar strata with the goal of increasing power in responsive strata while at the same time constraining type-I error inflation to a

Guanzhong Li, Shiguang Feng, Lvzhou Li

The original Grover's algorithm suffers from the souffle problem, which means that the success probability of quantum search decreases dramatically if the iteration time is too small or too large from the right time. To overcome the souffle problem, the fixed-point quantum search with an optimal number of queries was proposed [Phys. Rev. Lett. 113, 210501 (2

Prosenjit Paul, S. I. Kruglov

We investigate Einstein-Gauss-Bonnet (EGB) 4D massive gravity coupled to nonlinear electrodynamics (NED) in an Anti-de-Sitter (AdS) background and find an exact magnetically charged black hole solution. The metric function was analyzed for different values of massive gravity parameters. We verified the first law of black hole thermodynamics and the generaliz

N. Walter, M. Doppelbauer, S. Schaller, X. Liu

Aluminum monofluoride (AlF) is a suitable molecule for laser cooling and trapping. Such experiments require an extensive spectroscopic characterization of the electronic structure. Two of the theoretically predicted higher lying triplet states of AlF, the counterparts of the well-characterized D$^1\Delta$ and E$^1\Pi$ states, had experimentally not been iden

Shuvayan Brahmachary, Subodh M. Joshi, Aniruddha Panda, Kaushik Koneripalli

Large Language Models (LLMs) have demonstrated remarkable reasoning abilities, prompting interest in their application as black-box optimizers. This paper asserts that LLMs possess the capability for zero-shot optimization across diverse scenarios, including multi-objective and high-dimensional problems. We introduce a novel population-based method for numer

Zhipeng Ma, Bo Nørregaard Jørgensen, Zheng Ma

The transportation sector remains a major contributor to greenhouse gas emissions. The understanding of energy-efficient driving behaviors and utilization of energy-efficient driving strategies are essential to reduce vehicles' fuel consumption. However, there is no comprehensive investigation into energy-efficient driving behaviors and strategies. Furthermo

Umut Şimşekli, Mert Gürbüzbalaban, Sinan Yıldırım, Lingjiong Zhu

The injection of heavy-tailed noise into the iterates of stochastic gradient descent (SGD) has garnered growing interest in recent years due to its theoretical and empirical benefits for optimization and generalization. However, its implications for privacy preservation remain largely unexplored. Aiming to bridge this gap, we provide differential privacy (DP

Akepogu Venkateshwarlu, Akshayveer, Sundeep Singh, Roderick Melnik

Living tissues experience various external forces on cells, influencing their behaviour, physiology, shape, gene expression, and destiny through interactions with their environment. Despite much research done in this area, challenges remain in our better understanding of the behaviour of the cell in response to external stimuli, including the arrangement, qu

G. Di Battista, K. C. Fong, A. Diez-Carlon, K. Watanabe

The superconducting (SC) state of magic-angle twisted bilayer graphene (MATBG) shows exceptional properties, as it consists of an unprecedentedly small electron (hole) ensemble of only ~ 10 power 11 carriers per square centimeter, which is five orders of magnitude lower than in traditional superconductors. This results in an ultra-low electronic heat capacit

Xuechen Zhang, Xingyong Zhang

We investigate the existence of ground state solutions for a $(p,q)$-Laplacian system with $p,q>1$ and potential wells on a weighted locally finite graph $G=(V,E)$. By making use of the method of Nehari manifold and the Lagrange multiplier rule, we prove that if the nonlinear term $F$ takes on the super-$(p, q)$-linear growth and the potential functions $a(x

Rui-Jie Zhang, Xiao-Zhen Peng, Ri-Zhen Yang, Rui-Hua Ni

We present the first experimental observation of quantized Klein tunneling in a bounded Dirac system, implemented by a dimer chain of dielectric microwave resonators. Both the unusual quantized levels and corresponding spinor states hybridized from distinct particle and hole wavefunctions are measured. All observations are in quantitative agreement with the

Leonardo Mörlein, Dirk Manteuffel

The synthesis of antenna arrays in presence of mutual coupling using generalized scattering matrices in terms of characteristic modes is proposed. For the synthesis, the array is built of synthetic elements that are described by their modal scattering and radiation behavior. In particular, the question of how to describe the degrees of freedom of such elemen

Ruho Kondo, Yuki Sato, Rudy Raymond, Naoki Yamamoto

Quantum optimization methods use a continuous degree-of-freedom of quantum states to heuristically solve combinatorial problems, such as the MAX-CUT problem, which can be attributed to various NP-hard combinatorial problems. This paper shows that some existing quantum optimization methods can be unified into a solver to find the binary solution which is most

Amirhossein Taghvaei

Stochastic maximum principle (SMP) specifies a necessary condition for the solution of a stochastic optimal control problem. The condition involves a coupled system of forward and backward stochastic differential equations (FBSDE) for the state and the adjoint processes. Numerical solution of the FBSDE is challenging because the boundary condition of the adj

Rui Lourenço, Lucas Thomaz, Eduardo A. B. Silva, Sergio M. M. Faria

Light field cameras and multi-camera arrays have emerged as promising solutions for accurately estimating depth by passively capturing light information. This is possible because the 3D information of a scene is embedded in the 4D light field geometry. Commonly, depth estimation methods extract this information relying on gradient information, heuristic-base

Eduardo Vyhmeister, Rocio Paez, Gabriel Gonzalez

The significance of learning constraints from data is underscored by its potential applications in real-world problem-solving. While constraints are popular for modeling and solving, the approaches to learning constraints from data remain relatively scarce. Furthermore, the intricate task of modeling demands expertise and is prone to errors, thus constraint

Mathilde Caron, Ahmet Iscen, Alireza Fathi, Cordelia Schmid

In this paper, we address web-scale visual entity recognition, specifically the task of mapping a given query image to one of the 6 million existing entities in Wikipedia. One way of approaching a problem of such scale is using dual-encoder models (eg CLIP), where all the entity names and query images are embedded into a unified space, paving the way for an

Nico Lorenz

For a discrete valuation ring $R$ with quotient field $K$ and residue field $F$ both of characteristic not 2, we study low-dimensional quadratic forms with Witt class in the $n$-th power of the fundamental ideal of $F$ resp. $K$ and point out connections between forms over these fields. We analyse the minimal number of Pfister forms such that a given form is

Max van Haren, Kentaro Tsurumoto, Masahiro Mae, Lennart Blanken

Iterative learning control (ILC) is capable of improving the tracking performance of repetitive control systems by utilizing data from past iterations. The aim of this paper is to achieve both task flexibility, which is often achieved by ILC with basis functions, and the performance of frequency-domain ILC, with an intuitive design procedure. The cost functi

Emma Johanna Puranen, Emily Finer, Christiane Helling, V Anne Smith

Interest in science fiction's (SF's) potential science communication use is hindered by concerns about SF misrepresenting science. This study addresses these concerns by asking how SF media reflects scientific findings in exoplanet science. A database of SF exoplanets was analysed using a Bayesian network to find interconnected interactions between planetary

Qiaoling Xia

In this paper, (gradient) almost Ricci solitons on Finsler measure spaces $(M, F, m)$ are introduced and investigated. We prove that $(M, F, m)$ is a gradient almost Ricci soliton if and only if the infinity-Ricci curvature Ric$_\infty$ is a scalar function on $M$ when $M$ is compact. Moreover, we give an equivalent characterization of (gradient) almost Ricc

Yuxuan Liu

This dissertation is a multifaceted contribution to the advancement of vision-based 3D perception technologies. In the first segment, the thesis introduces structural enhancements to both monocular and stereo 3D object detection algorithms. By integrating ground-referenced geometric priors into monocular detection models, this research achieves unparalleled

Junjie Zeng, James Jun He, Zhen Ning, Dong-Hui Xu

In two-dimensional topological nodal superconductors, Majorana edge states have been conventionally believed to exhibit only spin-triplet pairing correlations. However, we reveal a substantial spin-singlet pairing component in Majorana edge states of antiferromagnetic topological nodal-point superconductors. This unexpected phenomenon emerges from the interp

Joost A. A. Opschoor, Christoph Schwab

We analyze deep Neural Network emulation rates of smooth functions with point singularities in bounded, polytopal domains $\mathrm{D} \subset \mathbb{R}^d$, $d=2,3$. We prove exponential emulation rates in Sobolev spaces in terms of the number of neurons and in terms of the number of nonzero coefficients for Gevrey-regular solution classes defined in terms o

Dmitry S. Bykov, Lorenzo Dania, Florian Goschin, Tracy E. Northup

Radiofrequency (RF) traps enable highly controlled interactions between charged particles, including reactions between cold molecular ions, sympathetic cooling of one ion species with another, and quantum logic spectroscopy. However, the charge-to-mass ($Q/m$) selectivity of RF traps limits the range of objects that can be confined simultaneously in the same

Siyuan Yu, Massimo Boninsegni

We revisit the problem of adsorption of a single He-4 layer on graphene, focusing on the commensurate C1/3 crystalline phase, specifically on whether it may possess a nonzero superfluid response, and on the existence of superfluid phases, either (metastable) liquid or vacancy-doped crystalline. We make use of canonical Quantum Monte Carlo simulations at zero

Federico Sau

We analyze nonequilibrium fluctuations of the averaging process on $\mathbb T_\varepsilon^d$, a continuous degenerate Gibbs sampler running over the edges of the discrete $d$-dimensional torus. We show that, if we start from a smooth deterministic non-flat interface, recenter, blow-up by a non-standard CLT-scaling factor $\theta_\varepsilon=\varepsilon^{-(d/

Pedro Ornelas, Isaac Nape, Robert De Mello Koch, Andrew Forbes

An open challenge in the context of quantum information processing and communication is improving the robustness of quantum information to environmental contributions of noise, a severe hindrance in real-world scenarios. Here, we show that quantum skyrmions and their nonlocal topological observables remain resilient to noise even as typical entanglement witn

Pietro Corvaja, Amos Turchet, Umberto Zannier

In this paper we study sets of points in the plane with rational distances from r prescribed points P_1, ...,P_r. A crucial case arises for r = 3, where we provide simple necessary and sufficient conditions for the density of this set in the real topology. We show in the Main Theorem that these conditions can be checked effectively (via congruences), proving

Donát M. Takács, Tamás Fülöp

We use backward error analysis for differential equations to obtain modified or distorted equations describing the behaviour of the Newmark scheme applied to the transient structural dynamics equation. Based on the newly derived distorted equations, we give expressions for the numerically or algorithmically distorted stiffness and damping matrices of a syste

Zhenkun Zhang, Hong Ren, Cunhua Pan, Sheng Hong

The integration of sensing capabilities into communication systems, by sharing physical resources, has a significant potential for reducing spectrum, hardware, and energy costs while inspiring innovative applications. Cooperative networks, in particular, are expected to enhance sensing services by enlarging the coverage area and enriching sensing measurement