July 2023 arXiv papers — page 35

Ahana Biswas, Tim Niven, Yu-Ru Lin

The Russian invasion of Ukraine has elicited a diverse array of responses from nations around the globe. During a global conflict, polarized narratives are spread on social media to sway public opinion. We examine the dynamics of the political narratives surrounding the Russia-Ukraine war during the first two months of the Russian invasion of Ukraine (RU) us

Alejandro Santacruz Hidalgo, Gord Sinnamon

Given a measure space and a totally ordered ordered collection of measurable sets, called an ordered core, the notion of a core decreasing function is introduced and used to define the down space of a Banach function space. This is done using a variant of the K\"othe dual restricted to core decreasing functions. To study down spaces, the least core decreasin

Andrey Vayner, Nadia L. Zakamska, Yuzo Ishikawa, Swetha Sankar

Quasar-driven galactic outflows are a major driver of the evolution of massive galaxies. We report observations of a powerful galactic-scale outflow in a $z=3$ extremely red, intrinsically luminous ($L_{\rm bol}\simeq 5\times 10^{47}$erg s$^{-1}$) quasar SDSSJ1652+1728 with the Near Infrared Spectrograph (NIRSpec) on board JWST. We analyze the kinematics of

Salar Fattahi, Andres Gomez

We study the problem of inferring sparse time-varying Markov random fields (MRFs) with different discrete and temporal regularizations on the parameters. Due to the intractability of discrete regularization, most approaches for solving this problem rely on the so-called maximum-likelihood estimation (MLE) with relaxed regularization, which neither results in

Jose Manuel Garcia Calcines, Luis Javier Hernandez Paricio, Maria Teresa Rivas Rodriguez

In this work, we analyze the combinatorial properties of cylinders and subdivisions of augmented semi-simplicial sets. These constructions are obtained as particular cases of a certain action from a co-semi-simplicial set on an augmented semi-simplicial set. We also consider cylinders and subdivision operators in the algebraic setting of augmented sequences

F. A. Chughtai

In this paper, Van der pol equation has been analyzed for stability and bifurcation phenomena with and without forcing component. Analytical solution of the Van der pol equation using Method of Multiple Scales (MMS) is compared with numerical results obtained using MATLAB ode45 solver. Limit cycle analysis has been performed at increasing order of nonlinear

Tony Gabriel-Fernandez Cayo, Fred Torres-Cruz

Time series analysis applied to occupational accident reports is a powerful tool for understanding the evolution of occupational accidents over time. It provides valuable information to make informed decisions. In this study, data from reports of work accidents collected from the MINISTRY OF LABOR AND EMPLOYMENT PROMOTION. MTPE were analyzed by time series.

Jakub Łącki, Bernhard Haeupler, Christoph Grunau, Václav Rozhoň

We study the consistent k-center clustering problem. In this problem, the goal is to maintain a constant factor approximate $k$-center solution during a sequence of $n$ point insertions and deletions while minimizing the recourse, i.e., the number of changes made to the set of centers after each point insertion or deletion. Previous works by Lattanzi and Vas

Muhammad Ali Farooq, Wang Yao, Gabriel Costache, Peter Corcoran

In this research work, we proposed a novel ChildGAN, a pair of GAN networks for generating synthetic boys and girls facial data derived from StyleGAN2. ChildGAN is built by performing smooth domain transfer using transfer learning. It provides photo-realistic, high-quality data samples. A large-scale dataset is rendered with a variety of smart facial transfo

Bernardo Fraiman, Mariana Graña, Héctor Parra De Freitas, Savdeep Sethi

Motivated by a recent construction of non-supersymmetric $\text{AdS}_3$, we revisit the $O(16)\times O(16)$ heterotic string compactified on a torus. The string one-loop potential energy has interesting dependence on the classical moduli; extrema of this potential include loci where the gauge symmetry is maximally enhanced. Focusing on the case of a circle,

Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi

Quasi-Newton methods still face significant challenges in training large-scale neural networks due to additional compute costs in the Hessian related computations and instability issues in stochastic training. A well-known method, L-BFGS that efficiently approximates the Hessian using history parameter and gradient changes, suffers convergence instability in

Santanu Das, Arad Nasiri, Yasaman K. Yazdi

This paper investigates Everpresent $\Lambda$, a stochastic dark energy model motivated by causal set theory and unimodular gravity, and confronts it with two key observational data sets, Supernova Ia (SN Ia) and Cosmic Microwave Background (CMB) data. A key feature of this model is that $\Lambda$ fluctuates over time and on average the magnitude of its fluc

Spyridon Afentoulidis-Almpanis, Gang Liu, Salah Mehdi

We study the behavior of Dirac cohomology under Howe's $\Theta$-correspondence in the case of complex reductive dual pairs. More precisely, if $(G_1,G_2)$ is a complex reductive dual pair with $G_1$ and $G_2$ viewed as real groups, we describe those Harish-Chandra modules $\pi_1$ of $G_1$ with nonzero Dirac cohomology whose $\Theta$-liftings $\Theta(\pi_1)$

Francisco Correa, Justo López-Sarrión

We notice an analogy between the motion of a relativistic particle with external homogeneous and time-dependent electromagnetic fields and the Dik'ii-Eilenberger equation for the Bogoliubov-de Gennes equation. By means of the integrable defocusing nonlinear Schr\"odinger hierarchy and their solitons appearing in the Gross-Neveu and Nambu-Jona-Lasinio models,

J. M. Tranquada, P. M. Lozano, Juntao Yao, G. D. Gu

The nature of the normal state of cuprate superconductors continues to stimulate considerable speculation. Of particular interest has been the linear temperature dependence of the in-plane resistivity in the low-temperature limit, which violates the prediction for a Fermi liquid. We present measurements of anisotropic resistivity in La$_{2-x}$Sr$_x$CuO$_4$ t

Chandler Osborne, Samir Salim, Mederic Boquien, Mark Dickinson

The Galaxy Evolution Explorer (GALEX) satellite performed the first and only large-area UV survey, which in tandem with the Sloan Digital Sky Survey (SDSS) has facilitated modeling of the spectral energy distributions (SEDs) of low-redshift galaxies and the determination of various galaxy properties, in particular the star formation rate. However, the relati

Prerana Biswas, Veselina Kalinova, Nirupam Roy, Narendra Nath Patra

Studying the kinematics and mass modelling of galaxies from HI 21 cm data provides valuable insights into the properties of both the baryonic components and the dark matter halo in nearby galaxies. Despite many observational studies, mass modelling of galaxies remains challenging due to different limitations. For example, most of the previous studies involvi

Isadora Veeren, Martin Plávala, Leevi Leppäjärvi, Roope Uola

We develop a method for semi-device-independent certification of number of measurements. We achieve this by testing whether Bob's steering equivalent observables (SEO) can be simulated by k measurements, which we do by testing whether they are k-compatible with separable joint observable. This test can be performed with the aid of hierarchy of semidefinite p

Satyaki Chowdhury, Martin Bojowald, Jakub Mielczarek

According to the pioneering work of Nielsen and collaborators, the length of the minimal geodesic in a geometric realization of a suitable operator space provides a measure of the quantum complexity of an operation. Compared with the original concept of complexity based on the minimal number of gates required to construct the desired operation as a product,

Indranil Halder, Ying-Hsuan Lin

We consider BPS states in M theory compactified on a Calabi-Yau threefold with one K\"ahler parameter, and investigate their relation to blackholes and blackrings. On the microscopic side, a characterization of the BPS degeneracy can be obtained from the non-perturbative part of the topological string free energy according to the Gopakumar-Vafa conjecture. O

Vitor Cardoso, Rodrigo Vicente, Zhen Zhong

Energy exchange mechanisms have important applications in particle physics, gravity, fluid mechanics, and practically every field in physics. In this letter we show, both in frequency and time domain, that energy enhancement is possible for waves scattering off fundamental solitons (time-periodic localized structures of bosonic fields), without the need for

Francisco Rodríguez Montero, Sergio Martin-Alvarez, Adrianne Slyz, Julien Devriendt

During the last decade, cosmological simulations have managed to reproduce realistic and morphologically diverse galaxies, spanning the Hubble sequence. Central to this success was a phenomenological calibration of the few included feedback processes, whilst glossing over higher complexity baryonic physics. This approach diminishes the predictive power of su

Till Sawala, Jorge Peñarrubia, Shihong Liao, Peter H. Johansson

The Timing Argument connects the motion of a two-body system to its mass in an expanding Universe with a finite age, under the assumption that it has evolved on a self-gravitating orbit. It is commonly applied to the present-day Milky Way-M31 system in order to infer its unknown mass from the measured kinematics. We use a set of Local Group analogues from th

Pedro De la Torre Luque, Shyam Balaji, Pierluca Carenza

We study MeV-scale electrophilic Feebly Interacting Particles (FIPs), that may be abundantly produced in Supernova (SN) explosions, escape the star and decay into electrons and positrons. This exotic injection of leptons in the Milky Way leaves an imprint in both photon and cosmic-ray fluxes. Specifically, positrons lose energy and annihilate almost at rest

Yaroslav Herasymenko, Anurag Anshu, Barbara Terhal, Jonas Helsen

We construct local fermionic Hamiltonians with no low-energy trivial states (NLTS), providing a fermionic counterpart to the NLTS theorem. Distinctly from the qubit case, we define trivial states via finite-depth $\textit{fermionic}$ quantum circuits. We furthermore allow free access to Gaussian fermionic operations, provided they involve at most $O(n)$ anci

Frédéric Dux, Cameron Lemon, Frédéric Courbin, Favio Neira

We present the proof-of-concept of a method to find strongly lensed quasars using their spatially-extended photometric variability through difference imaging in cadenced imaging survey data. We apply the method to Pan-STARRS, starting with an initial selection of 14 107 Gaia multiplets with quasar-like infrared colours from WISE. We identify 229 candidates s

Pedro De la Torre Luque, Shyam Balaji, Pierluca Carenza

During galactic Supernova (SN) explosions, a large amount of feebly interacting particles (FIPs) may be produced. In this work we analyze electrophilic FIPs with masses in the MeV-range that escape from SN and decay into electron-positron pairs, causing an exotic leptonic injection. This contribution adds up to known components, leading to an unexpected exce

Joe Bramante, Melissa Diamond, Christopher V. Cappiello, Aaron C. Vincent

Dark matter is typically assumed not to couple to the photon at tree level. While annihilation to photons through quark loops is often considered in indirect detection searches, such loop-level effects are usually neglected in direct detection, as they are typically subdominant to tree-level dark matter-nucleus scattering. However, when dark matter is lighte

Kiersten M. Boley, Wendy R. Panero, Cayman T. Unterborn, Joseph G. Schulze

Lava worlds are a potential emerging population of Super-Earths that are on close-in orbits around their host stars with likely partially molten mantles. To date, few studies address the impact of magma on the observed properties of a planet. At ambient conditions magma is less dense than solid rock; however, it is also more compressible with increasing pres

Masataka Kawano, Frank Pollmann, Michael Knap

Recent progress in material design enables the study of correlated, low-temperature phases and associated anomalous transport in two-dimensional kagome systems. Here, we show that unconventional spin transport can arise in such systems even at elevated temperatures due to emergent dynamical constraints. To demonstrate this effect, we consider a strong-coupli

Mohammad Akhond, Masazumi Honda, Francesco Mignosa

We consider generalisations of the recently proposed supersymmetry breaking deformation of the 5d rank-1 $E_1$ superconformal field theory to higher rank. We generalise the arguments to theories which admit a mass deformation leading to gauge theories coupled to matter hypermultiplets at low energies. These theories have a richer space of non-supersymmetric

Ryoki Matsukoba, Eduard I. Vorobyov, Takashi Hosokawa, Manuel Guedel

Direct imaging observations of planets revealed that wide-orbit ($>10$ au) giant planets exist even around subsolar-metallicity host stars and do not require metal-rich environments for their formation. A possible formation mechanism of wide-orbit giant planets in subsolar-metallicity environments is the gravitational fragmentation of massive protoplanetary

Bo Li, Haotian Liu, Liangyu Chen, Yong Jae Lee

Advancements in large pre-trained generative models have expanded their potential as effective data generators in visual recognition. This work delves into the impact of generative images, primarily comparing paradigms that harness external data (\ie generative \vs retrieval \vs original). Our key contributions are: \textbf{1) GenBench Construction:} We devi

Muhammad Awais, Muzammal Naseer, Salman Khan, Rao Muhammad Anwer

Vision systems to see and reason about the compositional nature of visual scenes are fundamental to understanding our world. The complex relations between objects and their locations, ambiguities, and variations in the real-world environment can be better described in human language, naturally governed by grammatical rules and other modalities such as audio

H. Qu, M. Sako, M. Vincenzi, C. Sanchez

Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is non-trivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmol

Vikram Jamwal, Ramaneswaran S

For an artist or a graphic designer, the spatial layout of a scene is a critical design choice. However, existing text-to-image diffusion models provide limited support for incorporating spatial information. This paper introduces Composite Diffusion as a means for artists to generate high-quality images by composing from the sub-scenes. The artists can speci

Alessio Conte, Roberto Grossi, Giulia Punzi, Takeaki Uno

Maximal Common Subsequences (MCSs) between two strings X and Y are subsequences of both X and Y that are maximal under inclusion. MCSs relax and generalize the well known and widely used concept of Longest Common Subsequences (LCSs), which can be seen as MCSs of maximum length. While the number both LCSs and MCSs can be exponential in the length of the strin

M. E. Shirokov

A revised version of the compactness criterion for families of quantum operations in the strong convergence topology (obtained previously) is presented, along with a more detailed proof and the examples showing the necessity of this revision. Several criteria for the existence of a limit point of a sequence of quantum operations w.r.t. the strong convergence

Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang

The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they have made a significant impact in the medical field. Large language models are now more abundant than ever, and many of these models exhibit bilingual capabilities, proficient in both

Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, Pranav Tadepalli

Large Language Models (LLMs) have demonstrated remarkable performance on various quantitative reasoning and knowledge benchmarks. However, many of these benchmarks are losing utility as LLMs get increasingly high scores, despite not yet reaching expert performance in these domains. We introduce ARB, a novel benchmark composed of advanced reasoning problems i

Kaled Telli, Okba Kraa, Yassine Himeur, Abdelmalik Ouamane

The growing interest in unmanned aerial vehicles (UAVs) from both scientific and industrial sectors has attracted a wave of new researchers and substantial investments in this expansive field. However, due to the wide range of topics and subdomains within UAV research, newcomers may find themselves overwhelmed by the numerous options available. It is therefo

Paul A. Johnson, A. Eugene DePrince

Richardson-Gaudin (RG) states are employed as a variational wavefunction ansatz for strongly correlated isomers of H$_4$ and H$_{10}$. In each case a single RG state describes the seniority-zero sector quite well. Simple natural orbital functionals offer a cheap and reasonable approximation of the outstanding weak correlation in the seniority-zero sector, wh

R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla

Neutrino oscillations at the highest energies and longest baselines provide a natural quantum interferometer with which to study the structure of spacetime and test the fundamental principles of quantum mechanics. If the metric of spacetime has a quantum mechanical description, there is a generic expectation that its fluctuations at the Planck scale would in

A. Picksley, J. Chappell, E. Archer, N. Bourgeois

We describe a simple scheme, truncated-channel injection, to inject electrons directly into the wakefield driven by a drive pulse guided by an all-optical plasma channel. We use this approach to generate dark-current-free 1.2 GeV, 4.5 % relative energy spread electron bunches with 120 TW laser pulses guided in a 110-mm-long hydrodynamic optical-field-ionized

Yang-Zhi Chou, Sankar Das Sarma

Motivated by the recently discovered incompressible insulating phase in the bilayer graphene exciton experiment [arXiv:2306.16995], we study using bosonization two Coulomb-coupled spinless quantum wires and examine the possibility of realizing the similar phenomenology in one dimension. We explore the possible phases as functions of $k_{F}$'s and interaction

Jacob Green, Cecilia Cabrera Diaz, Maximilian A. H. Jakobs, Andrea Dimitracopoulos

Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials, and to find highly active compounds faster. Interest from the Machine Learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is

Zeviel Imani, Shuchin Aeron, Taritree Wongjirad

For the first time, we show high-fidelity generation of LArTPC-like data using a generative neural network. This demonstrates that methods developed for natural images do transfer to LArTPC-produced images, which, in contrast to natural images, are globally sparse but locally dense. We present the score-based diffusion method employed. We evaluate the fideli

Gan Zhang, Wenjun Zhu

The physical and economic damages of hurricanes can acutely affect employment and the well-being of employees. However, a comprehensive understanding of these impacts remains elusive as many studies focused on narrow subsets of regions or hurricanes. Here we present an open-source dataset that serves interdisciplinary research on hurricane impacts on US empl

Christoph Grunau, Ahmet Alper Özüdoğru, Václav Rozhoň

The $k$-means++ algorithm by Arthur and Vassilvitskii [SODA 2007] is a classical and time-tested algorithm for the $k$-means problem. While being very practical, the algorithm also has good theoretical guarantees: its solution is $O(\log k)$-approximate, in expectation. In a recent work, Bhattacharya, Eube, Roglin, and Schmidt [ESA 2020] considered the follo

Alonso Luna, Tommaso Marchetti, Marina Rejkuba, Dante Minniti

The astrometry towards the Galactic Bulge is hampered by high stellar crowding and patchy extinction. This effect is particularly severe for optical surveys such as Gaia. In this study, we assess the consistency of proper motions (PMs) between optical (Gaia DR3) and near-infrared (VIRAC2) catalogues in comparison with PMs measured with the Hubble Space Teles

Tara Abrishami, Bogdan Alecu, Maria Chudnovsky, Sepehr Hajebi

A generalized $t$-pyramid is a graph obtained from a certain kind of tree (a subdivided star or a subdivided cubic caterpillar) and the line graph of a subdivided cubic caterpillar by identifying simplicial vertices. We prove that for every integer $t$ there exists a constant $c(t)$ such that every $n$-vertex even-hole-free graph with no clique of size $t$ a

Alberto Manuel Martínez-García, Andrés del Pino, Ewa L. Łokas, Roeland P. van der Marel

We present a kinematic study of a thousand of dwarf satellites of MW/M31-like hosts from the IllustrisTNG50 simulation. Internal kinematics were derived for all the snapshots to obtain a historical record of their rotation velocity in the plane of the sky ($|V_T|$) and the amplitude of their velocity gradients along the line of sight ($A_{\rm grad}^{v_z}$) m

Navin Aksornthong, Takehiko Gappo, James Holland, Grigor Sargsyan

We show that in the $\mathbb{P}_{\max}$ extension of a certain Chang-type model of determinacy, if $\kappa\in\{\omega_1, \omega_2, \omega_3\}$, then the restriction of the club filter on $\kappa\cap\mathrm{Cof}(\omega)$ to HOD is an ultrafilter in HOD. This answers Question 4.11 of [BNH23] raised by Ben-Neria and Hayut.

Valentin Deschaintre, Julia Guerrero-Viu, Diego Gutierrez, Tamy Boubekeur

We introduce text2fabric, a novel dataset that links free-text descriptions to various fabric materials. The dataset comprises 15,000 natural language descriptions associated to 3,000 corresponding images of fabric materials. Traditionally, material descriptions come in the form of tags/keywords, which limits their expressivity, induces pre-existing knowledg

Shaojie Li, Yong Liu

Gradient clipping is a commonly used technique to stabilize the training process of neural networks. A growing body of studies has shown that gradient clipping is a promising technique for dealing with the heavy-tailed behavior that emerged in stochastic optimization as well. While gradient clipping is significant, its theoretical guarantees are scarce. Most

Luca A. Bennett, Zahraa S. Abdallah

Multivariate time series classification is a rapidly growing research field with practical applications in finance, healthcare, engineering, and more. The complexity of classifying multivariate time series data arises from its high dimensionality, temporal dependencies, and varying lengths. This paper introduces a novel ensemble classifier called RED CoMETS

M. Ali Al-Radhawi, David Angeli, Eduardo Sontag

Biological networks are customarily described as structurally robust. This means that they often function extremely well under large forms of perturbations affecting both the concentrations and the kinetic parameters. In order to explain this property, various mathematical notions have been proposed in the literature. In this paper, we propose the notion of

Anshuman Das Mohapatra, Kwangsung Oh

Many data analytic systems have adopted a newly emerging compute resource, serverless (SL), to handle data analytics queries in a timely and cost-efficient manner, i.e., serverless data analytics. While these systems can start processing queries quickly thanks to the agility and scalability of SL, they may encounter performance- and cost-bottlenecks based on

Yekimov Sergey

In practice , quite often there is a need to describe the values set by means of a table in the form of some functional dependence . The observed values , due to certain circumstances , have an error . For approximation, it is advisable to use a functional dependence that would allow smoothing out the errors of the observation results. Approximation allows y

Pablo Álvarez, Davide Pittilini, Filippo Miserocchi, Sathyanarayanan Raamamurthy

Networks of coupled Kerr parametric oscillators (KPOs) are a leading physical platform for analog solving of complex optimization problems. These systems are colloquially known as ``Ising machines''. We experimentally and theoretically study such a network under the influence of an external force. The force breaks the collective phase-parity symmetry of the

Souvik Dey, Pat Lank, Ryo Takahashi

This article investigates strong generation within the module category of a commutative Noetherian ring. We establish a criterion for such rings to possess strong generators within their module category, addressing a question raised by Iyengar and Takahashi. As a consequence, this not only demonstrates that any Noetherian quasi-excellent ring of finite Krull

P. Short, A. Lawrence, M. Nicholl, M. Ward

Tidal disruption events (TDEs) occur when a star gets torn apart by a supermassive black hole as it crosses its tidal radius. We present late-time optical and X-ray observations of the nuclear transient AT2019qiz, which showed the typical signs of an optical-UV transient class commonly believed to be TDEs. Optical spectra were obtained 428, 481 and 828 rest-

Sabarinathan P Subramaniyan, Pavana Prabhakar

Syntactic foams have found widespread usage in various applications including, marine, aerospace, automotive, pipe insulation, electrical cable sheathing, and shoe insoles. However, syntactic foams are often exposed to moisture when used in these applications that potentially alter their viscoelastic properties, which influences their long-term durability. D

K. Böckmann, M. Brüggen, B. Koribalski, A. Veronica

The extended ROentgen Survey with an Imaging Telescope Array (eROSITA) telescope onboard the Spectrum-Roentgen-Gamma (SRG) mission has finished the first eROSITA All-Sky Survey (eRASS:1), and detected 10$^4$ galaxy clusters in the western Galactic hemisphere. In the radio band, the Australian Square Kilometre Array Pathfinder (ASKAP) telescope finished its p

Toni L. Heugel, R. Chitra, Alexander Eichler, Oded Zilberberg

Networks of nonlinear parametric resonators are promising candidates as Ising machines for annealing and optimization. These many-body out-of-equilibrium systems host complex phase diagrams of coexisting stationary states. The plethora of states manifest via a series of bifurcations, including bifurcations that proliferate purely unstable solutions, which we

Alina Marian, Andrei Neguţ

We describe the action of the shifted Yangian of sl_2 on the cohomology groups of the Quot schemes of 0-dimensional quotients on a smooth projective curve. We introduce a commuting family of r operators in the positive half of the Yangian, whose action yields a natural basis of the Quot cohomology. These commuting operators further lead to formulas for the o

Liane Makatura, Michael Foshey, Bohan Wang, Felix HähnLein

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we scrutinize the utility of LLMs in tasks such as: converting a text-based prompt into a design specification, transforming

Axel Durbet, Kevin Thiry-Atighehchi, Dorine Chagnon, Paul-Marie Grollemund

In a biometric authentication or identification system, the matcher compares a stored and a fresh template to determine whether there is a match. This assessment is based on both a similarity score and a predefined threshold. For better compliance with privacy legislation, the matcher can be built upon a privacy-preserving distance. Beyond the binary output

Qingtao Chen, Shengmao Zhu

This is the second article in a series devoted to the study of the asymptotic expansions of various quantum invariants related to the twist knots. In this article, following the method and results in \cite{CZ23-1}, we present an asymptotic expansion formula for the colored Jones polynomial of twist knot $\mathcal{K}_p$ with $p\geq 6$ at the root of unity $e^

Jürgen Berges, Kirill Boguslavski, Lillian de Bruin, Tara Butler

Nuclear collisions at sufficiently high energies are expected to produce far-from-equilibrium matter with a high density of gluons at early times. We show gauge condensation, which occurs as a consequence of the large density of gluons. To identify this condensation phenomenon, we construct two local gauge-invariant observables that carry the macroscopic zer

Arpit Dua, Nathanan Tantivasadakarn, Joseph Sullivan, Tyler D. Ellison

Floquet codes are a novel class of quantum error-correcting codes with dynamically generated logical qubits arising from a periodic schedule of non-commuting measurements. We utilize the interpretation of measurements in terms of condensation of topological excitations and the rewinding of measurement sequences to engineer new examples of Floquet codes. In p

Antoine Goldsborough, Stefanie Zbinden

We introduce the notion of mixed subtree quasi-isometries, which are self quasi-isometries of regular trees built in a specific inductive way. We then show that any self quasi-isometry of a regular tree is at bounded distance from a mixed-subtree quasi-isometry. Since the free group is quasi-isometric to a regular tree, this provides a way to describe all se

Hanqing Zhao, Boris A. Malomed, Ivan I. Smalyukh

Being ubiquitous, solitons have particle-like properties, exhibiting behaviour often associated with atoms. Bound solitons emulate dynamics of molecules, though solitonic analogues of polymeric materials have not been considered yet. Here we experimentally create and model soliton polymers, which we call polyskyrmionomers, built of atom-like individual solit

Y. M. Kim

In this paper, one can explicitly see the process of implementing the robust residual generator on digital domain, especially on FPGA. Firstly, the baseline model is developed in double precision floating point format. To develop the baseline model, key parameters such as SNR and detection window length are selected in the identification stage. (Please refer

Leiming Chen, Weishan Zhang, Cihao Dong, Sibo Qiao

Traditional federated learning uses the number of samples to calculate the weights of each client model and uses this fixed weight value to fusion the global model. However, in practical scenarios, each client's device and data heterogeneity leads to differences in the quality of each client's model. Thus the contribution to the global model is not wholly de

Emanuel Malvetti, Gunther Dirr, Frederik vom Ende, Thomas Schulte-Herbrüggen

For a symmetric Lie algebra $\mathfrak g=\mathfrak k\oplus\mathfrak p$ we consider a class of bilinear or more general control-affine systems on $\mathfrak p$ defined by a drift vector field $X$ and control vector fields $\mathrm{ad}_{k_i}$ for $k_i\in\mathfrak k$ such that one has fast and full control on the corresponding compact group $\mathbf K$. We show

Giulio Isacchini, Valentin Quiniou, Hélène Vantomme, Paul Stys

The adaptive immune response relies on T cells that combine phenotypic specialization with diversity of T cell receptors (TCRs) to recognize a wide range of pathogens. TCRs are acquired and selected during T cell maturation in the thymus. Characterizing TCR repertoires across individuals and T cell maturation stages is important for better understanding adap

Hadi Kharaghani, Thomas Pender, Vladimir D. Tonchev

A family of $\omega$-circulant balanced weighing matrices with classical parameters is used for the construction of optimal constant weight codes over an alphabet of size $g+1$ and length $n=(q^m -1)/(q-1)$, where $q$ is an odd prime power, $m>1$, and $g$ is a divisor of $q-1$.

Henry DeYoung, Andreia Mordido, Frank Pfenning, Ankush Das

We study the interaction of structural subtyping with parametric polymorphism and recursively defined type constructors. Although structural subtyping is undecidable in this setting, we describe a notion of parametricity for type constructors and then exploit it to define parametric subtyping, a conceptually simple, decidable, and expressive fragment of stru

Vladyslav Oles

The Gromov--Hausdorff distance measures the difference in shape between metric spaces and poses a notoriously difficult problem in combinatorial optimization. We introduce its quadratic relaxation over a convex polytope whose solutions provably deliver the Gromov--Hausdorff distance. The optimality guarantee is enabled by the fact that the search space of ou

Andrew P. Grace, David H. Richter, Andrew D. Bragg

Under the right circumstances, inertial particles (such as sand or dust) settling through the atmospheric boundary layer can experience a net enhancement in their average settling velocity due to their inertia. Since this enhancement arises due to their interactions with the surrounding turbulence it must be modelled at coarse scales. Models for the enhanced

Warren Buckley, Adrian Byrne, Nicholas Perello, Cyrus Cousins

We propose that future AI transparency and accountability regulations are based on an open global standard for exchanging information about AI systems, which allows co-existence of potentially conflicting local regulations. Then, we discuss key components of a lightweight and effective AI transparency and/or accountability regulation. To prevent overregulati

Thomas Mack, Ketao Zhang, Kaspar Althoefer

The human hand has an inherent ability to manipulate and re-orientate objects without external assistance. As a consequence, we are able to operate tools and perform an array of actions using just one hand, without having to continuously re-grasp objects. Emulating this functionality in robotic end-effectors remains a key area of study with efforts being mad

Theo Barre, Omar El Housni, Marouane Ibn Brahim, Andrea Lodi

Motivated by applications in e-retail and online advertising, we study the problem of assortment optimization under visibility constraints, that we refer to as APV. Here, we are given a universe of substitutable products and a stream of customers. The objective is to determine the optimal assortment of products to offer to each customer in order to maximize

Xunjian Yin, Xiaojun Wan

With the development of pre-trained models and the incorporation of phonetic and graphic information, neural models have achieved high scores in Chinese Spelling Check (CSC). However, it does not provide a comprehensive reflection of the models' capability due to the limited test sets. In this study, we abstract the representative model paradigm, implement i

Yuexiong Ding, Xiaowei Luo

Object detection has been widely applied for construction safety management, especially personal protective equipment (PPE) detection. Though the existing PPE detection models trained on conventional datasets have achieved excellent results, their performance dramatically declines in extreme construction conditions. A robust detection model NST-YOLOv5 is dev

Xiaoxue Qin, Alfonso H. W. Ngan, Yang Xiang

The Merriman-Bence-Osher threshold dynamics method is an efficient algorithm to simulate the motion by mean curvature. It has the advantages of being easy to implement and with high efficiency. In this paper, we propose a threshold dynamics method for dislocation dynamics in a slip plane, in which the spatial operator is essentially an anisotropic fractional

Di Liu, Florian Kaiser, Vladislav Bushmakin, Erik Hesselmeier

The negatively-charged silicon vacancy center ($\rm V_{Si}^-$) in silicon carbide (SiC) is an emerging color center for quantum technology covering quantum sensing, communication, and computing. Yet, limited information currently available on the internal spin-optical dynamics of these color centers prevents us achieving the optimal operation conditions and

Chih-Hung Wang, Yu-Huei Wu

We investigate the effects of external torsion fields on ideal gases and Fermi gases, and derive a macroscopic quantity, which we call torsion susceptibility. We first consider the Dirac fermions in the Riemann-Cartan spacetime minimally coupled to the background torsion and electromagnetic fields. After applying the Foldy-Wouthuysen transformation, Hamilton

Guowei Wu, Weike Pan, Zhong Ming

Graph neural networks (GNNs) have gained wide popularity in recommender systems due to their capability to capture higher-order structure information among the nodes of users and items. However, these methods need to collect personal interaction data between a user and the corresponding items and then model them in a central server, which would break the pri

Justin Engelmann, Amos Storkey, Miguel O. Bernabeu

Image quality remains a key problem for both traditional and deep learning (DL)-based approaches to retinal image analysis, but identifying poor quality images can be time consuming and subjective. Thus, automated methods for retinal image quality scoring (RIQS) are needed. The current state-of-the-art is MCFNet, composed of three Densenet121 backbones each

Nilesh Kumar, Prashnna K. Gyawali, Sandesh Ghimire, Linwei Wang

Obtaining labelled data in medical image segmentation is challenging due to the need for pixel-level annotations by experts. Recent works have shown that augmenting the object of interest with deformable transformations can help mitigate this challenge. However, these transformations have been learned globally for the image, limiting their transferability ac

Thomas Basile, Euihun Joung, TaeHwan Oh

We derive manifestly covariant actions of spinning particles starting from coadjoint orbits of isometry groups, by using Hamiltonian reductions. We show that the defining conditions of a classical Lie group can be treated as Hamiltonian constraints which generate the coadjoint orbits of another, dual, Lie group. In case of (inhomogeneous) orthogonal groups,

Alexander Grushin, Walt Woods, Alvaro Velasquez, Simon Khan

Any autonomous controller will be unsafe in some situations. The ability to quantitatively identify when these unsafe situations are about to occur is crucial for drawing timely human oversight in, e.g., freight transportation applications. In this work, we demonstrate that the true criticality of an agent's situation can be robustly defined as the mean redu

A. -K. Gallagher

We show that the Poincar\'{e} inequality holds on an open set $D\subset\mathbb{R}^n$ if and only if $D$ admits a smooth, bounded function whose Laplacian has a positive lower bound on $D$. Moreover, we prove that the existence of such a bounded, strictly subharmonic function on $D$ is equivalent to the finiteness of the strict inradius of $D$ measured with r

Xinyu Zhang, Abdeslam Boularias

Unsupervised localization and segmentation are long-standing robot vision challenges that describe the critical ability for an autonomous robot to learn to decompose images into individual objects without labeled data. These tasks are important because of the limited availability of dense image manual annotation and the promising vision of adapting to an evo

Will Rowan, Patrik Huber, Nick Pears, Andrew Keeling

Accurate 3D face reconstruction from 2D images is an enabling technology with applications in healthcare, security, and creative industries. However, current state-of-the-art methods either rely on supervised training with very limited 3D data or self-supervised training with 2D image data. To bridge this gap, we present a method to generate a large-scale sy

Abhishek Dalai

Layered Cellular Automata (LCA) extends the concept of traditional cellular automata (CA) to model complex systems and phenomena. In LCA, each cell's next state is determined by the interaction of two layers of computation, allowing for more dynamic and realistic simulations. This thesis explores the design, dynamics, and applications of LCA, with a focus on

João R. T. de Mello Neto

Ultra-high-energy cosmic neutrinos (UHE), with energies above 100 PeV, are unparalleled probes of the most energetic astrophysical sources and weak interactions at energies beyond the reach of accelerators. GRAND is an envisioned observatory of UHE particles - neutrinos, cosmic rays, and gamma rays - consisting of 200,000 radio antennas deployed in sub-array

Shayla Sharmin, Reza Koiler, Rifat Sadik, Arpan Bhattacharjee

For serious games on education, understanding the effectiveness of different learning methods in influencing cognitive processes remains a significant challenge. This study investigates the impact of serious games on graph structure learning. For this, we compared our in-house game-based learning (GBL) and video-based learning (VBL) methodologies by evaluati