May 2023 arXiv papers — page 128

V. Filinov, P. Levashov, A. Larkin

The Wigner formulation of quantum mechanics is used to derive a new path integral representation of quantum density of states. A path integral Monte Carlo approach is developed for the numerical investigation of density of states, internal energy and spin--resolved radial distribution functions for a 2D system of strongly correlated soft--sphere fermions. Th

Bijit Mukherjee, Matthew D. Frye, C. Ruth Le Sueur, Michael R. Tarbutt

We study collisions of ultracold CaF molecules in strong static electric fields. These fields allow the creation of long-range barriers in the interaction potential, effectively preventing the molecules from reaching the short-range region where inelastic and other loss processes are likely to occur. We carry out coupled-channel calculations of rate coeffici

Gabriela Ciuperca

We consider a linear model which can have a large number of explanatory variables, the errors with an asymmetric distribution or some values of the explained variable are missing at random. In order to take in account these several situations, we consider the non parametric empirical likelihood (EL) estimation method. Because a constraint in EL contains an i

Hakjin Lee, MinKi Song, Jamyoung Koo, Junghoon Seo

Detection Transformers (DETR) have recently set new benchmarks in object detection. However, their performance in detecting rotated objects lags behind established oriented object detectors. Our analysis identifies a key observation: the boundary discontinuity and square-like problem in bipartite matching poses an issue with assigning appropriate ground trut

Xu-Yang Hou, Zheng Zhou, Xin Wang, Hao Guo

The quantum geometric tensor (QGT) is a fundamental concept for characterizing the local geometry of quantum states. After casting the geometry of pure quantum states and extracting the QGT, we generalize the geometry to mixed quantum states via the density matrix and its purification. The gauge-invariant QGT of mixed states is derived, whose real and imagin

Jonas Bley, Eva Rexigel, Alda Arias, Nikolas Longen

In the field of quantum information science and technology, the representation and visualization of quantum states and related processes are essential for both research and education. In this context, a focus especially lies on ensembles of few qubits. There exist many powerful representations for single-qubit and multi-qubit systems, such as the famous Bloc

Gustavo P. de Brito, Astrid Eichhorn, Ludivine Fausten

In the Standard Model of particle physics, the mass of the Higgs particle can be linked to the scale at which the Standard Model breaks down due to a Landau pole/triviality problem: for a Higgs mass somewhat higher than the measured value, the Standard Model breaks down before the Planck scale. We take a first step towards investigating this relation in the

Sourena Khanzadeh, Samad Alias Nyein Chan, Richard Valenzano, Manar Alalfi

This paper presents an approach that evaluates best-first search methods to code refactoring. The motivation for code refactoring could be to improve the design, structure, or implementation of an existing program without changing its functionality. To solve a very specific problem of coupling and cohesion, we propose using heuristic search-based techniques

Cheuk Ting Li, Sherman S. M. Chow

Access control encryption (ACE) enforces, through a sanitizer as the mediator, that only legitimate sender-receiver pairs can communicate, without the sanitizer knowing the communication metadata, including its sender and recipient identity, the policy over them, and the underlying plaintext. Any illegitimate transmission is indistinguishable from pure noise

David B. Williams-Young, Stephen Yuwono, A. Eugene DePrince, Chao Yang

With growing demand for time-domain simulations of correlated many-body systems, the development of efficient and stable integration schemes for the time-dependent Schr\"odinger equation is of keen interest in modern electronic structure theory. In the present work, we present two novel approaches for the formation of the quantum propagator for time-dependen

Filip Talimdjioski

Let $K=2^\mathbb{N}$ be the Cantor set, let $\mathcal{M}$ be the set of all metrics $d$ on $K$ that give its usual (product) topology, and equip $\mathcal{M}$ with the topology of uniform convergence, where the metrics are regarded as functions on $K^2$. We prove that the set of metrics $d\in\mathcal{M}$ for which the Lipschitz-free space $\mathcal{F}(K,d)$

Andrei E. Egorov

The present work analyzes various aspects of M31 gamma-ray halo emission in its relation to annihilating dark matter (DM). The main aspect is the predicted effect of asymmetry of the intensity of emission due to inverse Compton scattering (ICS) of a possible population of relativistic electrons and positrons ($e^\pm$) in the galactic halo on starlight photon

R. Knapman, T. Tausendpfund, S. A. Díaz, K. Everschor-Sitte

Spatial topology endows topological solitons, such as skyrmions and hopfions, with fascinating dynamics. However, the temporal dimension has so far provided a passive stage on which topological solitons evolve. Here we construct spacetime magnetic hopfions: magnetic textures in two spatial dimensions that when excited by a time-periodic drive develop spaceti

Joannes Vermant, Klara Stokes

In structural rigidity, one studies frameworks of bars and joints in Euclidean space. Such a framework is an articulated structure consisting of rigid bars, joined together at joints around which the bars may rotate. In this paper, we will describe articulated motions of realisations of hypergraphs that uses the terminology of graph of groups, and describe t

Manolis Antonoyiannakis, Hugues Chaté, Serena Dalena, Jessica Thomas

As social issues related to gender bias attract closer scrutiny, accurate tools to determine the gender profile of large groups become essential. When explicit data is unavailable, gender is often inferred from names. Current methods follow a strategy whereby individuals of the group, one by one, are assigned a gender label or probability based on gender-nam

Sahib Julka, Michael Granitzer

Planetary science research involves analysing vast amounts of remote sensing data, which are often costly and time-consuming to annotate and process. One of the essential tasks in this field is geological mapping, which requires identifying and outlining regions of interest in planetary images, including geological features and landforms. However, manually l

S. C. Tripathy, K. Jain, D. Braun, P. Cally

The goal of helioseismology is to provide accurate information about the Sun's interior from the observations of the wave field at its surface. In the last three decades, both global and local helioseismology studies have made significant advances and breakthroughs in solar physics. However, 3-d mapping of the structure and dynamics of sunspots and active re

Biqian Feng, Chenyuan Feng, Daquan Feng, Yongpeng Wu

Stream media content caching is a key enabling technology to promote the value chain of future urban vehicular networks. Nevertheless, the high mobility of vehicles, intermittency of information transmissions, high dynamics of user requests, limited caching capacities and extreme complexity of business scenarios pose an enormous challenge to content caching

Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio

Training a modern machine learning architecture on a new task requires extensive learning-rate tuning, which comes at a high computational cost. Here we develop new Polyak-type adaptive learning rates that can be used on top of any momentum method, and require less tuning to perform well. We first develop MoMo, a Momentum Model based adaptive learning rate f

Peter Plantinga, Jaekwon Yoo, Chandra Dhir

Continual learning for end-to-end automatic speech recognition has to contend with a number of difficulties. Fine-tuning strategies tend to lose performance on data already seen, a process known as catastrophic forgetting. On the other hand, strategies that freeze parameters and append tunable parameters must maintain multiple models. We suggest a strategy t

B. P. Gompertz, M. Nicholl, J. C. Smith, S. Harisankar

We present a semi-analytic model for predicting kilonova light curves from the mergers of neutron stars with black holes (NSBH). The model is integrated into the MOSFiT platform, and can generate light curves from input binary properties and nuclear equation-of-state considerations, or incorporate measurements from gravitational wave (GW) detectors to perfor

Euan T. McGonigle, Haeran Cho

Modern time series data often exhibit complex dependence and structural changes which are not easily characterised by shifts in the mean or model parameters. We propose a nonparametric data segmentation methodology for multivariate time series termed NP-MOJO. By considering joint characteristic functions between the time series and its lagged values, NP-MOJO

Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt

Attention-based graph neural networks (GNNs), such as graph attention networks (GATs), have become popular neural architectures for processing graph-structured data and learning node embeddings. Despite their empirical success, these models rely on labeled data and the theoretical properties of these models have yet to be fully understood. In this work, we p

E. Churazov, I. I. Khabibullin, K. Dolag, N. Lyskova

While hot ICM in galaxy clusters makes these objects powerful X-ray sources, the cluster's outskirts and overdense gaseous filaments might give rise to much fainter sub-keV emission. Cosmological simulations show a prominent "focusing" effect of rich clusters on the space density of the Warm-Hot Intergalactic Medium (WHIM) filaments up to a distance of $\sim

Isabel Rebollido, Sebastian Zieba, Daniela Iglesias, Vincent Bourrier

The presence of minor bodies in exoplanetary systems is in most cases inferred through infra-red excesses, with the exception of exocomets. Even if over 35 years have passed since the first detection of exocomets around beta Pic, only ~ 25 systems are known to show evidence of evaporating bodies, and most of them have only been observed in spectroscopy. With

Z. H. Sun, G. Hagen, T. Papenbrock

Atomic nuclei can exhibit shape coexistence and multi-reference physics that enters in their ground states, and to accurately capture the ensuing correlations and entanglement is challenging. We address this problem by applying single-reference coupled-cluster theory based on spherical and deformed reference states and the tailored coupled-cluster method. Th

Hyungseop Kim

We construct a natural filtration on $T(1)$-local $\mathrm{TC}$ for any animated commutative rings using prismatic cohomology and descent theory. In the course of the construction, we also study some general properties of prismatic cohomology complexes over perfect prisms after inverting distinguished generators. The construction is intrinsic to $\mathrm{TC}

Miri Zilka, Riccardo Fogliato, Jiri Hron, Bradley Butcher

Algorithmic risk assessment instruments (RAIs) increasingly inform decision-making in criminal justice. RAIs largely rely on arrest records as a proxy for underlying crime. Problematically, the extent to which arrests reflect overall offending can vary with the person's characteristics. We examine how the disconnect between crime and arrest rates impacts RAI

Andrea Di Lorenzo, Roberto Fringuelli, Angelo Vistoli

We compute the integral Picard group of the moduli stack of polarized K3 surfaces of fixed degree whose singularities are at most rational double points. We also compute the integral Picard group of the stack of quasi-polarized K3 surfaces, and of the stacky period domain.

Larry Lüer, Marius Peters, Ana Sunčana Smith, Eva Dorschky

The recent successes of emerging photovoltaics (PV) such as organic and perovskite solar cells are largely driven by innovations in material science. However, closing the gap to commercialization still requires significant innovation to match contradicting requirements such as performance, longevity and recyclability. The rate of innovation, as of today, is

Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho

Originally introduced as a neural network for ensemble learning, mixture of experts (MoE) has recently become a fundamental building block of highly successful modern deep neural networks for heterogeneous data analysis in several applications of machine learning and statistics. Despite its popularity in practice, a satisfactory level of theoretical understa

Henriette Lipschütz, Ulrich Reitebuch, Konrad Polthier, Martin Skrodzki

Point clouds and polygonal meshes are widely used when modeling real-world scenarios. Here, point clouds arise, for instance, from acquisition processes applied in various surroundings, such as reverse engineering, rapid prototyping, or cultural preservation. Based on these raw data, polygonal meshes are created to, for example, run various simulations. For

Indra Kumar Banerjee, Ujjal Kumar Dey

In this article we investigate the cumulative stochastic gravitational wave spectra as a tool to gain insight on the creation mechanism of primordial black holes. We consider gravitational waves from the production mechanism of primordial black holes and from the gravitational interactions of those primordial black holes among themselves and other astrophysi

Alex Gnech, Laura Elisa Marcucci, Michele Viviani

We compute the muon capture on deuteron in the doublet hyperfine state for a variety of nuclear interactions and consistent nuclear currents. Our analysis includes a detailed examination of the theoretical uncertainties coming from different sources: the single-nucleon axial form factor, the truncation of the interaction and current chiral expansion, and the

Gianira N. Alfarano, Eimear Byrne

In this paper, we describe properties of the characteristic polynomial of a weighted lattice and show that it has a recursive description, which we use to obtain results on the critical exponent of $q$-polymatroids. We give a Critical Theorem for representable $q$-polymatroids and we provide a lower bound on the critical exponent. We show that $q$-polymatroi

Alexander Borisenko, Vicente Miquel

Let $M$ be a $2$-space form. Let $P$ be a convex polygon in $M$. For these polygons, we define (and justify) a curvature $\kappa_i$ at each vertex $A_i$ of the polygon and and prove the following Blaschke's type theorem: If $P$ is a convex plygon in $M$ with curvature at its vertices $\kappa_i\ge \kappa_0 >0$, then the circumradius $R$ of $P$ satisfies $ta_\

Vladimir Araujo, Alvaro Soto, Marie-Francine Moens

Existing question answering methods often assume that the input content (e.g., documents or videos) is always accessible to solve the task. Alternatively, memory networks were introduced to mimic the human process of incremental comprehension and compression of the information in a fixed-capacity memory. However, these models only learn how to maintain memor

Brian D Williamson, Richard Wyss, Elizabeth A Stuart, Lauren E Dang

Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these settings, it is important to document analytic decisions transparently and objectively to ensure that analyses meet their intended goals. The Causal Roadmap is an established framewor

Tim Axelrod, Abhijit Saha, Thomas Matheson, Edward W. Olszewski

Hot DA white dwarfs have fully radiative pure hydrogen atmospheres that are the least complicated to model. Pulsationally stable, they are fully characterized by their effective temperature Teff, and surface gravity log g, which can be deduced from their optical spectra and used in model atmospheres to predict their spectral energy distribution (SED). Based

Changjun Fan, Mutian Shen, Zohar Nussinov, Zhong Liu

We wish to thank Stefan Boettcher for prompting us to further check and highlight the accuracy and scaling of our results. Here we provide a comprehensive response to the Comment written by him. We argue that the Comment did not account for the fairness of the comparison between different methods in searching for the spin-glass ground states. We demonstrate

Siddhant Pinjarkar, Martin J. Hardcastle, Jeremy J. Harwood, Dharam V. Lal

Jets of energetic particles, as seen in FR type-I and FR type-II sources, ejected from the center of Radio-Loud AGN affect the sources surrounding intracluster medium/intergalactic medium. Placing constraints on the age of such sources is important in order to measure the jet powers and determine the effects on feedback. To evaluate the age of these sources

Michael M. Danziger, Omkar R. Gojala, Sean P. Cornelius

Though robustness of networks to random attacks has been widely studied, intentional destruction by an intelligent agent is not tractable with previous methods. Here we devise a single-player game on a lattice that mimics the logic of an attacker attempting to destroy a network. The objective of the game is to disable all nodes in the fewest number of steps.

Christopher J. Cho, Timothy J. Norman, Manuel Nunes

In a financial exchange, market impact is a measure of the price change of an asset following a transaction. This is an important element of market microstructure, which determines the behaviour of the market following a trade. In this paper, we first provide a discussion on the market impact observed in the BTC/USD Futures market, then we present a novel mu

Emanuele Bugliarello, Laurent Sartran, Aishwarya Agrawal, Lisa Anne Hendricks

While pretraining on large-scale image-text data from the Web has facilitated rapid progress on many vision-and-language (V&L) tasks, recent work has demonstrated that pretrained models lack "fine-grained" understanding, such as the ability to recognise relationships, verbs, and numbers in images. This has resulted in an increased interest in the community t

SHINE Collaboration, H. Adhikary, P. Adrich, K. K. Allison

The critical point of dense, strongly interacting matter is searched for at the CERN SPS in ${}^{40}$Ar + ${}^{45}$Sc collisions at 150A GeV/c. The dependence of second-order scaled factorial moments of proton multiplicity distribution on the number of subdivisions of transverse momentum space is measured. The intermittency analysis is performed using both t

Juan I. Bonetti, Agustín C. Galletto, Mario R. Hueda

In this work we provide a mathematical framework to describe the periodically time variant (PTV) linear systems. We study their frequency-domain features to estimate the output bandwidth, a necessary value to obtain a suitable digital representation of such systems. In addition, we derive several interesting properties enabling useful equivalences to represe

Belle II Collaboration, I. Adachi, K. Adamczyk, L. Aggarwal

We report a measurement of the $C\!P$-violating parameters $A$ and $S$ in $B^{0}\to K_{S}^{0} \pi^{0}$ decays at Belle II using a sample of $387\times 10^{6}$ $B\bar{B}$ events recorded in $e^{+}e^{-}$ collisions at a center-of-mass energy corresponding to the $\Upsilon(4S)$ resonance. These parameters are determined by fitting the proper decay-time distribu

Keenan J. A. Down, Pedro A. M. Mediano

The Shannon entropy of a random variable $X$ has much behaviour analogous to a signed measure. Previous work has concretized this connection by defining a signed measure $\mu$ on an abstract information space $\tilde{X}$, which is taken to represent the information that $X$ contains. This construction is sufficient to derive many measure-theoretical counterp

Tomotaka Momozaki, Tomoyuki Nakagawa

Ordinal response model is a popular and commonly used regression for ordered categorical data in a wide range of fields such as medicine and social sciences. However, it is empirically known that the existence of ``outliers'', combinations of the ordered categorical response and covariates that are heterogeneous compared to other pairs, makes the inference w

Mansi Goel, Shashank Dargar, Shounak Ghatak, Nidhi Verma

Diet is central to the epidemic of lifestyle disorders. Accurate and effortless diet logging is one of the significant bottlenecks for effective diet management and calorie restriction. Dish detection from food platters is a challenging problem due to a visually complex food layout. We present an end-to-end computational framework for diet management, from d

Fang Guo, Franklin Okoli, Ulrike Schick, Dimitris Visvikis

Non-coplanar Intensity-Modulated Radiation Therapy (IMRT) goes a step further by orienting the gantry carrying the radiation beam and the patient couch in a non-coplanar manner to accurately target the cancer region and better avoid organs-at-risk. The use of a non-coplanar treatment trajectory significantly enhances the degree of freedom and flexibility but

Florian Brück, Jean-David Fermanian, Aleksey Min

There exist some testing procedures based on the maximum mean discrepancy (MMD) to address the challenge of model specification. However, they ignore the presence of estimated parameters in the case of composite null hypotheses. In this paper, we first illustrate the effect of parameter estimation in model specification tests based on the MMD. Second, we pro

Jan Hückelheim, Harshitha Menon, William Moses, Bruce Christianson

Automatic differentiation, also known as backpropagation, AD, autodiff, or algorithmic differentiation, is a popular technique for computing derivatives of computer programs accurately and efficiently. Sometimes, however, the derivatives computed by AD could be interpreted as incorrect. These pitfalls occur systematically across tools and approaches. In this

G. Migliori, A. Siemiginowska, M. Sobolewska, C. C. Cheung

We present the first X-ray observation at sub-arcsecond resolution of the high-redshift ($z=6.18$) radio-loud quasar CFHQS J142952+544717 (J1429). The ~100 net-count 0.3-7 keV spectrum obtained from $\sim 30$ ksec Chandra exposure is best fit by a single power-law model with a photon index $\Gamma=2.0\pm0.2$ and no indication of an intrinsic absorber, implyi

Dimitrios Tyrovolas, Sotiris A. Tegos, Vasilis K. Papanikolaou, Yue Xiao

A primary objective of the forthcoming sixth generation (6G) of wireless networking is to support demanding applications, while ensuring energy efficiency. Programmable wireless environments (PWEs) have emerged as a promising solution, leveraging reconfigurable intelligent surfaces (RISs), to control wireless propagation and deliver exceptional quality-ofser

Jin Wang, Ali Khosravi, Andrea Silva, Michele Fabrizio

The freestanding twisted bilayer graphene (TBG) is unstable, below a critical twist angle {\theta}_c~3.7 degrees, against a moire (2 \times 1) buckling distortion at T=0. Realistic simulations reveal the concurrent unexpected collapse of the bending rigidity, an unrelated macroscopic mechanical parameter. An analytical model connects bending and buckling ano

Giuseppe Bogna, Lionel Mason

The construction of perturbative quantities on non-linear backgrounds leads to the possibility of incorporating strong field effects in perturbation theory. We continue a programme to construct QFT observables on self-dual backgrounds. The approach works with asymptotic data for fields defined at null infinity $\mathscr{I}$, extending earlier work on Yang-Mi

Ayan Banerjee, Takol Tangphati, Anirudh Pradhan

We explore the existence of wormholes in the context of $f(R,T)$ gravity. The $f(R,T)$ theory is a curvature-matter coupled modified gravity that depends on an arbitrary function of the Ricci scalar $R$ and the trace of the stress-energy tensor $T$. In this work, we adopt two different choices for the matter Lagrangian density ($\mathcal{L}_m= \mathcal{P}$ a

Amin Muhammad Shoib, Summaira Jabeen, Changbo Wang, Tassawar Ali

Jewellery item retrieval is regularly used to find what people want on online marketplaces using a sample query reference image. Considering recent developments, due to the simultaneous nature of various jewelry items, various jewelry goods' occlusion in images or visual streams, as well as shape deformation, content-based jewellery item retrieval (CBJIR) st

David Krieg, Kateryna Pozharska, Mario Ullrich, Tino Ullrich

We study the recovery of functions in various norms, including $L_p$ with $1\le p\le\infty$, based on function evaluations. We obtain worst case error bounds for general classes of functions in terms of the best $L_2$-approximation from a given nested sequence of subspaces and the Christoffel function of these subspaces. In the case $p=\infty$, our results i

Rajasekar Gopalsamy, Nicolas Chevaugeon, Olivier Chupin, Ferhat Hammoum

Fracture of viscoelastic materials is considered to be a complex phenomenon due to their highly rate sensitive behavior. In this context, we are interested in the quasi-static response of a viscoelastic solid subjected to damage. This paper outlines a new incremental variational based approach and its computational implementation to model damage in viscoelas

Junjia Chen, Zhibin Pan

Activation functions are essential to deep learning networks. Popular and versatile activation functions are mostly monotonic functions, some non-monotonic activation functions are being explored and show promising performance. But by introducing non-monotonicity, they also alter the positive input, which is proved to be unnecessary by the success of ReLU an

Antonio Capolupo, Salvatore Marco Giampaolo, Aniello Quaranta

We report on recent result according to which the fermion-fermion interaction mediated by axions and axion-like particles can be revealed by means of neutron interferometry. We assume that the initial neutron beam is split in two beams which are affected by differently oriented magnetic fields, in order that the phase difference depends only by the axion-ind

Asia La Rocca, Matteo Saveriano, Andrea Del Prete

Safety is often the most important requirement in robotics applications. Nonetheless, control techniques that can provide safety guarantees are still extremely rare for nonlinear systems, such as robot manipulators. A well-known tool to ensure safety is the Viability kernel, which is the largest set of states from which safety can be ensured. Unfortunately,

Péter Salvi

Most genuine multi-sided surface representations depend on a 2D domain that enables a mapping between local parameters and global coordinates. The shape of this domain ranges from regular polygons to curved configurations, but the simple circular domain - to the best of our knowledge - has not been investigated yet. Here we fill this gap, and introduce a par

Antonio Capolupo, Gaetano Lambiase, Aniello Quaranta

We develop the quantum field theory of fermion mixing in curved spacetime and discuss the role of unitarily inequivalent representations in the particle interpretation of the theory. We derive general oscillation formulae and apply them to specific spcetimes of interest, such as spatially flat FRW metrics and the Schwarzschild spacetime. We exhibit the main

Denise Lanzieri, François Lanusse, Chirag Modi, Benjamin Horowitz

We present the Differentiable Lensing Lightcone (DLL), a fully differentiable physical model designed for being used as a forward model in Bayesian inference algorithms requiring access to derivatives of lensing observables with respect to cosmological parameters. We extend the public FlowPM N-body code, a particle-mesh N-body solver, simulating lensing ligh

Vagner Figueredo de Santana, Larissa Monteiro Da Fonseca Galeno, Emilio Vital Brazil, Aliza Heching

Evaluating human-AI decision-making systems is an emerging challenge as new ways of combining multiple AI models towards a specific goal are proposed every day. As humans interact with AI in decision-making systems, multiple factors may be present in a task including trust, interpretability, and explainability, amongst others. In this context, this work prop

Maddalena Torricelli, Max Falkenberg, Alessandro Galeazzi, Fabiana Zollo

The public understanding of climate change plays a critical role in translating climate science into climate action. In the public discourse, climate impacts are often discussed in the context of extreme weather events. Here, we analyse 65 million Twitter posts and 240 thousand news media articles related to 18 major hurricanes from 2010 to 2022 to clarify h

Aboli Marathe, Deva Ramanan, Rahee Walambe, Ketan Kotecha

The open road poses many challenges to autonomous perception, including poor visibility from extreme weather conditions. Models trained on good-weather datasets frequently fail at detection in these out-of-distribution settings. To aid adversarial robustness in perception, we introduce WEDGE (WEather images by DALL-E GEneration): a synthetic dataset generate

Angzhen Li, Jonathan M. Ward, Ke Tian, Jibo Yu

The fabrication of whispering gallery lasers (WGL) is used to experimentally evaluate the evaporation rate (mol/$\mu$m) and ratio (mol/mol) of erbium and silica lost from a doped fiber during heating. Fixed lengths of doped silica fiber are spliced to different lengths of undoped fiber and then evaporated by feeding into the focus of a CO$_{2}$ laser. During

Isabelle Chalendar, Pavel Gumenyuk, John E. McCarthy

Motivated by the study of composition operators on model spaces launched by Mashreghi and Shabankha we consider the following problem: for a given inner function $\phi\not\in\mathsf{Aut}(\mathbb D)$, find a non-constant inner function $\Psi$ satisfying the functional equation $\Psi\circ\phi=\tau\Psi$, where $\tau$ is a unimodular constant. We prove that this

Panagiotis Kanellopoulos, Alexandros A. Voudouris, Rongsen Zhang

We study a truthful two-facility location problem in which a set of agents have private positions on the line of real numbers and known approval preferences over two different facilities. Given the locations of the two facilities, the cost of an agent is the total distance from the facilities she approves. The goal is to decide where to place the facilities

Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer, Daniel Cremers

Current MRI super-resolution (SR) methods only use existing contrasts acquired from typical clinical sequences as input for the neural network (NN). In turbo spin echo sequences (TSE) the sequence parameters can have a strong influence on the actual resolution of the acquired image and have consequently a considera-ble impact on the performance of the NN. We

I. V. Florinsky

Geomorphometric modeling is widely used in geosciences. However, geomorphometric modeling and mapping of Antarctic oases has not been performed so far. This article presents the first results of our work on geomorphometric modeling and mapping of several Antarctic oases including the Larsemann Hills, Thala Hills, Schirmacher oasis, and Fildes Peninsula. As i

Minjae Lee, Seongmin Park, Hyungmin Kim, Minyong Yoon

3D object detection using point cloud (PC) data is essential for perception pipelines of autonomous driving, where efficient encoding is key to meeting stringent resource and latency requirements. PointPillars, a widely adopted bird's-eye view (BEV) encoding, aggregates 3D point cloud data into 2D pillars for fast and accurate 3D object detection. However, t

Bo Jiang, Fei Xu, Ziyan Zhang, Jin Tang

To alleviate the local receptive issue of GCN, Transformers have been exploited to capture the long range dependences of nodes for graph data representation and learning. However, existing graph Transformers generally employ regular self-attention module for all node-to-node message passing which needs to learn the affinities/relationships between all node's

Shan Ren

Let $\mathbb{F}_p$ be the prime field of order $p>0$ and $G$ be an elementary abelian $p$-group.For some $n$-dimensional cohyperplane $G$-representations $V$ over $\mathbb{F}_p$, we show that $\mathbb{F}_p[V\oplus V^*]^G$, the invariant ring of a vector and a covector is a complete intersection by exhibiting an explicit generating set (in fact, a SAGBI basis

Peirong Ning, Wei Jiang, Ronggang Wang

In recent years, there has been rapid development in learned image compression techniques that prioritize ratedistortion-perceptual compression, preserving fine details even at lower bit-rates. However, current learning-based image compression methods often sacrifice human-friendly compression and require long decoding times. In this paper, we propose enhanc

Kunal Pal, Kuntal Pal, Rajibul Shaikh, Tapobrata Sarkar

The Event Horizon Telescope has recently observed the images and shadows of the compact objects M87$^*$ and Sgr A$^*$ at the centres of the galaxies Messier 87 and Milky Way. This has opened up a new window in observational astronomy to probe and test gravity and fundamental physics in the strong-field regime. In this paper, we consider a rotating version of

Pragathi Praveena, Yeping Wang, Emmanuel Senft, Michael Gleicher

We investigate how robotic camera systems can offer new capabilities to computer-supported cooperative work through the design, development, and evaluation of a prototype system called Periscope. With Periscope, a local worker completes manipulation tasks with guidance from a remote helper who observes the workspace through a camera mounted on a semi-autonom

V. A. Goloveshkin, A. G. Kudryavtsev, N. N. Myagkov

Exact solutions describing Rossby waves and vortices in ocean propagating along the zonal direction at a constant velocity are considered for the (3+1)-dimensional nonlinear Charney-Obukhov equation. In the first part of our work, we give examples of solutions of the Charney-Obukhov equation that satisfy the nonlinear boundary conditions of the ocean, for a

Santiago de Leon-Martinez, Robert Moro, Maria Bielikova

Eye tracking in recommender systems can provide an additional source of implicit feedback, while helping to evaluate other sources of feedback. In this study, we use eye tracking data to inform a collaborative filtering model for movie recommendation providing an improvement over the click-based implementations and additionally analyze the area of interest (

Anna Ivagnes, Nicola Demo, Gianluigi Rozza

In this paper, we propose a shape optimization pipeline for propeller blades, applied to naval applications. The geometrical features of a blade are exploited to parametrize it, allowing to obtain deformed blades by perturbating their parameters. The optimization is performed using a genetic algorithm that exploits the computational speed-up of reduced order

Kacper Kania, Stephan J. Garbin, Andrea Tagliasacchi, Virginia Estellers

Generating faithful visualizations of human faces requires capturing both coarse and fine-level details of the face geometry and appearance. Existing methods are either data-driven, requiring an extensive corpus of data not publicly accessible to the research community, or fail to capture fine details because they rely on geometric face models that cannot re

Paolo Abiuso

A proper quantum memory is argued to consist in a quantum channel which cannot be simulated with a measurement followed by classical information storage and a final state preparation, i.e. an entanglement breaking (EB) channel. The verification of quantum memories (non-EB channels) is a task in which an honest user wants to test the quantum memory of an untr

Youyang Qu, Xin Yuan, Ming Ding, Wei Ni

Machine Learning (ML) models have been shown to potentially leak sensitive information, thus raising privacy concerns in ML-driven applications. This inspired recent research on removing the influence of specific data samples from a trained ML model. Such efficient removal would enable ML to comply with the "right to be forgotten" in many legislation, and co

Matteus Vargas Simão da Silva, Rodrigo Reis Arrais, Jhessica Victoria Santos da Silva, Felipe Souza Tânios

Over the last few years, the number of works about deep learning applied to the medical field has increased enormously. The necessity of a rigorous assessment of these models is required to explain these results to all people involved in medical exams. A recent field in the machine learning area is explainable artificial intelligence, also known as XAI, whic

Evan Smith, Lani Oramas, Eric Perlman

We report a 325(-7, +8) day quasi-periodic oscillation (QPO) in the X-ray emission of the blazar Mkn 421, based on data obtained with the Rossi X-ray Timing Explorer (RXTE). The QPO is seen prominently in the ASM data (at least 15 cycles), due to the fact that it has had near-continuous sampling for more than a decade. The PCA data, where the sampling is not

A. J. Pan-Collantes, C. Muriel, A. Ruiz, J. L. Romero

For a system of ordinary differential equations (ODEs) or, more generally, an involutive distribution of vector fields, the problem of its integration is considered. Among the many approaches to this problem, solvable structures provide a systematic procedure of integration via Pfaffian equations that are integrable by quadratures. In this paper structures m

Ilias Chalkidis, Nicolas Garneau, Catalina Goanta, Daniel Martin Katz

In this work, we conduct a detailed analysis on the performance of legal-oriented pre-trained language models (PLMs). We examine the interplay between their original objective, acquired knowledge, and legal language understanding capacities which we define as the upstream, probing, and downstream performance, respectively. We consider not only the models' si

Ferdinand Bhavsar, Nicolas Desassis, Fabien Ors, Thomas Romary

The simulation of geological facies in an unobservable volume is essential in various geoscience applications. Given the complexity of the problem, deep generative learning is a promising approach to overcome the limitations of traditional geostatistical simulation models, in particular their lack of physical realism. This research aims to investigate the ap

Piotr Kabaciński, Pietro Marabotti, Patrick Serafini, Daniele Fazzi

One-dimensional (1D) linear nanostructures comprising sp-hybridized carbon atoms, as derivatives of the prototypical allotrope known as carbyne, are predicted to possess outstanding mechanical, thermal, and electronic properties. Despite recent advances in the synthesis, their chemical and physical properties are still poorly understood. Here, we investigate

Takanori Anegawa, Norihiro Iizuka, Arkaprava Mukherjee, Sunil Kumar Sake

We study a system of $N$ qubits with a random Hamiltonian obtained by drawing coupling constants from Gaussian distributions in various ways. This results in a rich class of systems which include the GUE and the fixed $q$ SYK theories. Our motivation is to understand the system at large $N$. In practice most of our calculations are carried out using exact di

Jiayi Huang, Sangwoo Park, Osvaldo Simeone

Deep learning models, including modern systems like large language models, are well known to offer unreliable estimates of the uncertainty of their decisions. In order to improve the quality of the confidence levels, also known as calibration, of a model, common approaches entail the addition of either data-dependent or data-independent regularization terms

Chaoan Li, Xianjie Yan, Dachun Yang

Let $A$ be a general expansive matrix and $X$ be a ball quasi-Banach function space on $\mathbb R^n$, whose certain power (namely its convexification) supports a Fefferman--Stein vector-valued maximal inequality and the associate space of whose other power supports the boundedness of the powered Hardy--Littlewood maximal operator. Let $H_X^A(\mathbb{R}^n)$ b

Jinqiang Li, Miao Ye, Linqiang Huang, Xiaofang Deng

Due to the highly dynamic changes in wireless network topologies, efficiently obtaining network status information and flexibly forwarding data to improve communication quality of service are important challenges. This article introduces an intelligent routing algorithm (DRL-PPONSA) based on proximal policy optimization deep reinforcement learning with netwo

Sonia Foschiatti

We consider the inverse problem of the simultaneous identification of the coefficients $\sigma$ and $q$ of the equation div$(\sigma\nabla u) + qu=0$ from the knowledge of the complete Cauchy data pairs. We assume that $\sigma=\gamma A$ where $A$ is a given matrix function and $\gamma, q$ are unknown piecewise affine scalar functions. No sign, nor spectrum co

Henk Bruin, Hector Homero Canales Farias

The aim of this paper is to obtain polynomial decay of correlations of a Lorenz-like flow where the hyperbolic saddle at the origin is replaced by a neutral saddle. To do that, we take the construction of the geometrical Lorenz flow and proceed by changing the nature of the saddle fixed point at the origin by a neutral fixed point. This modification is accom

Hannes Holey, Peter Gumbsch, Lars Pastewka

Although continuum theories have been proven quite robust to describe confined fluid flow at molecular length scales, molecular dynamics (MD) simulations reveal mechanistic insights into the interfacial dissipation processes. Most MD simulations of confined fluids have used setups in which the lateral box size is not much larger than the gap height, thus bre