July 2023 arXiv papers — page 148

Umberto D'Alesio, Leonard Gamberg, Francesco Murgia, Marco Zaccheddu

We present a phenomenological study on the role of charm contribution and $SU(2)$ isospin symmetry in the extraction of the $\Lambda$ polarizing fragmentation functions from $e^+e^- \to \Lambda^\uparrow (\bar\Lambda^\uparrow) \,h + X$ annihilation processes. We adopt the well-established transverse-momentum-dependent factorization formalism, within the Colli

Ana Guerberof Arenas, Antonio Toral

This article presents the results of a study involving the reception of a fictional story by Kurt Vonnegut translated from English into Catalan and Dutch in three conditions: machine-translated (MT), post-edited (PE) and translated from scratch (HT). 223 participants were recruited who rated the reading conditions using three scales: Narrative Engagement, En

Arif Wider, Sumedha Verma, Atif Akhtar

Data mesh is a socio-technical approach to decentralized analytics data management. To manage this decentralization efficiently, data mesh relies on automation provided by a self-service data infrastructure platform. A key aspect of this platform is to enable decentralized data governance. Because data mesh is a young approach, there is a lack of coherence i

Aubin JC. M. Prot, Michele Melchiorre, Felix Dingwell, Anastasia Zelenina

Record efficiency in chalcopyrite-based solar cells Cu(In,Ga)(S,Se)2 is achieved using a gallium gradient to increase the band gap of the absorber towards the back side. Although this structure has successfully reduced recombination at the back contact, we demonstrate that in industrial absorbers grown in the pilot line of Avancis, the back part is a source

Ester Piedipalumbo, Stefano Vignolo, Pasquale Feola, Salvatore Capozziello

In the framework of scalar-tensor gravity, we consider non-flat interacting quintessence cosmology where a scalar field is interacting with dark matter. Such a scalar field can be a standard or a phantom one. We use the Noether Symmetry Approach to obtain general exact solutions for cosmological equations and to select scalar-field self-interaction potential

S. Kladov, M. Bossard, J. Brandt, Y-K. Kim

We built a test stand for evaluating the performance of the thermionic electron sources for the electron lens project at the Integrable Optics Test Accelerator (IOTA) in Fermilab. The lens will be used to study nonlinear dynamics and electron cooling of 2.5 MeV protons with strong space charge. The test stand will validate the characteristics of the thermion

Lorenzo Lombardi, Alessandro Kovtun, Sebastiano Mantovani, Giulio Bertuzzi

We present an environmentally benign methodology for the covalent functionalization (arylation) of reduced graphene oxide (rGO) nanosheets with arylazo sulfones. A variety of tagged aryl units were conveniently accommodated at the rGO surface via visible light irradiation of suspensions of carbon nanostructured materials in aqueous media. Mild reaction condi

K. Lelas, I. Nakić

Common criteria used for measuring performance of vibrating systems have one thing in common: they do not depend on initial conditions of the system. In some cases it is assumed that the system has zero initial conditions, or some kind of averaging is used to get rid of initial conditions. The aim of this paper is to initiate rigorous study of the dependence

Haoran Miao, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan

Recently, there has been increasing progress in end-to-end automatic speech recognition (ASR) architecture, which transcribes speech to text without any pre-trained alignments. One popular end-to-end approach is the hybrid Connectionist Temporal Classification (CTC) and attention (CTC/attention) based ASR architecture. However, how to deploy hybrid CTC/atten

Simon Ekhammar, Joseph A. Minahan, Charles Thull

We use the quantum spectral curve to compute the Hagedorn temperature for ABJM theory in terms of the interpolating function $h(\lambda)$. At weak coupling we compute this temperature up to eight-loop order, showing that it matches the known tree-level and two-loop results. At strong coupling we compute the dependence numerically, showing that it is consiste

Moritz von Tresckow, Herbert De Gersem, Dimitrios Loukrezis

This work proposes a hybrid modeling framework based on recurrent neural networks (RNNs) and the finite element (FE) method to approximate model discrepancies in time dependent, multi-fidelity problems, and use the trained hybrid models to perform bias correction of the low-fidelity models. The hybrid model uses FE basis functions as a spatial basis and RNNs

Lukas Kienesberger, Thomas Juffmann, Stefan Nimmrichter

Optical near fields are at the heart of various applications in sensing and imaging. We investigate dipole scattering as a parameter estimation problem and show that optical near-fields carry more information about the location and the polarizability of the scatterer than the respective far fields. This increase in information originates from and occurs simu

Peter Lorenz, Ricard Durall, Janis Keuper

Diffusion models recently have been successfully applied for the visual synthesis of strikingly realistic appearing images. This raises strong concerns about their potential for malicious purposes. In this paper, we propose using the lightweight multi Local Intrinsic Dimensionality (multiLID), which has been originally developed in context of the detection o

Jehanne Dousse, Frédéric Jouhet, Isaac Konan

We show that the Bailey lattice can be extended to a bilateral version in just a few lines from the bilateral Bailey lemma, using a very simple lemma transforming bilateral Bailey pairs relative to $a$ into bilateral Bailey pairs relative to $a/q$. Using this and similar lemmas, we give bilateral versions and simple proofs of other (new and known) Bailey lat

Outongyi Lv, Bingxin Zhou

Modern reinforcement learning (RL) can be categorized into online and offline variants. As a pivotal aspect of both online and offline RL, current research on the Bellman equation revolves primarily around optimization techniques and performance enhancement rather than exploring the inherent structural properties of the Bellman error, such as its distributio

Mikko Jaskari

We apply the resonance method to Montgomery's convolution formula for $\textrm{Re}\left(e^{-i\theta}\log\zeta(\sigma+it)\right)$ in the strip $1/2 < \sigma < 1$. This gives new insight into maximal values of $\textrm{Re}\left(e^{-i\theta}\log\zeta(\sigma+it)\right)$ for $t \in [T^{\beta},T]$ for all $\beta \in (0,1)$ and real $\theta$.

A. Tesi, S. Leardini, L. Moleri, D. Gonzalez-Diaz

The operation of a cryogenic Resistive WELL (RWELL) in liquid argon vapor is reported for the first time. It comprises a Thick Gas Electron Multiplier (THGEM) structure coupled to a resistive Diamond-Like Carbon (DLC) anode deposited on an insulating substrate. The multiplier was operated at cryogenic temperature (90~K, 1.2~bar) in saturated argon vapor and

Matthias Grundmann, Hannes Hartenstein

Payment channel networks are an approach to improve the scalability of blockchain-based cryptocurrencies. Because payment channel networks are used for transfer of financial value, their security in the presence of adversarial participants should be verified formally. We formalize the protocol of the Lightning Network, a payment channel network built for Bit

Tristan Guyon, Arnaud Guillin, Manon Michel

Event-Chain Monte Carlo (ECMC) methods generate continuous-time and non-reversible Markov processes which often display significant accelerations compared to reversible counterparts. However their generalization to any system may appear less straightforward. In this work, our aim is to distinctly define the essential symmetries that such ECMC algorithms must

Timo Pierre Schrader, Teresa Bürkle, Sophie Henning, Sherry Tan

Scientific publications follow conventionalized rhetorical structures. Classifying the Argumentative Zone (AZ), e.g., identifying whether a sentence states a Motivation, a Result or Background information, has been proposed to improve processing of scholarly documents. In this work, we adapt and extend this idea to the domain of materials science research. W

Ludwig Mohr, Ismail Geles, Friedrich Fraundorfer

Rigid registration of point clouds is a fundamental problem in computer vision with many applications from 3D scene reconstruction to geometry capture and robotics. If a suitable initial registration is available, conventional methods like ICP and its many variants can provide adequate solutions. In absence of a suitable initialization and in the presence of

Kai-Peng Lu, Wenbin Li, Jia-Hui Huang

We consider the stability of six-dimensional singly rotating Myers-Perry black holes under massive scalar perturbations. Using Leaver's continued fraction method, we compute the quasinormal modes of the massive scalar fields. All modes found are damped under the quasinormal boundary conditions. It is also found that long-living modes called quasiresonances e

Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada

Flatness of the loss curve around a model at hand has been shown to empirically correlate with its generalization ability. Optimizing for flatness has been proposed as early as 1994 by Hochreiter and Schmidthuber, and was followed by more recent successful sharpness-aware optimization techniques. Their widespread adoption in practice, though, is dubious beca

Oleg Melichev, Roberto Percacci

Poincar\'e Gauge Theories are a class of Metric-Affine Gravity theories with a metric-compatible (i.e. Lorentz) connection and with an action quadratic in curvature and torsion. We perform an explicit one-loop calculation starting with a single term of each type and show that not only are all other terms generated, but also many others. In our particular mod

Yao Dai, Jun Xu, Jie Song, Guanwen Fang

By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band selected massive galaxies in the COSMOS-DASH field, which includes 17292 galaxies with stellar mass $M_{\star}>10^{10}~M_{\odot}$ at $0.5<z<2.5$. The classification scheme is designed to provide a complete morphology

Jiamiao Zhang, Yichen Chi, Jun Lyu, Wenming Yang

Limited by imaging systems, the reconstruction of Magnetic Resonance Imaging (MRI) images from partial measurement is essential to medical imaging research. Benefiting from the diverse and complementary information of multi-contrast MR images in different imaging modalities, multi-contrast Super-Resolution (SR) reconstruction is promising to yield SR images

Marco Ajello, Kohta Murase, Alex McDaniel

The recent detection of high-energy neutrinos by IceCube in the direction of the nearby Seyfert/starburst galaxy NGC 1068 implies that radio-quiet active galactic nuclei can accelerate cosmic-ray ions. Dedicated multi-messenger analyses suggest that the interaction of these high-energy ions { with ambient gas or photons} happens in a region of the galaxy tha

Andrés Domínguez Hernández, Kopo M. Ramokapane, Partha Das Chowdhury, Ola Michalec

The phrase "online harms" has emerged in recent years out of a growing political willingness to address the ethical and social issues associated with the use of the Internet and digital technology at large. The broad landscape that surrounds online harms gathers a multitude of disciplinary, sectoral and organizational efforts while raising myriad challenges

Suhwan Bong, Kwonsang Lee, Francesca Dominici

Observational studies are frequently used to estimate the effect of an exposure or treatment on an outcome. To obtain an unbiased estimate of the treatment effect, it is crucial to measure the exposure accurately. A common type of exposure misclassification is recall bias, which occurs in retrospective cohort studies when study subjects may inaccurately reca

Stefano Fasciani

This paper presents a bibliometric analysis that examines the works cited in, as well as those citing, NIME papers; for brevity, we refer to these as `references` and `citations`. Utilizing existing tools, we have computationally extracted data from the NIME proceedings archive and retrieved metadata from an academic database, including details of associated

Marco Skocaj, Francesca Conserva, Nicol Sarcone Grande, Andrea Orsi

The advent of novel 5G services and applications with binding latency requirements and guaranteed Quality of Service (QoS) hastened the need to incorporate autonomous and proactive decision-making in network management procedures. The objective of our study is to provide a thorough analysis of predictive latency within 5G networks by utilizing real-world net

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $e^+e^-$ collision datasets corresponding to total integrated luminosity of 21.7 fb$^{-1}$ collected with the BESIII detector at the BEPCII collider at center-of-mass energies ranging from 4.009 GeV to 4.951 GeV, the energy-dependent cross sections of $e^+e^-\to pK^-\bar{\Lambda}+c.c.$ are measured for the first time. By fitting these energy-dependent

Sung-Ho Lee, Jing Li, Valerio Olevano, Benoit Sklénard

Thermal conductivity is a fundamental material property that plays an essential role in technology, but its accurate evaluation presents a challenge for theory. In this work, we demonstrate the application of $E(3)$-equivariant neutral network interatomic potentials within Green-Kubo formalism to determine the lattice thermal conductivity in amorphous and cr

Shiqi Pan

We consider the Robber Locating Game, where an invisible moving robber tries to evade the pursuit of one or more helicopter cops, who send distance probes from anywhere on the graph. In this paper, we attempt to propose two useful constructions for general problems in this game: a state variable that describes the available game information for the cops, and

Jiaxin Yu, Liming Fu, Peng Liang, Amjed Tahir

Background: Despite the widespread use of automated security defect detection tools, software projects still contain many security defects that could result in serious damage. Such tools are largely context-insensitive and may not cover all possible scenarios in testing potential issues, which makes them susceptible to missing complex security defects. Hence

Alexandre Mota, Fei Yang, Cristiano Teixeira

Nowadays, smart contracts have become increasingly popular and, as with software development in general, testing is the standard method for verifying their correctness. However, smart contracts require a higher level of certainty regarding correctness because they are diffcult to modify once deployed and errors can result in significant financial losses. The

Tassilo Wald, Constantin Ulrich, Fabian Isensee, David Zimmerer

Independently trained machine learning models tend to learn similar features. Given an ensemble of independently trained models, this results in correlated predictions and common failure modes. Previous attempts focusing on decorrelation of output predictions or logits yielded mixed results, particularly due to their reduction in model accuracy caused by con

Matteo Prata, Giuseppe Masi, Leonardo Berti, Viviana Arrigoni

The recent advancements in Deep Learning (DL) research have notably influenced the finance sector. We examine the robustness and generalizability of fifteen state-of-the-art DL models focusing on Stock Price Trend Prediction (SPTP) based on Limit Order Book (LOB) data. To carry out this study, we developed LOBCAST, an open-source framework that incorporates

Rajat Subhra Hazra, Frank den Hollander, Maarten Markering

We consider an inhomogeneous Erd\H{o}s-R\'enyi random graph $G_N$ with vertex set $[N] = \{1,\dots,N\}$ for which the pair of vertices $i,j \in [N]$, $i\neq j$, is connected by an edge with probability $r_N(\tfrac{i}{N},\tfrac{j}{N})$, independently of other pairs of vertices. Here, $r_N\colon\,[0,1]^2 \to (0,1)$ is a symmetric function that plays the role o

Giang N. Nguyen, Clemens Spinnler, Mark R. Hogg, Liang Zhai

A spin-photon interface should operate with both coherent photons and a coherent spin to enable cluster-state generation and entanglement distribution. In high-quality devices, self-assembled GaAs quantum dots are near-perfect emitters of on-demand coherent photons. However, the spin rapidly decoheres via the magnetic noise arising from the host nuclei. Here

Caner Unal, Alexandros Papageorgiou, Ippei Obata

We demonstrate that the recently announced signal for a stochastic gravitational wave background (SGWB) from pulsar timing array (PTA) observations, if attributed to new physics, is compatible with primordial GW production due to axion-gauge dynamics during inflation. More specifically we find that axion-$U(1)$ models may lead to sufficient particle producti

Jakob Drachmann Havtorn, Amelie Royer, Tijmen Blankevoort, Babak Ehteshami Bejnordi

The input tokens to Vision Transformers carry little semantic meaning as they are defined as regular equal-sized patches of the input image, regardless of its content. However, processing uniform background areas of an image should not necessitate as much compute as dense, cluttered areas. To address this issue, we propose a dynamic mixed-scale tokenization

Taku Nakajima, Shuro Takano, Tomoka Tosaki, Akio Taniguchi

We present an imaging molecular line survey in the 3-mm band (85-114 GHz) focused on one of the nearest galaxies with an active galactic nucleus (AGN), NGC 1068, based on observations taken with the Atacama Large Millimeter/submillimeter Array (ALMA). Distributions of 23 molecular transitions are obtained in the central ~3 kpc region, including both the circ

Elizabeth Maggie Penn, John W. Patty

Classification algorithms are increasingly used in areas such as housing, credit, and law enforcement in order to make decisions affecting peoples' lives. These algorithms can change individual behavior deliberately (a fraud prediction algorithm deterring fraud) or inadvertently (content sorting algorithms spreading misinformation), and they are increasingly

Tonghan Wang, Paul Dütting, Dmitry Ivanov, Inbal Talgam-Cohen

Contract design involves a principal who establishes contractual agreements about payments for outcomes that arise from the actions of an agent. In this paper, we initiate the study of deep learning for the automated design of optimal contracts. We introduce a novel representation: the Discontinuous ReLU (DeLU) network, which models the principal's utility a

Joseph Breen, Ko Honda, Yang Huang

We establish the Giroux correspondence in arbitrary dimensions. As corollaries we (i) give an alternate proof of a result of Giroux-Pardon that states that any Weinstein domain is Weinstein homotopic to one which admits a Weinstein Lefschetz fibration and (ii) prove that any two Weinstein Lefschetz fibrations whose Weinstein domain structures are Weinstein h

F. Di Vruno, B. Winkel, C. G. Bassa, G. I. G. Józsa

We report on observations of 68 satellites belonging to the SpaceX Starlink constellation with the LOFAR radio telescope. Radiation associated with Starlink satellites was detected at observing frequencies between 110 and 188 MHz. A combination of broad-band features, covering the entire observed bandwidth, as well as narrow-band (bandwidth < 12.2 kHz) emiss

Josnei Novacoski, Mark Spivakovsky

The main goal of this paper is to characterize the module of K\"ahler differentials for an extension of valuation rings. More precisely, we consider a simple algebraic valued field extension $(L/K,v)$ and the corresponding valuation rings $\VR_L$ and $\VR_K$. In the case when $e(L/K,v)=1$ we present a characterization for $\Omega_{\VR_L/\VR_K}$ in terms of a

Zdeněk Dvořák, Abhiruk Lahiri

The maximum edge colouring problem considers the maximum colour assignment to edges of a graph under the condition that every vertex has at most a fixed number of distinct coloured edges incident on it. If that fixed number is $q$ we call the colouring a maximum edge $q$-colouring. The problem models a non-overlapping frequency channel assignment question on

Ana-Maria Bucur

In this work, we present the contribution of the BLUE team in the eRisk Lab task on searching for symptoms of depression. The task consists of retrieving and ranking Reddit social media sentences that convey symptoms of depression from the BDI-II questionnaire. Given that synthetic data provided by LLMs have been proven to be a reliable method for augmenting

Xing Li, Da-jun Zhang

The Lam\'e function can be used to construct plane wave factors and solutions to the Korteweg-de Vries (KdV) and Kadomtsev-Petviashvili (KP) hierarchy. The solutions are usually called elliptic solitons. In this chapter, first, we review recent development in the Hirota bilinear method on elliptic solitons of the KdV equation and KP equation, including bilin

J. W. Bruce, F. Tari

Congruences, or $2$-parameter families of lines in $3$-space are of interest in many situations, in particular in geometric optics. In this paper we consider elements of their geometry which are invariant under affine changes of co-ordinates, for example that associated with their focal sets, and less well studied focal planes. We use tools from singularity

Yannick Limmer, Blanka Horvath

The availability of deep hedging has opened new horizons for solving hedging problems under a large variety of realistic market conditions. At the same time, any model - be it a traditional stochastic model or a market generator - is at best an approximation of market reality, prone to model-misspecification and estimation errors. This raises the question, h

Shan Cheng, Shu-Lei Zhang

In this paper we revisit $D_s \to f_0$ form factors from the light-cone sum rules with the light meson light-cone distribution amplitudes. The main motivation of this study is the differential decay width of $D_s \to \left[\pi\pi \right]_{\rm S} e \nu_e$ measured recently by BESIII collaboration and the $D_s \to f_0$ form factor extracted under the intermedi

Saisai Ding, Jun Wang, Juncheng Li, Jun Shi

Whole slide image (WSI) classification is an essential task in computational pathology. Despite the recent advances in multiple instance learning (MIL) for WSI classification, accurate classification of WSIs remains challenging due to the extreme imbalance between the positive and negative instances in bags, and the complicated pre-processing to fuse multi-s

Mengyuan Cao, Monica Nevins, Hadi Salmasian

Let $\mathfrak g$ be either the Lie superalgebra $\mathfrak{gl}(V)\oplus\mathfrak{gl}(V)$ where $V:=\mathbb C^{m|n}$ or the Lie superalgebra $\mathfrak{gl}(V)$ where $V:=\mathbb C^{m|2n}$. Furthermore, let $W$ be the $\mathfrak g$-module defined by $W:=V\otimes V^*$ in the former case and $W:=\mathcal S^2(V)$ in the latter case. Associated to $(\mathfrak g,W

Berkin Bilgic, Mauro Costagli, Kwok-Shing Chan, Jeff Duyn

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generati

Jan K. Marucha

As recently shown, the a-anomaly of the UV fixed point of 4d quantum field theories, can be constrained by studying scattering amplitudes. The basic idea is to couple the QFT to a dilaton and impose unitarity of the scattering amplitudes of physical particles and probe dilatons. In this work we find new lower bounds on the $a$-anomaly in several gapped QFTs

R. J. J. Mackenbach, J. H. E. Proll, G. Snoep, P. Helander

Available energy (\AE{}), which quantifies the maximum amount of thermal energy that may be liberated and converted into instabilities and turbulence, has shown to be a useful metric for predicting saturated energy fluxes in trapped-electron-mode-driven turbulence. Here, we calculate and investigate the \AE{} in the analytical tokamak equilibria introduced b

M. P. Snelders, K. Nimmo, J. W. T. Hessels, Z. Bensellam

Fast radio bursts (FRBs) are extragalactic transients with typical durations of milliseconds. FRBs have been shown, however, to fluctuate on a wide range of timescales: some show sub-microsecond sub-bursts while others last up to a few seconds in total. Probing FRBs on a range of timescales is crucial for understanding their emission physics, how to detect t

Leyla Fathollahi, Mahmood Mohassel Feghhi, Mahmoud Atashbar

In this paper, we propose a novel design for the rotary-wing unmanned aerial vehicle (UAV)-enabled full-duplex (FD) wireless-powered Internet of Things (IoT) networks. In this network, the UAV is equipped with an antenna array, and the $K$ IoT sensors, which are distributed randomly, use single-antenna to communicate. By sending the energy, the UAV as a hybr

Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok

Natural language processing (NLP) made an impressive jump with the introduction of Transformers. ChatGPT is one of the most famous examples, changing the perception of the possibilities of AI even outside the research community. However, besides the impressive performance, the quadratic time and space complexity of Transformers with respect to sequence lengt

André V. Duarte, Arlindo L. Oliveira

Matching addresses is a critical task for companies and post offices involved in the processing and delivery of packages. The ramifications of incorrectly delivering a package to the wrong recipient are numerous, ranging from harm to the company's reputation to economic and environmental costs. This research introduces a deep learning-based model designed to

Frédéric Berthommier

A simplified model of articulatory synthesis involving four stages is presented. The planning of articulatory gestures is based on syllable graphs with arcs and nodes that are implemented in a complex representation. This was first motivated by a reduction in the many-to-one relationship between articulatory parameters and formant space. This allows for cons

François Riggio, Lorenzo Rosso, Dragi Karevski, Jérôme Dubail

Atom losses occur naturally during cold atoms experiments. Since this phenomenon is unavoidable, it is important to understand its effect on the remaining atoms. Here we study a gas of hard-core bosons on a lattice subject to $K$-body losses (where $K=1,2,3,\dots$ is the number of atoms lost in each loss event), and in particular we investigate the effect of

Lin Cao, Haifan Yin, Li Tan, Xilong Pei

Most research works on reconfigurable intelligent surfaces (RIS) rely on idealized models of the reflection coefficients, i.e., uniform reflection amplitude for any phase and sufficient phase shifting capability. In practice however, such models are oversimplified. This paper introduces a realistic reflection coefficient model for RIS based on measurements.

Hao Tang, Boning Li, Yixuan Song, Mengren Liu

Atomic diffusion in solids is an important process in various phenomena. However, atomistic simulations of diffusion processes are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interests. In this work, we developed a long-timescale method using reinforcement learning that simulates diff

Vibhavasu Pasumarti, Shantanu Desai

We use the spectral lag data of 32 long GRBs detected by Fermi/GBM, which has been recently collated in Liu et al (2022) to quantify the statistical significance of a transition in the spectral lag data based on Lorentz invariance violation (LIV) (for both sub-luminal and super-luminal propagation) using Bayesian model selection. We use two different paramet

Mikhail Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina Balcan

We study online meta-learning with bandit feedback, with the goal of improving performance across multiple tasks if they are similar according to some natural similarity measure. As the first to target the adversarial online-within-online partial-information setting, we design meta-algorithms that combine outer learners to simultaneously tune the initializat

Parinya Chalermsook, Seth Pettie, Sorrachai Yingchareonthawornchai

We consider the problem of comparison-sorting an $n$-permutation $S$ that avoids some $k$-permutation $\pi$. Chalermsook, Goswami, Kozma, Mehlhorn, and Saranurak prove that when $S$ is sorted by inserting the elements into the GreedyFuture binary search tree, the running time is linear in the extremal function $\mathrm{Ex}(P_\pi\otimes \text{hat},n)$. This i

Heming Zha, Wenjing Liu, Deyang Wang, Bo Zhao

Spin- and angle-resolved photoemission spectroscopy (SARPES) with high efficiency and resolution plays a crucial role in exploring the fine spin-resolved band structures of quantum materials. Here we report the performance of SARPES instrument with a second-generation home-made multichannel very-low-energy-electron-diffraction (VLEED) spin polarimeter. Its e

Amir-Reza Negari, Subhayan Sahu, Timothy H. Hsieh

We show how distinct phases of matter can be generated by performing random single-qubit measurements on a subsystem of toric code. Using a parton construction, such measurements map to random Gaussian tensor networks, and in particular, random Pauli measurements map to a classical loop model in which watermelon correlators precisely determine measurement-in

Junwen Chen, Yingcheng Wang, Keiji Yanai

Recent transformer-based methods achieve notable gains in the Human-object Interaction Detection (HOID) task by leveraging the detection of DETR and the prior knowledge of Vision-Language Model (VLM). However, these methods suffer from extended training times and complex optimization due to the entanglement of object detection and HOI recognition during the

Wenmin Gong

We investigate the question of whether the spectral metric on the orbit space of a fiber in the disk cotangent bundle of a closed manifold, under the action of the compactly supported Hamiltonian diffeomorphism group, is bounded. We utilize wrapped Floer cohomology to define the spectral invariant of an admissible Lagrangian submanifold within a Weinstein do

Tai D. Nguyen, Long H. Pham, Jun Sun

Fuzzing has emerged as a powerful technique for finding security bugs in complicated real-world applications. American fuzzy lop (AFL), a leading fuzzing tool, has demonstrated its powerful bug finding ability through a vast number of reported CVEs. However, its random mutation strategy is unable to generate test inputs that satisfy complicated branching con

Xuan-Quy Dao

This paper presents a performance comparison of three large language models (LLMs), namely OpenAI ChatGPT, Microsoft Bing Chat (BingChat), and Google Bard, on the VNHSGE English dataset. The performance of BingChat, Bard, and ChatGPT (GPT-3.5) is 92.4\%, 86\%, and 79.2\%, respectively. The results show that BingChat is better than ChatGPT and Bard. Therefore

Cyril Rauch, Panagiota Kyratzi, Andras Paldi

Based on the normal distribution and its properties, i.e., average and variance, Fisher works have provided a conceptual framework to identify genotype-phenotype associations. While Fisher intuition has proved fruitful over the past century, the current demands for higher mapping precisions have led to the formulation of a new genotype-phenotype association

Johannes Fiedler, Kim Lefmann, Wolf von Klitzing, Bodil Holst

Atom and, more recently, molecule interferometers are used in fundamental research and industrial applications. Most atom interferometers rely on gratings made from laser beams, which can provide high precision but cannot reach very short wavelengths and require complex laser systems to function. Contrary to this, simple monolithic interferometers cut from s

Keiichi Tamai, Tsuyoshi Okubo, Truong Vinh Truong Duy, Naotake Natori

We demonstrate that conventional artificial deep neural networks operating near the phase boundary of the signal propagation dynamics, also known as the edge of chaos, exhibit universal scaling laws of absorbing phase transitions in non-equilibrium statistical mechanics. We exploit the fully deterministic nature of the propagation dynamics to elucidate an an

Thomas Becher, Nicolas Schalch, Xiaofeng Xu

In cross sections with angular cuts, an intricate pattern of enhanced higher-order corrections known as non-global logarithms arises. The leading logarithmic terms were computed numerically two decades ago, but the resummation of subleading non-global logarithms remained a challenge that we solve in this Letter using renormalization group methods in effectiv

Toshiya Yurikusa

We study $g$-vector cones in a cluster algebra defined from a weighted orbifold of rank $n$ introduced by Felikson, Shapiro and Tumarkin. We determine the closure of the union of the $g$-vector cones. It is equal to $\mathbb{R}^n$ except for a weighted orbifold with empty boundary and exactly one puncture, in which case it is equal to the half space of a cer

Kun Li, George Vosselman, Michael Ying Yang

Interactive image segmentation aims to segment the target from the background with the manual guidance, which takes as input multimodal data such as images, clicks, scribbles, and bounding boxes. Recently, vision transformers have achieved a great success in several downstream visual tasks, and a few efforts have been made to bring this powerful architecture

Cristina Cipriani, Massimo Fornasier, Alessandro Scagliotti

The connection between Residual Neural Networks (ResNets) and continuous-time control systems (known as NeurODEs) has led to a mathematical analysis of neural networks which has provided interesting results of both theoretical and practical significance. However, by construction, NeurODEs have been limited to describing constant-width layers, making them uns

Pier P. Poier, Louis Lagardère, Jean-Philip Piquemal

We derive and implement an alternative formulation of the Stochastic Lanczos algorithm to be employed in connection with the Many-Body Dispersion model (MBD). Indeed, this formulation, which is only possible due to the Stochastic Lanczos' reliance on matrix-vector products, introduces generalized dipoles and fields. These key quantities allow for a state-of-

Jiaqi Shao, Shanshan Han, Chaoyang He, Bing Luo

Federated heavy-hitter analytics involves the identification of the most frequent items within distributed data. Existing methods for this task often encounter challenges such as compromising privacy or sacrificing utility. To address these issues, we introduce a novel privacy-preserving algorithm that exploits the hierarchical structure to discover local an

Ben Norman, Jeff Clune

Standard reinforcement learning (RL) agents never intelligently explore like a human (i.e. taking into account complex domain priors and adapting quickly based on previous exploration). Across episodes, RL agents struggle to perform even simple exploration strategies, for example systematic search that avoids exploring the same location multiple times. This

Felix Dangel

Despite their simple intuition, convolutions are more tedious to analyze than dense layers, which complicates the transfer of theoretical and algorithmic ideas to convolutions. We simplify convolutions by viewing them as tensor networks (TNs) that allow reasoning about the underlying tensor multiplications by drawing diagrams, manipulating them to perform fu

M. del Carmen Listán-García, María Pilar Romero de la Rosa

We present Korovkin approximation theorems that incorporate summability methods. These result allows us to obtain a unified treatment of several previous results, focusing on the underlying structure and the properties that a summability method should satisfy in order to establish a Korovkin-type approximation result. As a by-product we obtain new Korovkin-t

Yuxin Yang, Xiaoming Chen, Yinhe Han

Rigid body dynamics is a key technology in the robotics field. In trajectory optimization and model predictive control algorithms, there are usually a large number of rigid body dynamics computing tasks. Using CPUs to process these tasks consumes a lot of time, which will affect the real-time performance of robots. To this end, we propose a multifunctional r

Ahmed Ghorbel, Wassim Hamidouche, Luce Morin

Recently, the performance of neural image compression (NIC) has steadily improved thanks to the last line of study, reaching or outperforming state-of-the-art conventional codecs. Despite significant progress, current NIC methods still rely on ConvNet-based entropy coding, limited in modeling long-range dependencies due to their local connectivity and the in

Fan Du, Qiaoqiao Hua, Chunhua Wang

We consider the following critical fractional Schr\"{o}dinger equation \begin{equation*} (-\Delta)^s u+V(|y'|,y'')u = u^{2_s^*-1},\quad u>0,\quad y =(y',y'') \in \mathbb{R}^3\times\mathbb{R}^{N-3}, \end{equation*} where $N\geq 3,s\in(0,1)$, $2_s^*=\frac{2N}{N-2s}$ is the fractional critical Sobolev exponent and $V(|y'|,y'')$ is a bounded non-negative functio

Mohamed Amouch, Fernando León-Saavedra, M. P. Romero de la Rosa

An operator $T$ acting on a separable complex Hilbert space $H$ is said to be hypercyclic if there exists $f\in H$ such that the orbit $\{T^n f:\ n\in \mathbb{N}\}$ is dense in $H$. Godefroy and Shapiro \cite{GoSha} characterized those elements in the commutant of the Hardy backward shift which are hypercyclic. In this paper we study some dynamics properties

Yuguang Shi

One of the key problems in 3D object detection is to reduce the accuracy gap between methods based on LiDAR sensors and those based on monocular cameras. A recently proposed framework for monocular 3D detection based on Pseudo-Stereo has received considerable attention in the community. However, so far these two problems are discovered in existing practices,

Lasha Abzianidze, Joost Zwarts, Yoad Winter

While many natural language inference (NLI) datasets target certain semantic phenomena, e.g., negation, tense & aspect, monotonicity, and presupposition, to the best of our knowledge, there is no NLI dataset that involves diverse types of spatial expressions and reasoning. We fill this gap by semi-automatically creating an NLI dataset for spatial reasoning,

Elspeth K. H. Lee

Insight into the formation and global distribution of cloud particles in exoplanet atmospheres continues to be a key problem to tackle going into the JWST era. Understanding microphysical cloud processes and atmospheric feedback mechanisms in 3D has proven to be a challenging prospect for exoplaneteers. In an effort to address the large computational burden

Y. Y. Kovalev, A. V. Plavin, A. B. Pushkarev, S. V. Troitsky

The advancement of neutrino observatories has sparked a surge in multi-messenger astronomy. Multiple neutrino associations among blazars are reported while neutrino production site is located within their central (sub)parsecs. Yet many questions remain on the nature of those processes. The next generation Event Horizon Telescope (ngEHT) is uniquely positione

A. R. Kuzmak

The preparation of entangled quantum states is an inherent and indispensable step for the implementation of many quantum information algorithms. Depending on the physical system, there are different ways to control and measure them, which allow one to achieve the predefined quantum states. The diamond spin cluster is the system that can be applied for this p

Federico Luigi Dipasquale, Bianca Stroffolini

We study the regularity of local minimisers of a prototypical free-discontinuity problem involving both a manifold-valued constraint on the maps (which are defined on a bounded domain $\Omega \subset \R^2$) and a variable-exponent growth in the energy functional. To this purpose, we first extend to this setting the Sobolev approximation result for special fu

Helmut Abels, Christoph Hurm

We prove convergence of a sequence of weak solutions of the nonlocal Cahn-Hilliard equation to the strong solution of the corresponding local Cahn-Hilliard equation. The analysis is done in the case of sufficiently smooth bounded domains with Neumann boundary condition and a $W^{1,1}$-kernel. The proof is based on the relative entropy method. Additionally, w

Jianxiang Luo, Junyi Hu, Tianji Pang, Weihao Huang

Recently, the weight-sharing technique has significantly speeded up the training and evaluation procedure of neural architecture search. However, most existing weight-sharing strategies are solely based on experience or observation, which makes the searching results lack interpretability and rationality. In addition, due to the negligence of fairness, curren