November 2022 arXiv papers — page 85

Charbel Karam, Mara Meyer zum Alten Borgloh, Romain Vexiau, Maxence Lepers

We propose a method to engineer repulsive long-range interactions between ultracold ground-state molecules using optical fields, thus preventing short-range collisional losses. It maps the microwave coupling recently used for collisional shielding onto a two-photon transition, and takes advantage of optical control techniques. In contrast to one-photon optic

A. T. Costa, M. I. Vasilevskiy, J. Fernández-Rossier, N. M. R. Peres

Magnons and plasmons are two very different types of collective modes, acting on the spin and charge degrees of freedom, respectively. At first sight, the formation of hybrid plasmon-magnon polaritons in heterostructures of plasmonic and magnetic systems would face two challenges, the small mutual interaction, via Zeeman coupling of the electromagnetic field

Pranab J. Deka, Mayya Tokman, Lukas Einkemmer

Krylov-based algorithms have long been preferred to compute the matrix exponential and exponential-like functions appearing in exponential integrators. Of late, direct polynomial interpolation of the action of these exponential-like functions have been shown to be competitive with the Krylov methods. We analyse the performance of the state-of-the-art Krylov

Yuhito Shibaike, Shoji Mori

It has been considered that large satellites around gas planets form in-situ circumplanetary discs (CPDs). However, dust particles supplied into CPDs drift toward the central planets before they grow into satellitesimals, building blocks of the satellites. We investigate the dust growth in laminar CPDs with magnetic wind-driven accretion. In such laminar dis

Zhong-Yu Wang, Si-Qiang Luo, Zhi-Feng Sun, C. W. Xiao

The decay process $\Xi_{b}^{-} \rightarrow pK^{-}K^{-}$ is studied with the final state interaction approach by considering the contributions from the $S$-wave meson-baryon interactions, and also the intermediate state $\Lambda(1520)$ in the $D$-wave. The low-lying resonances $\Lambda(1405)$ and $\Lambda(1670)$ have significant contributions, which are both

ATLAS Collaboration

A search for resonances in events with at least one isolated lepton ($e$ or $\mu$) and two jets is performed using $139 \, {\text{fb}}^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data recorded by the ATLAS detector at the LHC. Deviations from a smoothly falling background hypothesis are tested in three- and four-body invariant mass distributions const

Guy Ohayon, Theo Adrai, Michael Elad, Tomer Michaeli

Stochastic restoration algorithms allow to explore the space of solutions that correspond to the degraded input. In this paper we reveal additional fundamental advantages of stochastic methods over deterministic ones, which further motivate their use. First, we prove that any restoration algorithm that attains perfect perceptual quality and whose outputs are

Montgomery Flora, Corey Potvin, Amy McGovern, Shawn Handler

With increasing interest in explaining machine learning (ML) models, the first part of this two-part study synthesizes recent research on methods for explaining global and local aspects of ML models. This study distinguishes explainability from interpretability, local from global explainability, and feature importance versus feature relevance. We demonstrate

Yuan Zhang, Zhiqi Bu

Machine learning models have shone in a variety of domains and attracted increasing attention from both the security and the privacy communities. One important yet worrying question is: Will training models under the differential privacy (DP) constraint have an unfavorable impact on their adversarial robustness? While previous works have postulated that priv

Gérsica Freitas, Alessandra Kreutz, Jean Lelis, Elaine Silva

In this paper, we consider the new family of recurrence sequences of $(q,k)$-generalized Fibonacci numbers. These sequences naturally extend the well-known sequences of $k$-generalized Fibonacci numbers and generalized $k$-order Pell numbers. We shall obtain a Binet-style formula and study the asymptotic behavior of dominant root of characteristic equation.

Christian Liedl, Felix Tebbenjohanns, Constanze Bach, Sebastian Pucher

Dicke superradiance describes the collective radiative decay of a fully inverted ensemble of two-level atoms. We experimentally investigate this effect for a chiral, i.e.,~direction-dependent light--matter coupling. Despite a fundamentally different interaction Hamiltonian which has a reduced symmetry compared to the standard Dicke case, we do observe a supe

Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi

In this paper, we propose the augmented physics-informed neural network (APINN), which adopts soft and trainable domain decomposition and flexible parameter sharing to further improve the extended PINN (XPINN) as well as the vanilla PINN methods. In particular, a trainable gate network is employed to mimic the hard decomposition of XPINN, which can be flexib

Yadong Jiang, Huan Wang, Jing Wang

We theoretically propose that the monolayer $A$Ti$X$ family (KTiSb, KTiBi, RbTiSb, SrTiSn) are potential candidates for large-gap quantum anomalous Hall insulators with high Chern number $\mathcal{C}=2$. Both of the topology and magnetism in these materials are from $3d$-orbitals of Ti. We construct the tight-binding model with symmetry analysis to reveal th

Fabrizio Fiore, Andrea Ferrara, Manuela Bischetti, Chiara Feruglio

The JWST discovery of a number of super-early (redshift $z>10$), blue galaxies requires these systems to be essentially dust-free in spite of their large stellar masses. A possible explanation is that dust is evacuated by radiatively-driven outflows. We test this hypothesis by deriving the Eddington ratio $\lambda_E=L_{\rm bol}/L_{E}$, where $L_{\rm bol}$ is

ALICE Collaboration

The production of strange hadrons (K$^{0}_{\rm S}$, $\Lambda$, $\Xi^{\pm}$, and $\Omega^{\pm}$), baryon-to-meson ratios ($\Lambda/{\rm K}^0_{\rm S}$, $\Xi/{\rm K}^0_{\rm S }$, and $\Omega/{\rm K}^0_{\rm S}$), and baryon-to-baryon ratios ($\Xi/\Lambda$, $\Omega/\Lambda$, and $\Omega/\Xi$) associated with jets and the underlying event were measured as a functi

Yasuaki Gyoda

In this paper, we demonstrate that the lattice structure of a set of clusters in a cluster algebra of finite type is anti-isomorphic to the torsion lattice of a certain Geiss-Leclerc-Schr\"oer (GLS) path algebra and to the $c$-Cambrian lattice. We prove this by explicitly describing the exchange quivers of cluster algebras of finite type. Specifically, we pr

Philipp J. Heckmeier, Jeannette Ruf, Brankica G. Janković, Peter Hamm

MCL-1 and its natural inhibitors, the BH3-only proteins PUMA, BIM, and NOXA regulate apoptosis by interacting promiscuously within an entangled binding network. Little is known about the transient processes and dynamic conformational fluctuations that are the basis for the formation and stability of the MCL-1/BH3-only complex. In this study, we designed phot

Sylvie Corteel, Sergi Elizalde, Carla Savage

In this paper we study partitions whose successive ranks belong to a given set. We enumerate such partitions while keeping track of the number of parts, the largest part, the side of the Durfee square, and the height of the Durfee rectangle. We also obtain a new bijective proof of a result of Andrews and Bressoud that the number of partitions of $N$ with all

Xidong Mu, Yuanwei Liu

This article investigates the exploitation of semantic communications in multi-user networks. We propose a novel heterogeneous semantic and bit multi-user framework for providing flawless, customized, and intelligent information transmission. We discuss both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) for the proposed heterogen

D. Kumar, A. K. B. Chand, P. R. Massopust

A novel approach to zipper fractal interpolation theory for functions of several variables is proposed. We develop multivariate zipper fractal functions in a constructive manner. We then perturb a multivariate function to construct its zipper $\alpha$-fractal varieties through free choices of base functions, scaling functions, and a binary matrix called sign

Yan Li, Yunquan Dong, Pingyi Fan, Khaled Ben Letaief

With the rapid development of Internet-of-Things (IoT) technology and machine-type communications, various emerging applications appear in industrial productions and our daily lives. Among these, applications like industrial sensing and controlling, remote surgery, and automatic driving require an extremely low latency and a very small jitter. Delivering inf

David Berger, René L. Schilling, Eugene Shargorodsky

The classical Liouville property says that all bounded harmonic functions in $\mathbb{R}^n$, i.e.\ all bounded functions satisfying $\Delta f = 0$, are constant. In this paper we obtain necessary and sufficient conditions on the symbol of a Fourier multiplier operator $m(D)$, such that the solutions $f$ to $m(D)f=0$ are Lebesgue a.e.\ constant (if $f$ is bou

ALICE Collaboration

This article reports measurements of the angle between differently defined jet axes in pp collisions at $\sqrt{s} = 5.02$ TeV carried out by the ALICE Collaboration. Charged particles at midrapidity are clustered into jets with resolution parameters $R=0.2$ and 0.4. The jet axis, before and after Soft Drop grooming, is compared to the jet axis from the Winne

Ahmed ElGazzar, Rajat Thomas, Guido van Wingen

Graph Neural Networks (GNNs) have emerged as a powerful tool to learn from graph-structured data. A paramount example of such data is the brain, which operates as a network, from the micro-scale of neurons, to the macro-scale of regions. This organization deemed GNNs a natural tool of choice to model brain activity, and have consequently attracted a lot of a

Igor G. Korepanov

Cubic blocks are studied assembled from linear operators $\mathcal R$ acting in the tensor product of $d$ linear "spin" spaces. Such operator is associated with a linear transformation $A$ in a vector space over a field $F$ of a finite characteristic $p$, like "permutation-type" operators studied by Hietarinta. One small difference is that we do not require

Davide Astesiano, Matteo Luca Ruggiero

We use the gravitoelectromagnetic approach to the solutions of Einstein's equations in the weak-field and slow-motion approximation to investigate the impact of General Relativity on galactic dynamics. In particular, we focus on a class of the solutions for the gravitomagnetic field, and show that, contrary to what is expected, they may introduce non negligi

Felipe Sulantay, Macarena Lagos, Máximo Bañados

We study the parity-breaking higher-curvature gravity theory of Chern-Simons (CS), using the Palatini formulation in which the metric and connection are taken to be independent fields. We first show that Palatini CS gravity leads to first-order derivative equations of motion and thus avoid the typical instabilities of CS gravity in the metric formalism. As a

Ajay Annamareddy, Bu Wang, Paul M. Voyles, Dane Morgan

Short-timescale atomic rearrangements are fundamental to the kinetics of glasses and frequently dominated by one atom moving significantly (a rearrangement), while others relax only modestly. The rates and directions of such rearrangements (or hops) are dominated by the distributions of activation barriers (Eact) for rearrangement for a single atom and how t

Maxime Fortier Bourque

We show that for every $\varepsilon>0$, there exists some $g\geq 2$ such that the set of closed hyperbolic surfaces of genus $g$ whose systoles fill has dimension at least $(5-\varepsilon) g$. In particular, the dimension of this set -- proposed as a spine for moduli space by Thurston -- is larger than the virtual cohomological dimension of the mapping class

Guo-Qiang Zhang, Yimin Wang, Wei Xiong

We show how to enhance the detection sensitivity of magnon Kerr nonlinearity (MKN) in cavity magnonics. The considered cavity-magnon system consists of a three-dimensional microwave cavity containing two yttrium iron garnet (YIG) spheres, where the two magnon modes (one has the MKN, while the other is linear) in YIG spheres are simultaneously coupled to micr

Brajesh Kumar, Hitesh Kumar, Khushal Singh Dangwal, Himanshu Rawat

The 4m International Liquid Mirror Telescope (ILMT) is a zenith-pointing optical observing facility at ARIES Devasthal observatory (Uttarakhand, India). The first light preparatory activities of the ILMT were accomplished in April 2022 followed by on-sky tests that were carried out at the beginning of May 2022. This telescope will perform a multi-band optica

Kalle Koskinen

For the discrete random field Curie-Weiss models, the infinite volume Gibbs states and metastates have been investigated and determined for specific instances of random external fields. In general, there are not many examples in the literature of non-trivial limiting metastates for discrete or continuous spin systems. We analyze the infinite volume Gibbs sta

Jiahao Cui, Qiushi Li, Yuezhi Pen

This research mainly explores the characteristics of different strategies and whether VIX INDEX positively influences the investment portfolio in any period. Our portfolio has six significant cryptocurrencies, VIX INDEX and gold. We perform parameter estimation on all raw data and bring the two types into different investment strategies, complete them effect

Alexander Hock

Let $W_{g,n}$ be the correlators computed by Topological Recursion for some given spectral curve $(x,y)$ and $W^\vee_{g,n}$ for $(y,x)$, where the role of $x,y$ is inverted. These two sets of correlators $W_{g,n}$ and $W^\vee_{g,n}$ are related by the $x$-$y$ symplectic transformation. Bychkov, Dunin-Barkowski, Kazarian and Shadrin computed a functional rela

Leonardo Horn Iwaya, Muhammad Ali Babar, Awais Rashid

Privacy engineering, as an emerging field of research and practice, comprises the technical capabilities and management processes needed to implement, deploy, and operate privacy features and controls in working systems. For that, software practitioners and other stakeholders in software companies need to work cooperatively toward building privacy-preserving

Jichao Jia, Xue Cao, Xuekai Ma, Jianbo De

Circularly polarized (CP) electroluminescence from organic light-emitting diodes (OLEDs) has aroused considerable attention for their potential in future display and photonic technologies. The development of CP-OLEDs relies largely on chiral-emitters, which not only remain rare owing to difficulties in design and synthesis but also limit the performance of e

Qi Guo, Yong Qi, Saiyu Qi, Di Wu

Federated semi-supervised learning (FSSL), facilitates labeled clients and unlabeled clients jointly training a global model without sharing private data. Existing FSSL methods predominantly employ pseudo-labeling and consistency regularization to exploit the knowledge of unlabeled data, achieving notable success in raw data utilization. However, these train

Jenny G. Sorce, Antonino Troja, Isaac Tutusaus

With the immense number of images, data, and sources that Euclid will deliver, the consortium will be in a unique position to create/provide/construct legacy catalogues. The latter will have exquisite imaging quality and good near-infrared spectroscopy, with impact on many areas of galaxy science. These proceedings review the prospects and scientific output

Isaac Tutusaus, Jenny G. Sorce, Antonino Troja

Euclid will observe 15 000 deg$^2$ of the darkest sky, in regions free of contamination by light from our Galaxy and our Solar System. Three "Euclid Deep Fields" surveys covering around 40 deg$^2$ in total will extend the scientific scope of the mission to the high-redshift Universe. The complete survey will be constituted by hundreds of thousands of images

J. M. Velásquez-Cadavid, Fabio D. Lora-Clavijo, Oscar M. Pimentel, J. A. Arrieta-Villamizar

Magnetic fields in black hole accretion disks are associated with processes of mass accretion and energy amplification. The contribution of the magnetic field due to the magnetic polarization of the material induces effects on the physical properties of the medium that have repercussions on the radiation coming from the accretion disks. Hence, from observati

Antonino Troja, Isaac Tutusaus, Jenny G. Sorce

Euclid is a European Space Agency (ESA) mission designed to constrain the properties of dark energy and gravity via weak gravitational lensing and galaxy clustering. It will carry out a wide area imaging and spectroscopy survey in visible and near-infrared bands, covering approximately 15 000 deg2 of the extragalactic sky in six years. Euclid will be equippe

Lei Wang, Ziyi Zhao, Hanwei Liu, Junwei Pang

With the introduction of ChatGPT, the public's perception of AI-generated content (AIGC) has begun to reshape. Artificial intelligence has significantly reduced the barrier to entry for non-professionals in creative endeavors, enhancing the efficiency of content creation. Recent advancements have seen significant improvements in the quality of symbolic music

Marco Locatelli, Veronica Piccialli, Antonio M. Sudoso

In this paper, we propose a branch-and-bound algorithm for solving nonconvex quadratic programming problems with box constraints (BoxQP). Our approach combines existing tools, such as semidefinite programming (SDP) bounds strengthened through valid inequalities, with a new class of optimality-based linear cuts which leads to variable fixing. The most importa

Jingxuan Pang, Chunguang Li

Anomaly detection (AD) has attracted considerable attention in both academia and industry. Due to the lack of anomalous data in many practical cases, AD is usually solved by first modeling the normal data pattern and then determining if data fit this model. Generative models (GMs) seem a natural tool to achieve this purpose, which learn the normal data distr

Ming Tang, Junwei Huang, Feng Qin, Kun Zhai

Controlling the magnetic anisotropy of ferromagnetic materials plays a key role in magnetic switching devices and spintronic applications. Examples of spin-orbit torque devices with different magnetic anisotropy geometries (in-plane or out-of-plane directions) have been demonstrated with novel magnetization switching mechanisms for extended device functional

Mark Dukes

In this paper we define a variant of the Ising model in which spins are replaced with permutations. The energy between two spins is a function of the relative disorder of one spin, a permutation, to the other. This model is motivated by a complexity measure for declarative systems. For such systems a state is a permutation and the permutation sorting complex

Ahmet Tekcan, Alper Erdem

In this work, we determined the general terms of all almost balancing numbers of first and second type in terms of balancing numbers and conversely we determined the general terms of all balancing numbers in terms of all almost balancing numbers of first and second type. We also set a correspondence between all almost balancing numbers of first and second ty

Petja Paakkinen

Nuclear parton distribution functions (nuclear PDFs), collinearly factorizable in perturbative QCD (pQCD), are currently extracted most reliably from global analyses of experimental data. Recently, the progress in this field has been driven mainly by the new data from LHC proton-lead collisions. I will review the progress in using data from LHC Run 1 and 2 a

Thomas Izgin, Philipp Öffner, Davide Torlo

Modified Patankar (MP) schemes are conservative, linear implicit and unconditionally positivity preserving time-integration schemes constructed for production-destruction systems. For such schemes, a classical stability analysis does not yield any information about the performance. Recently, two different techniques have been proposed to investigate the prop

Hao Qu, Lilian Zhang, Xiaoping Hu, Xiaofeng He

Accurately perceiving location and scene is crucial for autonomous driving and mobile robots. Recent advances in deep learning have made it possible to learn egomotion and depth from monocular images in a self-supervised manner, without requiring highly precise labels to train the networks. However, monocular vision methods suffer from a limitation known as

Yuebing Liang, Guan Huang, Zhan Zhao

For bike sharing systems, demand prediction is crucial to ensure the timely re-balancing of available bikes according to predicted demand. Existing methods for bike sharing demand prediction are mostly based on its own historical demand variation, essentially regarding it as a closed system and neglecting the interaction between different transportation mode

Virna Kisiček, Damir Dominko, Matija Čulo, Željko Rapljenović

The search for new materials for energy-efficient electronic devices has gained unprecedented importance. Among the various classes of magnetic materials driving this search are antiferromagnets, magnetoelectrics, and systems with topological spin excitations. Cu$_3$TeO$_6$ is a material that belongs to all three of these classes. Combining static electric p

Taofeng Xie, Chentao Cao, Zhuoxu Cui, Fanshi Li

MRI and PET are important modalities and can provide complementary information for the diagnosis of brain diseases because MRI can provide structural information of brain and PET can obtain functional information of brain. However, PET is usually missing. Especially, simultaneous PET and MRI imaging at ultrahigh field is not achievable in the current. Thus,

Seungchan Ko, Seok-Bae Yun, Youngjoon Hong

In this paper, we perform the convergence analysis of unsupervised Legendre--Galerkin neural networks (ULGNet), a deep-learning-based numerical method for solving partial differential equations (PDEs). Unlike existing deep learning-based numerical methods for PDEs, the ULGNet expresses the solution as a spectral expansion with respect to the Legendre basis a

Bing-Guang Chen, Tong Liu, Yan-Qing Qi, Bao-Quan Huang

In the coalescence events of binary neutron star (NS) or a black hole (BH) and an NS, a BH hyperaccretion disk might be eventually formed. At very high mass accretion rates, MeV neutrinos will be emitted from this disk, which is called a neutrino-dominated accretion flow (NDAF). Neutrino annihilation in the space out of the disk is energetic enough to launch

Varad Deshmukh, Robert Meikle, Elizabeth Bradley, James D. Meiss

Reconstructing state-space dynamics from scalar data using time-delay embedding requires choosing values for the delay $\tau$ and the dimension $m$. Both parameters are critical to the success of the procedure and neither is easy to formally validate. While embedding theorems do offer formal guidance for these choices, in practice one has to resort to heuris

Yongxin Li

This work starts from definition of randomness, the results of algorithmic randomness are analyzed from the perspective of application. Then, the source and nature of randomness is explored, and the relationship between infinity and randomness is found. The properties of randomness are summarized from the perspective of interaction between systems, that is,

Petja Paakkinen

The progress in constraining proton and nuclear parton distribution functions is briefly summarised. Some persistent uncertainties are pointed out and recent experimental advancements highlighted.

Elise Grosjean, Yvon Maday

Reduced Basis Methods (RBMs) are frequently proposed to approximate parametric problem solutions. They can be used to calculate solutions for a large number of parameter values (e.g. for parameter fitting) as well as to approximate a solution for a new parameter value (e.g. real time approximation with a very high accuracy). They intend to reduce the computa

Shuo Zhang, Zhuo-Peng Huang, Tian-Ci Tian, Zheng-Yang Wu

Conventional theoretical studies on the ground-state laser cooling of a trapped ion have mostly focused on the weak sideband coupling (WSC) regime, where the cooling rate is inverse proportional to the linewidth of the excited state. In a recent work~[New J. Phys. 23, 023018 (2021)], we proposed a theoretical framework to study the ground state cooling of a

Tsuneya Yoshida, Yasuhiro Hatsugai

Despite recent extensive studies of the non-Hermitian topology, understanding interaction effects is left as a crucial question. In this paper, we address interaction effects on exceptional points which are protected by the non-trivial point-gap topology unique to non-Hermitian systems. Our analysis in a two-dimensional parameter space elucidates the existen

Xinyao Shu, Shiyang Yan, Zhenyu Lu, Xinshao Wang

Unsupervised domain adaption (UDA) is a transfer learning task where the data and annotations of the source domain are available but only have access to the unlabeled target data during training. Most previous methods try to minimise the domain gap by performing distribution alignment between the source and target domains, which has a notable limitation, i.e

Fabrizio Schiano, Przemyslaw Mariusz Kornatowski, Leonardo Cencetti, Dario Floreano

Cargo drones are designed to carry payloads with predefined shape, size, and/or mass. This lack of flexibility requires a fleet of diverse drones tailored to specific cargo dimensions. Here we propose a new reconfigurable drone based on a modular design that adapts to different cargo shapes, sizes, and mass. We also propose a method for the automatic generat

Tianze Luo, Zhanfeng Mo, Sinno Jialin Pan

Generating graph-structured data is a challenging problem, which requires learning the underlying distribution of graphs. Various models such as graph VAE, graph GANs, and graph diffusion models have been proposed to generate meaningful and reliable graphs, among which the diffusion models have achieved state-of-the-art performance. In this paper, we argue t

Véronique Bruyère, Guillermo A. Perez, Gaëtan Staquet

We present a new streaming algorithm to validate JSON documents against a set of constraints given as a JSON schema. Among the possible values a JSON document can hold, objects are unordered collections of key-value pairs while arrays are ordered collections of values. We prove that there always exists a visibly pushdown automaton (VPA) that accepts the same

Sarah Brandt, Julien Siebert

This paper presents the results of interviews conducted as part of the DYNASOS project. The objective was to collect challenges related to the design, implementation and management of system-of-systems (SoS) in the context of climate adaptation and greening of smart cities. 23 individuals from cities, academia, and industry were interviewed between March and

Andrew J. Harvie, John C. de Mello

The Open Lock-In Amplifier (OLIA) is a microcontroller-based digital lock-in amplifier built from a small number of inexpensive and easily sourced electronic components. Despite its small credit card-sized form-factor and low build-cost of around US$35, OLIA is a capable instrument that offers many features associated with far costlier commercial devices. Ke

Ting-Hsuan Liao, Huang-Ru Liao, Shan-Ya Yang, Jie-En Yao

Many unsupervised domain adaptation (UDA) methods have been proposed to bridge the domain gap by utilizing domain invariant information. Most approaches have chosen depth as such information and achieved remarkable success. Despite their effectiveness, using depth as domain invariant information in UDA tasks may lead to multiple issues, such as excessively h

Hongwei Xue, Peng Gao, Hongyang Li, Yu Qiao

Masked Autoencoders (MAE) have been prevailing paradigms for large-scale vision representation pre-training. By reconstructing masked image patches from a small portion of visible image regions, MAE forces the model to infer semantic correlation within an image. Recently, some approaches apply semantic-rich teacher models to extract image features as the rec

Jorik Jooken, Pieter Leyman, Patrick De Causmaecker

Decades of research on the 0-1 knapsack problem led to very efficient algorithms that are able to quickly solve large problem instances to optimality. This prompted researchers to also investigate whether relatively small problem instances exist that are hard for existing solvers and investigate which features characterize their hardness. Previously the auth

Shengyao Li, Bojun Miao, Xueyan Wang, Siew Lang Teo

Among various types of neuromorphic devices towards artificial intelligence, the electrochemical synaptic transistor emerges, in which the channel conductance is modulated by the insertion of ions according to the history of gate voltage across the electrolyte. Despite the striking progress in exploring novel channel materials, few studies report on the ferr

Anderson Kendi Kohara

Elastic scattering of charged hadrons is described by the combination of nuclear and Coulomb amplitudes. It is well know that at the very forward range the nuclear real and Coulomb parts interplay a crucial role in the determination of the magnitude of the real part at $|t|=0$. However, beyond $|t|=0$ the real and imaginary nuclear amplitudes have different

Suraj Dhiwar, Kanak Saha, Avishai Dekel, Abhishek Paswan

We study the evolution of $L_{*}$ elliptical galaxies in the color-magnitude diagram in terms of their star-formation history and environment, in an attempt to learn about their quenching process. We have visually extracted 1109 $L_{*}$ galaxies from a sample of 36500 galaxies that were spectroscopically selected from Stripe82 of the Sloan Digital Sky Survey

Emiliano Díaz Salas-Porras, Kenza Tazi, Ashwin Braude, Daniel Okoh

A first causal discovery analysis from observational data of pyroCb (storm clouds generated from extreme wildfires) is presented. Invariant Causal Prediction was used to develop tools to understand the causal drivers of pyroCb formation. This includes a conditional independence test for testing $Y$ conditionally independent of $E$ given $X$ for binary variab

Kamal Shaker, Hamed Khezrzadeh

A statistical multi-step self-consistent (SMSSC) micromechanical model for predicting elastic and plastic properties of a three-dimensional Representative Volume Element (RVE) is proposed in this research. A body with randomly distributed rough penny-shaped microcracks is considered for the first time in which the distribution of cracks is included through d

Dwarikanath Mahapatra

We present a novel framework for explainable labeling and interpretation of medical images. Medical images require specialized professionals for interpretation, and are explained (typically) via elaborate textual reports. Different from prior methods that focus on medical report generation from images or vice-versa, we novelly generate congruent image--repor

Otto Kolbinger, Chenyuyan Yang, Martin Lames

Due to the unfavourable climatic conditions in Qatar during summertime, the FIFA World Cup 2022 will be played during on-going seasons of the major European leagues. This study investigates how national teams' tournaments scheduled at such a time window impact the playing time of released players, using data from the Africa Cups of Nations (AFCON). For 262 i

Zhe Wang, Yongxiong Wang, Chuanfei Hu, Zhong Yin

Both the temporal dynamics and spatial correlations of Electroencephalogram (EEG), which contain discriminative emotion information, are essential for the emotion recognition. However, some redundant information within the EEG signals would degrade the performance. Specifically,the subjects reach prospective intense emotions for only a fraction of the stimul

Isaac Sihlangu, Nadeem Oozeer, Bruce Bassett

Radio Frequency Interference (RFI) is unwanted noise that swamps the desired astronomical signal. Radio astronomers have always had to deal with RFI detection and excision around telescope sites, but little has been done to understand the full scope, nature and evolution of RFI in a unified way. We undertake this for the MeerKAT array using a probabilistic m

Xin Gu, Yinghua Shen, Chaohui Lv

We propose a method to recommend background music for videos. Current work rarely considers the emotional information of music, which is essential for video music retrieval. To achieve this, we design two paths to process content information and emotional information between modal. Based on characteristics of video and music, we design various feature extrac

Manuel Reichert, Zhi-Wei Wang

We discuss the stochastic gravitational-wave spectrum from dark confinement and chiral phase transitions in the early Universe. Specifically, we look at pure Yang-Mills theory for an arbitrary number of colours as well as SU(3) with quarks in different representations. We utilise thermodynamic lattice data and map it to effective models, such as the Polyakov

Mariia Gumberidze, Michal Kolář, Radim Filip

Quantum coherence represented by a superposition of energy eigenstates is, together with energy, an important resource for quantum technology and thermodynamics. Energy and quantum coherence however, can be complementary. The increase of energy can reduce quantum coherence and vice versa. Recently, it was realized that steady-state quantum coherence could be

Mattes Mollenhauer, Nicole Mücke, T. J. Sullivan

We consider the problem of learning a linear operator $\theta$ between two Hilbert spaces from empirical observations, which we interpret as least squares regression in infinite dimensions. We show that this goal can be reformulated as an inverse problem for $\theta$ with the feature that its forward operator is generally non-compact (even if $\theta$ is ass

Scott Lawrence

Semidefinite programs can be constructed to provide a non-perturbative view of the zero-temperature behavior of quantum systems. This paper examines the properties of these semidefinite programs when applied to lattice-regulated field theories exhibiting fermion sign problems. Specifically on the finite-density Thirring model, there is no indication that the

V. O Yurovsky, A. I. Peryatinskaya, I. Kudryashov

The paper numerically investigates the propagation of galactic cosmic rays in a model magnetic field, which is a composition of an isotropic turbulent field with the Kolmogorov turbulence spectrum and a regular constant field. The dependence of the diffusion tensor components on the particle energy is studied. It is shown that the transport anisotropy increa

Yujie Yang, Changsheng Quan, Xiaofei Li

In multichannel speech enhancement, both spectral and spatial information are vital for discriminating between speech and noise. How to fully exploit these two types of information and their temporal dynamics remains an interesting research problem. As a solution to this problem, this paper proposes a multi-cue fusion network named McNet, which cascades four

Jun Zhou, Zhichao Yin, Pengpeng Yue

This paper proposes a brand-new measure of energy efficiency at household level and explores how it is affected by access to credit. We calculate the energy and carbon intensity of the related sectors, which experience a substantial decline from 2005 to 2019. Although there is still high inequality in energy use and carbon emissions among Chinese households,

Amit Chaudhary, Daniele Pinna

We assess the market risk of the DeFi lending protocols using a multi-asset agent-based model to simulate ensembles of users subject to price-driven liquidation risk. Our multi-asset methodology shows that the protocol's systemic risk is small under stress and that enough collateral is always present to underwrite active loans. Our simulations use a wide var

Saul D. Freedman

Let $G$ be a (finite or infinite) group such that $G/Z(G)$ is not simple. The non-commuting, non-generating graph $\Xi(G)$ of $G$ has vertex set $G \setminus Z(G)$, with vertices $x$ and $y$ adjacent whenever $[x,y] \ne 1$ and $\langle x, y \rangle \ne G$. We investigate the relationship between the structure of $G$ and the connectedness and diameter of $\Xi

Lu Xia, Bin Nan, Yi Li

The Scientific Registry of Transplant Recipients (SRTR) system has become a rich resource for understanding the complex mechanisms of graft failure after kidney transplant, a crucial step for allocating organs effectively and implementing appropriate care. As transplant centers that treated patients might strongly confound graft failures, Cox models stratifi

Wen Zhao, Xuan Tang, Xueshi Guo, Xiaoying Li

SU(1,1) interferometer (SUI) is a novel type of interferometer that uses directly entangled quantum fields for sensing phase change. For rotational sensing, Sagnac geometry is usually adopted. However, because SUI depends on the phase sum of the two arms, traditional Sagnac geometry, when applied to SUI, will result in null signal. In this paper, we modify t

JoonHo Lee, Gyemin Lee

Unsupervised domain adaptation (UDA) aims to improve the prediction performance in the target domain under distribution shifts from the source domain. The key principle of UDA is to minimize the divergence between the source and the target domains. To follow this principle, many methods employ a domain discriminator to match the feature distributions. Some r

Alexander Gorfer, Christoph Dellago, Marcello Sega

We investigate the properties of water along the liquid/vapor coexistence line in the supercooled regime down to the no-man's land. Extensive molecular dynamics simulations of the TIP4P/2005 liquid/vapor interface in the range 198 -- 348 K allow us to locate the second surface tension inflection point with high accuracy at 283$\pm$5 K, close to the temperatu

Peter Rot, Peter Peer, Vitomir Štruc

Soft-biometric privacy-enhancing techniques represent machine learning methods that aim to: (i) mitigate privacy concerns associated with face recognition technology by suppressing selected soft-biometric attributes in facial images (e.g., gender, age, ethnicity) and (ii) make unsolicited extraction of sensitive personal information infeasible. Because such

Anukriti Kumar, Tanuja Ganu, Saikat Guha

Infographics are often an integral component of scientific documents for reporting qualitative or quantitative findings as they make it much simpler to comprehend the underlying complex information. However, their interpretation continues to be a challenge for the blind, low-vision, and other print-impaired (BLV) individuals. In this paper, we propose ChartP

Sumit Suthar, Soumyendu Raha

A general way of representing Stochastic Differential Equations (SDEs) on smooth manifold is based on Schwartz morphism. In this manuscript we are interested in SDEs on a smooth manifold $M$ that are driven by p-dimensional Wiener process $W_t \in \mathbb{R}^p$. In terms of Schwartz morphism, such SDEs are represented by Schwartz morphism that morphs the sem

Axel Chemla--Romeu-Santos, Philippe Esling

Machine learning approaches now achieve impressive generation capabilities in numerous domains such as image, audio or video. However, most training \& evaluation frameworks revolve around the idea of strictly modelling the original data distribution rather than trying to extrapolate from it. This precludes the ability of such models to diverge from the orig

Mariia Gumberidze, Michal Kolář, Radim Filip

Quantum coherent superpositions of states with different energies, i.e., states with coherence with respect to energy basis, are important resource for modern quantum technologies. States with small coherence can be obtained either autonomously, due to the effect of a weak coherent drive or, potentially, due to the presence of an environment. In this paper,

Avishag Shapira, Ron Bitton, Dan Avraham, Alon Zolfi

Adversarial attacks against deep learning-based object detectors (ODs) have been studied extensively in the past few years. These attacks cause the model to make incorrect predictions by placing a patch containing an adversarial pattern on the target object or anywhere within the frame. However, none of prior research proposed a misclassification attack on O

Shayan Hundrieser, Florian Heinemann, Marcel Klatt, Marina Struleva

We analyze statistical properties of plug-in estimators for unbalanced optimal transport quantities between finitely supported measures in different prototypical sampling models. Specifically, our main results provide non-asymptotic bounds on the expected error of empirical Kantorovich-Rubinstein (KR) distance, plans, and barycenters for mass penalty paramet