August 2022 arXiv papers — page 94

Yi-Xuan Yao, Qing Ai

Inspired by the photosynthetic energy transfer process, we theoretically propose a method to realize non-reciprocal optical transmission in an array of coupled resonators. The optical non-reciprocity of the coupled resonators arises from the frequency gradient between adjacent cavities and the interaction with the environment, which is similar to photosynthe

Stefano Catani, Prasanna K. Dhani

The singular behaviour of QCD squared amplitudes in the collinear limit is factorized and controlled by splitting kernels with a process-independent structure. We use these kernels to define collinear functions that can be used in QCD resummation formulae of hard-scattering observables. Different collinear functions are obtained by integrating the splitting

Oleg Antipin, Jahmall Bersini, Pantelis Panopoulos

We extend the fixed-charge semiclassical method by computing anomalous dimensions of fixed-charge scalar operators in models with Yukawa interactions. In particular, we discuss the Nambu-Jona-Lasinio-Yukawa theory as well as an asymptotically safe gauge-Yukawa model in four dimensions. In the weakly coupled regime, we cross-check our results to the respectiv

Vijaya Raghavan T. Ramkumar, Elahe Arani, Bahram Zonooz

Scene change detection (SCD), a crucial perception task, identifies changes by comparing scenes captured at different times. SCD is challenging due to noisy changes in illumination, seasonal variations, and perspective differences across a pair of views. Deep neural network based solutions require a large quantity of annotated data which is tedious and expen

Ekta Chaubey, Ina Hönemann, Stefan Weinzierl

We consider the full set of master integrals with internal top-and $W$-propagators contributing to the three-loop Higgs self-energy diagrams of order ${\mathcal O}(\alpha^2 \alpha_s)$. We split the master integrals into a system relevant to the Feynman diagrams proportional to the product of Yukawa couplings $y_b y_t$ and the complement. For both systems we

Elizabeth Fons, Alejandro Sztrajman, Yousef El-laham, Alexandros Iosifidis

Implicit neural representations (INRs) have recently emerged as a powerful tool that provides an accurate and resolution-independent encoding of data. Their robustness as general approximators has been shown in a wide variety of data sources, with applications on image, sound, and 3D scene representation. However, little attention has been given to leveragin

Andrew Kresch, Yuri Tschinkel

We construct new invariants of equivariant birational isomorphisms taking values in equivariant Burnside groups.

Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto

Practical image segmentation tasks concern images which must be reconstructed from noisy, distorted, and/or incomplete observations. A recent approach for solving such tasks is to perform this reconstruction jointly with the segmentation, using each to guide the other. However, this work has so far employed relatively simple segmentation methods, such as the

Liviu Ornea, Misha Verbitsky

A complex manifold $X$ is called "LCK manifolds with potential" if it can be realized as a complex submanifold of a Hopf manifold. Let $Y$ its $\Z$-covering, considered as a complex submanifold in $C^n \backslash 0$. We prove that $Y$ is algebraic. We call the manifolds obtained this way the algebraic cones, and show that the affine algebraic structure on $Y

Yaping Zhao, Shuhui Shi, Ramgopal Ravi, Zhongrui Wang

The study of socioeconomic status has been reformed by the availability of digital records containing data on real estate, points of interest, traffic and social media trends such as micro-blogging. In this paper, we describe a heterogeneous, multi-source, multi-modal, multi-view and multi-distributional dataset named "H4M". The mixed dataset contains data o

Sung Won Jung, Luke C. Rhodes, Matthew D. Watson, Daniil V. Evtushinsky

The electronic structures of the iron-based superconductors have been intensively studied by using angleresolved photoemission spectroscopy (ARPES). A considerable amount of research has been focused on the LaFeAsO family, showing the highest transition temperatures, where previous ARPES studies have found much larger Fermi surfaces than bulk theoretical cal

Stefan Catoiu, Ian M. Musson

For a simple Lie algebra, Shapovalov elements give rise to highest weight vectors in Verma modules. The usual construction of these elements uses induction on the length of a certain Weyl group element. If $\mathfrak{g}= \mathfrak{sl}(N+1)$ explicit expressions for Shapovalov elements were given in [Mus22a]. Here we adapt the argument to the quantized envelo

Julius Richter, Simon Welker, Jean-Marie Lemercier, Bunlong Lay

In this work, we build upon our previous publication and use diffusion-based generative models for speech enhancement. We present a detailed overview of the diffusion process that is based on a stochastic differential equation and delve into an extensive theoretical examination of its implications. Opposed to usual conditional generation tasks, we do not sta

Thibaud Godon, Pier-Luc Plante, Baptiste Bauvin, Elina Francovic-Fontaine

Background: Understanding the relationship between the Omics and the phenotype is a central problem in precision medicine. The high dimensionality of metabolomics data challenges learning algorithms in terms of scalability and generalization. Most learning algorithms do not produce interpretable models -- Method: We propose an ensemble learning algorithm bas

Fan Chung, Qizhong Lin

For graphs $G$ and $H$, we consider Ramsey numbers $r(G,H)$ with tight lower bounds, namely, $r(G,H) \geq (\chi(G)-1)(|H|-1)+1,$ where $\chi(G)$ denotes the chromatic number of $G$ and $|H|$ denotes the number of vertices in $H$. We say $H$ is $G$-good if the equality holds. Let $G+H$ be the join graph obtained from graphs $G$ and $H$ by adding all edges bet

Kaiyin Huang, Shaoyun Shi, Shuangling Yang

The Morales-Ramis theory provides an effective and powerful non-integrability criterion for complex analytical Hamiltonian systems via the differential Galoisian obstruction. In this paper we give a new Morales-Ramis type theorem on the meromorphic Jacobi non-integrability of general analytic dynamical systems. The key point is to show the existence of Jacob

Zhuo-Xu Cui, Sen Jia, Qingyong Zhu, Congcong Liu

Recently, untrained neural networks (UNNs) have shown satisfactory performances for MR image reconstruction on random sampling trajectories without using additional full-sampled training data. However, the existing UNN-based approach does not fully use the MR image physical priors, resulting in poor performance in some common scenarios (e.g., partial Fourier

Hans Henrik Sievertsen

Assessments such as standardized tests and teacher evaluations of students' classroom participation are central elements of most educational systems. Assessments inform the student, parent, teacher, and school about the student learning progress. Individuals use the information to adjust their study efforts and to make guide their course choice. Schools and

Elizabeth R. Stanway

The anecdotal connection between an interest in science fiction and career aspirations in astrophysics is well established. However strong statistical evidence for such a connection, and a quantitative assessment of its prevalence, has been missing. Here I report the results of two surveys examining the connection between science fiction enthusiasm and astro

Julian Stobbe, Georg Rohringer

In the last decades, dynamical mean-field theory (DMFT) and its diagrammatic extensions have been successfully applied to describe local and nonlocal correlation effects in correlated electron systems. Unfortunately, except for the exact solution, it is impossible to fulfill both the Pauli principle and conservation laws at the same time. Consequently, funda

Caden Schuessler, Anthony Remijan, Ci Xue, Joshua Carder

The formation of molecules in the interstellar medium (ISM) remains a complex and unresolved question in astrochemistry. A group of molecules of particular interest involves the linkage between a -carboxyl and -amine group, similar to that of a peptide bond. The detection of molecules containing these peptide-like bonds in the ISM can help elucidate possible

Krzysztof A. Meissner, Hermann Nicolai

We study the quantization of the bosonic sector of supermembrane theory in double dimensional reduction, in order to extract the dependence of the resulting world-sheet action on the string dilaton (which cannot be obtained from a purely kinematic reduction). Our construction relies on a Polyakov-type approach with all six metric components on the world-volu

Guozheng Li, Runfei Li, Zicheng Wang, Chi Harold Liu

Tabular visualization techniques integrate visual representations with tabular data to avoid additional cognitive load caused by splitting users' attention. However, most of the existing studies focus on simple flat tables instead of hierarchical tables, whose complex structure limits the expressiveness of visualization results and affects users' efficiency

David Reiher, Axel Hahn

Modern highly automated and autonomous traffic systems and subsystems require new approaches to test their functional safety in the context of validation and verification. One approach that has taken a leading role in current research is scenario-based testing. For various reasons, simulation is considered to be the most practicable solution for a wide range

Sohail Ahmed Khan, Duc-Tien Dang-Nguyen

Deepfake media is becoming widespread nowadays because of the easily available tools and mobile apps which can generate realistic looking deepfake videos/images without requiring any technical knowledge. With further advances in this field of technology in the near future, the quantity and quality of deepfake media is also expected to flourish, while making

Alfredo García, Javier Tejel, Birgit Vogtenhuber, Alexandra Weinberger

Simple drawings are drawings of graphs in the plane or on the sphere such that vertices are distinct points, edges are Jordan arcs connecting their endpoints, and edges intersect at most once (either in a proper crossing or in a shared endpoint). Simple drawings are generalized twisted if there is a point $O$ such that every ray emanating from $O$ crosses ev

Mengze Li, Tianbao Wang, Haoyu Zhang, Shengyu Zhang

Video Object Grounding (VOG) is the problem of associating spatial object regions in the video to a descriptive natural language query. This is a challenging vision-language task that necessitates constructing the correct cross-modal correspondence and modeling the appropriate spatio-temporal context of the query video and caption, thereby localizing the spe

Mhd Saria Allahham, Amr Mohamed, Aiman Erbad, Hossam Hassanein

Extreme edge computing (EEC) refers to the endmost part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer computational resources, which may consist of wearable devices, personal mobile devices, drones, etc. Such devices are opportunistically or

C. L. Zhang, X. He, Z. W. Li, S. J. Zhang

Studies on polyhydrides are attracting growing attentions recently due to their potential high temperature superconductivity (SC). We here report the discovery of SC in hafnium polyhydrides at high pressures. The hafnium superhydrides are synthesized at high pressure and high temperature conditions using diamond anvil cell in combination with in-situ high pr

Pablo Andujar Guerrero, Will Johnson

We prove some technical results on definable types in $p$-adically closed fields, with consequences for definable groups and definable topological spaces. First, the code of a definable $n$-type (in the field sort) can be taken to be a real tuple (in the field sort) rather than an imaginary tuple (in the geometric sorts). Second, any definable type in the re

Jianan Han, Shaoxing Zhang, Aidong Men, Yang Liu

It is inevitably crucial to classify sleep stage for the diagnosis of various diseases. However, existing automated diagnosis methods mostly adopt the "gold-standard" lectroencephalogram (EEG) or other uni-modal sensing signal of the PolySomnoGraphy (PSG) machine in hospital, that are expensive, importable and therefore unsuitable for point-of-care monitorin

Neha Malik, Steven Spallone

We describe the Stiefel-Whitney classes (SWCs) of orthogonal representations $\pi$ of the finite special linear groups $G=\text{SL}(2,\mathbb F_q)$, in terms of character values of $\pi$. From this calculation, we can answer interesting questions about SWCs of $\pi$. For instance, we determine the subalgebra of $H^*(G,\mathbb Z/2\mathbb Z)$ generated by the

Taras Mel'nyk, Christian Rohde

We consider for a small parameter $\varepsilon >0$ a parabolic convection-diffusion problem with P\'eclet number of order $\mathcal{O}(\varepsilon^{-1})$ in a three-dimensional graph-like junction consisting of thin curvilinear cylinders with radii of order $\mathcal{O}(\varepsilon)$ connected through a domain (node) of diameter $\mathcal{O}(\varepsilon).$ I

R. S. Shaikhaidarov, K. H. Kim, J. W. Dunstan, I. V. Antonov

The AC Josephson effect predicted in 1962 and observed experimentally in 1963 as quantised voltage steps (the Shapiro steps) from photon assisted tunnelling of Cooper pairs is among the most fundamental phenomena of quantum mechanics and is vital for metrological quantum voltage standards. The physically dual effect, the AC coherent quantum phase slip (CQPS)

Minji Kim, Seungkwan Lee, Jungseul Ok, Bohyung Han

Despite the extensive adoption of machine learning on the task of visual object tracking, recent learning-based approaches have largely overlooked the fact that visual tracking is a sequence-level task in its nature; they rely heavily on frame-level training, which inevitably induces inconsistency between training and testing in terms of both data distributi

Nicola Cavallucci

We reprove in an easier way a result of Brian Clarke: the completion of the space of Riemannian metrics of a compact, orientable smooth manifold with respect to the $L^2$-distance is CAT$(0)$. In particular we show that this completion is isometric to the space of $L^2$-maps from a standard probability space to a fixed CAT$(0)$ space.

Xiong Liu, An Wang, Junfan Zhu, Ling Ye

We propose and experimentally realize a general scheme of differential imaging employing the idea of weak measurement. We show that the weak coupling between the system of interest and a two-level ancilla can introduce a two-beam circuit after an arbitrary pre-selection of the ancilla. By choosing the post-selection orthogonal to the pre-selection measuremen

A. Sanna, P. Bult, M. NG, P. S. Ray

The detection of coherent X-ray pulsations at ~314 Hz (3.2 ms) classifies MAXI J1957+032 as a fast-rotating, accreting neutron star. We present the temporal and spectral analysis performed using NICER observations collected during the latest outburst of the source. Doppler modulation of the X-ray pulsation revealed the ultra-compact nature of the binary syst

Dongryul M. Kim, Hee Oh

Let $\Gamma<\mathrm{PSL}_2(\mathbb{C})\simeq \mathrm{Isom}^+(\mathbb{H}^3)$ be a finitely generated non-Fuchsian Kleinian group whose ordinary set $\Omega=\mathbb{S}^2-\Lambda$ has at least two components. Let $\rho : \Gamma \to \mathrm{PSL}_2(\mathbb{C})$ be a faithful discrete non-Fuchsian representation with boundary map $f:\Lambda\to \mathbb{S}^2$ on the

Anton Simen Albino, Lucas Correia Jardim, Diego Campos Knupp, Antonio Jose Silva Neto

In this work, we obtain the numerical temperature field to a thermally developing fluid flow inside parallel plates problem with a quantum computing method. The physical problem deals with the heat transfer of a steady state, hydrodinamically developed and thermally developing fluid flow inside two parallel plates channel subjected to a prescribed constant h

Edoardo Donadoni, Paulo Siani, Giulia Frigerio, Cristiana Di Valentin

Strategies based on the active targeting of tumor cells are emerging as smart and efficient nanomedical procedures. Folic acid (FA) is a vitamin and a well-established tumor targeting agent because of its strong affinity for the folate receptor (FR), which is an overexpressed protein on the cell membranes of the tumor cells. FA can be successfully anchored t

Enrico Russo, Alberto Mercurio, Fabio Mauceri, Rosario Lo Franco

The hopping mechanism plays a key role in collective phenomena emerging in many-body physics. The ability to create and control systems that display this feature is important for next generation quantum technologies. Here we study two cavities separated by a vibrating two-sided perfect mirror and show that, within currently available experimental parameters,

Francesco Ferrante, Giorgio Valmorbida

The stability analysis of a class of discontinuous discrete-time systems is studied in this paper. The system under study is modeled as a feedback interconnection of a linear system and a set-valued nonlinearity. An equivalent representation, based on a constrained optimization problem, is proposed to represent the set-valued nonlinearity via a collection of

Anthony Devaux, Catherine Helmer, Robin Genuer, Cécile Proust-Lima

Predicting the individual risk of a clinical event using the complete patient history is still a major challenge for personalized medicine. Among the methods developed to compute individual dynamic predictions, the joint models have the assets of using all the available information while accounting for dropout. However, they are restricted to a very small nu

Niall O' Mahony, Sean Campbell, Lenka Krpalkova, Joseph Walsh

Fine-Grained Change Detection and Regression Analysis are essential in many applications of ArtificialIntelligence. In practice, this task is often challenging owing to the lack of reliable ground truth information andcomplexity arising from interactions between the many underlying factors affecting a system. Therefore,developing a framework which can repres

Dmitry Vasilyev

The Mu-phase, which is an intermetallic compound, can form in steels and superalloys, and significantly degrade their mechanical properties. The thermal expansion of Co7Mo6 Mu-phase have been investigated by first-principles based quasi-harmonic Debye-Gr\"uneisen approximation and by comparing the free energies calculated along different paths of thermal exp

Christian Porter, Edmund Dable-Heath, Cong Ling

In this work, we determine a sharp upper bound on the orthogonality defect of HKZ reduced bases up to dimension $3$. Using this result, we determine a general upper bound for the orthogonality defect of HKZ reduced bases of arbitrary rank. This upper bound seems to be sharper than existing bounds in literature, such as the one determined by Lagarias, Lenstra

Carina M. Persson, Iskra Y. Georgieva, Davide Gandolfi, Lorena Acuña

Highly irradiated planets in the hot Neptune desert are usually either small (R < 2 Rearth) and rocky or they are gas giants with radii of >1 Rjup. Here, we report on the intermediate-sized planet TOI-2196 on a 1.2 day orbit around a G-type star discovered by TESS in sector 27. We collected 42 radial velocity measurements with the HARPS spectrograph to deter

Subhash Mahapatra, Indrani Banerjee

We study the method of extended gravitational decoupling in obtaining static black hole solutions satisfying Einstein's equations with a tensor vacuum. The source has quite generic characteristics and satisfies the strong energy condition. The stationary, axisymmetric counterpart of the static metric is obtained by applying the Newman-Janis and Azreg-A\"{i}n

Vasiliy Usatyuk

We modified Cole's Importance Sampling (IS) method for enumerating of Trapping Sets (TS, asymmetric subgraphs) causing an error under message-passing decoder. Proposed Cole's IS modifications based on combination of several ideas: parallel TS impulse tree decomposition using unwrapping of message passing iterations, according short cycles dense and straightf

Anton Simen Albino, Otto Menegasso Pires, Peterson Nogueira, Renato Ferreira de Souza

Quantum computing is in its early stage of implementation. Its capacity has been growing in the last years but its application in several fields of sciences is still restricted to oversimplified problems. In this stage, it is important to identify the situations where quantum computing presents the most promising results to be prepared when the technology is

Carlo Gigli, Amirhossein Saba, Ahmed Bassam Ayoub, Demetri Psaltis

Deep neural networks trained on physical losses are emerging as promising surrogates of nonlinear numerical solvers. These tools can predict solutions of Maxwell's equations and compute gradients of output fields with respect to the material and geometrical properties in millisecond times which makes them attractive for inverse design or inverse scattering a

Ken Wharton, Emily Adlam

For any experiment with two entangled photons, some joint measurement outcomes can have zero probability for a precise choice of basis. These perfect anti-correlations would seem to be a purely quantum phenomenon. It is therefore surprising that these very anti-correlations are also evident when the input to the same experiment is analyzed via classical elec

Alexey Kutalev, Alisa Lapina

In this paper we want to present the results of empirical verification of some issues concerning the methods for overcoming catastrophic forgetting in neural networks. First, in the introduction, we will try to describe in detail the problem of catastrophic forgetting and methods for overcoming it for those who are not yet familiar with this topic. Then we w

Miguel Escobedo

Short time existence of classical solutions is proved for a system of equations that involves a three excitations kinetic operator. The system is related to the description of a gas of bosons below but close to the critical temperature, where the three excitations integral aims at describing the interaction between the particles in the condensate and the exc

Brian P. Powell, Saul A. Rappaport, Tamás Borkovits, Veselin B. Kostov

We report the discovery with TESS of a remarkable quadruple star system with a 2+1+1 configuration. The two unique characteristics of this system are that (i) the inner eclipsing binary (stars Aa and Ab) eclipses the star in the outermost orbit (star C), and (ii) these outer 4th body eclipses last for $\sim$12 days, the longest of any such system known. The

Meiling Fang, Fadi Boutros, Naser Damer

The supervised-learning-based morphing attack detection (MAD) solutions achieve outstanding success in dealing with attacks from known morphing techniques and known data sources. However, given variations in the morphing attacks, the performance of supervised MAD solutions drops significantly due to the insufficient diversity and quantity of the existing MAD

Liang Guo, Zi-an Deng, Yue-cheng Meng, Jing Chen

Protein-based high internal phase emulsions (HIPEs) have gained tremendous attention in diverse fields, but their mechanism in the emulsification process remains elusive. In this article, HIPEs were stabilized directly by food-grade proteins, depending on a self-organized process featuring a fluid laminarization. We elucidated that the emulsification with th

Alexey Belenkin, Michael Hartz, Thomas Schuster

We consider variational regularization of nonlinear inverse problems in Banach spaces using Tikhonov functionals. This article addresses the problem of $\Gamma$-convergence of a family of Tikhonov functionals and assertions of the convergence of their respective infima. Such questions arise, if model uncertainties, inaccurate forward operators, finite dimens

Shaina Raza, Deepak John Reji, Chen Ding

Because of the increasing use of data-centric systems and algorithms in machine learning, the topic of fairness is receiving a lot of attention in the academic and broader literature. This paper introduces Dbias (https://pypi.org/project/Dbias/), an open-source Python package for ensuring fairness in news articles. Dbias can take any text to determine if it

Neel Trivedi, Ravi Kiran Sarvadevabhatla

Pose-based action recognition is predominantly tackled by approaches which treat the input skeleton in a monolithic fashion, i.e. joints in the pose tree are processed as a whole. However, such approaches ignore the fact that action categories are often characterized by localized action dynamics involving only small subsets of part joint groups involving han

Yuchen Ding

In this short note, we answer two questions of Chen and Ruzsa negatively and answer a problem of Ma and Chen affirmatively.

Qiang Li, Greg Ver Steeg, Jesus Malo

Recent studies invoke the superiority of the multivariate Total Correlation concept over the conventional pairwise measures of functional connectivity in biological networks. Those seminal works certainly show that empirical measures of Total Correlation lead to connectivity patterns that differ from what is obtained using the most popular measure, linear co

Tommaso Pajero

After playing a pivotal role in the birth of the Standard Model in the 70's, the study of charm physics has undergone a revival during the last decade, triggered by a wealth of precision measurements from the charm and $B$ factories, and from the CDF and especially the LHCb experiments. In this article, we sum up how the unique phenomenology of charmed hadro

Chuanguang Yang, Zhulin An, Helong Zhou, Linhang Cai

Unlike the conventional Knowledge Distillation (KD), Self-KD allows a network to learn knowledge from itself without any guidance from extra networks. This paper proposes to perform Self-KD from image Mixture (MixSKD), which integrates these two techniques into a unified framework. MixSKD mutually distills feature maps and probability distributions between t

Laixi Shi, Yuejie Chi

This paper concerns the central issues of model robustness and sample efficiency in offline reinforcement learning (RL), which aims to learn to perform decision making from history data without active exploration. Due to uncertainties and variabilities of the environment, it is critical to learn a robust policy -- with as few samples as possible -- that perf

Ninh Van Thu, Nguyen Thi Kim Son, Nguyen Quang Dieu

In this paper, we characterize weakly pseudoconvex domains of finite type in $\mathbb C^n$ in terms of the boundary behavior of automorphism orbits by using the scaling method.

Ameer Jaber

A complex intuitionistic fuzzy Lie superalgebra is a generalization of intuitionistic fuzzy Lie superalgebra whose membership function takes values in the unit disk in the complex plane. In this research, the concepts of complex intuitionistic fuzzy sets are introduced to Lie superalgebras. We define the complex intuitionistic fuzzy Lie sub superalgebras and

Edwin J. Beggs, John V. Tucker

The rise of AI in human contexts places new demands on automated systems to be transparent and explainable. We examine some anthropomorphic ideas and principles relevant to such accountablity in order to develop a theoretical framework for thinking about digital systems in complex human contexts and the problem of explaining their behaviour. Structurally, sy

Yun-Ya Huang, Chih-Ya Shen

k-plex is a representative definition of communities in networks. While the cliques is too stiff to applicate to real cases, the k-plex relaxes the notion of the clique, allowing each node to miss up to k connections. Although k-plexes are more flexible than cliques, finding them is more challenging as their number is greater. In this paper, we aim to detect

Barnabás Szabó

We study the existence of products of primes in arithmetic progressions, building on the work of Ramar\'e and Walker. One of our main results is that if $q$ is a large modulus, then any invertible residue class mod $q$ contains a product of three primes where each prime is at most $q^{6/5+\epsilon}$. Our arguments use results from a wide range of areas, such

Eloisa Detomi, Andrea Lucchini

Given a finite group $G$ and an element $g\in G$, we may compare the expected number $e(G)$ of elements needed to generate $G$ and the expected number $e(G,g)$ of elements of $G$ needed to generate $G$ together with $g.$ We address the following question: how large can the difference $e(G)-e(G,g)$ be?

Aleš Cahlík, Danyang Liu, Berk Zengin, Mert Taskin

The on-surface synthesis of nano-graphenes has led the charge in prototyping structures with perspectives beyond silicon-based technology. Following reports of open-shell systems in graphene-nanoribbons (GNR), a flurry of research activities is directed at investigating their magnetic properties with a keen eye for spintronic applications. Although the synth

Gaoyang Li, Fuming Xu, Jian Wang

We numerically investigate the magnon-mediated spin transport and scaling behaviors of a nonmagnetic metal/nonmagnetic metal/ferromagnetic insulator (NM/NM/FI) heterostructure in the presence of Anderson disorders. For the two-dimensional (2D) NM/NM/FI system, an enhancement of spin conductance in the weak disorder regime is found due to the increasing of th

Yosuke Ueno, Masaaki Kondo, Masamitsu Tanaka, Yasunari Suzuki

Quantum error correction (QEC) is essential for quantum computing to mitigate the effect of errors on qubits, and surface code (SC) is one of the most promising QEC methods. Decoding SCs is the most computational expensive task in the control device of quantum computers (QCs), and many works focus on accurate decoding algorithms for SCs, including ones with

Keenan Jones, Enes Altuncu, Virginia N. L. Franqueira, Yichao Wang

In recent years there has been substantial growth in the capabilities of systems designed to generate text that mimics the fluency and coherence of human language. From this, there has been considerable research aimed at examining the potential uses of these natural language generators (NLG) towards a wide number of tasks. The increasing capabilities of powe

Milan Sil

My thesis work aims to study the inter-relation between various physical and chemical conditions in a wide range of astrophysical environments. Our studied regions range from the super-hot regions (i.e., nebular, photon-dominated, or photodissociation regions, diffuse area, through which the lights of the background stars can reach us) to the super-cold regi

F. Mahmoudi

We present an overview of the recent neutral current $B$ decays focusing on the deviations with respect to the Standard Model predictions that are observed in $b \to s \ell^+\ell^-$ transitions, and discuss their implications for new physics scenarios in a model-independent way by means of global statistical fits. The prospects for future discoveries in the

Mustafa Z. Yousif, Linqi Yu, Sergio Hoyas, Ricardo Vinuesa

Turbulence is a complex phenomenon that has a chaotic nature with multiple spatio-temporal scales, making predictions of turbulent flows a challenging topic. Nowadays, an abundance of high-fidelity databases can be generated by experimental measurements and numerical simulations, but obtaining such accurate data in full-scale applications is currently not po

Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jiaxin Mao

Recent advance in Dense Retrieval (DR) techniques has significantly improved the effectiveness of first-stage retrieval. Trained with large-scale supervised data, DR models can encode queries and documents into a low-dimensional dense space and conduct effective semantic matching. However, previous studies have shown that the effectiveness of DR models would

Pagdame Tiebekabe, Serge Adonsou, Ismaïla Diouf

\noindent In this article, we determine all the integers $c$ having at least two representations as difference between two linear recurrent sequences. This is a variant of the Pillai's equation. This equation is an exponential Diophantine equation. The proof of our main theorem uses lower bounds for linear forms of logarithms, properties of continued fractio

Jingbo Zhang, Xiaoyu Li, Ziyu Wan, Can Wang

We propose a Few-shot Dynamic Neural Radiance Field (FDNeRF), the first NeRF-based method capable of reconstruction and expression editing of 3D faces based on a small number of dynamic images. Unlike existing dynamic NeRFs that require dense images as input and can only be modeled for a single identity, our method enables face reconstruction across differen

Parthapratim Saha, Bipan Hazarika

For a locally compact group $H$ with a left Haar measure, we study variable Lebesgue algebra $\mathcal{L}^{p(\cdot)}(H)$ with respect to a convolution. We show that if $\mathcal{L}^{p(\cdot)}(H)$ has bounded exponent, then it contains a left approximate identity. We also prove a necessary and sufficient condition for $\mathcal{L}^{p(\cdot)}(H)$ to have an id

Xiao-Xiong Zeng, M. Israr Aslam, Rabia Saleem

Thanks for the releasing image of supermassive black holes (BHs) by the event horizon telescope (EHT) at the heart of the $M87$ galaxy. After the discovery of this mysterious object, scientists paid attention to exploring the BH shadow features under different gravitational backgrounds. In this scenario, we study the light rings and observational properties

David Tayouri, Nick Baum, Asaf Shabtai, Rami Puzis

Organizations employ various adversary models in order to assess the risk and potential impact of attacks on their networks. Attack graphs represent vulnerabilities and actions an attacker can take to identify and compromise an organization's assets. Attack graphs facilitate both visual presentation and algorithmic analysis of attack scenarios in the form of

Arnob Kumar Ghosh, Tanay Nag, Arijit Saha

We propose a practically feasible time-periodic sinusoidal drive protocol in onsite mass term to generate the two-dimensional~(2D) Floquet second-order topological superconductor, hosting both the regular $0$- and anomalous $\pi$-Majorana corner modes~(MCMs) while starting from a static 2D topological insulator/$d$-wave superconductor heterostructure setup.

Sheng-Nan Li, Carlo Campajola, Claudio J. Tessone

The core of many cryptocurrencies is the decentralised validation network operating on proof-of-work technology. In these systems, validation is done by so-called miners who can digitally sign blocks once they solve a computationally-hard problem. Conventional wisdom generally considers this protocol as secure and stable as miners are incentivised to follow

Sebastian Blauth

The space mapping technique is used to efficiently solve complex optimization problems. It combines the accuracy of fine model simulations with the speed of coarse model optimizations to approximate the solution of the fine model optimization problem. In this paper, we propose novel space mapping methods for solving shape optimization problems constrained by

R. Matthias Geilhufe, Wolfram Hergert

High intensity THz lasers allow for the coherent excitation of individual phonon modes. The ultrafast control of emergent magnetism by means of phonons opens up new tuning mechanisms for functional materials. While theoretically predicted phonon magnetic moments are tiny, recent experiments hint towards a significant magnetization in various materials. To ex

Quentin Blampey, Nadège Bercovici, Charles-Antoine Dutertre, Isabelle Pic

Cytometry enables precise single-cell phenotyping within heterogeneous populations. These cell types are traditionally annotated via manual gating, but this method suffers from a lack of reproducibility and sensitivity to batch-effect. Also, the most recent cytometers - spectral flow or mass cytometers - create rich and high-dimensional data whose analysis v

Trung Pham, Chaoning Zhang, Axi Niu, Kang Zhang

Exponential Moving Average (EMA or momentum) is widely used in modern self-supervised learning (SSL) approaches, such as MoCo, for enhancing performance. We demonstrate that such momentum can also be plugged into momentum-free SSL frameworks, such as SimCLR, for a performance boost. Despite its wide use as a fundamental component in modern SSL frameworks, th

Redouane Lguensat, Julie Deshayes, Homer Durand, V. Balaji

The objective of this study is to evaluate the potential for History Matching (HM) to tune a climate system with multi-scale dynamics. By considering a toy climate model, namely, the two-scale Lorenz96 model and producing experiments in perfect-model setting, we explore in detail how several built-in choices need to be carefully tested. We also demonstrate t

Weining Zhu

Environmental model performances need to be assessed using some statistical parameters, such as mean absolute error (MAE) and root mean square error (RMSE). The advantages and disadvantages of these parameters are still in controversial. The purpose of this study is to introduce a statistical parameter, type A uncertainty (UA), into model performance evaluat

Xinyi Chen

Clarivate Analytics announces highly cited researchers (HCRs) every November to recognise true pioneers in their respective fields over the last decade who are one in 1,000 according to citation analysis based on the Web of Science database. However, the scientometric rules underlying HCR selections have constantly evolved over the years; thus, a comparative

Dmytro Tarasevych, Andreas Rückriegel, Savio Keupert, Vasilios Mitsiioannou

We use our recently developed functional renormalization group (FRG) approach for quantum spin systems to investigate the phase diagram of the frustrated $J_{1}J_{2}J_{3}$ quantum Heisenberg model on a cubic lattice. From a simple truncation of the hierarchy of FRG flow equations for the irreducible spin-vertices which retains only static spin fluctuations a

Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li

Bound propagation methods, when combined with branch and bound, are among the most effective methods to formally verify properties of deep neural networks such as correctness, robustness, and safety. However, existing works cannot handle the general form of cutting plane constraints widely accepted in traditional solvers, which are crucial for strengthening

M. Cristina Câmara, David Krejcirik

We develop the concept of operators in Hilbert spaces which are similar to their adjoints via antiunitary operators, the latter being not necessarily involutive. We discuss extension theory, refined polar and singular-value decompositions, and antilinear eigenfunction expansions. The study is motivated by physical symmetries in quantum mechanics with non-sel

G. Guerrero, A. M. Stejko, A. G. Kosovichev, P. K Smolarkiewicz

Simulating deep solar convection and its coupled mean-field motions is a formidable challenge where few observational results constrain models that suffer from the non-physical influence of the grid resolution. We present hydrodynamic global Implicit Large-Eddy simulations (ILES) of deep solar convection performed with the EULAG-MHD code, and explore the eff

Bright Kudzaishe Mahembe, Clement Nyirenda

This paper introduces a Modified User Datagram Protocol (UDP) for Federated Learning to ensure efficiency and reliability in the model parameter transport process, maximizing the potential of the Global model in each Federated Learning round. In developing and testing this protocol, the NS3 simulator is utilized to simulate the packet transport over the netw

Saurabh Dash, Xueyuan She, Saibal Mukhopadhyay

We present a novel Recurrent Graph Network (RGN) approach for predicting discrete marked event sequences by learning the underlying complex stochastic process. Using the framework of Point Processes, we interpret a marked discrete event sequence as the superposition of different sequences each of a unique type. The nodes of the Graph Network use LSTM to inco