July 2022 arXiv papers — page 129

Rajen Kumar, Sushant Kumar Jha, Prashant Kumar Srivastava, Sudhan Majhi

In this letter, we propose a novel construction of type-II $Z$-complementary code set (ZCCS) having arbitrary sequence length using the Kronecker product between a complete complementary code (CCC) and mutually orthogonal uni-modular sequences. In this construction, Barker sequences are used to reduce row sequence peak-to-mean envelope power ratio (PMEPR) fo

J. Fernandes, J. Sá Silva, A. Rodrigues, S. Sinche

As the number of smart devices that surround us increases, so do the opportunities to create smart socially-aware systems. In this context, mobile devices can be used to collect data about students and to better understand how their day-to-day routines can influence their academic performance. Moreover, the Covid-19 pandemic led to new challenges and difficu

Praveen Kumar, Sudhan Majhi, Subhabrata Paul

This letter presents a direct construction of cross Z-complementary sequence sets (CZCSSs), whose aperiodic correlation sums exhibit zero correlation zones at both the front-end and tail-end shifts. CZCSS can be regarded as an extension of the symmetrical Z-complementary code set (SZCCS). The available construction of SZCCS has a limitation on the set size,

Azur Hodžić, Peder J. Olesen, Clara M. Velte

The application of Fourier analysis in combination with the Proper Orthogonal Decomposition (POD) is investigated. In this approach to turbulence decomposition, which has recently been termed Spectral POD (SPOD), Fourier modes are considered as solutions to the corresponding Fredholm integral equation of the second kind along homogeneous-periodic or homogene

Sarina Thomas, Andrew Gilbert, Guy Ben-Yosef

Accurate and consistent predictions of echocardiography parameters are important for cardiovascular diagnosis and treatment. In particular, segmentations of the left ventricle can be used to derive ventricular volume, ejection fraction (EF) and other relevant measurements. In this paper we propose a new automated method called EchoGraphs for predicting eject

J. Kluson

We propose an action for the D0-brane anti-D0-brane system that has its exact solution corresponding to the marginal tachyon profile defined for arbitrary constant separation of these D-branes. We also find its covariant formulation and generalization to higher dimensional Dp-branes.

Xiaocheng Yang, Mingyu Yan, Shirui Pan, Xiaochun Ye

Heterogeneous graph neural networks (HGNNs) have powerful capability to embed rich structural and semantic information of a heterogeneous graph into node representations. Existing HGNNs inherit many mechanisms from graph neural networks (GNNs) over homogeneous graphs, especially the attention mechanism and the multi-layer structure. These mechanisms bring ex

Daisuke Kurisu, Riku Fukami, Yuta Koike

In this paper, we develop a general theory for adaptive nonparametric estimation of the mean function of a non-stationary and nonlinear time series model using deep neural networks (DNNs). We first consider two types of DNN estimators, non-penalized and sparse-penalized DNN estimators, and establish their generalization error bounds for general non-stationar

Maria Suveges, Sofia C. Olhede

This article proposes methods to model nonstationary temporal graph processes. This corresponds to modelling the observation of edge variables (relationships between objects) indicating interactions between pairs of nodes (or objects) exhibiting dependence (correlation) and evolution in time over interactions. This article thus blends (integer) time series m

Theodore L. Chang, Chin-Long Lee

This work presents a general finite element formulation based on a six--field variational principle that incorporates the consistent couple stress theory. A simple, efficient and local iteration free solving procedure that covers both elastic and inelastic materials is derived to minimise computation cost. With proper interpolations, membrane elements of var

Stefanos Nikolopoulos, Ioannis Kalogeris, Vissarion Papadopoulos, George Stavroulakis

Recent advances in the field of machine learning open a new era in high performance computing. Applications of machine learning algorithms for the development of accurate and cost-efficient surrogates of complex problems have already attracted major attention from scientists. Despite their powerful approximation capabilities, however, surrogates cannot produ

Manuel Brenner, Florian Hess, Jonas M. Mikhaeil, Leonard Bereska

In many scientific disciplines, we are interested in inferring the nonlinear dynamical system underlying a set of observed time series, a challenging task in the face of chaotic behavior and noise. Previous deep learning approaches toward this goal often suffered from a lack of interpretability and tractability. In particular, the high-dimensional latent spa

Hongyu Zhou, Zheng Ge, Songtao Liu, Weixin Mao

To date, the most powerful semi-supervised object detectors (SS-OD) are based on pseudo-boxes, which need a sequence of post-processing with fine-tuned hyper-parameters. In this work, we propose replacing the sparse pseudo-boxes with the dense prediction as a united and straightforward form of pseudo-label. Compared to the pseudo-boxes, our Dense Pseudo-Labe

Xin Lu, Tianle Liu, Hanzhong Liu, Peng Ding

Complete randomization balances covariates on average, but covariate imbalance often exists in finite samples. Rerandomization can ensure covariate balance in the realized experiment by discarding the undesired treatment assignments. Many field experiments in public health and social sciences assign the treatment at the cluster level due to logistical constr

Qian Ye, Masanori Suganuma, Jun Xiao, Takayuki Okatani

Reconstructing ghosting-free high dynamic range (HDR) images of dynamic scenes from a set of multi-exposure images is a challenging task, especially with large object motion and occlusions, leading to visible artifacts using existing methods. To address this problem, we propose a deep network that tries to learn multi-scale feature flow guided by the regular

Cassandra Milbradt

We are concerned with the problem of detecting a single change point in the model parameters of time series data generated from an exponential family. In contrast to the existing literature, we allow that the true location of the change point is itself random, possibly depending on the data. Under the alternative, we study the case when the size of the chang

Alexey Potapov, Maria Elisabetta Palumbo, Zelia Dionnet, Andrea Longobardo

The origin of organic compounds detected in meteorites and comets, some of which could serve as precursors of life on Earth, still remains an open question. The aim of the present study is to make one more step in revealing the nature and composition of organic materials of extraterrestrial particles by comparing infrared spectra of laboratory-made refractor

Samuel Cognolato, Alberto Testolin

Mathematical reasoning is one of the most impressive achievements of human intellect but remains a formidable challenge for artificial intelligence systems. In this work we explore whether modern deep learning architectures can learn to solve a symbolic addition task by discovering effective arithmetic procedures. Although the problem might seem trivial at f

Yang Li, Shixin Zhu

The Galois hull of a linear code is the intersection of itself and its Galois dual code, which has aroused the interest of researchers in these years. In this paper, we study Galois hulls of linear codes. Firstly, the symmetry of the dimensions of Galois hulls of linear codes is found. Some new necessary and sufficient conditions for linear codes being Galoi

Haggai Roitman, Uriel Singer, Yotam Eshel, Alexander Nus

We address the product question generation task. For a given product description, our goal is to generate questions that reflect potential user information needs that are either missing or not well covered in the description. Moreover, we wish to cover diverse user information needs that may span a multitude of product types. To this end, we first show how t

Cristina Cano, Hug March

Energy efficiency is at the core of sustainability solutions for 5/6G networks. We argue this is a too narrow perspective on sustainability, as it ignores the effects of the increased traffic demand these networks stimulate and the need for additional equipment that this demand requires. The hope is that techniques to reduce the network's energy consumption

Alessio Martini, Stefano Meda, Maria Vallarino, Giona Veronelli

In this paper we establish inclusions and noninclusions between various Hardy type spaces on noncompact Riemannian manifolds $M$ with Ricci curvature bounded from below, positive injectivity radius and spectral gap. Our first main result states that, if $\mathscr{L}$ is the positive Laplace-Beltrami operator on $M$, then the Riesz-Hardy space $H^1_\mathscr{R

Boris Lublinsky, Elise Jennings, Viktória Spišaková

Many scientific workflows require dedicated compute resources, including HPC clusters with optimized software, quantum resources, and dedicated hardware cluster systems like Ray, for example. At the same time, many scientific workflows today are built on Kubernetes leveraging growing support for workflow and support tools. To address the growing demand to su

Yong-Cong Chen, Chunxiao Shi, J. M. Kosterlitz, Xiaomei Zhu

A noisy stabilized Kuramoto-Sivashinsky equation is analyzed by stochastic decomposition. For values of control parameter for which periodic stationary patterns exist, the dynamics can be decomposed into diffusive and transverse parts which act on a stochastic potential. The relative positions of stationary states in the stochastic global potential landscape

Yuan Yao, Fengze Liu, Zongwei Zhou, Yan Wang

Shape information is a strong and valuable prior in segmenting organs in medical images. However, most current deep learning based segmentation algorithms have not taken shape information into consideration, which can lead to bias towards texture. We aim at modeling shape explicitly and using it to help medical image segmentation. Previous methods proposed V

Anirban Banerjee, Rajiv Mishra, Samiron Parui

Starting with an isolated vertex, here we construct a threshold hypergraph by repeatedly adding an isolated vertex or a $k$-dominating vertex set. We represent a threshold hypergraph by a string of non-negative integers and find the Laplacian spectrum of threshold hypergraphs from their string representation. We also compute the complete Laplacian spectrum o

Shams Nafisa Ali, Md. Tazuddin Ahmed, Joydip Paul, Tasnim Jahan

The recent monkeypox outbreak has become a public health concern due to its rapid spread in more than 40 countries outside Africa. Clinical diagnosis of monkeypox in an early stage is challenging due to its similarity with chickenpox and measles. In cases where the confirmatory Polymerase Chain Reaction (PCR) tests are not readily available, computer-assiste

Houssine Zine, Abderrahim El Adraoui, Delfim F. M. Torres

We propose a mathematical spatiotemporal epidemic SICA model with a control strategy. The spatial behavior is modeled by adding a diffusion term with the Laplace operator, which is justified and interpreted both mathematically and physically. By applying semigroup theory on the ordinary differential equations, we prove existence and uniqueness of the global

Marco Pizzolato, Erick Jorge Canales-Rodríguez, Mariam Andersson, Tim B. Dyrby

We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherical averaging. The use of strong diffusion weightings in magnetic resonance imaging (MRI) allows to approx

Soumitra Ghara, Rajeev Gupta, Md. Ramiz Reza

We prove a local Douglas formula for higher order weighted Dirichlet-type integrals. With the help of this formula, we study the multiplier algebra of the associated higher order weighted Dirichlet-type spaces $\mathcal H_{\pmb\mu},$ induced by an $m$-tuple $\pmb \mu =(\mu_1,\ldots,\mu_{m})$ of finite non-negative Borel measures on the unit circle. In partic

Margarete Mühlleitner, Johannes Schlenk, Michael Spira

Higgs-boson pair production at hadron colliders is dominantly mediated by the loop-induced gluon-fusion process $gg\to HH$ that is generated by heavy top loops within the Standard Model with a minor per-cent level contamination of bottom-loop contributions. The QCD corrections turn out to be large for this process. In this note, we derive the top-Yukawa-indu

Sameh Othman, Johannes Schulz, Marco Baity-Jesi, Caterina De Bacco

In community detection, datasets often suffer a sampling bias for which nodes which would normally have a high affinity appear to have zero affinity. This happens for example when two affine users of a social network were not exposed to one another. Community detection on this kind of data suffers then from considering affine nodes as not affine. To solve th

David Rau, Jaap Kamps

Even though term-based methods such as BM25 provide strong baselines in ranking, under certain conditions they are dominated by large pre-trained masked language models (MLMs) such as BERT. To date, the source of their effectiveness remains unclear. Is it their ability to truly understand the meaning through modeling syntactic aspects? We answer this by mani

Faezeh Khodabandehlou, Christian Maes, Karel Netočný

Using local detailed balance we rewrite the Kirchhoff formula for stationary distribution of Markov jump processes in terms of a physically interpretable tree-ensemble. We use that arborification of path-space integration to derive a McLennan-tree characterization close to equilibrium, as well as to obtain response formula for the stationary distribution in

Léonard Desvignes, Francesca Chiodi, Géraldine Hallais, Dominique Débarre

Secondary Ions Mass Spectroscopy and Hall effect measurements were performed on boron doped silicon with concentration between 0.02 at.% and 12 at.%. Ultra-high boron doping was made by saturating the chemisorption sites of a Si wafer with BCl3, followed by nanosecond laser anneal (Gas Immersion Laser Doping). The boron concentration varies thus nearly linea

Alessandro Simoni, Stefano Pini, Guido Borghi, Roberto Vezzani

Knowing the exact 3D location of workers and robots in a collaborative environment enables several real applications, such as the detection of unsafe situations or the study of mutual interactions for statistical and social purposes. In this paper, we propose a non-invasive and light-invariant framework based on depth devices and deep neural networks to esti

Sam Spilsbury, Alexander Ilin

We provide a study of how induced model sparsity can help achieve compositional generalization and better sample efficiency in grounded language learning problems. We consider simple language-conditioned navigation problems in a grid world environment with disentangled observations. We show that standard neural architectures do not always yield compositional

Margarita Capretto, Martin Ceresa, Cesar Sanchez

Blockchains are modern distributed systems that provide decentralized financial capabilities with trustable guarantees. Smart contracts are programs written in specialized programming languages running on a blockchain and govern how tokens and cryptocurrency are sent and received. Smart contracts can invoke other contracts during the execution of transaction

Su Young Kim, Hyeonjin Park, Kyuyong Shin, Kyung-Min Kim

As online merchandise become more common, many studies focus on embedding-based methods where queries and products are represented in the semantic space. These methods alleviate the problem of vocab mismatch between the language of queries and products. However, past studies usually dealt with queries that precisely describe the product, and there still exis

Shahzad Ali, Arif Mahmood, Soon Ki Jung

Continuous monitoring of foot ulcer healing is needed to ensure the efficacy of a given treatment and to avoid any possibility of deterioration. Foot ulcer segmentation is an essential step in wound diagnosis. We developed a model that is similar in spirit to the well-established encoder-decoder and residual convolution neural networks. Our model includes a

Futoshi Minato, Tomoya Naito, Osamu Iwamoto

Muon captures on nuclei have provided us with plenty of knowledge of nuclear properties. Recently, this reaction attracts attention in electronics, because it is argued that charged particle emissions following muon capture on silicon trigger non-negligible soft errors in memory devices. To investigate the particle emissions from a nuclear physics point of v

Tamitake Itoh, Yuko S. Yamamoto

The spectral relationships between surface enhanced resonant Raman scattering (SERRS) and plasmon resonance observed in far field scattering cross are investigated using single silver nanoparticle dimers with focusing on the lowest energy (superradiant) plasmon resonance. We find that these relationships can be classified into two types. The first is SERRS s

Oskar Sjögren, Gustav Grund Pihlgren, Fredrik Sandin, Marcus Liwicki

Measuring the similarity of images is a fundamental problem to computer vision for which no universal solution exists. While simple metrics such as the pixel-wise L2-norm have been shown to have significant flaws, they remain popular. One group of recent state-of-the-art metrics that mitigates some of those flaws are Deep Perceptual Similarity (DPS) metrics,

Pierluigi Cesana, Lucia De Luca, Marco Morandotti

We present a variational theory for lattice defects of rotational and translational type. We focus on finite systems of planar wedge disclinations, disclination dipoles, and edge dislocations, which we model as the solutions to minimum problems for isotropic elastic energies under the constraint of kinematic incompatibility. Operating under the assumption of

Giulio Chiribella, Kenneth R. Davidson, Vern I. Paulsen, Mizanur Rahaman

The theory of positive maps plays a central role in operator algebras and functional analysis, and has countless applications in quantum information science. The theory was originally developed for operators acting on complex Hilbert spaces, and little is known about its variant on real Hilbert spaces. In this article we study positive maps acting on a full

Ya-Qing Hu

The purpose of this paper is to introduce the concept of reflecting numbers to the realm of number theory and to classify reflecting numbers of certain types. For us, reflecting numbers are coming from congruent numbers, above congruent numbers, and away from congruent numbers. Explicitly speaking, a reflecting number of type $(k,m)$ is the average of two di

Yaraslau Tamashevich, Marco Ornigotti

We generalise the usual framework of Dirac-Bloch equations, used to compute the nonlinear optical response of 2D materials excited by spatially uniform optical pulses, to the case of structured light pulses. We derive the general form of Dirac-Bloch equations in the presence of a spatially inhomogeneous field, for the case of a graphene-like material. Then,

Andreas Crivellin

The determinations of the Cabibbo angle from kaon, pion, $D$ and tau decays disagree with the one from super-allowed beta decays. The resulting $\approx 3\,\sigma$ deficit in first row (but also first column) CKM unitarity is known as the Cabibbo angle anomaly (CAA). Determining $V_{ud}$ from beta decays requires knowledge of the Fermi constant $G_F$, usuall

Evangelos Bitsikas, Christina Pöpper

The Public Warning System (PWS) is an essential part of cellular networks and a country's civil protection. Warnings can notify users of hazardous events (e.g., floods, earthquakes) and crucial national matters that require immediate attention. PWS attacks disseminating fake warnings or concealing precarious events can have a serious impact, causing fraud, p

Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho

We show that standard Transformers without graph-specific modifications can lead to promising results in graph learning both in theory and practice. Given a graph, we simply treat all nodes and edges as independent tokens, augment them with token embeddings, and feed them to a Transformer. With an appropriate choice of token embeddings, we prove that this ap

Hai-Ming Xu, Hao Chen, Lingqiao Liu, Yufei Yin

Open-set panoptic segmentation (OPS) problem is a new research direction aiming to perform segmentation for both \known classes and \unknown classes, i.e., the objects ("things") that are never annotated in the training set. The main challenges of OPS are twofold: (1) the infinite possibility of the \unknown object appearances makes it difficult to model the

Da Wang, Jun-Qi Xu, Hai-Jun Zhang, Qiang-Hua Wang

In our recent work [Phys. Rev. Lett. 128, 137001 (2002)], we proposed that the apical oxygen vacancies act as anisotropic scattering impurities. Within the Born approximation, this leads to a quasi-particle scattering rate that is maximal (zero) in the antinodal (nodal) direction. This unique angular dependence provides a straightforward mechanism for some p

Kevin De Porre, Carla Ferreira, Elisa Gonzalez Boix

Distributed systems adopt weak consistency to ensure high availability and low latency, but state convergence is hard to guarantee due to conflicts. Experts carefully design replicated data types (RDTs) that resemble sequential data types and embed conflict resolution mechanisms that ensure convergence. Designing RDTs is challenging as their correctness depe

Fredrik Johansson

We describe an algorithm for arbitrary-precision computation of the elementary functions (exp, log, sin, atan, etc.) which, after a cheap precomputation, gives roughly a factor-two speedup over previous state-of-the-art algorithms at precision from a few thousand bits up to millions of bits. Following an idea of Sch{\"o}nhage, we perform argument reduction u

Francis Bernardeau

Context: Statistical properties of the cosmic density fields are to a large extent encoded in the shape of the one-point density probability distribution functions (PDF). In order to successfully exploit such observables, a detailed functional form of the covariance matrix of the one-point PDF is needed. Aims: The objectives are to model the properties of th

Marcos Caso-Huerta, Antonio Degasperis, Priscila Leal da Silva, Sara Lombardo

Models describing long wave-short wave resonant interactions have many physical applications from fluid dynamics to plasma physics. We consider here the Yajima-Oikawa-Newell (YON) model, which has been recently introduced combining the interaction terms of two long wave-short wave, integrable models, one proposed by Yajima-Oikawa, and the other one by Newell

Ritu Garg, Alka Upadhyay

We studied $F$-wave bottom mesons in heavy quark effective theory. The available experimental and theoretical data is used to calculate the masses of $F$-wave bottom mesons. The decay widths of bottom mesons are analyzed to find upper bounds of the associated couplings. We also construct Regge trajectories for our predicted data in planes ($J$, $M^2$ ) and o

Paul Nicaise, Jie Hu, Jean-Marc Martin, Samir Beldi

To improve the optical coupling in Microwave Kinetic Inductance Detectors (MKIDs), we investigate the use of a reflective plate beneath the meandered absorber. We designed, fabricated and characterized high-Q factors TiN-based MKIDs on sapphire operating at optical wavelengths with a Au/Nb reflective thin bilayer below the meander. The reflector is set at a

Oishee Banerjee, Jun-Yong Park, Johannes Schmitt

We compute the (stable) \'etale cohomology of $\mathrm{Hom}_{n}(C, \mathcal{P}(\vec{\lambda}))$, the moduli stack of degree $n$ morphisms from a smooth projective curve $C$ to the weighted projective stack $\mathcal{P}(\vec{\lambda})$, the latter being a stacky quotient defined by $\mathcal{P}(\vec{\lambda}) := \left[\mathbb{A}^N-\{0\}/\mathbb{G}_m\right]$,

Zehan Li, Haoran Miao, Keqi Deng, Gaofeng Cheng

There is often a trade-off between performance and latency in streaming automatic speech recognition (ASR). Traditional methods such as look-ahead and chunk-based methods, usually require information from future frames to advance recognition accuracy, which incurs inevitable latency even if the computation is fast enough. A causal model that computes without

Zhoujian Sun, Panpan Fang, Xinwei Shi, X. S. Wang

There has been a plethora of studies on domain wall dynamics in magnetic nanostrips, mainly because of its versatile non-linear physics and potential applications in data storage devices. However, most of the studies focus on out-of-plane domain walls or in-plane head-to-head (tail-to-tail) domain walls. Here, we numerically study the field-driven dynamics o

Giovanni Masciocchi, Johannes Wilhelmus van der Jagt, Maria-Andromachi Syskaki, Alessio Lamperti

This study reports the effects of post-growth He$^+$ irradiation on the magneto-elastic properties of a $Ni$ /$Fe$ multi-layered stack. The progressive intermixing caused by He$^+$ irradiation at the interfaces of the multilayer allows us to tune the saturation magnetostriction value with increasing He$^+$ fluences, and even to induce a reversal of the sign

Audrey Duran, Gaspard Dussert, Carole Lartizien

To our knowledge, all deep computer-aided detection and diagnosis (CAD) systems for prostate cancer (PCa) detection consider bi-parametric magnetic resonance imaging (bp-MRI) only, including T2w and ADC sequences while excluding the 4D perfusion sequence,which is however part of standard clinical protocols for this diagnostic task. In this paper, we question

Yangyi Chen, Xu Ge, Wei Luo, Shiheng Liang

In contrast with rich investigations about the translation of an antiferromagnetic (AFM) texture, spin precession in an AFM texture is seldom concerned for lacking an effective driving method. In this work, however, we show that under an alternating spin-polarized current with spin along the AFM anisotropy axis, spin precession can be excited in an AFM DW. E

Julian Scheuer, Chao Xia

We prove quantitative versions for several results from geometric partial differential equations. Firstly, we obtain a double stability theorem for Serrin's overdetermined problem in spaceforms. Secondly, we prove stability theorems for Brendle's Heintze-Karcher inequality respectively constant mean curvature classification in a class of warped product space

Umberto Guarnotta, Roberto Livrea, Salvatore Angelo Marano

A short account of some recent existence, multiplicity, and uniqueness results for singular p-Laplacian problems either in bounded domains or in the whole space is performed, with a special attention to the case of convective reactions. An extensive bibliography is also provided.

Rahul Saini, Debajyoti Halder, Anand M. Baswade

With the advent of new IEEE 802.11ax (WiFi 6) devices, enabling security is a priority. Since previous versions were found to have security vulnerabilities, to fix the most common security flaws, the WiFi Protected Access 3 (WPA3) got introduced. Although WPA3 is an improvement over its predecessor in terms of security, recently it was found that WPA3 has a

Panu Lahti, Andrea Pinamonti, Xiaodan Zhou

We study a characterization of BV and Sobolev functions via nonlocal functionals in metric spaces equipped with a doubling measure and supporting a Poincar\'e inequality. Compared with previous works, we consider more general functionals. We also give a counterexample in the case $p=1$ demonstrating that unlike in Euclidean spaces, in metric measure spaces t

Debajyoti Halder, Saksham Bhushan, Gundu Shreya, Prashant Kumar

The growing demand for connecting with each other across the world has proved to be a boon to the growth of social media platforms. But when it comes to ensuring the privacy and security of the platform, the control is in hands of few monopolies. Some claim to provide a secure medium of communication but their exploitation of users and misusing users' data w

Christian Axler

In this paper, we give a new upper bound for the number $N_{\mathcal{R}}$ which is defined to be the smallest positive integer such that a certain inequality due to Ramanujan involving the prime counting function $\pi(x)$ holds for every $x \geq N_{\mathcal{R}}$.

Shunsuke C. Furuya, Katsuhiro Morita

We report that a spin-1/2 tetrahedral Heisenberg chain realizes a gapless symmetry-protected topological (gSPT) phase characterized by the coexistence of the Tomonaga-Luttinger-liquid criticality due to chirality degrees of freedom and the symmetry-protected edge state due to spin degrees of freedom. This gSPT phase has an interesting feature that no symmetr

Jacek Szczepkowski, Anna Grochola, Wlodzimierz Jastrzebski, Pawel Kowalczyk

Using the polarisation labelling spectroscopy, we performed the detailed analysis of the level structure of excited electronic states of the $^{39}$KCs molecule in the excitation energy interval between 17500~cm$^{-1}$ and 18600~cm$^{-1}$ above the $v=0$ level of the $X^1\Sigma^+$ ground state. We prove that the observed states are strongly coupled by spin-o

Soukaina Zayat

An equivalent directed version of the celebrated unresolved conjecture of Erdos and Hajnal proposed by Alon, Pack, and Solymosi states that for every tournament H there exists epsilon(H)>0 such that every H-free n-vertex tournament T contains a transitive subtournament of order at least n^(epsilon(H)). A tournament H has the strong EH-property if there exist

Yiqing Guo, Karel Mokany, Cindy Ong, Peyman Moghadam

Diversity of terrestrial plants plays a key role in maintaining a stable, healthy, and productive ecosystem. Though remote sensing has been seen as a promising and cost-effective proxy for estimating plant diversity, there is a lack of quantitative studies on how confidently plant diversity can be inferred from spaceborne hyperspectral data. In this study, w

Abdelkrim Moussaoui, Dany Nabab, Jean Velin

The paper deals with the existence of solutions for quasilinear elliptic systems involving singular and convection terms with variable exponents. Our approach combines the sub-supersolutions method and Schauder's fixed point theorem.

B. Lentjes, L. Spek, M. M. Bosschaert, Yu. A. Kuznetsov

In this paper we prove the existence of a periodic smooth finite-dimensional center manifold near a nonhyperbolic cycle in classical delay differential equations by using the Lyapunov-Perron method. The results are based on the rigorous functional analytic perturbation framework for dual semigroups (sun-star calculus). The generality of the dual perturbation

Rugang Geng, Adrian Mena, William J. Pappas, Dane R. McCamey

Quantum sensing and imaging of magnetic fields has attracted broad interests due to its potential for high sensitivity and spatial resolution. Common systems used for quantum sensing require either optical excitation (e.g., nitrogen-vacancy centres in diamond, atomic vapor magnetometers), or cryogenic temperatures (e.g., SQUIDs, superconducting qubits), whic

James Daniel Brandenburg, Zhangbu Xu, Wangmei Zha, Cheng Zhang

We study azimuthal asymmetries in diffractive J/$\psi$ production in ultraperipheral heavy-ion collisions at RHIC and LHC energies using the color glass condensate effective theory. Our calculation successfully describes azimuthal averaged $J/\psi$ production cross section measured by STAR and ALICE. We further predict very large $\cos 2\phi$ and $\cos 4\phi

Nadjat Amaouche, Maroua Sekhri, Rahma Zerimeche, Maamache Mustapha

We investigate in this paper time-dependent non-Hermitian Hamiltonians, which consist respectively of SU(1,1) and SU(2) generators. The former Hamiltonian is PT symmetric but the latter one is not. A time-dependent non-unitary operator is proposed to construct the non-Hermitian invariant, which is verified as pseudo-Hermitian with real eigenvalues. The exact

Andreas Karrenbauer, Kurt Mehlhorn, Pranabendu Misra, Paolo Luigi Rinaldi

Given a sequence of $n$ numbers and $k$ parallel First-in-First-Out (FIFO) queues, how close can one bring the sequence to sorted order? It is known that $k$ queues suffice to sort the sequence if the Longest Decreasing Subsequence (LDS) of the input sequence is at most $k$. But, what if the number of queues is too small for sorting completely? - We give a s

Ken Miyajima, Yuki Noguchi, Takayuki Yamada

In this paper, stress-constrained topology optimization is applied to the design of compliant displacement magnification mechanisms. By formulating the objective function based on the concept of effective energy, it is not necessary to place artificial spring components at the boundaries of the output and input ports as in previous methods. This makes it pos

Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon

This work studies operators mapping vector and scalar fields defined over a manifold $\mathcal{M}$, and which commute with its group of diffeomorphisms $\text{Diff}(\mathcal{M})$. We prove that in the case of scalar fields $L^p_\omega(\mathcal{M,\mathbb{R}})$, those operators correspond to point-wise non-linearities, recovering and extending known results on

Caroline Belser, Julie Poulain, Karine Labadie, Frederick Gavory

Coral reef science is a fast-growing field propelled by the need to better understand coral health and resilience to devise strategies to slow reef loss resulting from environmental stresses. Key to coral resilience are the symbiotic interactions established within a complex holobiont, i.e. the multipartite assemblages comprising the host coral organism, end

D. H. González-Buitrago, J. V. Hernández Santisteban, A. J. Barth, E. Jimenez-Bailón

We present a revised analysis of the photometric reverberation mapping campaign of the narrow-line Seyfert 1 galaxy PKS 0558-504 carried out with the Swift Observatory during 2008--2010. Previously, Gliozzi et al.\ found using the Discrete Correlation Function (DCF) method that the short-wavelength continuum variations lagged behind variations at longer wave

Guy Bunin, Laura Foini, Jorge Kurchan

The spectral form factor of quantum chaotic systems has the familiar `ramp $+$ plateau' form. Techniques to determine its form in the semiclassical or the thermodynamic limit have been devised, in both cases based on the average over an energy range or an ensemble of systems. For a single instance, fluctuations are large, do not go away in the limit, and dep

Morteza Aghaee, Arun Akkala, Zulfi Alam, Rizwan Ali

We present measurements and simulations of semiconductor-superconductor heterostructure devices that are consistent with the observation of topological superconductivity and Majorana zero modes. The devices are fabricated from high-mobility two-dimensional electron gases in which quasi-one-dimensional wires are defined by electrostatic gates. These devices e

Anatolii V. Tushev

In the paper we show that any irreducible representation of a finitely generated nilpotent group $G$ over a finitely generated field $F$ of characteristic zero is induced from a primitive representation of some subgroup of $G$.

Xiao-Kan Guo, Zhiqiang Huang

There are strong evidences in the literature that quantum non-Markovianity would hinder the presence of Quantum Darwinism. In this Letter, we study the relation between quantum Darwinism and approximate quantum Markovianity for open quantum systems by exploiting the properties of quantum conditional mutual information. We show that for approximately Markovia

Ismail Irmakci, Zeki Emre Unel, Nazli Ikizler-Cinbis, Ulas Bagci

In our comprehensive experiments and evaluations, we show that it is possible to generate multiple contrast (even all synthetically) and use synthetically generated images to train an image segmentation engine. We showed promising segmentation results tested on real multi-contrast MRI scans when delineating muscle, fat, bone and bone marrow, all trained on s

Jiazhen Lou, Hong Wen, Fuyu Lv, Jing Zhang

Recommender Systems (RS), as an efficient tool to discover users' interested items from a very large corpus, has attracted more and more attention from academia and industry. As the initial stage of RS, large-scale matching is fundamental yet challenging. A typical recipe is to learn user and item representations with a two-tower architecture and then calcul

Jinwei Lin

This paper has provided a novel design idea and some implementation methods to make a real time detection of multi-areas with multiple detecting areas that are generated by the real time drawing on the screen display of the video. The drawing on the video will remain the output as polylines, and the colors of the outlines will change when the stage of drawin

Yifan Zhang, Qijian Zhang, Zhiyu Zhu, Junhui Hou

The inherent ambiguity in ground-truth annotations of 3D bounding boxes, caused by occlusions, signal missing, or manual annotation errors, can confuse deep 3D object detectors during training, thus deteriorating detection accuracy. However, existing methods overlook such issues to some extent and treat the labels as deterministic. In this paper, we formulat

Thomas Berry, Alex Simpson, Matt Visser

Loosely inspired by the somewhat fanciful notion of detecting an arbitrarily advanced alien civilization, we consider a general-relativistic thin-shell Dyson mega-sphere completely enclosing a central star-like object, and perform a full general-relativistic analysis using the Israel--Lanczos--Sen junction conditions. We focus attention on the surface mass d

Shengjie Wang, Yuxue Cao, Xiang Zheng, Tao Zhang

Recent years have seen the emergence of non-cooperative objects in space, like failed satellites and space junk. These objects are usually operated or collected by free-float dual-arm space manipulators. Thanks to eliminating the difficulties of modeling and manual parameter-tuning, reinforcement learning (RL) methods have shown a more promising sign in the

Przemyslaw Joniak, Akiko Aizawa

Language model debiasing has emerged as an important field of study in the NLP community. Numerous debiasing techniques were proposed, but bias ablation remains an unaddressed issue. We demonstrate a novel framework for inspecting bias in pre-trained transformer-based language models via movement pruning. Given a model and a debiasing objective, our framewor

M. Frachet, P. W. Wiecki, T. Lacmann, S. M. Souliou

Electronic nematicity, the breaking of the crystal lattice rotational symmetry by the electronic fluid, is a fascinating quantum state of matter. Recently, BaNi$_2$As$_2$ has emerged as a promising candidate for a novel type of nematicity triggered by charge fluctuations. In this work, we scrutinize the electronic nematicity of BaNi$_2$(As$_{1-x}$P$_x$)$_2$

W. Yu, D. X. Rademacher, N. R. Valdez, M. A. Rodriguez

Dirac semimetals have attracted a great deal of current interest due to their potential applications in topological quantum computing, low-energy electronic applications, and single photon detection in the microwave frequency range. Herein are results from analyzing the low magnetic (B) field weak-antilocalization behaviors in a Dirac semimetal $Cd_{3}As_{2}

Jonathan Novak

The Berezin-Karpelevich integral is a double integral over unitary matrices which plays the role of the Itzykson-Zuber integral in rectangular matrix models. We obtain a topological expansion of the Berezin-Karpelevich integral in terms of monotone Hurwitz numbers, and obtain from this certain combinatorial identities.

M. Mackaay, V. Miemietz, P. Vaz

In this paper, we use Soergel calculus to define a monoidal functor, called the evaluation functor, from extended affine type A Soergel bimodules to the homotopy category of bounded complexes in finite type A Soergel bimodules. This functor categorifies the well-known evaluation homomorphism from the extended affine type A Hecke algebra to the finite type A

Jungyu Ahn, Sungwoo Park, Jiwoon Kim, Ju-hong Lee

Asset allocation using reinforcement learning has advantages such as flexibility in goal setting and utilization of various information. However, existing asset allocation methods do not consider the following viewpoints in solving the asset allocation problem. First, State design without considering portfolio management and financial market characteristics.