November 2022 arXiv papers — page 124

Kalyan Chakraborty, Shubham Gupta, Azizul Hoque

Let $d\equiv 2\pmod 4$ be a square-free integer such that $x^2 - dy^2 =- 1$ and $x^2 - dy^2 = 6$ are solvable in integers. We prove the existence of infinitely many quadruples in $\mathbb{Z}[\sqrt{d}]$ with the property $D(n)$ when $n \in \{(4m + 1) + 4k\sqrt{d}, (4m + 1) + (4k + 2)\sqrt{d}, (4m + 3) + 4k\sqrt{d}, (4m + 3) + (4k + 2)\sqrt{d}, (4m + 2) + (4k

Xiuqiao Xiang, Baochang Shi

Wall-driven flow in square cavity has been studied extensively, yet it is more frequently for the rectangular cavity flow occurring in practical problems, and some flow characteristics about rectangular cavity have not been fully investigated. As a promising numerical simulation tool, the Lattice Boltzmann Method (LBM) is employed to simulate the lid-driven

Rute Santos, Orfeu Bertolami, E. Castanho, P. Silva

AEROS aims to develop a nanosatellite as a precursor of a future system of systems, which will include assets and capabilities of both new and existing platforms operating in the Ocean and Space, equipped with state-of-the-art sensors and technologies, all connected through a communication network linked to a data gathering, processing and dissemination syst

Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs'ka, Xiang 'Anthony' Chen

There are many potential benefits to news readers accessing diverse sources. Modern news aggregators do the hard work of organizing the news, offering readers a plethora of source options, but choosing which source to read remains challenging. We propose a new framework to assist readers in identifying source differences and gaining an understanding of news

Monika Henzinger, Jalaj Upadhyay, Sarvagya Upadhyay

The first large-scale deployment of private federated learning uses differentially private counting in the continual release model as a subroutine (Google AI blog titled "Federated Learning with Formal Differential Privacy Guarantees"). In this case, a concrete bound on the error is very relevant to reduce the privacy parameter. The standard mechanism for co

Marco Fanizza, Yihui Quek, Matteo Rosati

We introduce a general statistical learning theory for processes that take as input a classical random variable and output a quantum state. Our setting is motivated by the practical situation in which one desires to learn a quantum process governed by classical parameters that are out of one's control. This framework is applicable, for example, to the study

Jaap Pedersen, Thi Thai Le, Thorsten Koch, Janina Zittel

Many energy-intensive industries, like the steel industry, plan to switch to renewable energy sources. Other industries, such as the cement industry, have to rely on carbon capture utilization and storage (CCUS) technologies to reduce their production processes' inevitable carbon dioxide (CO2) emissions. However, a new transport infrastructure needs to be es

Shinsuke Iwao, Kohei Motegi, Travis Scrimshaw

We give a presentation of refined (dual) canonical Grothendieck polynomials and their skew versions using free-fermions. Using this, we derive a number of identities, including the skew Cauchy identities, branching rules, expansion formulas, and integral formulas.

Tian-Yu Jing, Zi-Yan Han, Zhi-Hao He, Ming-Xin Shao

We systematically investigated the low-temperature transport properties of a series of NbN epitaxial films with thickness $t$ ranging from $\sim$2.0 to $\sim$4.0 nm. The films undergo a superconductor-insulator transition (SIT) with decreasing film thickness, and the critical sheet resistance for the SIT is close to the quantum resistance of Cooper pairs $h/

Sambatra Andrianomena, Francisco Villaescusa-Navarro, Sultan Hassan

We explore the possibility of using deep learning to generate multifield images from state-of-the-art hydrodynamic simulations of the CAMELS project. We use a generative adversarial network to generate images with three different channels that represent gas density (Mgas), neutral hydrogen density (HI), and magnetic field amplitudes (B). The quality of each

Sebin Varghese, Jake Dudley Mehew, Alexander Block, David Saleta Reig

Diffusion is one of the most ubiquitous transport phenomena in nature. Experimentally, it can be tracked by following point spreading in space and time. Here, we introduce a spatiotemporal pump-probe microscopy technique that exploits the residual spatial temperature profile obtained through the transient reflectivity when probe pulses arrive before pump pul

Karel Zimmermann

We present a conceptually simple and intuitive method to calculate and to measure the dissimilarities among 2D shapes. Several methods to interpret and to visualize the resulting dissimilarity matrix are presented and compared.

R. C. Bastidas Briceño, V. I. Fernandez, R. E. Alonso

In the search for new renewable energy to replace fossil fuels, Hydrogen is one of the most promising candidates for clean energy production. But cheap Hydrogen separation and storage is still a big challenge. Photoelectrochemical devices look promising for the decomposition of the water molecule into $2H_2+O_2$. Every day new materials and combinations are

Diego Martin Arroyo, Alessio Tonioni, Federico Tombari

Current methods for image-to-image translation produce compelling results, however, the applied transformation is difficult to control, since existing mechanisms are often limited and non-intuitive. We propose ParGAN, a generalization of the cycle-consistent GAN framework to learn image transformations with simple and intuitive controls. The proposed generat

Zhuoyu Li, Camille Petri, James Howard, Graham Cole

Background: Increased pericardial adipose tissue (PAT) is associated with many types of cardiovascular disease (CVD). Although cardiac magnetic resonance images (CMRI) are often acquired in patients with CVD, there are currently no tools to automatically identify and quantify PAT from CMRI. The aim of this study was to create a neural network to segment PAT

Michal Dory, Mohsen Ghaffari

The minimum-cost $k$-edge-connected spanning subgraph ($k$-ECSS) problem is a generalization and strengthening of the well-studied minimum-cost spanning tree (MST) problem. While the round complexity of distributedly computing the latter has been well-understood, the former remains mostly open, especially as soon as $k\geq 3$. In this paper, we present the f

Andrea Eirale, Mauro Martini, Marcello Chiaberge

Robot assistants are emerging as high-tech solutions to support people in everyday life. Following and assisting the user in the domestic environment requires flexible mobility to safely move in cluttered spaces. We introduce a new approach to person following for assistance and monitoring. Our methodology exploits an omnidirectional robotic platform to deta

John R. Klein, Cary Malkiewich, Maxime Ramzi

In this short paper, we give two proofs that the Euler characteristic is multiplicative, for fiber sequences of finitely dominated spaces. This is equivalent to proving that the Becker-Gottlieb transfer is functorial on $\pi_0$.

Ralph A. M. J. Wijers, Koen H. Kuijken, Michael W. Wise

This document describes the Netherlands' decadal strategic planning process for the current decade. We give the scientific rationale for our prioritization of research areas and the facility choices that follow from our scientific priorities. We also describe actions needed for the sustainability of our community and our work, and the budgets needed to fulfi

Yue Song, Rui Yin, Yiqian He, Benrong Mu

In this paper, we investigated the chaos of the phantom AdS black hole in near-horizon regions and at a certain distance from the black hole, where the Lyapunov exponent was calculated by the Jacobian determinant. We found that the angular momenta of charged particles nearby the black hole affect the position of the equilibrium orbit as well as the Lyapunov

Jordan Aiko Deja

The task of learning the piano has been a centuries-old challenge for novices, experts and technologists. Several innovations have been introduced to support proper posture, movement, and motivation, while sight-reading and improvisation remain the least-explored areas. In this PhD, we address this gap by redesigning the piano augmentation as an interactive

Yuyang Miao, Yao Xu, Danilo Mandic

Predicting metro passenger flow precisely is of great importance for dynamic traffic planning. Deep learning algorithms have been widely applied due to their robust performance in modelling non-linear systems. However, traditional deep learning algorithms completely discard the inherent graph structure within the metro system. Graph-based deep learning algor

Vishnu Dutt Sharma, John P. Dickerson, Pratap Tokekar

Green Security Games with real-time information (GSG-I) add the real-time information about the agents' movement to the typical GSG formulation. Prior works on GSG-I have used deep reinforcement learning (DRL) to learn the best policy for the agent in such an environment without any need to store the huge number of state representations for GSG-I. However, t

Nikita Koval, Dan Alistarh, Roman Elizarov

Asynchronous programming has gained significant popularity over the last decade: support for this programming pattern is available in many popular languages via libraries and native language implementations, typically in the form of coroutines or the async/await construct. Instead of programming via shared memory, this concept assumes implicit synchronizatio

Benedikt Hartl, Marek Mihalkovič, Ladislav Šamaj, Martial Mazars

We have re-analysed the rich plethora of ground state configurations of the asymmetric Wigner bilayer system that we had recently published in a related diagram of states [M. Antlanger \textit{et al.}, Phys. Rev. Lett. \textbf{117}, 118002 (2016)], comprising roughly 60~000 state points in the phase space spanned by the distance between the plates and the ch

Mateo Neira, Roberto Murcio

Streets networks provide an invaluable source of information about the different temporal and spatial patterns emerging in our cities. These streets are often represented as graphs where intersections are modelled as nodes and streets as links between them. Previous work has shown that raster representations of the original data can be created through a lear

Dana Abou Ali

Let $f$ be a Petersson normalized Hecke-Maass cusp form with spectral parameter $t\geq 2$ and let $\mathcal{C}_{D}$ be the union of closed geodesics in $\text{Sl}_{2}(\mathbb{Z})\setminus \mathbb{H}$ associated to a fundamental discriminant $D>0$. Following a suggestion by Sarnak in his letter to Reznikov, we express the restriction norm $||f|_{\mathcal{C}_{

Meng K. Ma, Chengyu Wang, Y. J. Chung, L. N. Pfeiffer

In a low-disorder two-dimensional electron system, when two Landau levels of opposite spin or pseudospin cross at the Fermi level, the dominance of the exchange energy can lead to a ferromagnetic, quantum Hall ground state whose gap is determined by the exchange energy and has skyrmions as its excitations. This is normally achieved via applying either hydros

Talya Eden, Shyam Narayanan, Jakub Tětek

Sampling edges from a graph in sublinear time is a fundamental problem and a powerful subroutine for designing sublinear-time algorithms. Suppose we have access to the vertices of the graph and know a constant-factor approximation to the number of edges. An algorithm for pointwise $\varepsilon$-approximate edge sampling with complexity $O(n/\sqrt{\varepsilon

Adrian Shuai Li, Reihaneh Safavi-Naini, Philip W. L. Fong

Controlled sharing is fundamental to distributed systems. We consider a capability-based distributed authorization system where a client receives capabilities (access tokens) from an authorization server to access the resources of resource servers. Capability-based authorization systems have been widely used on the Web, in mobile applications and other distr

Kristian Fenech, Ádám Fodor, Sean P. Bergeron, Rachid R. Saboundji

Dyadic and small group collaboration is an evolutionary advantageous behaviour and the need for such collaboration is a regular occurrence in day to day life. In this paper we estimate the perceived personality traits of individuals in dyadic and small groups over thin-slices of interaction on four multimodal datasets. We find that our transformer based pred

Ang Li, Gao-Chan Yong, Ying-Xun Zhang

We demonstrate the consistency of the quark deconfinement phase transition parameters in the beta-stable neutron star matter and in the nearly symmetric nuclear matter formed in heavy-ion collisions (HICs). We investigate the proton and $\Lambda$ flow in Au+Au collisions at 3 and 4.5 GeV/nucleon incident beam energies with the pure hadron cascade version of

Khang Hoang

This chapter illustrates the use of defect physics as a conceptual and theoretical framework for understanding and designing battery materials. It starts with a methodology for first-principles studies of defects in complex transition-metal oxides. The chapter then considers defects that are activated in a cathode material during synthesis, during measuremen

Emin Nakilcioglu, Anisa Rizvanolli und Olaf Rendel

Purpose: Traffic volume in empty container depots has been highly volatile due to external factors. Forecasting the expected container truck traffic along with having a dynamic module to foresee the future workload plays a critical role in improving the work efficiency. This paper studies the relevant literature and designs a forecasting model addressing the

D. Angerhausen, M. Ottiger, F. Dannert, Y. Miguel

Phosphine could be a key molecule in the understanding of exotic chemistry happening in (exo)planetary atmospheres. While it has been detected in the Solar System's giant planets, it has not been observed in exoplanets yet. In the exoplanetary context however it has been theorized as a potential biosignature molecule. The goal of our study is to identify whi

Andrew Wagenmaker, Aldo Pacchiano

Two central paradigms have emerged in the reinforcement learning (RL) community: online RL and offline RL. In the online RL setting, the agent has no prior knowledge of the environment, and must interact with it in order to find an $\epsilon$-optimal policy. In the offline RL setting, the learner instead has access to a fixed dataset to learn from, but is un

Zhiqi Bu

Adversarial perturbation plays a significant role in the field of adversarial robustness, which solves a maximization problem over the input data. We show that the backward propagation of such optimization can accelerate $2\times$ (and thus the overall optimization including the forward propagation can accelerate $1.5\times$), without any utility drop, if we

Yutaro Ishida, Sansei Hori, Yuichiro Tanaka, Yuma Yoshimoto

Our team, Hibikino-Musashi@Home (the shortened name is HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. We have participated in the RoboCup@Home Japan open competition open platform league every year since 2010. Moreover, we participated in the RoboCup 2017 Nagoya as open platform league and domestic standard platfor

Michele Cafagna, Kees van Deemter, Albert Gatt

Image captioning models tend to describe images in an object-centric way, emphasising visible objects. But image descriptions can also abstract away from objects and describe the type of scene depicted. In this paper, we explore the potential of a state-of-the-art Vision and Language model, VinVL, to caption images at the scene level using (1) a novel datase

Cuimei Cao, Shiwei Chen, Rui-Chun Xiao, Zengtai Zhu

Cubic materials host high crystal symmetry and hence are not expected to support anisotropy in transport phenomena. In contrast to this common expectation, here we report an anomalous anisotropy of spin current can emerge in the (001) film of Mn${_3}$Pt, a noncollinear antiferromagnetic spin source with face-centered cubic structure. Such spin current anisot

Nicolás F. Del Grosso, Fernando C. Lombardo, Francisco D. Mazzitelli, Paula I. Villar

The development of quantum technologies present important challenges such as the need for fast and precise protocols for implementing quantum operations. Shortcuts to adiabaticity (STA) are a powerful tool for achieving these goals, as they enable us to perform an exactly adiabatic evolution in finite time. In this paper we present a shortcut to adiabaticity

Y. Wu, Yu Gao, Jun-Feng Wang

We identify and investigate a possible correlation between the $\rm{[CII]} 158{\mu}m$ luminosity and linewidth in the $\rm{[CII]}$-detected galaxies. Observationally, the strength of the $\rm{[CII]} 158{\mu}m$ emission line is usually stronger than that of the CO emission line and this $\rm{[CII]}$ line has been used as another tracer of the galactic charact

M. Mittag, K. -P. Schröder, V. Perdelwitz, D. Jack

The so-called great dimming event of alpha Ori in late 2019 and early 2020 sparked our interest in the behaviour of chromospheric activity during this period. To study the timeline of chromospheric activity, we derive a S_MWO time series of TIGRE and Mount Wilson values, and we compare this long time series with photometric data from the AAVSO database. In a

Andrew Frigyik

With the rapid development of quantum computers the currently secure cryptographic protocols may not stay that way. Quantum mechanics provides means to create an inherently secure communication channel that is protected by the laws of physics and not by the computational hardness of certain mathematical problems. This paper is a non-technical overview of qua

Charles Moussa, Max Hunter Gordon, Michal Baczyk, M. Cerezo

Quantum-enhanced data science, also known as quantum machine learning (QML), is of growing interest as an application of near-term quantum computers. Variational QML algorithms have the potential to solve practical problems on real hardware, particularly when involving quantum data. However, training these algorithms can be challenging and calls for tailored

Yew Lee Tan, Adams Wai-kin Kong, Jung-Jae Kim

Scene text recognition (STR) involves the task of reading text in cropped images of natural scenes. Conventional models in STR employ convolutional neural network (CNN) followed by recurrent neural network in an encoder-decoder framework. In recent times, the transformer architecture is being widely adopted in STR as it shows strong capability in capturing l

Xiaojian Lu

The higher APR tilting modules and higher BB tilting modules were introduced and studied in higher Auslander-Reiten theory. Our objective is to consider these tilting modules by the corresponding simple modules, and show that the tensor product of higher APR (BB) tilting modules is a higher APR (BB) tilting module.

Andrew Weng, Sravan Pannala, Jason B. Siegel, Anna G. Stefanopoulou

In this work, we derive analytical expressions governing state-of-charge and current imbalance dynamics for two parallel-connected batteries. The model, based on equivalent circuits and an affine open circuit voltage relation, describes the evolution of state-of-charge and current imbalance over the course of a complete charge and discharge cycle. Using this

Toshinori Shimizu, Taichi Uyama, Yasunori Hori, Motohide Tamura

Giant planets around young stars serve as a clue to unveiling their formation history and orbital evolution. CI Tau is a 2\,Myr-old classical T-Tauri star hosting an eccentric hot Jupiter, CI Tau\,b. The standard formation scenario of a hot Jupiter predicts that planets formed further out and migrated inward. A high eccentricity of CI Tau b may be suggestive

Nicholas Kissel, Jing Lei

We derive high-dimensional Gaussian comparison results for the standard $V$-fold cross-validated risk estimates. Our results combine a recent stability-based argument for the low-dimensional central limit theorem of cross-validation with the high-dimensional Gaussian comparison framework for sums of independent random variables. These results give new insigh

G. A. Ramírez, W. Román Acevedo, M. Rengifo, J. M. Nuñez

In this work, we have investigated the coexistance of volatile and non-volatile memristive effects in epitaxial phase-separated La$_{\text{0.5}}$Ca$_{\text{0.5}}$MnO$_{3}$ thin films. At low temperatures (50 K), we observed volatile resistive changes arising from self-heating effects in the vicinity of a metal-to-insulator transition. At higher temperatures

David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic

An effective aggregation of node features into a graph-level representation via readout functions is an essential step in numerous learning tasks involving graph neural networks. Typically, readouts are simple and non-adaptive functions designed such that the resulting hypothesis space is permutation invariant. Prior work on deep sets indicates that such rea

Kyoung-Woong Moon, Jungbum Yoon, Changsoo Kim, Jae-Hun Sim

A moving magnetic skyrmion exhibits transverse deflection. This so-called skyrmion Hall effect has been explained by the Thiele equation. Here, we provide an alternative interpretation of the skyrmion Hall effect based on the dynamics of domain walls enclosing the skyrmion. We relate the spin-torque-induced local rotation of the domain wall segments to the s

Mikhail Zaidenberg

It is known that every Fano-Mukai fourfold X of genus 10 is acted upon by an involution $\tau$ which comes from the center of the Weyl group of the simple algebraic group of type ${\rm G}_2$. This involution is uniquely defined up to conjugation in the group Aut(X). In this note we describe the set of fixed points of $\tau$ and the surface scroll swept out b

Karyn Le Hur, Sariah Al Saati

Graphene is a two-dimensional Dirac semimetal showing interesting properties as a result of its dispersion relation with both quasiparticles and quasiholes or matter and anti-matter. We introduce a topological nodal ring semimetal in graphene with a quantized quantum Hall response, a robust one-dimensional chiral edge mode and a quadratic Fermi-liquid spectr

Pepa Atanasova

A major concern of Machine Learning (ML) models is their opacity. They are deployed in an increasing number of applications where they often operate as black boxes that do not provide explanations for their predictions. Among others, the potential harms associated with the lack of understanding of the models' rationales include privacy violations, adversaria

Hoang Ky Nguyen

In violation of the generalized Lichnerowicz theorem advocated by Nelson and others, quadratic gravity admits vacua with non-constant scalar curvature. In a recent publication [Phys. Rev. D 106, 104004 (2022)], we revitalized a program that Buchdahl originated but prematurely abandoned circa 1962 [Nuovo Cimento 23, 141 (1962)], and uncovered a novel exhausti

Xuda Ding, Han Wang, Yi Ren, Yu Zheng

Designing safety-critical control for robotic manipulators is challenging, especially in a cluttered environment. First, the actual trajectory of a manipulator might deviate from the planned one due to the complex collision environments and non-trivial dynamics, leading to collision; Second, the feasible space for the manipulator is hard to obtain since the

Yujie Xing, Jon Atle Gulla

Despite the rapid progress of open-domain generation-based conversational agents, most deployed systems treat dialogue contexts as single-turns, while systems dealing with multi-turn contexts are less studied. There is a lack of a reliable metric for evaluating multi-turn modelling, as well as an effective solution for improving it. In this paper, we focus o

Jurek Leonhardt, Marcel Jahnke, Avishek Anand

Dual-encoder-based neural retrieval models achieve appreciable performance and complement traditional lexical retrievers well due to their semantic matching capabilities, which makes them a common choice for hybrid IR systems. However, these models exhibit a performance bottleneck in the online query encoding step, as the corresponding query encoders are usu

Shi-Ping He

In minimal leptoquark (LQ) models, the $R_2$ and $S_1$ can be the solution to the $(g-2)_{\mu}$ anomaly because of the chiral enhancements. Here, we study the LQ and vectorlike quark (VLQ) extended models. In the one LQ and one VLQ extended models, the $(g-2)_{\mu}$ can receive the contributions from top and top partner $T$ because of the $t-T$ mixing. Besid

Li Wang, Qiang Xu

Concerned with elliptic operators with stationary random coefficients of integrable correlations and bounded Lipschitz domains, arising from stochastic homogenization theory, this paper is mainly devoted to studying Calder\'on-Zygmund estimates. As an application, we obtain the homogenization error in the sense of oscillation and fluctuation, respectively. T

Zhaolin Li, Jan Niehues

When building state-of-the-art speech translation models, the need for large computational resources is a significant obstacle due to the large training data size and complex models. The availability of pre-trained models is a promising opportunity to build strong speech translation systems efficiently. In a first step, we investigate efficient strategies to

Julien Clément, Antoine Genitrini

For three decades binary decision diagrams, a data structure efficiently representing Boolean functions, have been widely used in many distinct contexts like model verification, machine learning, cryptography and also resolution of combinatorial problems. The most famous variant, called reduced ordered binary decision diagram (ROBDD for short), can be viewed

Rose-Marie Baland, Aurélien Hees, Marie Yseboodt, Adrien Bourgoin

Context: The orientation and rotation of Mars, which can be described by a set of Euler angles, is estimated from radioscience data and is then used to infer Mars internal properties. The data are analyzed using a modeling expressed within the Barycentric Celestial Reference System (BCRS). Aims: We provide new and more accurate (to the $0.1$ mas level) estim

Sarah Koppensteiner, Jordy Timo van Velthoven, Felix Voigtlaender

This paper provides a classification theorem for expansive matrices $A \in \mathrm{GL}(d, \mathbb{R})$ generating the same anisotropic homogeneous Triebel-Lizorkin space $\dot{\mathbf{F}}^{\alpha}_{p, q}(A)$ for $\alpha \in \mathbb{R}$ and $p,q \in (0,\infty]$. It is shown that $\dot{\mathbf{F}}^{\alpha}_{p, q}(A) = \dot{\mathbf{F}}^{\alpha}_{p, q}(B)$ if an

B. Bugeat, P. C. Boldini, A. M. Hasan, R. Pecnik

This paper addresses the stability of plane Couette flow in the presence of strong density and viscosity stratifications. It demonstrates the existence of a generalised inflection point that satisfies the generalised Fjortoft's criterion of instability when a minimum of kinematic viscosity is present in the base flow. The characteristic scales associated wit

Neelesh K Shukla, Msp Raja, Raghu Katikeri, Amit Vaid

Business documents come in a variety of structures, formats and information needs which makes information extraction a challenging task. Due to these variations, having a document generic model which can work well across all types of documents and for all the use cases seems far-fetched. For document-specific models, we would need customized document-specifi

Takahiko Masuda, Ayami Hiramoto, Daniel G. Ang, Cole Meisenhelder

The application of silicon photomultiplier (SiPM) technology for weak-light detection at a single photon level has expanded thanks to its better photon detection efficiency in comparison to a conventional photomultiplier tube (PMT). SiPMs with large detection area have recently become commercially available, enabling applications where the photon flux is low

Michael A. DuVernois, Giuseppe Di Sciascio

The fields of cosmic ray astrophysics, gamma-ray astrophysics, and neutrino astrophysics have diverged somewhat. But for the air showers in the GeV and TeV energy ranges, the ground-based detector techniques have considerable overlaps. VHE gamma-ray astronomy is the observational study measuring the directions, flux, energy spectra, and time variability of t

Hesameddin Khosravi, Suyi Li

This study investigates the programming of elastic wave propagation bandgaps in a kirigami material by intentionally sequencing its constitutive mechanical bits. Such sequencing exploits the multi-stable nature of the stretched kirigami, allowing each mechanical bit to switch between two stable equilibria with different external shapes (aka. "(0)" and "(1)"

Jinghan Jia, Mingyi Hong, Yimeng Zhang, Mehmet Akçakaya

Although deep learning (DL) has received much attention in accelerated magnetic resonance imaging (MRI), recent studies show that tiny input perturbations may lead to instabilities of DL-based MRI reconstruction models. However, the approaches of robustifying these models are underdeveloped. Compared to image classification, it could be much more challenging

David Kofroň, Petr Kotlařík

We provide an explicit, closed and compact expression for the Debye superpotential of a circular source. This superpotential is obtained by integrating the Green function of Teukolsky Master Equation (TME). The Debye potential itself is then, for a particular configuration, calculated in the same manner as the $\phi_0$ field component is calculated from the

Tassilo Klein, Moin Nabi

This paper presents miCSE, a mutual information-based contrastive learning framework that significantly advances the state-of-the-art in few-shot sentence embedding. The proposed approach imposes alignment between the attention pattern of different views during contrastive learning. Learning sentence embeddings with miCSE entails enforcing the structural con

Hanwei Zhu, Baoliang Chen, Lingyu Zhu, Shiqi Wang

ImageNet pre-trained deep neural networks (DNNs) show notable transferability for building effective image quality assessment (IQA) models. Such a remarkable byproduct has often been identified as an emergent property in previous studies. In this work, we attribute such capability to the intrinsic texture-sensitive characteristic that classifies images using

Sajith Rajapaksa, Farzad Khalvati

Deep learning techniques have greatly benefited computer-aided diagnostic systems. However, unlike other fields, in medical imaging, acquiring large fine-grained annotated datasets such as 3D tumour segmentation is challenging due to the high cost of manual annotation and privacy regulations. This has given interest to weakly-supervise methods to utilize the

A. Galoyan, V. Grichine, A. Ribon, V. Uzhinsky

It is expected that charmed particles will be copiously produced at Future Circular Collider (FCC). Due to relatively large life-time of the particles, it will be needed to account their interactions with surrounded materials and detector's materials. In order to satisfy the requirements, charmed particle production in soft interactions has been implemented

Salvatore Fara, Orlaith Hickey, Alexandra Georgescu, Stefano Goria

Predicting the presence of major depressive disorder (MDD) using behavioural and cognitive signals is a highly non-trivial task. The heterogeneous clinical profile of MDD means that any given speech, facial expression and/or observed cognitive pattern may be associated with a unique combination of depressive symptoms. Conventional discriminative machine lear

Runmin Liu, Defeng Zou, Shuang Niu, Youjian Song

Collision refers to a striking nonlinear interaction in dissipative systems, revealing the particle-like properties of solitons. In dual-wavelength mode-locked fiber lasers, collisions are inherent and periodic. However, how collisions influence the dynamical transitions in the dual-wavelength mode-locked state has still not been explored. In our research, d

Jannik Matuschke

Given a set system $(E, \mathcal{P})$ with $\rho \in [0, 1]^E$ and $\pi \in [0,1]^{ \mathcal{P}}$, our goal is to find a probability distribution for a random set $S \subseteq E$ such that $\operatorname{Pr}[e \in S] = \rho_e$ for all $e \in E$ and $\operatorname{Pr}[P \cap S \neq \emptyset] \geq \pi_P$ for all $P \in \mathcal{P}$. We extend the results of D

Armin Goudarzi

This paper presents an alternative energy function for Global Optimization (GO) beamforming, tailored to acoustic broadband sources. Given, that properties such as the source location, multipole rotation, or flow conditions are parameterized over the frequency, a CSM-fitting can be performed for all frequencies at once. A numerical analysis shows that the no

Chengxu Yang, Ralf Klasing, Yaping Mao, Xingchao Deng

Foucaud et al. [Discrete Appl. Math. 319 (2022), 424-438] recently introduced and initiated the study of a new graph-theoretic concept in the area of network monitoring. For a set $M$ of vertices and an edge $e$ of a graph $G$, let $P(M, e)$ be the set of pairs $(x, y)$ with a vertex $x$ of $M$ and a vertex $y$ of $V(G)$ such that $d_G(x, y)\neq d_{G-e}(x, y

Jader E. Brasil, Elismar R. Oliveira, Rafael Rigão Souza

This paper introduces a theory of Thermodynamic Formalism for Iterated Function Systems with Measures (IFSm). We study the spectral properties of the Transfer and Markov operators associated to a IFSm. We introduce variational formulations for the topological entropy of holonomic measures and the topological pressure of IFSm given by a potential. A definitio

Rafail Kartsioukas, Rajat Tandon, Zheng Gao, Jelena Mirkovic

Network operators and system administrators are increasingly overwhelmed with incessant cyber-security threats ranging from malicious network reconnaissance to attacks such as distributed denial of service and data breaches. A large number of these attacks could be prevented if the network operators were better equipped with threat intelligence information t

Thibault D. Décoppet

We prove that the Drinfeld center of a fusion 2-category is invariant under Morita equivalence. We go on to show that the concept of Morita equivalence between connected fusion 2-categories recovers exactly the notion of Witt equivalence between braided fusion 1-categories. A strongly fusion 2-category is a fusion 2-category whose braided fusion 1-category o

Tomasz Sowiński

We point out that argumentation presented in [Phys. Lett. A 417, 127699 (2021)], leading to the conclusion that in periodic systems there is a superselection principle forbidding two different Bloch states to form a coherent superposition of a fixed phase, is unjustified and false. As an example, we show that the operator projecting to the selected Wannier s

Awad Abdelhalim, Daniela Shuman, Anson F Stewart, Kayleigh B Campbell

There are substantial differences in travel behavior by gender on public transit. Studies have concluded that these differences are largely attributable to household responsibilities typically falling disproportionately on women, leading to women being more likely to utilize transit for purposes referred to by the umbrella concept of "mobility of care". In c

Jean-Luc Baril, Sergey Kirgizov, Rémi Maréchal, Vincent Vajnovszki

Grand Dyck paths with air pockets (GDAP) are a generalization of Dyck paths with air pockets by allowing them to go below the $x$-axis. We present enumerative results on GDAP (or their prefixes) subject to various restrictions such as maximal/minimal height, ordinate of the last point and particular first return decomposition. In some special cases we give b

Marc Betoule, Sarah Antier, Emmanuel Bertin, Pierre Éric Blanc

The Hubble diagram of type-Ia supernovae (SNe-Ia) provides cosmological constraints on the nature of dark energy with an accuracy limited by the flux calibration of currently available spectrophotometric standards. The StarDICE experiment aims at establishing a 5-stage metrology chain from NIST photodiodes to stars, with a targeted accuracy of \SI{1}{mmag} i

Sahar Borzooei, Victorita Dolean, Pierre-Henri Tournier, Claire Migliaccio

Numerical discretization of the large-scale Maxwell's equations leads to an ill-conditioned linear system that is challenging to solve. The key requirement for successive solutions of this linear system is to choose an efficient solver. In this work we use Perfectly Matched Layers (PML) to increase this efficiency. PML have been widely used to truncate numer

Qing-Hua Shen, Ju-Jun Xie

The three-body $\eta K^*\bar{K}^*$, $\pi K^*\bar{K}^*$ and $KK^*\bar{K}^*$ systems are investigated within the framework of fixed-center approximation to the Faddeev equations, where $K^*\bar{K}^*$ is treated as the scalar meson $f_0(1710)$. The interactions between $\pi$, $\eta$, $K$ and $K^*$ are taking from the chiral unitary approach. By scattering the $

Esmaeil Taghizadeh Sisakht, Farhad Fazileh, S. Javad Hashemifar, Francois M. Peeters

Two-dimensional gapped semi-Dirac (GSD) materials are systems with a finite band gap that their charge carriers behave relativistically in one direction and Schr\"odinger-like in the other. In the present work, we show that besides the two well-known energy bands features (curvature and chirality), the band-gap parameter also play a crucial role in the index

Francesco Sartini

This thesis is dedicated to the study of symmetries in reduced models of gravity, with some frozen degrees of freedom. We focus on the minisuperspace reduction whith a finite number of degrees of freedom. Minisuperspaces are treated as mechanical models, evolving in one spacetime direction. This evolution parameter represents the orthogonal coordinate to the

Ivan Svogor, Christian Eichenberger, Markus Spanring, Moritz Neun

A growing number of Machine Learning Frameworks recently made Deep Learning accessible to a wider audience of engineers, scientists, and practitioners, by allowing straightforward use of complex neural network architectures and algorithms. However, since deep learning is rapidly evolving, not only through theoretical advancements but also with respect to har

Matteo Longo, Stefano Vigni

Assuming specific instances of two general conjectures in arithmetic algebraic geometry (bijectivity of $p$-adic regulator maps, injectivity of $p$-adic Abel-Jacobi maps), we prove several cases of the $p$-part of the Tamagawa number conjecture ($p$-TNC) of Bloch-Kato and Fontaine-Perrin-Riou for (homological) motives of modular forms of even weight $\geq4$

Bartosz Rzepkowski, Katarzyna Roszak

We study a decoherence reduction scheme that involves an intermediate measurement on the qubit in an equal superposition basis, in the general framework of all qubit-environment interactions that lead to qubit pure decoherence. We show under what circumstances the scheme always leads to a gain of coherence on average, regardless of the time at which the meas

Hardy Hardy, Miguel Ballesteros, Faisal Ladhak, Muhammad Khalifa

Summarizing novel chapters is a difficult task due to the input length and the fact that sentences that appear in the desired summaries draw content from multiple places throughout the chapter. We present a pipelined extractive-abstractive approach where the extractive step filters the content that is passed to the abstractive component. Extremely lengthy in

V. M. Braun, Yao Ji, A. N. Manashov

Using the recent results on the contributions of descendants of the leading twist operators to the operator product expansion of two electromagnetic currents we derive explicit expressions for the kinematic finite-$t$ and target mass corrections to the DVCS helicity amplitudes to the $1/Q^4$ power accuracy. The cancellation of IR divergences for kinematic co

Bo Dong, Wei Wang

In this paper, numerical experiments are carried out to investigate the impact of penalty parameters in the numerical traces on the resonance errors of high order multiscale discontinuous Galerkin (DG) methods [6, 7] for one-dimensional stationary Schr\"{o}dinger equation. Previous work showed that penalty parameters were required to be positive in error ana

Yu Ji, Chang-Wang Lian, Yin Shi, Rui Yan

We propose a new way of axial magnetic fields generation in a non-relativistic laser intensity regime by using a twisted light carrying orbital angular momentum (OAM) to stimulate two-plasmon decay (TPD) in a plasma. The growth of TPD driven by an OAM light in a Laguerre-Gauss (LG) mode is investigated through three dimensional fluid simulations and theory.