May 2022 arXiv papers — page 41

K. Chandrasekran, D. J. Prabhakaran

We consider the integral operator $\mathcal{I}^{a,b,c}_{d,e}(f)(z)$ involving Clausen's Hypergeometric Function by means of convolution introduced by Chandrasekran and Prabhakaran for investigation. The conditions on the parameters $ a,b, c$ are determined using the integral operator $\mathcal{I}^{a,\frac{b}{2},\frac{b+1}{2}}_{\frac{c}{2}, \frac{c+1}{2}}(f)(

Sophie Kriz

The purpose of this paper is mainly to record how certain homotopy-theoretical constructions on ordinary G-equivariant cohomology spectra HM for a Mackey functor M, in particular products and duality, can be described on chain level. We will also discuss certain facts about modules over the constant Green functor $\underline{\mathbb{Z}}$.

Aishwarya Agrawal, Ivana Kajić, Emanuele Bugliarello, Elnaz Davoodi

Vision-and-language (V&L) models pretrained on large-scale multimodal data have demonstrated strong performance on various tasks such as image captioning and visual question answering (VQA). The quality of such models is commonly assessed by measuring their performance on unseen data that typically comes from the same distribution as the training data. Howev

Yongliang Ou, Yuji Ikeda, Oliver Clemens, Blazej Grabowski

The impact of ordered vacancies on the dynamic stability of perovskites is investigated under the $\textit{ab initio}$ framework with a focus on cubic BaFeO$_{3}$ ($Pm\bar{3}m$) and vacancy-ordered monoclinic BaFeO$_{2.67}$ ($P2_{1}/m$). The harmonic approximation shows that both structures are dynamically unstable at 0 K. For the monoclinic structure, the i

Yao Xiao, Carlos Cardenas, Dong Joo Rhee, Tucker Netherton

In this work, we developed and evaluated a novel pipeline consisting of two landmark-based field aperture generation approaches for WBRT treatment planning; they are fully automated and customizable. The automation pipeline is beneficial for both clinicians and patients, where we can reduce clinician workload and reduce treatment planning time. The customiza

R. Alfaro, C. Alvarez, J. D. Álvarez, J. R. Angeles Camacho

The High Altitude Water Cherenkov (HAWC) gamma-ray observatory observes atmospheric showers produced by incident gamma rays and cosmic rays with energy from 300 GeV to more than 100 TeV. A crucial phase in analyzing gamma-ray sources using ground-based gamma-ray detectors like HAWC is to identify the showers produced by gamma rays or hadrons. The HAWC observ

Gouranga Charan, Andrew Hredzak, Christian Stoddard, Benjamin Berrey

Millimeter-wave (mmWave) and terahertz (THz) communication systems typically deploy large antenna arrays to guarantee sufficient receive signal power. The beam training overhead associated with these arrays, however, make it hard for these systems to support highly-mobile applications such as drone communication. To overcome this challenge, this paper propos

Xueying Bai, Jinghuan Shang, Yifan Sun, Niranjan Balasubramanian

Continual learning aims to sequentially learn new tasks without forgetting previous tasks' knowledge (catastrophic forgetting). One factor that can cause forgetting is the interference between the gradients on losses from different tasks. When the gradients on the current task's loss are in opposing directions to those on previous tasks' losses, updating the

Erin Munro Krull, Christoph Börgers

Gap junctions are channels in cell membranes allowing ions to pass directly between cells. They connect cells throughout the body, including heart myocytes, neurons, and astrocytes. Propagation mediated by gap junctions can be passive or active. In passive propagation, the membrane potential of one cell influences that of neighboring cells without triggering

Harley Wiltzer, David Meger, Marc G. Bellemare

Continuous-time reinforcement learning offers an appealing formalism for describing control problems in which the passage of time is not naturally divided into discrete increments. Here we consider the problem of predicting the distribution of returns obtained by an agent interacting in a continuous-time, stochastic environment. Accurate return predictions h

Yi-Hua Huang, Yue He, Yu-Jie Yuan, Yu-Kun Lai

3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered from different views. Directly applying methods for image or video stylization to 3D scenes cannot achieve such consistency. Thanks to recently proposed neural radiance fields (NeRF)

Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass

The non-orthogonal local submatrix method applied to electronic-structure based molecular dynamics simulations is shown to exceed 1.1 EFLOP/s in FP16/FP32 mixed floating-point arithmetic when using 4,400 NVIDIA A100 GPUs of the Perlmutter system. This is enabled by a modification of the original method that pushes the sustained fraction of the peak performan

Neha Srikanth, Rachel Rudinger

When strong partial-input baselines reveal artifacts in crowdsourced NLI datasets, the performance of full-input models trained on such datasets is often dismissed as reliance on spurious correlations. We investigate whether state-of-the-art NLI models are capable of overriding default inferences made by a partial-input baseline. We introduce an evaluation s

Maximilian Hüttenrauch, Gerhard Neumann

Most successful stochastic black-box optimizers, such as CMA-ES, use rankings of the individual samples to obtain a new search distribution. Yet, the use of rankings also introduces several issues such as the underlying optimization objective is often unclear, i.e., we do not optimize the expected fitness. Further, while these algorithms typically produce a

Rafael de la Madrid, Huy Luong, Jacob Zumwalt

We calculate the normal capillary retention force that anchors a drop to a solid surface in the direction perpendicular to the surface, and study the relationship between such force and the Young-Dupre work of adhesion. We also calculate the work necessary to create or destroy a patch of solid-liquid interface by moving the triple line on a solid substrate.

Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu

The rising popularity of online social network services has attracted lots of research on mining social media data, especially on mining social events. Social event detection, due to its wide applications, has now become a trivial task. State-of-the-art approaches exploiting Graph Neural Networks (GNNs) usually follow a two-step strategy: 1) constructing tex

Robin D. Allert, Karl D. Briegel, Dominik B. Bucher

Quantum technologies have seen a rapid developmental surge over the last couple of years. Though often overshadowed by quantum computation, quantum sensors show tremendous potential for widespread applications in chemistry and biology. One system stands out in particular: the nitrogen-vacancy (NV) center in diamond, an atomic-sized sensor allowing the detect

Juan-David Guerrero-Balaguera, Luigi Galasso, Robert Limas Sierra, Matteo Sonza Reorda

Currently, Deep learning and especially Convolutional Neural Networks (CNNs) have become a fundamental computational approach applied in a wide range of domains, including some safety-critical applications (e.g., automotive, robotics, and healthcare equipment). Therefore, the reliability evaluation of those computational systems is mandatory. The reliability

Laura Zeidler, Juri Opitz, Anette Frank

Evaluating the quality of generated text is difficult, since traditional NLG evaluation metrics, focusing more on surface form than meaning, often fail to assign appropriate scores. This is especially problematic for AMR-to-text evaluation, given the abstract nature of AMR. Our work aims to support the development and improvement of NLG evaluation metrics th

Ariel Edery

We consider the Nielsen-Olesen vortex non-minimally coupled to Einstein gravity with cosmological constant $\Lambda$. A non-minimal coupling term $\xi\,R\,|\phi|^2$ is natural to add to the vortex as it preserves gauge-invariance (here $R$ is the Ricci scalar and $\xi$ a dimensionless coupling constant). This term plays a dual role: it contributes to the pot

Simone Cecchini, Daniel Räde, Rudolf Zeidler

Let $M$ be an orientable connected $n$-dimensional manifold with $n\in\{6,7\}$ and let $Y\subset M$ be a two-sided closed connected incompressible hypersurface which does not admit a metric of positive scalar curvature (abbreviated by psc). Moreover, suppose that the universal covers of $M$ and $Y$ are either both spin or both non-spin. Using Gromov's $\mu$-

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence of some misbehaving (a.k.a., {\em Byzantine}) workers. Although a myriad of techniques addressing the p

Jan-F. Pietschmann, Matthias Schlottbom

We present a framework enabling variational data assimilation for gradient flows in general metric spaces, based on the minimizing movement (or Jordan-Kinderlehrer-Otto) approximation scheme. After discussing stability properties in the most general case, we specialise to the space of probability measures endowed with the Wasserstein distance. This setting c

Simone Riva, Luca Banetta, Alessio Zaccone

We developed an analytical theoretical method to determine the microscopical structure of weakly to moderately sheared colloidal suspensions in dilute conditions. The microstructure is described by the static structure factor, obtained by solving the stationary two-body Smoluchowski advection-diffusion equation. The singularly perturbed PDE problem is solved

Timothée Schmoderer, Witold Respondek

We address the problem of characterisation of null-forms of conic $3$-dimensional systems, that is, control-affine systems whose field of admissible velocities forms a conic (without parameters) in the tangent space. Those systems have been previously identified as the simplest control systems under a conic nonholonomic constraint or as systems of zero curva

Maxwell Kuschel, Claudia Scarlata, Vihang Mehta, Harry I. Teplitz

We explore how the fraction of quenched galaxies changes in groups of galaxies with respect to the distance to the center of the group, redshift, and stellar mass to determine the dominant process of environmental quenching in $0.2 < z < 0.8$ groups. We use new UV data from the UVCANDELS project in addition to existing multiband photometry to derive new gala

Ali Menati, Sid Chi-Kin Chau, Minghua Chen

Online decision-making in the presence of uncertain future information is abundant in many problem domains. In the critical problem of energy generation scheduling for microgrids, one needs to decide when to switch energy supply between a cheaper local generator with startup cost and the costlier on-demand external grid, considering intermittent renewable ge

Slah Eddin Ben Abdeljalil, Atef Ben Essid, Saloua Mani Aouadi

In this paper, we conduct a thorough mathematical analysis of a tumor growth model with treatments. The model is a system describing the evolution of metastatic tumors and the number of cells present in a primary tumor. The former evolution is described by a linear transport equation and the latter by an ordinary differential equation of Gompertzian type. Th

Johannes Branahl, Alexander Hock

We prove that the Langmann-Szabo-Zarembo (LSZ) model with quartic potential, a toy model for a quantum field theory on noncommutative spaces grasped as a complex matrix model, obeys topological recursion of Chekhov, Eynard and Orantin. By introducing two families of correlation functions, one corresponding to the meromorphic differentials $\omega_{g,n}$ of t

Elijah Pelofske, Georg Hahn, Hristo N. Djidjev

Quantum annealing has the potential to find low energy solutions of NP-hard problems that can be expressed as quadratic unconstrained binary optimization problems. However, the hardware of the quantum annealer manufactured by D-Wave Systems, which we consider in this work, is sparsely connected and moderately sized (on the order of thousands of qubits), thus

János Flesch, Eilon Solan

We study multiplayer Blackwell games, which are repeated games where the payoff of each player is a bounded and Borel-measurable function of the infinite stream of actions played by the players during the game. These games are an extension of the two-player perfect-information games studied by David Gale and Frank Stewart (1953). Recently, various new ideas

Samrit Mainali, Fabien Gatti, Osman Atabek

Motivated by the major role funneling dynamics plays in light-harvesting processes, we built some laser control strategies inspired from basic mechanisms such as interference and kicks, and apply them to the case of pyrazine. We are studying the internal conversion between the two excited states, the highest and directly reachable from the initial ground sta

Marshall C. Johnson, Ji Wang, Anusha Pai Asnodkar, Aldo S. Bonomo

Recent observations have shown that the atmospheres of ultra hot Jupiters (UHJs) commonly possess temperature inversions, where the temperature increases with increasing altitude. Nonetheless, which opacity sources are responsible for the presence of these inversions remains largely observationally unconstrained. We used LBT/PEPSI to observe the atmosphere o

Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden, Gordon Dobie

Ultrasonic guided waves offer a convenient and practical approach to structural health monitoring and non-destructive evaluation, thanks to some distinct advantages. Guided waves, in particular Lamb waves, can be used to localise damage by utilising prior knowledge of propagation and reflection characteristics. Typical localisation methods make use of the ti

Yumi Aoki, David Attié, Ties Behnke, Alain Bellerive

A time projection chamber (TPC) with micropattern gaseous detector (MPGD) readout is investigated as main tracking device of the International Large Detector (ILD) concept at the planned International Linear Collider (ILC). A prototype TPC equipped with a triple gas electron multiplier (GEM) readout has been built and operated in an electron test beam. The T

Glen Smith, Qiao Zhang, Christopher MacLellan

Computer-aided diagnosis for medical imaging is a well-studied field that aims to provide real-time decision support systems for physicians. These systems attempt to detect and diagnose a plethora of medical conditions across a variety of image diagnostic technologies including ultrasound, x-ray, MRI, and CT. When designing AI models for these systems, we ar

Roman Jacome, Jorge Bacca, Henry Arguello

Compressive spectral imaging (CSI) has attracted significant attention since it employs synthetic apertures to codify spatial and spectral information, sensing only 2D projections of the 3D spectral image. However, these optical architectures suffer from a trade-off between the spatial and spectral resolution of the reconstructed image due to technology limi

Shiguang Deng, Carlos Mora, Diran Apelian, Ramin Bostanabad

Fracture modeling of metallic alloys with microscopic pores relies on multiscale damage simulations which typically ignore the manufacturing-induced spatial variabilities in porosity. This simplification is made because of the prohibitive computational expenses of explicitly modeling spatially varying microstructures in a macroscopic part. To address this ch

Nicolas Keriven

We analyze graph smoothing with \emph{mean aggregation}, where each node successively receives the average of the features of its neighbors. Indeed, it has quickly been observed that Graph Neural Networks (GNNs), which generally follow some variant of Message-Passing (MP) with repeated aggregation, may be subject to the oversmoothing phenomenon: by performin

Emily Jensen, Maya Luster, Hansol Yoon, Brandon Pitts

In this paper, we use the concept of artificial risk fields to predict how human operators control a vehicle in response to upcoming road situations. A risk field assigns a non-negative risk measure to the state of the system in order to model how close that state is to violating a safety property, such as hitting an obstacle or exiting the road. Using risk

Gizem Sümen, Güneş Karabulut Kurt, Ali Görçin

There is no doubt that we need to keep our eyes on the sky as satellite networks aim to address the demands of 6G and beyond communications systems. On the other hand, the existence of millions of space debris pieces, large or small, poses a threat to the new space communications systems which consist of large number of small satellites, especially in the lo

Gengen Zhang, Chaolong Jiang, Hao Huang

In this paper, we present a novel class of high-order energy-preserving schemes for solving the Zakharov-Rubenchik equations. The main idea of the scheme is first to introduce an quadratic auxiliary variable to transform the Hamiltonian energy into a modified quadratic energy and the original system is then reformulated into an equivalent system which satisf

Aiping Liu, Lei Xu, Xin-Biao Xu, Guang-Jie Chen

The hybrid photon-atom integrated circuits, which include photonic microcavities and trapped single neutral atom in their evanescent field, are of great potential for quantum information processing. In this platform, the atoms provide the single-photon nonlinearity and long-lived memory, which are complementary to the excellent passive photonics devices in c

Lenin Patricio Jiménez Jiménez, Fernando Darío Almeida García, Maria Cecilia Luna Alvarado, Gustavo Fraidenraich

This work analyzes the performance of a downlink multi-user multiple-input multiple-output (MU-MIMO) non-orthogonal multiple access (NOMA) communications system. To reduce hardware complexity and exploit antenna diversity, we consider a transmit antenna selection (TAS) scheme and equal-gain combining (EGC) receivers. Further, we consider Weibull-distributed

Yuri J. F. Sulyma

For a perfectoid ring $R$, we compute the full $\mathrm{RO}(\mathbb T)$-graded ring $\mathrm{TF}_\bigstar(R;\mathbf Z_p)$. This extends and simplifies work of Gerhardt and Angeltveit-Gerhardt. In even degrees, we find an $\mathrm{RU}(\mathbb T)$-graded version of B\"okstedt periodicity, with some additional classes in the case of perfect $\mathbf F_p$-algebr

J. I. Kapusta, T. Welle

Whether Quantum Chromodynamics (QCD) exhibits a phase transition at finite temperature and density is an open question. It is important for hydrodynamic modeling of heavy ion collisions and neutron star mergers. Lattice QCD simulations have definitively shown that the transition from hadrons to quarks and gluons is a crossover when the baryon chemical potent

Shiguang Deng, Diran Apelian, Ramin Bostanabad

Concurrent multiscale damage models are often used to quantify the impacts of manufacturing-induced micro porosity on the damage response of macroscopic metallic components. However, these models are challenged by major numerical issues including mesh dependency, convergence difficulty, and low accuracy in concentration regions. We make two contributions tha

Ahmet Üstün, Arianna Bisazza, Gosse Bouma, Gertjan van Noord

Massively multilingual models are promising for transfer learning across tasks and languages. However, existing methods are unable to fully leverage training data when it is available in different task-language combinations. To exploit such heterogeneous supervision, we propose Hyper-X, a single hypernetwork that unifies multi-task and multilingual learning

Merce Guerrero, Gonzalo J. Olmo, Diego Rubiera-Garcia, Diego Sáez-Chillón Gómez

We discuss the importance of multi-ring images in the optical appearance of a horizonless spherically symmetric compact object, when illuminated by an optically thin accretion disk. Such an object corresponds to a sub-case of an analytically tractable extension of the Kerr solution dubbed as the {\it eye of the storm} by Simpson and Visser in [JCAP \textbf{0

Davide Miceli, Lara Nava

Afterglow radiation in gamma-ray bursts (GRB), extending from the radio band to GeV energies, is produced as a result of the interaction between the relativistic jet and the ambient medium. Although in general the origin of the emission is robustly identified as synchrotron radiation from the shock-accelerated electrons, many aspects remain poorly constraine

Rodrigo Siqueira, Nelson Lago, Fabio Kon, Dejan Milojičić

Operating Systems are built upon a set of abstractions to provide resource management and programming APIs for common functionality, such as synchronization, communication, protection, and I/O. The process abstraction is the bridge across these two aspects; unsurprisingly, research efforts pay particular attention to the process abstraction, aiming at enhanc

Shubhamoy Nandan

We consider the spatially inhomogeneous Moran model with seed-banks introduced in den Hollander and Nandan (2021). Populations comprising $active$ and $dormant$ individuals are structured in colonies labelled by $\mathbb{Z}^d,~d\geq 1$. The population sizes are drawn from an ergodic, translation-invariant, uniformly elliptic field that form a random environm

Weiming Zhuang, Xin Gan, Yonggang Wen, Shuai Zhang

The increasingly stringent data privacy regulations limit the development of person re-identification (ReID) because person ReID training requires centralizing an enormous amount of data that contains sensitive personal information. To address this problem, we introduce federated person re-identification (FedReID) -- implementing federated learning, an emerg

Jin Ming, Suprateek Kundu

Objective: Brain networks have gained increasing recognition as potential biomarkers in mental health studies, but there are limited approaches that can leverage complex brain networks for accurate classification. Our goal is to develop a novel Bayesian Support Vector Machine (SVM) approach that incorporates high-dimensional networks as covariates and is abl

Huub Donkers, Koen Mesman, Zaid Al-Ars, Matthias Möller

This paper presents the benchmark score definitions of QPack, an application-oriented cross-platform benchmarking suite for quantum computers and simulators, which makes use of scalable Quantum Approximate Optimization Algorithm and Variational Quantum Eigensolver applications. Using a varied set of benchmark applications, an insight of how well a quantum co

Shutong Wu, Sizhe Chen, Cihang Xie, Xiaolin Huang

Unlearnable examples (ULEs) aim to protect data from unauthorized usage for training DNNs. Existing work adds $\ell_\infty$-bounded perturbations to the original sample so that the trained model generalizes poorly. Such perturbations, however, are easy to eliminate by adversarial training and data augmentations. In this paper, we resolve this problem from a

Alexander Salganik, Sergey S. Tsygankov, Alexander A. Lutovinov, Anlaug A. Djupvik

In this work, the temporal and spectral properties of the poorly studied X-ray pulsar Swift J1808.4$-$1754 were investigated in the 0.8-79 keV energy range based on the data from the NuSTAR and Swift observatories collected during the 2014 outburst. Strong pulsations with a period of $909.73\pm0.03$ s were detected in the source light curve, with the pulsed

Raffaele Zippo, Paul Nikolaus, Giovanni Stea

Network Calculus (NC) is an algebraic theory that represents traffic and service guarantees as curves in a Cartesian plane, in order to compute performance guarantees for flows traversing a network. NC uses transformation operations, e.g., min-plus convolution of two curves, to model how the traffic profile changes with the traversal of network nodes. Such o

Tanya Shreedhar, Danesh Zeynali, Oliver Gasser, Nitinder Mohan

Multipath TCP (MPTCP) extends traditional TCP to enable simultaneous use of multiple connection endpoints at the source and destination. MPTCP has been under active development since its standardization in 2013, and more recently in February 2020, MPTCP was upstreamed to the Linux kernel. In this paper, we provide an in-depth analysis of MPTCPv0 in the Inter

Cornelius Fritz, Marius Mehrl, Paul W. Thurner, Göran kauermann

Substantive research in the Social Sciences regularly investigates signed networks, where edges between actors are either positive or negative. For instance, schoolchildren can be friends or rivals, just as countries can cooperate or fight each other. This research often builds on structural balance theory, one of the earliest and most prominent network theo

Matteo Piccolini, Farzam Nosrati, Gerardo Adesso, Roberto Morandotti

Identical quantum subsystems can possess a property which does not have any classical counterpart: indistinguishability. As a long-debated phenomenon, identical particles' indistinguishability has been shown to be at the heart of various fundamental physical results. When concerned with the spatial degree of freedom, identical constituents can be made indist

Yunpeng Bai, Cairong Wang, Chun Yuan, Yanbo Fan

Existing neural style transfer researches have studied to match statistical information between the deep features of content and style images, which were extracted by a pre-trained VGG, and achieved significant improvement in synthesizing artistic images. However, in some cases, the feature statistics from the pre-trained encoder may not be consistent with t

Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu

The score-based query attacks (SQAs) pose practical threats to deep neural networks by crafting adversarial perturbations within dozens of queries, only using the model's output scores. Nonetheless, we note that if the loss trend of the outputs is slightly perturbed, SQAs could be easily misled and thereby become much less effective. Following this idea, we

Ming Li, Lin Li, Qing Xie, Jingling Yuan

Bundle recommendation systems aim to recommend a bundle of items for a user to consider as a whole. They have become a norm in modern life and have been applied to many real-world settings, such as product bundle recommendation, music playlist recommendation and travel package recommendation. However, compared to studies of bundle recommendation approaches i

Roy Shiloh, Tomas Chlouba, Peter Hommelhoff

Not long after the laser was invented, it has been marked as a candidate source of strong, high-frequency electromagnetic radiation for acceleration of particles. Indeed, while the complex particle accelerator facilities today are an astonishing culmination of decades of work contributed by generations of physicists, engineers, and a host of scientists, new

Johannes N. Hansen, Edward T. A. Mitchard, Stuart King

Forests are vital for the wellbeing of our planet. Large and small scale deforestation across the globe is threatening the stability of our climate, forest biodiversity, and therefore the preservation of fragile ecosystems and our natural habitat as a whole. With increasing public interest in climate change issues and forest preservation, a large demand for

Emil Løvbak, Giovanni Samaey

Kinetic equations model the position-velocity distribution of particles subject to transport and collision effects. Under a diffusive scaling, these combined effects converge to a diffusion equation for the position density in the limit of an infinite collision rate. Despite this well-defined limit, numerical simulation is expensive when the collision rate i

Elio D. Di Claudio, Paolo Giannitrapani, Giovanni Jacovitti

One major problem of objective Image Quality Assessment (IQA) methods is the lack of linearity of their quality estimates with respect to scores expressed by human subjects. For this reason, usually IQA metrics undergo a calibration process based on subjective quality examples. However, example-based training makes generalization problematic, hampering resul

Yuci Han, Alper Yilmaz

In this paper, we propose Sparse Imitation Reinforcement Learning (SIRL), a hybrid end-to-end control policy that combines the sparse expert driving knowledge with reinforcement learning (RL) policy for autonomous driving (AD) task in CARLA simulation environment. The sparse expert is designed based on hand-crafted rules which is suboptimal but provides a ri

Yanglin Hu, Yingkai Ouyang, Marco Tomamichel

Quantum homomorphic encryption, which allows computation by a server directly on encrypted data, is a fundamental primitive out of which more complex quantum cryptography protocols can be built. For such constructions to be possible, quantum homomorphic encryption must satisfy two privacy properties: data privacy which ensures that the input data is private

Giovanni Urga, Fa Wang

This paper proposes maximum (quasi)likelihood estimation for high dimensional factor models with regime switching in the loadings. The model parameters are estimated jointly by the EM (expectation maximization) algorithm, which in the current context only requires iteratively calculating regime probabilities and principal components of the weighted sample co

Petra Berenbrink, Max Hahn-Klimroth, Dominik Kaaser, Lena Krieg

We consider the so-called Independent Cascade Model for rumor spreading or epidemic processes popularized by Kempe et al.\ [2003]. In this model, a small subset of nodes from a network are the source of a rumor. In discrete time steps, each informed node "infects" each of its uninformed neighbors with probability $p$. While many facets of this process are st

T. Takayama, M. Blankenhorn, J. Bertinshaw, D. Haskel

When spin-orbit-entangled $d$-electrons reside on a honeycomb lattice, rich quantum states are anticipated to emerge, as exemplified by the $d^5$ Kitaev materials. Distinct yet equally intriguing physics may be realized with a $d$-electron count other than $d^5$. We found that the layered ruthenate Ag$_3$LiRu$_2$O$_6$ with $d^4$ Ru$^{4+}$ ions at ambient pre

A. Ssenoga, H. Ddumba, J. Y. T. Mugisha

In this paper, we present a mathematical model for the interaction between honey bees and mites. The dynamics of a mite-infested honey bee colony and the evaluation of the commonly used mite-control strategies (traditional, mechanical and chemical) are studied. The mite-free and mite reproduction numbers are derived using the next generation operator approac

Vadim Kravtsov, Andrei V. Berdyugin, Ilia A. Kosenkov, Alexandra Veledina

Polarimetry provides an avenue for probing the geometry and physical mechanisms producing optical radiation in many astrophysical objects, including stellar binary systems. We present the results of multiwavelength (BVR) polarimetric studies of a sample of historical black hole X-ray binaries, observed during their outbursts or in the quiescent (or near-quie

Philipp H. Boersch-Supan, Hugh J. Hanmer, Robert A. Robinson

Molt is an essential life-history event in birds and many mammals, as maintenance of feathers and fur is critical for survival. Despite this molt remains an understudied life-history event. Non-standard statistical techniques are required to estimate the phenology of molt from observations of plumage or pelage state, and existing molt phenology models have s

Oleg Andreev

For the case of two light flavors we propose the stringy description of the system made of one heavy and one light quark-antiquark pair, with the aim of exploring the two lower-lying Born-Oppenheimer potentials as a function of a separation of the heavy quark-antiquark pair. Our analysis reveals three critical separations related to the processes of string r

Tilo H. Yang, Hsiang-Chi Hu, Fu-Xiang Rikudo Chen, Po-Yen Lin

The discovery of interfacial ferroelectricity in two-dimensional rhombohedral (3R)-stacked semiconductors opens up a new pathway for achieving ultrathin computing-in-memory devices. However, exploring ferroelectricity switching in natural 3R crystals is difficult due to lack of co-existing 3R stacking domains. Here, we present that MoS2 homoepitaxial pattern

Liang Xu, Yi Cheng, Fan Zhang, Bingxuan Wu

Deep convolutional neural networks often perform poorly when faced with datasets that suffer from quantity imbalances and classification difficulties. Despite advances in the field, existing two-stage approaches still exhibit dataset bias or domain shift. To counter this, a phased progressive learning schedule has been proposed that gradually shifts the emph

Yasuaki Ogawa

The aim of this paper is to develop a framework for localization theory of triangulated categories $\mathcal{C}$, that is, from a given extension-closed subcategory $\mathcal{N}$ of $\mathcal{C}$, we construct a natural extriangulated structure on $\mathcal{C}$ together with an exact functor $Q:\mathcal{C}\to\widetilde{\mathcal{C}}_\mathcal{N}$ satisfying a

Beatrice Murorunkwere, Fidele Twagirayezu, Albert Munyeshyaka, Joseph Ntahompagaze

The equivalence between $f(R)$ and scalar-tensor theories is revisited, we consequently explored different $f(R)$ models. After consideration of specific definition of the scalar field, we derived the potentials $V(\phi)$ for each $f(R)$ model focusing on the early Universe, mostly the inflation epoch. For a given potential, we applied the slow-roll approxim

Vojtěch Havlena, Lukáš Holík, Ondřej Lengál, Jan Vašák

Matching regexes (regular expressions) is a common problem in many areas of computer science, with requirements on high speed and robust performance. Regexes with backreferences allow one to express certain patterns (even beyond regular) concisely, however, since the matching is usually done by backtracking, the matching speed can degrade to a degree that co

Elias Stengel-Eskin, Benjamin Van Durme

Children acquiring English make systematic errors on subject control sentences even after they have reached near-adult competence (C. Chomsky, 1969), possibly due to heuristics based on semantic roles (Maratsos, 1974). Given the advanced fluency of large generative language models, we ask whether model outputs are consistent with these heuristics, and to wha

Jun Yang, Krzysztof Łatuszyński, Gareth O. Roberts

High-dimensional distributions, especially those with heavy tails, are notoriously difficult for off-the-shelf MCMC samplers: the combination of unbounded state spaces, diminishing gradient information, and local moves results in empirically observed ``stickiness'' and poor theoretical mixing properties -- lack of geometric ergodicity. In this paper, we intr

Anna Pastuszczak, Rafał Stojek, Piotr Wróbel, Rafał Kotyński

The speed and quality of single-pixel imaging (SPI) are fundamentally limited by image modulation frequency and by the levels of optical noise and compression noise. In an approach to come close to these limits, we introduce a SPI technique, which is inherently differential, and comprises a novel way of measuring the zeroth spatial frequency of images and ma

Christiane P. Koch, Ugo Boscain, Tommaso Calarco, Gunther Dirr

Quantum optimal control, a toolbox for devising and implementing the shapes of external fields that accomplish given tasks in the operation of a quantum device in the best way possible, has evolved into one of the cornerstones for enabling quantum technologies. The last few years have seen a rapid evolution and expansion of the field. We review here recent p

Anne Hartebrodt, Richard Röttger, David B. Blumenthal

Federated learning (FL) is emerging as a privacy-aware alternative to classical cloud-based machine learning. In FL, the sensitive data remains in data silos and only aggregated parameters are exchanged. Hospitals and research institutions which are not willing to share their data can join a federated study without breaching confidentiality. In addition to t

Tsz Ho Chan

In this paper, we study the variance of the number of squarefull numbers in short intervals. As a result, we are able to prove that, for any $0 < \theta < 1/2$, almost all short intervals $(x, x + x^{1/2 + \theta}]$ contain about $\frac{\zeta(3/2)}{2 \zeta(3)} x^\theta$ squarefull numbers.

Alexander Karlovitz

This work presents an algorithm for numerically computing Maass forms and their eigenvalues for Fuchsian groups of infinite covolume. By Patterson-Sullivan theory, this has the added benefit of computing Hausdorff dimensions of the limit sets of these groups. To approximate Maass forms, we consider their Fourier expansions in different coordinate systems. To

Lynn Heller, Sebastian Heller, Martin Traizet

The non-abelian Hodge correspondence is a real analytic map between the moduli space of stable Higgs bundles and the deRham moduli space of irreducible flat connections mediated by solutions to the self-duality equations. In this paper we construct self-duality solutions for strongly parabolic $\mathfrak{sl}(2,\mathbb C)$ Higgs fields on a $4$-punctured sphe

Feilong Chen, Xiuyi Chen, Jiaxin Shi, Duzhen Zhang

In the past few years, the emergence of vision-language pre-training (VLP) has brought cross-modal retrieval to a new era. However, due to the latency and computation demand, it is commonly challenging to apply VLP in a real-time online retrieval system. To alleviate the defect, this paper proposes a \textbf{Hi}erarchical \textbf{V}ision-\textbf{}Language \t

Guillaume Braun, Hemant Tyagi

Clustering bipartite graphs is a fundamental task in network analysis. In the high-dimensional regime where the number of rows $n_1$ and the number of columns $n_2$ of the associated adjacency matrix are of different order, existing methods derived from the ones used for symmetric graphs can come with sub-optimal guarantees. Due to increasing number of appli

Igor Kukavica, Amjad Tuffaha

We obtain the local existence and uniqueness for a system describing interaction of an incompressible inviscid fluid, modeled by the Euler equations, and an elastic plate, represented by the fourth-order hyperbolic PDE. We provide a~priori estimates for the existence with the optimal regularity $H^{r}$, for $r>2.5$, on the fluid initial data and construct a

Hanxu Zhou, Qixuan Zhou, Zhenyuan Jin, Tao Luo

Substantial work indicates that the dynamics of neural networks (NNs) is closely related to their initialization of parameters. Inspired by the phase diagram for two-layer ReLU NNs with infinite width (Luo et al., 2021), we make a step towards drawing a phase diagram for three-layer ReLU NNs with infinite width. First, we derive a normalized gradient flow fo

Sumit Ghosh, Stefan Blügel, Yuriy Mokrousov

We propose a new mechanism to produce a meron-antimeron pair in a two dimensional antiferromagnet with an ultrafast laser pulse via thermal Schwinger mechanism. Unlike ultrafast skyrmion nucleation, this process conserves total topological charge. We systematically show different stages of the dynamics and define proper topological invariants to characterise

Francisco-Javier Turiel

Consider a smooth action of $\mathbb R^n$ on a connected manifold $M$, not necessarily compact, of dimension $m$ and rank $k$. Assume that $M$ is not a cylinder. Then there exists an orbit of the action of dimension $<(m+k)/2$. As a consequence, one shows that if there is a non-zero element of the ring of Pontrjagin classes of $M$ of degree $4\ell\geq 4$, th

Zhiqin Zhu, Zheng Yao, Guanqiu Qi, Neal Mazur

As a necessary process in drug development, finding a drug compound that can selectively bind to a specific protein is highly challenging and costly. Drug-target affinity (DTA), which represents the strength of drug-target interaction (DTI), has played an important role in the DTI prediction task over the past decade. Although deep learning has been applied

Yo Yehudi, Lukas Hughes-Noehrer, Carole Goble, Caroline Jay

In 2020, the COVID-19 pandemic resulted in a rapid response from governments and researchers worldwide. As of late 2023, over millions have died as a result of COVID-19, with many COVID-19 survivors going on to experience long-term effects weeks, months, or years after their illness. Despite this staggering toll, those who work with pandemic-relevant data of

Nourelhouda Groun, Maria Villalba-Orero, Enrique Lara-Pezzi, Eusebio Valero

Cardiac cine magnetic resonance imaging (MRI) can be considered the optimal criterion for measuring cardiac function. This imaging technique can provide us with detailed information about cardiac structure, tissue composition and even blood flow. This work considers the application of the higher order dynamic mode decomposition (HODMD) method to a set of MR

C. Cui, R. Ma, E. Martínez-Pañeda

We present a phase field-based electro-chemo-mechanical formulation for modelling mechanics-enhanced corrosion and hydrogen-assisted cracking in elastic-plastic solids. A multi-phase-field approach is used to present, for the first time, a general framework for stress corrosion cracking, incorporating both anodic dissolution and hydrogen embrittlement mechan