August 2022 arXiv papers — page 25

Weiqi Chu, Mason A. Porter

Traditional models of opinion dynamics, in which the nodes of a network change their opinions based on their interactions with neighboring nodes, consider how opinions evolve either on time-independent networks or on temporal networks with edges that follow Poisson statistics. Most such models are Markovian. However, in many real-life networks, interactions

Carmen Mazijn, Carina Prunkl, Andres Algaba, Jan Danckaert

AI systems can create, propagate, support, and automate bias in decision-making processes. To mitigate biased decisions, we both need to understand the origin of the bias and define what it means for an algorithm to make fair decisions. Most group fairness notions assess a model's equality of outcome by computing statistical metrics on the outputs. We argue

F. Becattini

Exergy is a very important thermodynamic quantity in several fields such as economy, engineering, ecology and yet it has attracted little attention in pure physics. One of the main problems of the currently used definition of exergy is its dependence on an arbitrarily chosen reference state, which is the thermodynamic state of a reservoir the system is suppo

Chao Li, Xiao Chai, Linzhao Zhuo, Bochao Wei

We have achieved stimulated laser cooling of thermal rubidium atomic beams on a silicon chip. Following pre-collimation via a silicon microchannel array, we perform beam brightening via a blue-detuned optical molasses. Owing to the small size of the chip elements, we require only 8 mW, or nine times lower power than earlier free-space experiments on cesium [

Sudheesh Kattumannil, Sreedevi E. P, N. Balakrishnan

In this work, we establish a connection between the cumulative residual entropy and the Gini mean difference (GMD). Some relationships between the extropy and the GMD, and the truncated GMD and dynamic versions of the cumulative extropy are also established. We then show that several entropy and extropy measures discussed here can be brought into the framewo

Nick Brown, Brandon Echols, Justs Zarins, Tobias Grosser

The Cerebras Wafer Scale Engine (WSE) is an accelerator that combines hundreds of thousands of AI-cores onto a single chip. Whilst this technology has been designed for machine learning workloads, the significant amount of available raw compute means that it is also a very interesting potential target for accelerating traditional HPC computational codes. Man

Bruno Di Giorgi, Mark Levy, Richard Sharp

Vocoders are models capable of transforming a low-dimensional spectral representation of an audio signal, typically the mel spectrogram, to a waveform. Modern speech generation pipelines use a vocoder as their final component. Recent vocoder models developed for speech achieve a high degree of realism, such that it is natural to wonder how they would perform

Zecheng Liu, Jia Wei, Rui Li

Due to the difficulties of obtaining multimodal paired images in clinical practice, recent studies propose to train brain tumor segmentation models with unpaired images and capture complementary information through modality translation. However, these models cannot fully exploit the complementary information from different modalities. In this work, we thus p

T. Arkan, J. Kaluzny, D. Bafia, D. Bice

The Linac Coherent Light Source (LCLS) is an X-ray science facility at SLAC National Accelerator Laboratory. The LCLS-II project (an upgrade to LCLS) is in the commissioning phase; the LCLS-II-HE (High Energy) project is another upgrade to the facility, enabling higher energy operation. An electron beam is accelerated using superconducting radio frequency (S

Cephas Samende, Zhong Fan, Jun Cao

Smart energy networks provide for an effective means to accommodate high penetrations of variable renewable energy sources like solar and wind, which are key for deep decarbonisation of energy production. However, given the variability of the renewables as well as the energy demand, it is imperative to develop effective control and energy storage schemes to

Daniel F. Urrego, Juan P. Torres

We put forward and demonstrate experimentally a {\it quantum-inspired} protocol that allows to quantify the degree of similarity between two spatial shapes embedded in two optical beams without the need to measure the amplitude and phase across each beam. Instead the sought-after information can be retrieved measuring the degree of polarization of the combin

Ashutosh Timilsina, Simone Silvestri

The widespread adoption of distributed energy resources, and the advent of smart grid technologies, have allowed traditionally passive power system users to become actively involved in energy trading. Recognizing the fact that the traditional centralized grid-driven energy markets offer minimal profitability to these users, recent research has shifted focus

Zecheng Liu, Jia Wei, Rui Li, Jianlong Zhou

People perceive the world with different senses, such as sight, hearing, smell, and touch. Processing and fusing information from multiple modalities enables Artificial Intelligence to understand the world around us more easily. However, when there are missing modalities, the number of available modalities is different in diverse situations, which leads to a

Guangtao Zhu, Tomoya Miyamae, Kohei Noda, Heeyoung Lee

We propose a newly configured optical correlation-domain reflectometry (OCDR) without the use of an electrical spectrum analyzer (ESA) for high-speed distributed reflectivity measurement with an enhanced spatial resolution. First, the operation of ESA-free OCDR is analyzed by numerical simulation, the results of which show the potential of the configuration

Stephanie L. Yardley, Lucie M. Green, Alexander W. James, David Stansby

Forecasting solar energetic particles (SEPs), and identifying flare/CMEs from active regions (ARs) that will produce SEP events in advance is extremely challenging. We investigate the magnetic field environment of AR 12673, including the AR's magnetic configuration, the surrounding field configuration in the vicinity of the AR, the decay index profile, and t

Bernhard G. Bodmann, Iris Emilsdottir

This paper develops an adaptive version of Mallat's scattering transform for signals on graphs. The main results are norm bounds for the layers of the transform, obtained from a version of a Beurling-Deny inequality that permits to remove the nonlinear steps in the scattering transform. Under statistical assumptions on the input signal, the norm bounds can b

Gabriel Rodriguez-Canal, Nick Brown, Yuri Torres, Arturo Gonzalez-Escribano

FPGAs are an attractive type of accelerator for all-purpose HPC computing systems due to the possibility of deploying tailored hardware on demand. However, the common tools for programming and operating FPGAs are still complex to use, specially in scenarios where diverse types of tasks should be dynamically executed. In this work we present a programming abs

Xingyuan Chen, Goncalo dos Reis

We consider in this work the convergence of a split-step Euler type scheme (SSM) for the numerical simulation of interacting particle Stochastic Differential Equation (SDE) systems and McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with full super-linear growth in the spatial and the interaction component in the drift, and non-constant Lipschitz d

Xuyang Li, Hamed Bolandi, Talal Salem, Nizar Lajnef

Structural monitoring for complex built environments often suffers from mismatch between design, laboratory testing, and actual built parameters. Additionally, real-world structural identification problems encounter many challenges. For example, the lack of accurate baseline models, high dimensionality, and complex multivariate partial differential equations

Luigi De Simone, Mario Di Mauro, Roberto Natella, Fabio Postiglione

Nowadays, most telecommunication services adhere to the Service Function Chain (SFC) paradigm, where network functions are implemented via software. In particular, container virtualization is becoming a popular approach to deploy network functions and to enable resource slicing among several tenants. The resulting infrastructure is a complex system composed

Alexandra M. Tayar, Fernando Caballero, Trevor Anderberg, Omar A. Saleh

Demixing of binary liquids is a ubiquitous transition, which is explained using a well-established thermodynamic formalism that requires equality of intensive thermodynamics parameters across the phase boundaries. Demixing transitions also occur when binary fluid mixtures are driven away from equilibrium, for example, by external shear flow. Predicting demix

Victor S Dotsenko, Pascal Viot, Alberto Imparato, Gleb Oshanin

We study the two-dimensional Langevin dynamics of a two-component system, whose components are in contact with heat baths kept at different temperatures. Dynamics is constrained by an optical trap and the \text{dissimilar} species interact via a quadratic potential. We realize that the system evolves towards a peculiar non-equilibrium steady-state with a non

N. Dagoneau, S. Schanne

The SVOM mission under development will carry four instruments, and in particular the coded-mask telescope named ECLAIRs, with a large field of view of about 2 sr, operating in the 4-150 keV energy band. The trigger software on board ECLAIRs will search for high-energy transients such as gamma-ray bursts and peculiar behaviour (e.g. strong outbursts) from kn

Ryan Tan, Christoph Bruder, Martin Koppenhöfer

We study the quantum synchronization of a single spin driven by an external semiclassical signal for spin numbers larger than $S = 1$, the smallest system to host a quantum self-sustained oscillator. The occurrence of interference-based quantum synchronization blockade is found to be qualitatively different for integer vs. half-integer spin number $S$. We ex

Jacob L. Bourjaily, Cristian Vergu, Matt von Hippel

Landau's work on the singularities of Feynman diagrams suggests that they can only be of three types: either poles, logarithmic divergences, or the roots of quadratic polynomials. On the other hand, many Feynman integrals exist whose singularities involve arbitrarily higher-order polynomial roots. We investigate this apparent paradox using concrete examples

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

This paper studies the problem of designing an optimal sequence of interventions in a causal graphical model to minimize cumulative regret with respect to the best intervention in hindsight. This is, naturally, posed as a causal bandit problem. The focus is on causal bandits for linear structural equation models (SEMs) and soft interventions. It is assumed t

Abdulrahman Kerim, Washington L. S. Ramos, Leandro Soriano Marcolino, Erickson R. Nascimento

Video stabilization plays a central role to improve videos quality. However, despite the substantial progress made by these methods, they were, mainly, tested under standard weather and lighting conditions, and may perform poorly under adverse conditions. In this paper, we propose a synthetic-aware adverse weather robust algorithm for video stabilization tha

Jason Semeraro

In this note, we initiate the study of $\mathcal{F}$-weights for an $\ell$-local compact group $\mathcal{F}$ over a discrete $\ell$-toral group $S$ with discrete torus $T$. Motivated by Alperin's Weight Conjecture for simple groups of Lie-type, we conjecture that when $T$ is the unique maximal abelian subgroup of $S$ up to $\mathcal{F}$-conjugacy and every e

Jussi Behrndt, Markus Holzmann, Matěj Tušek

In this paper the two-dimensional Dirac operator with a general hermitian $\delta$-shell interaction supported on a straight line is introduced as a self-adjoint operator and its spectral properties are investigated in detail. In particular, it is demonstrated that the singularly continuous spectrum is always empty and that by switching a certain $\delta$-sh

Rodolfo Machuca, Fatoumata Sankare

As big data collection continues to grow, more and more organizations are relying on outsourcing their data to cloud-based environments. This includes the federal government and several agencies that depend on maintaining our citizens' secure data. Law enforcement agencies from the national level down to large city police departments are also using the cloud

Jonathan Lorraine, Nihesh Anderson, Chansoo Lee, Quentin De Laroussilhe

Our goal is to assess if AutoML system changes - i.e., to the search space or hyperparameter optimization - will improve the final model's performance on production tasks. However, we cannot test the changes on production tasks. Instead, we only have access to limited descriptors about tasks that our AutoML system previously executed, like the number of data

Olivier Mathieu

Let $K$ be a field, and let $\Aut \,K^2$ be the group of polynomial automorphisms of $K^2$. We investigate which subgroups are linear or not. In characteristic zero, there are small nonlinear subgroups and some big linear subgroups. When $K$ has finite characteristic, the whole group $\Aut\,K^2$ is linear whenever $K$ is finite, and nonlinear otherwise.

Ziyang Li, Wangmei Zha, Zebo Tang

Spin alignment of vector mesons in noncentral relativistic heavy ion collisions provides a novel probe of the global quark polarization and hadronization mechanism. In this paper, we discuss the spin alignment of a short-lived vector meson, namely K*, arising from the hadronic rescattering process using the UrQMD model. This spin alignment is not related to

Muhammad Zawish, Steven Davy, Lizy Abraham

Recent advances in Artificial Intelligence (AI) on the Internet of Things (IoT)-enabled network edge has realized edge intelligence in several applications such as smart agriculture, smart hospitals, and smart factories by enabling low-latency and computational efficiency. However, deploying state-of-the-art Convolutional Neural Networks (CNNs) such as VGG-1

Eslam Badr, Francesc Bars

We obtain the list of automorphism groups for smooth plane sextic curves over an algebraically closed field K of characteristic p=0 or p>21. Moreover, we assign to each group a geometrically complete family over K describing its corresponding stratum, that is, a generic defining polynomial equation with parameters such that any curve in the stratum is K-isom

Ghiles Ziat, Vincent Botbol, Matthieu Dien, Arnaud Gotlieb

In program verification, constraint-based random testing is a powerful technique which aims at generating random test cases that satisfy functional properties of a program. However, on recursive constrained data-structures (e.g., sorted lists, binary search trees, quadtrees), and, more generally, when the structures are highly constrained, generating uniform

Kang-Da Wu, Chengran Yang, Ren-Dong He, Mile Gu

Complex systems are embedded in our everyday experience. Stochastic modelling enables us to understand and predict the behaviour of such systems, cementing its utility across the quantitative sciences. Accurate models of highly non-Markovian processes -- where the future behaviour depends on events that happened far in the past -- must track copious amounts

Man Zhang, Andrea Arcuri, Yonggang Li, Yang Liu

Remote Procedure Call (RPC) is a communication protocol to support client-server interactions among services over a network. RPC is widely applied in industry for building large-scale distributed systems, such as Microservices. Modern RPC frameworks include for example Thrift, gRPC, SOFARPC and Dubbo. Testing such systems is very challenging, due to the comp

ATLAS Collaboration

The electroweak production of $Z(\nu\bar{\nu})\gamma$ in association with two jets is studied in a regime with a photon of high transverse momentum above 150 GeV using proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider. The analysis uses a data sample with an integrated luminosity of 139 fb$^{-1}$ collected by the ATLA

Aditya M. Arabhavi, Peter Woitke, Stephanie M. Cazaux, Inga Kamp

In cold and shielded environments, molecules freeze out on dust grain surfaces to form ices such as H2O, CO, CO2, CH4, CH3OH, and NH3. In protoplanetary disks, the exact radial and vertical ice extension depend on disk mass, geometry, and stellar UV irradiation. The goal of this work is to present a computationally efficient method to compute ice and bare-gr

Jaime Cofre, Kay Saalfeld

The decisive role of Embryology in understanding the evolution of animal forms is founded and deeply rooted in the history of science. It is recognized that the emergence of multicellularity would not have been possible without the formation of the first embryo. We speculate that biophysical phenomena and the surrounding environment of the Ediacaran ocean we

Clement Mommessin, Renyu Yang, Natalia V. Shakhlevich, Xiaoyang Sun

Resource provisioning plays a pivotal role in determining the right amount of infrastructure resource to run applications and target the global decarbonization goal. A significant portion of production clusters is now dedicated to long-running applications (LRAs), which are typically in the form of microservices and executed in the order of hours or even mon

Vivek Gopalakrishnan, Polina Golland

The use of digitally reconstructed radiographs (DRRs) to solve inverse problems such as slice-to-volume registration and 3D reconstruction is well-studied in preoperative settings. In intraoperative imaging, the utility of DRRs is limited by the challenges in generating them in real-time and supporting optimization procedures that rely on repeated DRR synthe

Elisabetta Landini, Karsten Reuter, Harald Oberhofer

Lead-free halide double perovskites are promising stable and non-toxic alternatives to methylammonium lead iodide in the field of photovoltaics. In this context, the most commonly used double perovskite is Cs$_2$AgBiBr$_6$, due to its favorable charge transport properties. However, the maximum power conversion efficiency obtained for this material does not e

Sabine M. Neumayer, Anton V. Ievlev, Alexander Tselev, Sergey A. Basun

Smart electronic circuits that support neuromorphic computing on the hardware level necessitate materials with memristive, memcapacitive, and neuromorphic-like functional properties; in short, the electronic response must depend on the voltage history, thus enabling learning algorithms. Here we demonstrate volatile ferroelectric switching of Sn$_2$P$_2$S$_6$

Zihan Liu, Ge Wang, Yun Luo, Stan Z. Li

Recent research has revealed that Graph Neural Networks (GNNs) are susceptible to adversarial attacks targeting the graph structure. A malicious attacker can manipulate a limited number of edges, given the training labels, to impair the victim model's performance. Previous empirical studies indicate that gradient-based attackers tend to add edges rather than

Ernesto Savaglio, Stefano Vannucci

Two characterizations of the whole class of strategy-proof aggregation rules on rich domains of locally unimodal preorders in finite median join-semilattices are provided. In particular, it is shown that such a class consists precisely of generalized weak sponsorship rules induced by certain families of order filters of the coalition poset. It follows that t

Leonidas Tsepenekas, Ivan Brugere, Freddy Lecue, Daniele Magazzeni

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems. However, access to an accurate similarity function should not always be considered guaranteed, and this point was even r

Morten Akhøj, Xavier Pennec, Stefan Sommer

Phylogenetic PCA (p-PCA) is a version of PCA for observations that are leaf nodes of a phylogenetic tree. P-PCA accounts for the fact that such observations are not independent, due to shared evolutionary history. The method works on Euclidean data, but in evolutionary biology there is a need for applying it to data on manifolds, particularly shapes. We prov

Guangyi Zhu

An Intrusion Detection System (IDS) is one of the security tools that can automatically analyze network traffic and detect suspicious activities. They are widely implemented as security guarantee tools in various business networks. However, the high rate of false-positive alerts creates an overwhelming number of unnecessary alerts for security analysts to si

Hanbing Liu, Gengsheng Wang, Huaiqiang Yu

For linear control systems, the usual state feedback stabilizability has two components: one is a continuous observation mode (i.e., to observe solutions continuously in time), and the other is a class of feedback laws (which is usually the space of all of the linear and bounded operators from a state space to a control space). This paper studies the stabili

Balázs Ráth, Kitti Varga, Panna Tímea Fekete, Roland Molontay

We study a variant of the color-avoiding percolation model introduced by Krause et al., namely we investigate the color-avoiding bond percolation setup on (not necessarily properly) edge-colored Erd\H{o}s-R\'{e}nyi random graphs. We say that two vertices are color-avoiding connected in an edge-colored graph if after the removal of the edges of any color, the

Nicola Leone, Marco Manna, Maria Concetta Morelli, Simona Perri

The paper investigates the relative expressiveness of two logic-based languages for reasoning over streams, namely LARS Programs -- the language of the Logic-based framework for Analytic Reasoning over Streams called LARS -- and LDSR -- the language of the recent extension of the I-DLV system for stream reasoning called I-DLV-sr. Although these two languages

Elena Berardini, Alain Couvreur, Grégoire Lecerf

In 1874 Brill and Noether designed a seminal geometric method for computing bases of Riemann-Roch spaces. From then, their method has led to several algorithms, some of them being implemented in computer algebra systems. The usual proofs often rely on abstract concepts of algebraic geometry and commutative algebra. In this paper we present a short self-conta

Massimo Quadrana, Antoine Larreche-Mouly, Matthias Mauch

Song embeddings are a key component of most music recommendation engines. In this work, we study the hyper-parameter optimization of behavioral song embeddings based on Word2Vec on a selection of downstream tasks, namely next-song recommendation, false neighbor rejection, and artist and genre clustering. We present new optimization objectives and metrics to

S. Drew Chojnowski, Swetlana Hubrig, Jonathan Labadie-Bartz, Thomas Rivinius

We report the discovery of a new example of the rare class of highly magnetized, rapidly rotating, helium enhanced, early B stars that produce anomalously wide hydrogen emission due to a centrifugal magnetosphere (CM). The star is Trumpler 16-26, a B1.5 V member of the Trumpler 16 open cluster. A CM was initially suspected based on hydrogen Brackett series e

Thijs van der Horst, Marc van Kreveld, Tim Ophelders, Bettina Speckmann

The Fr\'echet distance is a commonly used similarity measure between curves. It is known how to compute the continuous Fr\'echet distance between two polylines with $m$ and $n$ vertices in $\mathbb{R}^d$ in $O(mn (\log \log n)^2)$ time; doing so in strongly subquadratic time is a longstanding open problem. Recent conditional lower bounds suggest that it is u

Fabo Feng, R. Paul Butler, Steven S. Vogt, Matthew S. Clement

We analyze 5108 AFGKM stars with at least five high precision radial velocity points as well as Gaia and Hipparcos astrometric data utilizing a novel pipeline developed in previous work. We find 914 radial velocity signals with periods longer than 1000\,d. Around these signals, 167 cold giants and 68 other types of companions are identified by combined analy

J. Brunekreef, R. Loll

Three-dimensional Lorentzian quantum gravity, expressed as the continuum limit of a nonperturbative sum over spacetimes, is tantalizingly close to being amenable to analytical methods, and some of its properties have been described in terms of effective matrix and other models. To gain a more detailed understanding of three-dimensional quantum gravity, we pe

Brook Wander, Kirby Broderick, Zachary W. Ulissi

Catalyst discovery is paramount to support access to energy and key chemical feedstocks in a post fossil fuel era. Exhaustive computational searches of large material design spaces using ab-initio methods like density functional theory (DFT) are infeasible. We seek to explore large design spaces at relatively low computational cost by leveraging large, gener

Yi-chong Xia, Bin Chen, Yan Feng, Tian-shuo Ge

As a probabilistic modeling technique, the flow-based model has demonstrated remarkable potential in the field of lossless compression \cite{idf,idf++,lbb,ivpf,iflow},. Compared with other deep generative models (eg. Autoregressive, VAEs) \cite{bitswap,hilloc,pixelcnn++,pixelsnail} that explicitly model the data distribution probabilities, flow-based models

Patrick Ebel, Kim Julian Gülle, Christoph Lingenfelder, Andreas Vogelsang

In this work, we present ICEBOAT an interactive tool that enables automotive UX experts to explore how users interact with In-vehicle Information Systems. Based on large naturalistic driving data continuously collected from production line vehicles, ICEBOAT visualizes drivers' interactions and driving behavior on different levels of detail. Hence, it allows

Ramón Torres

The collapse of astrophysically significant bodies generates, under suitable conditions, black holes. Since one expects the generator of the black hole to be a rotating body, the black hole will also rotate. The existence of inner singularities in classical solutions for rotating black holes and the fact that General Relativity is incompatible with Quantum M

Frederik Garbe, Jan Hladký, Gábor Kun, Kristýna Pekárková

The theory of limits of permutations leads to limit objects called permutons, which are certain Borel measures on the unit square. We prove that permutons avoiding a given permutation of order $k$ have a particularly simple structure. Namely, almost every fiber of the disintegration of the permuton (say, along the x-axis) consists only of atoms, at most $(k-

Saihao Huang, Lijie Wang, Zhenghua Li, Zeyang Liu

As the first session-level Chinese dataset, CHASE contains two separate parts, i.e., 2,003 sessions manually constructed from scratch (CHASE-C), and 3,456 sessions translated from English SParC (CHASE-T). We find the two parts are highly discrepant and incompatible as training and evaluation data. In this work, we present SeSQL, yet another large-scale sessi

Pavel Shuldiner, R. Wayne Oldford

Motivated by an approach to visualization of high dimensional statistical data given in Hurley and Oldford (2011), this work examines the clique structure of $J_n(m, m-1)$ Johnson graphs. Cliques and maximal cliques are characterized and proved to be of one of only two types. These types are characterized by features of the intersection and of the union of t

Matthew Brahlek, Maria Gazda, Veerle Keppens, Alessandro R. Mazza

High entropy oxides are emerging as an exciting new avenue to design highly tailored functional behaviors that have no traditional counterparts. Study and application of these materials are bringing together scientists and engineers from physics, chemistry, and materials science. The diversity of each of these disciplines comes with perspectives and jargon t

Matthias Kahl, Daniel Jorde, Hans-Arno Jacobsen

Non-intrusive load monitoring (NILM) aims at energy consumption and appliance state information retrieval from aggregated consumption measurements, with the help of signal processing and machine learning algorithms. Representation learning with deep neural networks is successfully applied to several related disciplines. The main advantage of representation l

Marco Schreyer, Timur Sattarov, Damian Borth

The ongoing 'digital transformation' fundamentally changes audit evidence's nature, recording, and volume. Nowadays, the International Standards on Auditing (ISA) requires auditors to examine vast volumes of a financial statement's underlying digital accounting records. As a result, audit firms also 'digitize' their analytical capabilities and invest in Deep

Nelson Martins-Ferreira

A generalization to the categorical notion of biproduct, called semibiproduct, which in the case of groups covers classical semidirect products, has recently been analysed in the category of monoids with surprising results in the classification of weakly Schreier extensions. The purpose of this paper is to extend the study of semibiproducts to the category o

J. Asadollahi, F. Padashnik, S. Sadeghi, H. Treffinger

Let $B$ be a finite dimensional algebra and $A=B[P_0]$ be the one-point extension algebra of $B$ with respect to the finitely generated projective $B$-module $P_0$. The categories of $B$-modules and $A$-modules are related by two adjoint functors $\mathcal{R}$ and $\mathcal{E}$, called the restriction and the extension functors, respectively. Based on the ni

Abdulmajeed Alqasem, Heshan Aravinda, Arnaud Marsiglietti, James Melbourne

A remarkable conjecture of Feige (2006) asserts that for any collection of $n$ independent non-negative random variables $X_1, X_2, \dots, X_n$, each with expectation at most $1$, $$ \mathbb{P}(X < \mathbb{E}[X] + 1) \geq \frac{1}{e}, $$ where $X = \sum_{i=1}^n X_i$. In this paper, we investigate this conjecture for the class of discrete log-concave probabil

Adam Thelen, Xiaoge Zhang, Olga Fink, Yan Lu

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, w

Roland Bittleston, Atul Sharma, David Skinner

We consider holomorphic Poisson-BF theory on twistor space. Classically, this describes self-dual Einstein gravity on space-time, but at the quantum level it is plagued by an anomaly. The anomaly corresponds to the fact that integrability of the self-dual vacuum Einstein equations does not survive in self-dual quantum gravity. We compute the anomaly polynomi

Lucas Rosenblatt, Bernease Herman, Anastasia Holovenko, Wonkwon Lee

Differential privacy (DP) data synthesizers support public release of sensitive information, offering theoretical guarantees for privacy but limited evidence of utility in practical settings. Utility is typically measured as the error on representative proxy tasks, such as descriptive statistics, accuracy of trained classifiers, or performance over a query w

J. Sheil, O. O. Versolato, V. Bakshi, H. A. Scott

We review the results of the 1st Extreme Ultraviolet (EUV) Light Sources Code Comparison Workshop, which was held online on 3rd November 2020. The goal of this workshop was to provide a platform for specialists in EUV light source plasma modeling to benchmark and validate their numerical codes using well-defined case studies. Eight institutions spanning four

Shunsuke Kurima

This paper deals with a singular nonlocal phase field system of conserved type.Colli--K.\ [Nonlinear Anal.\ 190 (2020)] have derived existence of solutions to a singular phase field system of conserved type. On the other hand, Davoli--Scarpa--Trussardi [Arch. Ration. Mech. Anal.\ 239 (2021)] have studied nonlocal to local convergence of Cahn-Hilliard equatio

Tong Wu, Jiaqi Wang, Xingang Pan, Xudong Xu

Neural surface reconstruction aims to reconstruct accurate 3D surfaces based on multi-view images. Previous methods based on neural volume rendering mostly train a fully implicit model with MLPs, which typically require hours of training for a single scene. Recent efforts explore the explicit volumetric representation to accelerate the optimization via memor

Nanami Ichinose, Mina Maruyama, Takato Hotta, Zheng Liu

Ultrathin lateral heterostructures of monolayer MoS2 and WS2 have successfully been realized with the metal-organic chemical vapor deposition method. Atomic-resolution HAADF-STEM observations have revealed that the junction widths of lateral heterostructures range from several nanometers to single-atom thickness, the thinnest heterojunction in theory. The in

Mariem Abdellatif, Martin Friesen, Peter Kuchling, Barbara Rüdiger

In this work we investigate limit theorems for the time-averaged process $\left(\frac{1}{t}\int_0^t X_s^x ds\right)_{t\geq 0}$ where $X^x$ is a subcritical continuous-state branching processes with immigration (CBI processes) starting in $x \geq 0$. Under a second moment condition on the branching and immigration measures we first prove the law of large numb

Maxim Bonnaerens, Matthias Freiberger, Marian Verhelst, Joni Dambre

In this work we propose a methodology to accurately evaluate and compare the performance of efficient neural network building blocks for computer vision in a hardware-aware manner. Our comparison uses pareto fronts based on randomly sampled networks from a design space to capture the underlying accuracy/complexity trade-offs. We show that our approach allows

Piotr Lebiedowicz, Otto Nachtmann, Antoni Szczurek

The two-tensor-pomeron model proposed previously to describe low $x$ DIS data is applied to real and virtual Compton scattering on a proton. The model includes two tensor pomerons, a soft and a hard one, and tensor reggeons. We include contributions of both transverse and longitudinal virtual photons. We show that this model gives a very good description of

Matas Tartėnas, Kastytis Zubovas

The large galactic scales are connected to the many orders of magnitude smaller supermassive black hole (SMBH) scales by an episodic cycle of feeding and feedback. Active galactic nuclei (AGN) are powered by accretion onto SMBH and the majority of AGN energy, in near-Eddington regime, is produced in thin sub-pc accretion discs. Currently, it is very difficul

Eder Baron-Prada, Renzo Caballero, Eric Feron

Introductory state-space linear control courses focus on linear, time-invariant systems and spend intense efforts by introducing system realizations that allow the student to grasp fundamental concepts, among which controllability, observability, and controller and observer design. This note describes a graphical mechanism to transform a system expressed in

Claudia Maria Chanu, Giovanni Rastelli

We introduce St\"ackel separable coordinates on the covering manifolds $M_k$, where $k$ is a rational parameter, of certain constant-curvature Riemannian manifolds with the structure of warped manifold. These covering manifolds appear implicitly in literature as connected with superintegrable systems with polynomial in the momenta first integrals of arbitrar

Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

With the tremendous success of Graph Convolutional Networks (GCNs), they have been widely applied to recommender systems and have shown promising performance. However, most GCN-based methods rigorously stick to a common GCN learning paradigm and suffer from two limitations: (1) the limited scalability due to the high computational cost and slow training conv

J. O. Button

We look at isometric actions on arbitrary hyperbolic spaces of generalised Baumslag - Solitar groups of arbitrary dimension (the rank of the free abelian vertex and edge subgroups). It is known that being a hierarchically hyperbolic group is not a quasi-isometric invariant. We show that virtually being a hierarchically hyperbolic group is not invariant under

Iqra Altaf, Marianna Csörnyei, Kornélia Héra

We consider the Hausdorff dimension of planar Besicovitch sets for rectifiable sets $\Gamma$, i.e. sets that contain a rotated copy of $\Gamma$ in each direction. We show that for a large class of Cantor sets $C$ and Cantor-graphs $\Gamma$ built on $C$, the Hausdorff dimension of any $\Gamma$-Besicovitch set must be at least $\min\left(2-s^2,\frac{1}{s}\righ

Stephan M. Birkmann, Giovanna Giardino, Marco Sirianni, Pierre Ferruit

The Near-Infrared Spectrograph (NIRSpec) is one the four focal plane instruments on the James Webb Space Telescope (JWST) which was launched on December 25, 2021. We present the in-flight status and performance of NIRSpec's detector system as derived from the instrument commissioning data. The instrument features two 2048 x 2048 HAWAII-2RG sensor chip assemb

Theo Mckenzie, Mostafa Sabri

We prove quantum ergodicity for a family of periodic Schr\"odinger operators $H$ on periodic graphs. This means that most eigenfunctions of $H$ on large finite periodic graphs are equidistributed in some sense, hence delocalized. Our results cover the adjacency matrix on $\mathbb{Z}^d$, the triangular lattice, the honeycomb lattice, Cartesian products and pe

Simone Lisi, Valérie Guisset, Philippe David, Estelle Mazaleyrat

Two-dimensional confinement of lattices produces a variety of order and disorder phenomena. When the confining walls have atomic granularity, unique structural phases are expected, of relevance in nanotribology, porous materials or intercalation compounds where \textit{e.g.} electronic states can emerge accordingly. The interlayer's own order is frustrated b

Shen-Fu Tsai

A 0-1 matrix $M$ is saturating for a 0-1 matrix $P$ if $M$ does not contain a submatrix that can be turned into $P$ by flipping any number of its $1$-entries to $0$-entries, and changing any $0$-entry to $1$-entry of $M$ introduces a copy of $P$. Matrix $M$ is semisaturating for $P$ if changing any $0$-entry to $1$-entry of $M$ introduces a new copy of $P$,

G. M. Birajdar, N. D. Sangle

In this paper, we introduce the class $k$-USH $(u,v,\alpha,\lambda)$ using Al-Oboudi operator which is a subclass of $k$-uniformly harmonic functions. A subclass $k$-UTH $(u,v,\alpha,\lambda)$ of $k$-USH $(u,v,\alpha,\lambda)$ is also been defined and studied in this paper. Extreme points, distortion bounds, convolution condition and convex combination of fu

Jiangmeng Li, Yanan Zhang, Wenwen Qiang, Lingyu Si

Few-shot learning models learn representations with limited human annotations, and such a learning paradigm demonstrates practicability in various tasks, e.g., image classification, object detection, etc. However, few-shot object detection methods suffer from an intrinsic defect that the limited training data makes the model cannot sufficiently explore seman

Natalie O. Butterfield, Cornelia C. Lang, Adam Ginsburg, Mark R. Morris

We present high-resolution (~2-3"; ~0.1 pc) radio observations of the Galactic center cloud M0.10-0.08 using the Very Large Array at K and Ka band (~25 and 36 GHz). The M0.10-0.08 cloud is located in a complex environment near the Galactic center Radio Arc and the adjacent M0.11-0.11 molecular cloud. From our data, M0.10-0.08 appears to be a compact molecula

G. M. Birajdar, N. D. Sangle

In this paper, we introduce the subclass $SHP^{-m}(\alpha,\beta)$ using integral operator and give sufficient coefficient conditions for normalized harmonic univalent function in the subclass $SHP^{-m}(\alpha,\beta)$.These conditions are also shown to be necessary when the coefficients are negative.

Max Lipton, Gokul Nair

Plateau problems with elastic boundary energies have been of recent theoretical and applied interest. However, strong assumptions have to be made to avoid self-intersections of the boundary curve during energy minimization. We introduce a class of Plateau problems for boundaries with self-repulsive energies that obviates self-contact in energy minimization p

Debraj Chandra, Nur Alam

This article deals with certain star variants of the Scheepers property. We introduce and study the star-$K$-Scheepers property and corresponding game. The relationships between the game corresponding to the star-$K$-Scheepers property and other variants of the Scheepers games are investigated. Furthermore, the relation among the winning strategies of the pl

L. D. Molag

As recently proved in generality by Hedenmalm and Wennman, it is a universal behavior of complex random normal matrix models that one finds a complementary error function behavior at the boundary (also called edge) of the droplet as the matrix size increases. Such behavior is seen both in the density of the eigenvalues, and the correlation kernel, where the

Shin-I Cheng, Yu-Jie Chen, Wei-Chen Chiu, Hung-Yu Tseng

Generating images from hand-drawings is a crucial and fundamental task in content creation. The translation is difficult as there exist infinite possibilities and the different users usually expect different outcomes. Therefore, we propose a unified framework supporting a three-dimensional control over the image synthesis from sketches and strokes based on d