July 2022 arXiv papers — page 91

K. Trachenko

We review fundamental problems involved in liquid theory including both classical and quantum liquids. Understanding classical liquids involves exploring details of their microscopic dynamics and its consequences. Here, we apply the same general idea to quantum liquids. We discuss momentum condensation in liquid helium which is consistent with microscopic dy

L. Sandles, E. Curtis-Lake, S. Charlot, J. Chevallard

The Hubble Frontier Fields represent the opportunity to probe the high-redshift evolution of the main sequence of star-forming galaxies to lower masses than possible in blank fields thanks to foreground lensing of massive galaxy clusters. We use the BEAGLE SED-fitting code to derive stellar masses, $\mathrm{M_{\star}}=\log(M/\mathrm{M_{\odot}})$, SFRs, $\Psi

Nikolaj Glazunov

V.V. Sharko in his papers and books has investigated functions on manifolds and cobordism. Braids intimately connect with functions on manifolds. These connections are represented by mapping class groups of corresponding discs, by fundamental groups of corresponding punctured discs, and by some other topological or algebraic structures. This paper presents s

Mona Azadkia, Fadoua Balabdaoui

Consider the regression problem where the response $Y\in\mathbb{R}$ and the covariate $X\in\mathbb{R}^d$ for $d\geq 1$ are \textit{unmatched}. Under this scenario, we do not have access to pairs of observations from the distribution of $(X, Y)$, but instead, we have separate datasets $\{Y_i\}_{i=1}^n$ and $\{X_j\}_{j=1}^m$, possibly collected from different

Christopher Ryba

A celebrated result of Farahat and Higman constructs an algebra $\mathrm{FH}$ which "interpolates" the centres $Z(\mathbb{Z}S_n)$ of group algebras of the symmetric groups $S_n$. We extend these results from symmetric group algebras to type $A$ Iwahori-Hecke algebras, $H_n(q)$. In particular, we explain how to construct an algebra $\mathrm{FH}_q$ "interpolat

Zishuo Zhao, Xi Chen, Xuefeng Zhang, Yuan Zhou

A major challenge for ridesharing platforms is to guarantee profit and fairness simultaneously, especially in the presence of misaligned incentives of drivers and riders. We focus on the dispatching-pricing problem to maximize the total revenue while keeping both drivers and riders satisfied. We study the computational complexity of the problem, provide a no

Jose María Ezquiaga, Juan García-Bellido, Vincent Vennin

It is generally assumed within the standard cosmological model that initial density perturbations are Gaussian at all scales. However, primordial quantum diffusion unavoidably generates non-Gaussian, exponential tails in the distribution of inflationary perturbations. These exponential tails have direct consequences for the formation of collapsed structures

Arthur Marmin, José Henrique de Morais Goulart, Cédric Févotte

This article introduces new multiplicative updates for nonnegative matrix factorization with the $\beta$-divergence and sparse regularization of one of the two factors (say, the activation matrix). It is well known that the norm of the other factor (the dictionary matrix) needs to be controlled in order to avoid an ill-posed formulation. Standard practice co

Sergio Díaz-Suárez, Roberto Soler

It has been shown in a previous work that torsional Alfv\'en waves can drive turbulence in nonuniform coronal loops with a purely axial magnetic field. Here we explore the role of the magnetic twist. We model a coronal loop as a transversely nonuniform straight flux tube, anchored in the photosphere, and embedded in a uniform coronal environment. We consider

Sara Buson, Andrea Tramacere, Leonard Pfeiffer, Lenz Oswald

Neutrinos are the most elusive particles in the Universe, capable of traveling nearly unimpeded across it. Despite the vast amount of data collected, a long standing and unsolved issue is still the association of high-energy neutrinos with the astrophysical sources that originate them. Amongst the candidate sources of neutrinos there are blazars, a class of

Jana Lasser, Segun Taofeek Aroyehun, Almog Simchon, Fabio Carrella

Increased sharing of untrustworthy information on social media platforms is one of the main challenges of our modern information society. Because information disseminated by political elites is known to shape citizen and media discourse, it is particularly important to examine the quality of information shared by politicians. Here we show that from 2016 onwa

Avijit Duley, Rohit Tyagi, Sandeep B. Bari, A. H. Kelkar

We present the development and performance of a newly built recoil ion momentum spectrometer to study the fragmentation dynamics of ionized molecules. The spectrometer is based on the two-stage Wiley-McLaren geometry and satisfies both time and velocity focusing conditions. An electrostatic lens has been introduced in the drift region to achieve velocity ima

C. R. García, Diego F. Torres, Alessandro Patruno

The $P\dot P$ diagram is a cornerstone of pulsar research. It is used in multiple ways for classifying the population, understanding evolutionary tracks, identifying issues in our theoretical reach, and more. However, we have been looking at the same plot for more than five decades. A fresh appraisal may be healthy. Is the $P\dot P$-diagram the most useful o

Jonas Beuchert, Amanda Matthes, Alex Rogers

Location tracking with global navigation satellite systems (GNSS), such as the GPS, is used in many applications, including the tracking of wild animals for research. Snapshot GNSS is a technique that only requires milliseconds of satellite signals to infer the position of a receiver. This is ideal for low-power applications such as animal tracking. However,

Pengfei Shen, Yulin Shao, Qi Cao, Lu Lu

5G radio access network (RAN) is consuming much more energy than legacy RAN due to the denser deployments of gNodeBs (gNBs) and higher single-gNB power consumption. In an effort to achieve an energy-conserving RAN, this paper develops a dynamic on-off switching paradigm, where the ON/OFF states of gNBs can be dynamically configured according to the evolvemen

Song He, Zhang-Cheng Liu, Yuan Sun

In this work, we perturbatively calculate the modular Hamiltonian to obtain the entanglement entropy in a free fermion theory on a torus with three typical deforma- tions, e.g., T\bar{T} deformation, local bilinear operator deformation, and mass deformation. For T\bar{T} deformation, we find that the leading order correction of entanglement entropy is propor

Latika Aggarwal, Swagato Banerjee, Sunil Bansal, Florian Bernlochner

Belle II is an experiment operating at the intensity frontier. Over the next decades, it will record the decay of billions of bottom mesons, charm hadrons, and tau leptons produced in 10 GeV electron-positron collisions at the SuperKEKB high-luminosity collider at KEK. These data, collected in low-background and kinematically known conditions, will allow us

Thibaut Maury, Sara Morales Serrano, Philippe Loubet, Guido Sonnemann

Like any industry, space activities generate pressures on the environment and strives towards more sustainable activities. A consensus among the European industrial stakeholders and national agencies in the Space sector is emerging on the need to address eco-design through the prism of the environmental Life Cycle Assessment (LCA) methodology. While the use

Matt Menickelly, Stefan M. Wild

We consider the solution of finite-sum minimization problems, such as those appearing in nonlinear least-squares or general empirical risk minimization problems. We are motivated by problems in which the summand functions are computationally expensive and evaluating all summands on every iteration of an optimization method may be undesirable. We present the

Jiawei Zhang, Wenqiang Pu, Zhi-Quan Luo

It is well-known that the lower bound of iteration complexity for solving nonconvex unconstrained optimization problems is $\Omega(1/\epsilon^2)$, which can be achieved by standard gradient descent algorithm when the objective function is smooth. This lower bound still holds for nonconvex constrained problems, while it is still unknown whether a first-order

S. Allak, A. Akyuz, E. Sonbas, K. S. Dhuga

In this work, we deploy archival data from {\it HST}, {\it Chandra}, {\it XMM-Newton}, and {\it Swift-XRT}, to probe the nature of 9 candidate ULXs in NGC 1672. Specifically, our study focuses on using the precise source positions obtained via improved astrometry based on {\it Chandra} and {\it HST} observations to search for and identify potential optical c

Loic Marsot, Peng-Ming Zhang, Peter Horvathy

Using the fact that the horizon of black holes is a Carroll manifold, we show that an ``exotic photon'' i.e. a particle without mass and charge but with anyonic spin, magnetic moment and ``exotic'' charges associated with the 2-parameter central extension of the 2-dimensional Carroll group moves on the horizon of a Kerr-Newman Black Hole consistently with th

Elia Bruè, Camillo De Lellis

In this paper, we consider the forced incompressible Navier-Stokes equations with vanishing viscosity on the three-dimensional torus. We show that there are (classical) solutions for which the dissipation rate of the kinetic energy is bounded away from zero, uniformly in the viscosity parameter, while the body forces are uniformly bounded in some reasonable

Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Ankita Rajaram Naik

As demonstrated by GPT-3 and T5, transformers grow in capability as parameter spaces become larger and larger. However, for tasks that require a large amount of knowledge, non-parametric memory allows models to grow dramatically with a sub-linear increase in computational cost and GPU memory requirements. Recent models such as RAG and REALM have introduced r

Michele Botti, Alessio Fumagalli, Anna Scotti

In this work, we present an uncertainty quantification analysis to determine the influence and importance of some physical parameters in a reactive transport model in fractured porous media. An accurate description of flow and transport in the fractures is key to obtain reliable simulations, however, fractures geometry and physical characteristics pose sever

Natalia Giovenale, Omar Osenda

The information content of one-electron bulk and edge states in semiconductor quantum wells is calculated in the inverted regime, where edge states, topologically protected, are responsible for the conduction in Spin Quantum Hall effect experiments. To study the information content of these states we first calculate realistic two dimensional one-electron sta

Maksim Ulybyshev, Christopher Winterowd, Fakher Assaad, Savvas Zafeiropoulos

In this article we consider a path integral formulation of the Hubbard model based on a SU(2)-symmetrical Hubbard-Stratonovich transformation that couples auxiliary field to the local electronic density. This decoupling is known to have a regular saddle-point structure: each saddle point is a set of elementary field configurations localized in space and imag

Yingli Li

Motivated by Xia-Zhou's recent work on applying symmetry groups to the N-body problem, we will study relative equilibria of the equilateral triangle and the square configurations under $\alpha$-homogeneous and quasi-homogeneous potentials with this method. After linearizing the corresponding second order equations, with appropriate coordinate transformations

Simon Kochen

We strengthen the Free Will Theorem, which proved the spontaneity of particles, based on the free will of the experimenter. The new result is unconditional, and does not require the experimenter's free will to prove the particles' spontaneity.

Yash J. Patel, Sofiene Jerbi, Thomas Bäck, Vedran Dunjko

Variational quantum algorithms such as the Quantum Approximation Optimization Algorithm (QAOA) in recent years have gained popularity as they provide the hope of using NISQ devices to tackle hard combinatorial optimization problems. It is, however, known that at low depth, certain locality constraints of QAOA limit its performance. To go beyond these limitat

Zhaoqi Zang, Richard Batley, Xiangdong Xu, David Z. W. Wang

Extensive empirical studies show that the long distribution tail of travel time and the corresponding unexpected delay can have much more serious consequences than expected or moderate delay. However, the unexpected delay due to the distribution tail of travel time has received limited attention in recent studies of the valuation of travel time variability.

Ziming Shi

Let $D$ be a bounded strictly pseudoconvex domain in $\mathbb{C}^n$. Assuming $bD \in C^{k+3+\alpha}$ where $k$ is a non-negative integer and $0 < \alpha \leq 1$, we show that 1) the Bergman kernel $B(\cdot, w_0) \in C^{k+ \min\{\alpha, \frac12 \} } (\overline D)$, for any $w_0 \in D$; 2) The Bergman projection on $D$ is a bounded operator from $C^{k+\beta}(

D. Boumediene, V. Francais, J. Apostolakis, G. Folger

The CALICE Semi-Digital Hadron Calorimeter technological prototype completed in 2011 is a sampling calorimeter using Glass Resistive Plate Chamber (GRPC) detectors as the active medium. This technology is one of the two options proposed for the hadron calorimeter of the International Large Detector for the International Linear Collider. The prototype was exp

Xin Xu, Yidong Tan

Laser heterodyne interferometry plays a key role in the proof mass's monitor and control by measuring its multiple degrees of freedom motions in the Space Gravitational Wave Detection. Laboratory development of polarization-multiplexing heterodyne interferometer (PMHI) using quadrant photodetectors (QPD) is presented in this paper, intended for measuring the

Boris Bukh, R. Amzi Jeffs

We show that every convex code realizable by compact sets in the plane admits a realization consisting of polygons, and analogously every open convex code in the plane can be realized by interiors of polygons. We give factorial-type bounds on the number of vertices needed to form such realizations. Consequently we show that there is an algorithm to decide wh

Jie Yao, Saleh Rezaeiravesh, Philipp Schlatter, Fazle Hussain

Well-resolved direct numerical simulations (DNSs) have been performed of the flow in a smooth circular pipe of radius $R$ and axial length $10\pi R$ at friction Reynolds numbers up to $Re_\tau=5200$. Various turbulence statistics are documented and compared with other DNS and experimental data in pipes as well as channels.Small but distinct differences betwe

Lorenzo Baldassari, Alice L. Vanel, Pierre Millien

In this paper, we show that it is possible to overcome one of the fundamental limitations of super-resolution microscopy techniques: the necessity to be in an \emph{optically homogeneous} environment. Using recent modal approximation results we show as a proof of concept that it is possible to recover the position of a single point-like emitter in a \emph{kn

Daniel Delbourgo, Heiko Knospe

Following both Ernvall-Mets\"{a}nkyl\"{a} and Ellenberg-Jain-Venkatesh, we study the density of the number of zeroes (i.e. the cyclotomic $\lambda$-invariant) for the $p$-adic zeta-function twisted by a Dirichlet character $\chi$ of any order. We are interested in two cases: (i) the character $\chi$ is fixed and the prime $p$ varies, and (ii) $\text{ord}(\ch

Christian Liedtke

We establish a McKay correspondence for finite and linearly reductive subgroup schemes of $\mathrm{SL}_2$ in positive characteristic. As an application, we obtain a McKay correspondence for all rational double point singularities in characteristic $p\geq7$. We discuss linearly reductive quotient singularities and canonical lifts over the ring of Witt vectors

Kanis Saengchote, Talis Putniņš, Krislert Samphantharak

Decentralized Finance (DeFi) is built on a fundamentally different paradigm: rather than having to trust individuals and institutions, participants in DeFi potentially only have to trust computer code that is enforced by a decentralized network of computers. We examine a natural experiment that exogenously stress tests this alternative paradigm by revealing

Paolo Carniti, Claudio Gotti, Gianluigi Pessina

BiDAQ is a custom filtering and data acquisition system designed for next-gen bolometric experiments dedicated to the search of neutrinoless double beta decay. The system is composed of 12-channel analog-to-digital boards interfaced with FPGA SoC modules that collect and transmit the 24-bit data to the storage computers with a sampling rate up to 25 kHz. Low

David Wiesner, Julian Suk, Sven Dummer, David Svoboda

Methods allowing the synthesis of realistic cell shapes could help generate training data sets to improve cell tracking and segmentation in biomedical images. Deep generative models for cell shape synthesis require a light-weight and flexible representation of the cell shape. However, commonly used voxel-based representations are unsuitable for high-resoluti

Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi

Quantization is one of the most applied Deep Neural Network (DNN) compression strategies, when deploying a trained DNN model on an embedded system or a cell phone. This is owing to its simplicity and adaptability to a wide range of applications and circumstances, as opposed to specific Artificial Intelligence (AI) accelerators and compilers that are often de

Kostiantyn Iusenko, John MacQuarrie

In this expository article, we give a self-contained introduction to the wonderfully well-behaved class of pseudocompact algebras, focusing on the foundational classes of semisimple and separable algebras. We give characterizations of such algebras analogous to those for finite dimensional algebras. We give a self-contained proof of the Wedderburn-Malcev The

Tommaso Maria Botta

There are multiple conjectures relating the cohomological Hall algebras (CoHAs) of certain substacks of the moduli stack of representations of a quiver $Q$ to the Yangian $Y^{Q}_{MO}$ by Maulik-Okounkov, whose construction is based on the notion of stable envelopes of Nakajima varieties. In this article, we introduce the cohomological Hall algebra of the mod

Yair Antman, Andres Gil-Molina, Ohad Westreich, Xingchen Ji

The lack of high power integrated lasers have been limiting silicon photonics. Despite much progress made in chip-scale laser integration, power remains below the level required for key applications. The main inhibiting factor for high power is the low energy efficiency at high pumping currents, dictated by the small size of the active device. Here we break

Marie-Sophie Hartig, Sönke Schuster, Gerhard Heinzel, Gudrun Wanner

This paper is the second in a set of two investigating tilt-to-length (TTL) coupling. TTL describes the cross-coupling of angular or translational jitter into an interferometric phase signal and is an important noise source in precision interferometers, including space gravitational wave detectors like LISA. We discussed in 10.1088/2040-8986/ac675e the TTL c

Dhruv Makwana, Subhrajit Nag, Onkar Susladkar, Gayatri Deshmukh

We propose a novel deep learning model named ACLNet, for cloud segmentation from ground images. ACLNet uses both deep neural network and machine learning (ML) algorithm to extract complementary features. Specifically, it uses EfficientNet-B0 as the backbone, "`a trous spatial pyramid pooling" (ASPP) to learn at multiple receptive fields, and "global attentio

Alex G. Dias, Julio Leite, B. L. Sánchez-Vega

Motivated by a possible interplay between the mechanism of dynamical symmetry breaking and the seesaw mechanism for generating fermion masses, we present a scale-invariant model that extends the gauge symmetry of the Standard Model electroweak sector to SU(3)$_L\otimes$U(1)$_X\otimes$U(1)$_N$, with a built-in $B-L$ symmetry. The model is based on the symmetr

François Grolleau, Francois Petit, Raphaël Porcher

Individualized treatment rules (ITRs) are deterministic decision rules that recommend treatments to individuals based on their characteristics. Though ubiquitous in medicine, ITRs are hardly ever evaluated in randomized controlled trials. To evaluate ITRs from observational data, we introduce a new probabilistic model and distinguish two situations: i) the s

Giovanni Franzina, Danilo Licheri

For a non-local semilinear eigenvalue problem, we prove simplicity and isolation of the first eigenvalue with homogeneous Dirichlet boundary conditions on open sets supporting a suitable compact Sobolev embedding.

José Pombal, André F. Cruz, João Bravo, Pedro Saleiro

In recent years, machine learning algorithms have become ubiquitous in a multitude of high-stakes decision-making applications. The unparalleled ability of machine learning algorithms to learn patterns from data also enables them to incorporate biases embedded within. A biased model can then make decisions that disproportionately harm certain groups in socie

Sean R. Sinclair, Felipe Frujeri, Ching-An Cheng, Luke Marshall

Many resource management problems require sequential decision-making under uncertainty, where the only uncertainty affecting the decision outcomes are exogenous variables outside the control of the decision-maker. We model these problems as Exo-MDPs (Markov Decision Processes with Exogenous Inputs) and design a class of data-efficient algorithms for them ter

Neophytos Charalambides, Mert Pilanci, Alfred Hero

A cumbersome operation in many scientific fields, is inverting large full-rank matrices. In this paper, we propose a coded computing approach for recovering matrix inverse approximations. We first present an approximate matrix inversion algorithm which does not require a matrix factorization, but uses a black-box least squares optimization solver as a subrou

Quentin G. Bailey, Jennifer L. James, Janessa R. Slone

We review the status of tests of spacetime symmetries with gravity. Recent theoretical and experimental work has involved gravitational wave signals, precision solar-system tests, and sensitive laboratory tests searching for violations of spacetime symmetries. We present some new theoretical results relevant for short-range gravity tests, with features of mu

Jiayu Yao, Sonali Parbhoo, Weiwei Pan, Finale Doshi-Velez

We develop a Reinforcement Learning (RL) framework for improving an existing behavior policy via sparse, user-interpretable changes. Our goal is to make minimal changes while gaining as much benefit as possible. We define a minimal change as having a sparse, global contrastive explanation between the original and proposed policy. We improve the current polic

E. Iancu, A. H. Mueller, D. N. Triantafyllopoulos, S. Y. Wei

Within the colour dipole picture for deep inelastic scattering at small Bjorken $x$, we study the production of a pair of relatively hard jets via coherent diffraction. By "relatively hard" we mean that the transverse momenta of the two jets -- the quark ($q$) and the antiquark ($\bar{q}$) generated by the decay of the virtual photon -- are much larger than

Prashant Bhat, Bahram Zonooz, Elahe Arani

Continual learning (CL) over non-stationary data streams remains one of the long-standing challenges in deep neural networks (DNNs) as they are prone to catastrophic forgetting. CL models can benefit from self-supervised pre-training as it enables learning more generalizable task-agnostic features. However, the effect of self-supervised pre-training diminish

Ryan Curry, R. Amzi Jeffs, Nora Youngs, Ziyu Zhao

We prove algebraic and combinatorial characterizations of the class of inductively pierced codes, resolving a conjecture of Gross, Obatake, and Youngs. Starting from an algebraic invariant of a code called its canonical form, we explain how to compute a piercing order in polynomial time, if one exists. Given a piercing order of a code, we explain how to cons

Salar Mohtaj, Babak Naderi, Sebastian Möller, Faraz Maschhur

Text readability assessment has a wide range of applications for different target people, from language learners to people with disabilities. The fast pace of textual content production on the web makes it impossible to measure text complexity without the benefit of machine learning and natural language processing techniques. Although various research addres

Nayandeep Deka Baruah, Hirakjyoti Das, Pranjal Talukdar

In the eleventh paper in the series on MacMahons partition analysis, Andrews and Paule [1] introduced the $k$ elongated partition diamonds. Recently, they [2] revisited the topic. Let $d_k(n)$ count the partitions obtained by adding the links of the $k$ elongated plane partition diamonds of length $n$. Andrews and Paule [2] obtained several generating functi

Andreas Kyritsakis

Field electron emission from nanometer-scale objects deviates from the predictions of the classical emission theory as both the electrostatic potential curves within the tunneling region and the image potential deviates from the planar one. This impels the inclusion of additional correction terms in the potential barrier. At the apex of a tip-like rotational

Suryansh Kumar, Luc Van Gool

This paper advocates the use of organic priors in classical non-rigid structure from motion (NRSfM). By organic priors, we mean invaluable intermediate prior information intrinsic to the NRSfM matrix factorization theory. It is shown that such priors reside in the factorized matrices, and quite surprisingly, existing methods generally disregard them. The pap

Filip Ilic, Thomas Pock, Richard P. Wildes

Intuition might suggest that motion and dynamic information are key to video-based action recognition. In contrast, there is evidence that state-of-the-art deep-learning video understanding architectures are biased toward static information available in single frames. Presently, a methodology and corresponding dataset to isolate the effects of dynamic inform

Perry Kleinhenz

Energy decay is established for the damped wave equation on compact Riemannian manifolds where the damping coefficient is allowed to depend on time. Using a time dependent observability inequality, it is shown that the energy of solutions decays at an exponential rate if the damping coefficient satisfies a time dependent analogue of the classical geometric c

Shweta Sharma, Praveen C. Srivastava, Anil Kumar, Toshio Suzuki

In the present work, we report a comprehensive shell-model study of the $\log ft$ values for the forbidden $\beta^-$ decay transitions in the north-east region of $^{208}$Pb. For this we have considered $^{210-215}$Pb $\rightarrow$ $^{210-215}$Bi and $^{210-215}$Bi $\rightarrow$ $^{210-215}$Po transitions. We have performed shell-model calculation using KHPE

C. A. L. Bailer-Jones

Close encounters of stars to the Sun could affect life on Earth through gravitational perturbations of comets in the Oort cloud or exposure to ionizing radiation. By integrating orbits through the Galactic potential, I identify which of 33 million stars in Gaia DR3 with complete phase space information come close to the Sun. 61 stars formally approach within

Patrik Joslin Kenfack, Kamil Sabbagh, Adín Ramírez Rivera, Adil Khan

Fairness has become an essential problem in many domains of Machine Learning (ML), such as classification, natural language processing, and Generative Adversarial Networks (GANs). In this research effort, we study the unfairness of GANs. We formally define a new fairness notion for generative models in terms of the distribution of generated samples sharing t

Marcela Reale, David Margarit, Ariel Scagliotti, Lilia Romanelli

In a previous work, we presented a model that integrates cancer cell differentiation and immunotherapy, analysing a particular therapy against cancer stem cells by cytotoxic cell vaccines. As every biological system is exposed to random fluctuations, it is important to study its stochasticity. The influence of demographic and multiplicative noise in the syst

Enrico Segre

An accurate method for warping images is presented. Differently from most commonly used techniques, this method guarantees the conservation of the intensity of the transformed image, evaluated as the sum of its pixel values over the whole image or over corresponding transformed subregions of it. Such property is mandatory for quantitative analysis, as, for i

S. Ma, J. Z. Liu, Y. Zhang, Q. S. Hu

We performed new photometric observations for two contact binaries (i.e., CRTS J025408.1+265957 and CRTS J012111.1+272933), which were observed by the 1.0-m telescope at Xingjiang Astronomical Observatory. From our light curves and several survey data, we derived several sets of photometric solutions. We found that CRTS J025408.1+265957 and CRTS J012111.1+27

Ziyan Yin

In modern data science, it is common that large-scale data are stored and processed parallelly across a great number of locations. For reasons including confidentiality concerns, only limited data information from each parallel center is eligible to be transferred. To solve these problems more efficiently, a group of communication-efficient methods are being

Wuyang Luo, Su Yang, Hong Wang, Bo Long

Semantic image editing utilizes local semantic label maps to generate the desired content in the edited region. A recent work borrows SPADE block to achieve semantic image editing. However, it cannot produce pleasing results due to style discrepancy between the edited region and surrounding pixels. We attribute this to the fact that SPADE only uses an image-

Joel Foisy, Justin Raimondi

The purpose of this paper is to show that all maximally planar subgraphs of graphs in the Petersen Family have associated conflict graphs unbalanced. All but three strong conflict graphs arising from Petersen Family Graphs are unbalanced, and the three that are balanced all come from $K_{4,4}-e$.

Nicola Fusco, Domenico Angelo La Manna

In this paper we study two different weighted isoperimetric inequalities. In the first part of the paper we prove a sharp stability result for the isoperimetric inequality with a log-convex weight. In the second part we analize the behavior of a negative power weight for the perimeter thus providing a complete picture of the isoperimetric problem in this con

Guillaume Cébron, Nicolas Gilliers

Voiculescu's freeness emerges in computing the asymptotic of spectra of polynomials on $N\times N$ random matrices with eigenspaces in generic positions: they are randomly rotated with a uniform unitary random matrix $U_N$. In this article we elaborate on the previous point by proposing a random matrix model, which we name the Vortex model, where $U_N$ has t

Vaclav Kotesovec

The exponential generating function for the sequence A143405 in the OEIS is exp(exp(x)*(exp(x) - 1)). This paper analyzes the more general generating function exp(m*exp(b*x) + r*exp(d*x) + s) and provides asymptotics for the sequences A143405, A355291, A002872, A002874 and others in the OEIS.

Huijuan Zhou, Yong Chen

A series of new soliton solutions are presented for the inhomogeneous variable coefficient Hirota equation by using the Riemann Hilbert method and transformation relationship. First, through a standard dressing procedure, the N-soliton matrix associated with the simple zeros in the Riemann Hilbert problem for the Hirota equation is constructed. Then the N-so

Leila Mizrahi, Shyam Nandan, William Savran, Stefan Wiemer

The development of new earthquake forecasting models is often motivated by one of the following complementary goals: to gain new insights into the governing physics and to produce improved forecasts quantified by objective metrics. Often, one comes at the cost of the other. Here, we propose a question-driven ensemble (QDE) modeling approach to address both g

Simon Eberle, Arnulf Jentzen, Adrian Riekert, Georg Weiss

The training of artificial neural networks (ANNs) is nowadays a highly relevant algorithmic procedure with many applications in science and industry. Roughly speaking, ANNs can be regarded as iterated compositions between affine linear functions and certain fixed nonlinear functions, which are usually multidimensional versions of a one-dimensional so-called

Mohab Abdalla, Clément Zrounba, Raphael Cardoso, Paul Jimenez

Reservoir computing is an analog bio-inspired computation model for efficiently processing time-dependent signals, the photonic implementations of which promise a combination of massive parallel information processing, low power consumption, and high speed operation. However, most implementations, especially for the case of time-delay reservoir computing (TD

Joel Foisy

Tutte showed that a graph $G$ is planar if and only if the conflict graph associated to every cycle of $G$ is bipartite. We define a (not necessarily unique) signed conflict graph associated to a maximally planar subgraph of a nonplanar graph such that if $G$ has a flat embedding, every possible conflict graph associated to every maximally planar subgraph of

Bernadette Charron-Bost, Louis Penet de Monterno

We consider the fundamental problem of clock synchronization in a synchronous multi-agent system. Each agent holds a clock with an arbitrary initial value, and clocks must eventually indicate the same value. Previous algorithms worked in static networks with drastic connectivity properties and assumed that global information is available at each agent. In th

Danna Xue, Fei Yang, Pei Wang, Luis Herranz

Accurate semantic segmentation models typically require significant computational resources, inhibiting their use in practical applications. Recent works rely on well-crafted lightweight models to achieve fast inference. However, these models cannot flexibly adapt to varying accuracy and efficiency requirements. In this paper, we propose a simple but effecti

John Donaghy, Kai Germaschewski

The inclusion of kinetic effects into fluid models has been a long standing problem in magnetic reconnection and plasma physics. Generally the pressure tensor is reduced to a scalar which is an approximation used to aid in the modeling of large scale global systems such as the Earth's magnetosphere. This unfortunately omits important kinetic physics which ha

Erik Prume, Stefanie Reese, Michael Ortiz

We extend the model-free Data-Driven computing paradigm to solids and structures that are stochastic due to intrinsic randomness in the material behavior. The behavior of such materials is characterized by a likelihood measure instead of a constitutive relation. We specifically assume that the material likelihood measure is known only through an empirical po

Rahool Kumar Barman, Geneviève Bélanger, Biplob Bhattacherjee, Rohini M. Godbole

We explore the parameter space of the phenomenological Minimal Supersymmetric Standard Model (pMSSM) with a light neutralino thermal dark matter ($m_{\tilde{\chi}_1^0} \leq m_h/2$) that is consistent with current collider and astrophysical constraints. We consider both positive and negative values of the higgsino mass parameter ($\mu$). Our investigation sho

Miguel Romero, Felipe Kenji Nakano, Jorge Finke, Camilo Rocha

The availability of genomic data has grown exponentially in the last decade, mainly due to the development of new sequencing technologies. Based on the interactions between genes (and gene products) extracted from the increasing genomic data, numerous studies have focused on the identification of associations between genes and functions. While these studies

Subash Neupane, Jesse Ables, William Anderson, Sudip Mittal

The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity challenges has gained traction in industry and academia, partially as a result of widespread malware attacks on critical systems such as cloud infrastructures and government institutions. Intrusion Detection Systems (IDS), using some forms of AI, have received widespre

Bo Hu, Tat-Jen Cham

Some group activities, such as team sports and choreographed dances, involve closely coupled interaction between participants. Here we investigate the tasks of inferring and predicting participant behavior, in terms of motion paths and actions, under such conditions. We narrow the problem to that of estimating how a set target participants react to the behav

Julien Cornebise, Ivan Oršolić, Freddie Kalaitzis

Analyzing the planet at scale with satellite imagery and machine learning is a dream that has been constantly hindered by the cost of difficult-to-access highly-representative high-resolution imagery. To remediate this, we introduce here the WorldStrat dataset. The largest and most varied such publicly available dataset, at Airbus SPOT 6/7 satellites' high r

Sreejani Karmakar, Souren Adhikary, Sudipta Dutta

In this work, using a hybrid density functional theory (DFT) based calculation, we propose a new two-dimensional (2D) B-C-N material, $g-B_{3}C_{2}N_{3}$, with the promising prospect of metal-free photocatalysis. A comprehensive investigation demonstrates that it is a near ultraviolet (UV) absorbing direct band gap (3.69 eV) semiconductor with robust dynamic

Igor Franović, Sebastian Eydam

We disclose a new class of patterns, called patched patterns, in arrays of non-locally coupled excitable units with attractive and repulsive interactions. Self-organization process involves formation of two types of patches, majority and minority ones, characterized by uniform average spiking frequencies. Patched patterns may be temporally periodic, quasiper

Vasco Grossmann, Lars Schmarje, Reinhard Koch

High-quality data is a key aspect of modern machine learning. However, labels generated by humans suffer from issues like label noise and class ambiguities. We raise the question of whether hard labels are sufficient to represent the underlying ground truth distribution in the presence of these inherent imprecision. Therefore, we compare the disparity of lea

Jose A. R. Cembranos, Luis J. Garay, Sergio A. Ortega

Accelerating black holes are described by the so-called C-metric. In this work, we analyse the causal structure of such black holes by using null geodesics. We construct explicitly the relevant Penrose diagrams. First, we recover well-known results associated with the sub-accelerating black holes. Then, we extend the study to the super-accelerating case, in

Paolo Boldi, Flavio Furia, Sebastiano Vigna

Is it always beneficial to create a new relationship (have a new follower/friend) in a social network? This question can be formally stated as a property of the centrality measure that defines the importance of the actors of the network. Score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity mea

Daniela De Silva, Seongmin Jeon, Henrik Shahgholian

We study vector-valued almost minimizers of the energy functional $$\int_D\left(|\nabla\mathbf{u}|^2+\frac2{1+q}\left(\lambda_+(x)|\mathbf{u}^+|^{q+1}+\lambda_-(x)|\mathbf{u}^-|^{q+1}\right)\right)dx,\quad0<q<1.$$ For H\"older continuous coefficients $\lambda_\pm(x)>0$, we take the epiperimetric inequality approach and prove the regularity for both almost mi

Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo

Tackling new machine learning problems with neural networks always means optimizing numerous hyperparameters that define their structure and strongly impact their performances. In this work, we study the use of goal-oriented sensitivity analysis, based on the Hilbert-Schmidt Independence Criterion (HSIC), for hyperparameter analysis and optimization. Hyperpa

Amirkoushyar Ziabari, Derek C. Rose, Abbas Shirinifard, David Solecki

Microscopy imaging techniques are instrumental for characterization and analysis of biological structures. As these techniques typically render 3D visualization of cells by stacking 2D projections, issues such as out-of-plane excitation and low resolution in the $z$-axis may pose challenges (even for human experts) to detect individual cells in 3D volumes as

Lars Schmarje, Vasco Grossmann, Claudius Zelenka, Sabine Dippel

High-quality data is necessary for modern machine learning. However, the acquisition of such data is difficult due to noisy and ambiguous annotations of humans. The aggregation of such annotations to determine the label of an image leads to a lower data quality. We propose a data-centric image classification benchmark with ten real-world datasets and multipl