March 2023 arXiv papers — page 125

Maarten van Pruijssen

We develop a theory of Jacobi polynomials for parabolic subgroups of finite reflection groups that specializes to the cases studied by Heckman and Opdam in which the whole group and the trivial group are considered. For the intermediate cases we combine results of Steinberg and Heckman and Opdam to obtain new examples of families of vector-valued orthogonal

Mohammad Otoofi, William J. B. Midgley, Leo Laine, Henderson Leon

It is common to utilise dynamic models to measure the tyre-road friction in real-time. Alternatively, predictive approaches estimate the tyre-road friction by identifying the environmental factors affecting it. This work aims to formulate the problem of friction estimation as a visual perceptual learning task. The problem is broken down into detecting surfac

Steffen Bötzel, Ilya M. Eremin, Frank Lechermann

The normal-state transport properties of superconducting infinite-layer nickelates are investigated within an interacting three-orbital model. It includes effective Ni-$d_{z^2}$, Ni-$d_{x^2-y^2}$ bands as well as the self-doping band degree of freedom. Thermopower, Hall coefficient and optical conductivity are modelled within a quasiparticle approximation to

Hrishikesh Danawe, Serife Tol

Subwavelength imaging of elastic/acoustic waves using phononic crystals (PCs) is limited to a narrow frequency range via the two existing mechanisms that utilize either the intense Bragg scattering in the first phonon band or negative effective properties (left-handed material) in the second (or higher) phonon band. In the first phonon band, the imaging phen

E. C. Schösser, J. M. Burgess, J. Greiner

Context. Recent observations of GRB 200415A, a short and very bright pulse of $\gamma$-rays, have been claimed to be an extragalactic magnetar giant flare (MGF) whose proposed host galaxy is the nearby ${\mathrm{NGC} \, 253}$. However, as the redshift of the transient object was not measured, it is possible that the measured location of the transient on the

Tatsuya Terao

In the matroid partitioning problem, we are given $k$ matroids $\mathcal{M}_1 = (V, \mathcal{I}_1), \dots , \mathcal{M}_k = (V, \mathcal{I}_k)$ defined over a common ground set $V$ of $n$ elements, and we need to find a partitionable set $S \subseteq V$ of largest possible cardinality, denoted by $p$. Here, a set $S \subseteq V$ is called partitionable if th

J. de León, J. Licandro, N. Pinilla-Alonso, N. Moskovitz

The NASA Lucy mission is aimed at the study of the very interesting population of Jupiter Trojans, considered as time capsules from the origin of our solar system. During its journey, the mission will pass near a main belt asteroid, Donaldjohanson. Recently, NASA has announced that a new asteroid in the belt will also be visited by Lucy: 152830 Dinkinesh (19

Michał J. Tyszkiewicz, Pascal Fua, Eduard Trulls

Diffusion models generating images conditionally on text, such as Dall-E 2 and Stable Diffusion, have recently made a splash far beyond the computer vision community. Here, we tackle the related problem of generating point clouds, both unconditionally, and conditionally with images. For the latter, we introduce a novel geometrically-motivated conditioning sc

Anuj Jakhar, Srinivas Kotyada

Let $n$ be a positive integer and $f_n(x)= 1+x+\frac{x^2}{2!}+\cdots + \frac{x^n}{n!}$ denote the $n$-th Taylor polynomial of the exponential function. Let $K = \mathbf{Q}(\theta)$ be an algebraic number field where $\theta$ is a root of $f_n(x)$ and $\mathbf{Z}_K$ denote the ring of algebraic integers of $K$. In this paper, we prove that for any prime $p$,

Julia Steinmetz, Carsten Jentsch

Mack's distribution-free chain ladder reserving model belongs to the most popular approaches in non-life insurance mathematics. Proposed to determine the first two moments of the reserve, it does not allow to identify the whole distribution of the reserve. For this purpose, Mack's model is usually equipped with a tailor-made bootstrap procedure. Although wid

François Gauthier-Clerc, Hoel Le Capitaine, Fabien Claveau, Philippe Chevrel

This article presents an identification benchmark based on data from a public swimming pool in operation. Such a system is both a complex process and easily understandable by all with regard to the stakes. Ultimately, the objective is to reduce the energy bill while maintaining the level of quality of service. This objective is general in scope and is not li

Bruno A. Krinski, Daniel V. Ruiz, Rayson Laroca, Eduardo Todt

Due to the COVID-19 global pandemic, computer-assisted diagnoses of medical images have gained much attention, and robust methods of semantic segmentation of Computed Tomography (CT) images have become highly desirable. In this work, we present a deeper analysis of how data augmentation techniques improve segmentation performance on this problem. We evaluate

Marco Eckhoff, Markus Reiher

Machine learning potentials (MLPs) trained on accurate quantum chemical data can retain the high accuracy, while inflicting little computational demands. On the downside, they need to be trained for each individual system. In recent years, a vast number of MLPs has been trained from scratch because learning additional data typically requires to train again o

Andrea Pasquale, Daniel Krefl, Stefano Carrazza, Frank Nielsen

The estimation of probability density functions is a non trivial task that over the last years has been tackled with machine learning techniques. Successful applications can be obtained using models inspired by the Boltzmann machine (BM) architecture. In this manuscript, the product Jacobi-Theta Boltzmann machine (pJTBM) is introduced as a restricted version

Mohammad Modiri

The brain is a nonlinear and highly Recurrent Neural Network (RNN). This RNN is surprisingly plastic and supports our astonishing ability to learn and execute complex tasks. However, learning is incredibly complicated due to the brain's nonlinear nature and the obscurity of mechanisms for determining the contribution of each synapse to the output error. This

Andressa Cerqueira, Elizaveta Levina

Community structure is common in many real networks, with nodes clustered in groups sharing the same connections patterns. While many community detection methods have been developed for networks with binary edges, few of them are applicable to networks with weighted edges, which are common in practice. We propose a pseudo-likelihood community estimation algo

S. V. Talalov

In this paper, a model of the development of a quantum turbulence in its initial stage is proposed. The origin of the turbulence in the suggested model is the decay of vortex loops with an internal structure. We consider the initial stage of this process, before an equilibrium state is established. As result of our study, the density matrix of developing tur

Quentin Remy

We present an extension to simple s-d models, aiming at simulating ultrafast magnetization dynamics and spin transport in metallic heterostructures. In particular, we consider an alternative spin dissipation channel due to a finite exchange splitting of the s band. From this theory, we show three different mechanisms governing the dynamics of spin accumulati

Zewei Xiong, Meng-Ru Wu, Yong-Zhong Qian

We identify a geometric symmetry on the two-flavor Bloch sphere for collective flavor oscillations of a homogeneous dense neutrino gas. Based on this symmetry, analytical solutions to the periodic bipolar flavor evolution are derived. Using numerical calculations, we show that for configurations without this symmetry, the flavor evolution displays deviations

Fenton John Doolan

Observed first by amateur astronomer Stephen J. O'Meara in the 1970s and then subsequently observed by the Voyager Spacecraft flybys in the early 1980s, it was realised that the 'spokes' flare out like spokes on a bicycle wheel. The observed behaviour of the 'spokes' indicates that they are not governed by gravitational interactions with the planets, moons,

Pranjal Sarmah, Avik De, Umananda Dev Goswami

The possible anisotropic nature in the early phases of the Universe is one of the interesting aspects of study in cosmology. We investigate the evolution of the Universe in terms of few cosmological parameters considering an anisotropic locally rotationally symmetric (LRS) Bianchi type-I spacetime (LRS-BI) under the $f(Q)$ gravity of symmetric teleparallel t

Fabian Hartung, Billy Joe Franks, Tobias Michels, Dennis Wagner

This paper provides the first comprehensive evaluation and analysis of modern (deep-learning) unsupervised anomaly detection methods for chemical process data. We focus on the Tennessee Eastman process dataset, which has been a standard litmus test to benchmark anomaly detection methods for nearly three decades. Our extensive study will facilitate choosing a

Béranger Seguin

For a fixed finite group $G$, we study the fields of definition of geometrically irreducible components of Hurwitz moduli schemes of marked branched $G$-covers of the projective line. The main focus is on determining whether components obtained by "gluing" two other components, both defined over a number field $K$, are also defined over $K$. The article pres

J. C. Bellido, J. Cueto, C. Mora-Corral

We consider Riesz' fractional gradient and a truncated version of it. The equations of nonlocal nonlinear elasticity based on those gradients are known. We perform a formal linearization and arrive at the equations of linear elasticity based on those nonlocal operators. We prove the existence of solutions of the linear equations, notably, by a nonlocal versi

Patrick Stöckle, Michael Sammereier, Bernd Grobauer, Alexander Pretschner

Insecure default values in software settings can be exploited by attackers to compromise the system that runs the software. As a countermeasure, there exist security-configuration guides specifying in detail which values are secure. However, most administrators still refrain from hardening existing systems because the system functionality is feared to deteri

Tarek Bouazza, Pieter Van Goor, Robert Mahony, Tarek Hamel

Feature-based homography estimation approaches rely on extensive image processing for feature extraction and matching, and do not adequately account for the information provided by the image. Therefore, developing efficient direct techniques to extract the homography from images is essential. This paper presents a novel nonlinear direct homography observer t

Zurab Aghdgomelashvili

In the work is considered one of up to now unsolved by Hugo Steinhaus task on having integer length square and located in its plane point that are on integer distances from its vertexes.

Claudio Busatto, Mark van de Wiel

High-dimensional data often arise from clinical genomics research to infer relevant predictors of a particular trait. A way to improve the predictive performance is to include information on the predictors derived from prior knowledge or previous studies. Such information is also referred to as ``co-data''. To this aim, we develop a novel Bayesian model for

Qingnan An, Zhicaho Liu

Suppose that $A,B$ are nuclear, separable ${\rm C}^*$-algebras of stable rank one and real rank zero, $A$ is unital simple, $B$ is stable and $({\rm K}_0(B),{\rm K}_0^+(B))$ is weakly unperforated in the sense of Elliott \cite{Ell}. We show that any unital extension with trivial index maps of $A$ by $B$ is absorbing.

Pedro J. Villasana T., Janusz Klejsa, Lars Villemoes, Per Hedelin

We provide an example of a distribution preserving source separation method, which aims at addressing perceptual shortcomings of state-of-the-art methods. Our approach uses unconditioned generative models of signal sources. Reconstruction is achieved by means of mix-consistent sampling from a distribution conditioned on a realization of a mix. The separated

Anna Naszodi

We apply a pseudo panel analysis of survey data from the years 2010 and 2017 about Americans' self-reported marital preferences and perform some formal tests on the sign and magnitude of the change in educational homophily from the generation of the early Boomers to the late Boomers, as well as from the early GenerationX to the late GenerationX. In the analy

Marian Stengl

In this paper an alternative version of the quantum phase estimation is proposed, in which the Hadamard gates at the beginning are substituted by a quantum Fourier transform. This new circuit coincides with the original one, when the ancilla is initialized with $\ket{0}$. With the help of a projection-based tensor decomposition and closed-form expressions of

Cezara Dragoi, Constantin Enea, Srinidhi Nagendra, Mandayam Srivas

Large-scale, fault-tolerant, distributed systems are the backbone for many critical software services. Since they must execute correctly in a possibly adversarial environment with arbitrary communication delays and failures, the underlying algorithms are intricate. In particular, achieving consistency and data retention relies on intricate consensus (state m

Luting Wang, Yi Liu, Penghui Du, Zihan Ding

Open-vocabulary object detection aims to provide object detectors trained on a fixed set of object categories with the generalizability to detect objects described by arbitrary text queries. Previous methods adopt knowledge distillation to extract knowledge from Pretrained Vision-and-Language Models (PVLMs) and transfer it to detectors. However, due to the n

Anthony Hills, Adam Tsakalidis, Federico Nanni, Ioannis Zachos

There is increasing interest to work with user generated content in social media, especially textual posts over time. Currently there is no consistent way of segmenting user posts into timelines in a meaningful way that improves the quality and cost of manual annotation. Here we propose a set of methods for segmenting longitudinal user posts into timelines l

Zhaoshuai Qi, Jingqi Pang, Yifeng Hao, Yanning Zhang

We construct constraints from consistency between estimated parameters from different spheres, termed inter-sphere consistency. It facilitates more flexible calibration using only two spheres, which has been considered a challenging and not well addressed ill-posed problem.

Jérémy Dousselin

We investigate the large values of class numbers of cubic fields, showing that one can find arbitrary long sequences of "close" abelian cubic number fields with class numbers as large as possible. We also give a first step toward an explicit lower bound for extreme values of class numbers of abelian cubic fields.

Huy Pham, Konstantin Egorov, Alexey Kazakov, Semen Budennyy

Cardiovascular disease remains a significant problem in modern society. Among non-invasive techniques, the electrocardiogram (ECG) is one of the most reliable methods for detecting abnormalities in cardiac activities. However, ECG interpretation requires expert knowledge and it is time-consuming. Developing a novel method to detect the disease early could pr

V. K. Oikonomou

We investigate the effects of short axion kination eras on the energy spectrum of the primordial gravitational waves corresponding to modes that re-enter the Hubble horizon at the post-electroweak symmetry breaking epoch, well within the radiation domination era. Our main assumption is the existence of an extremely weakly coupled hidden sector between the Hi

David Müller, Emerson Melo, Ruben Schlotter

This paper introduces the distributionally robust random utility model (DRO-RUM), which allows the preference shock (unobserved heterogeneity) distribution to be misspecified or unknown. We make three contributions using tools from the literature on robust optimization. First, by exploiting the notion of distributionally robust social surplus function, we sh

Linh T. Dang, Oliver Breunig, Zhiwei Wang, Henry F. Legg

When a charge current is injected into the surface state of a topological insulator (TI), the resulting shift of the spin-momentum-locked Fermi surface leads to the appearance of a net spin polarization. The helical spin structure of the Dirac-cone surface state of a TI should lead to a fixed sign of this spin polarization for a given current direction, but

Jiakang Yuan, Bo Zhang, Xiangchao Yan, Tao Chen

Unsupervised Domain Adaptation (UDA) technique has been explored in 3D cross-domain tasks recently. Though preliminary progress has been made, the performance gap between the UDA-based 3D model and the supervised one trained with fully annotated target domain is still large. This motivates us to consider selecting partial-yet-important target data and labeli

Qian-Qian Chen, Ji-Ming Guo

Let $\mathcal{G}_{n, \beta^*}$ $(\mathcal{G}^*_{n,\beta^*})$ be the set of all (connected) graphs of order $n$ with fractional matching number $\beta^*$. In this paper, the graphs with maximal spectral radius in $\mathcal{G}_{n,\beta^*}$ and $\mathcal{G}^*_{n,\beta^*}$ are characterized, respectively. Moreover, a lower bound for the spectral radius in graphs

Sinya Aoki, Hidenori Fukaya, Jishnu Goswami, Shoji Hashimoto

We report on our finite temperature 2+1 flavor lattice QCD simulation to study the thermodynamic properties of QCD near the (pseudo) critical point employing $N_T=12$ and $16$. The simulation points are chosen along the lines of constant physics. The quark mass for M\"obius domain-wall fermion are tuned by taking into account the residual mass either by fine

Tatsumi Aoyama, Issaku Kanamori, Kazuyuki Kanaya, Hideo Matsufuru

Bridge++ is a general-purpose code set for lattice QCD simulations aiming at a readable, extensible, and portable code while keeping practical high performance. The new version 2.0 employs machine-dependent optimization, enabling flexible data layout in float/double precision, while it was fixed layout and only with the double precision in previous versions.

Mohammad Akil, Serge Nicaise, Ahmet Özkan Özer, Virginie Régnier

In this paper, the stability of longitudinal vibrations for transmission problems of two smart-system designs are studied: (i) a serially-connected Elastic-Piezoelectric-Elastic design with a local damping acting only on the piezoelectric layer and (ii) a serially-connected Piezoelectric-Elastic design with a local damping acting on the elastic part only. Un

Marius Tărnăuceanu

Let $o(G)$ be the average order of a finite group $G$. M. Herzog, P. Longobardi and M. Maj \cite{7} showed that if $G$ is non-solvable and $o(G)=o(A_5)$, then $G\cong A_5$. In this note, we prove that the equality $o(G)=o(A_5)$ does not hold for any finite solvable group $G$. Consequently, up to isomorphism, $A_5$ is determined by its average order.

Noam Soker

I consider a flow structure by which main sequence companions that enter a common envelope evolution (CEE) with giant stars might launch jets even when the accreted gas has a sub-Keplerian specific angular momentum. I first show that after a main sequence star enters the envelope of a giant star the specific angular momentum of the accreted gas is sub-Kepler

Jamy Lafenetre, Ngoc Long Nguyen, Gabriele Facciolo, Thomas Eboli

Image resolution is an important criterion for many applications based on satellite imagery. In this work, we adapt a state-of-the-art kernel regression technique for smartphone camera burst super-resolution to satellites. This technique leverages the local structure of the image to optimally steer the fusion kernels, limiting blur in the final high-resoluti

Jian Sun, Bo Fu

Making causal inferences from observational studies can be challenging when confounders are missing not at random. In such cases, identifying causal effects is often not guaranteed. Motivated by a real example, we consider a treatment-independent missingness assumption under which we establish the identification of causal effects when confounders are missing

Michał Borowski, Iwona Chlebicka, Filomena De Filippis, Błażej Miasojedow

We study classes of weights ensuring the absence and presence of the Lavrentiev's phenomenon for double phase functionals upon every choice of exponents. We introduce a new sharp scale for weights for which there is no Lavrentiev's phenomenon up to a counterexample we provide. This scale embraces the sharp range for $\alpha$-H\"older continuous weights. More

Martina Juhnke-Kubitzke, Liam Solus, Lorenzo Venturello

A cosmological polytope is defined for a given Feynman diagram, and its canonical form may be used to compute the contribution of the Feynman diagram to the wavefunction of certain cosmological models. Given a subdivision of a polytope, its canonical form is obtained as a sum of the canonical forms of the facets of the subdivision. In this paper, we identify

Jean-Bernard Zuber

The counting of partitions according to their genus is revisited. The case of genus 0 -- non-crossing partitions -- is well known. Our approach relies on two pillars: first a functional equation between generating functions, originally written in genus 0 and interpreted graphically by Cvitanovic, is generalized to higher genus; secondly, we show that all par

Sunyoung Kim, Masakazu Kojima

We study the equivalence of several well-known sufficient optimality conditions for a general quadratically constrained quadratic program (QCQP). The conditions are classified in two categories. The first one is for determining an optimal solution and the second one is for finding an optimal value. The first category of conditions includes the existence of a

Norman Marlier, Olivier Brüls, Gilles Louppe

General robotic grippers are challenging to control because of their rich nonsmooth contact dynamics and the many sources of uncertainties due to the environment or sensor noise. In this work, we demonstrate how to compute 6-DoF grasp poses using simulation-based Bayesian inference through the full stochastic forward simulation of the robot in its environmen

Kui Zhao, Jianfei Xiao, Huaiyuan Liu, Linfeng Tu

The application of in-plane magnetic fields to Josephson junctions enables fundamental exploration of quantum phenomena, including Zeeman-driven 0-$\pi$ transitions and planar topological superconductivity. However, intrinsic orbital effects arising from nanoscale rippled geometries in practical devices can dominate phase interference signatures, complicatin

Hemin Ali Qadir, Younghak Shin, Jacob Bergsland, Ilangko Balasingham

An efficient deep learning model that can be implemented in real-time for polyp detection is crucial to reducing polyp miss-rate during screening procedures. Convolutional neural networks (CNNs) are vulnerable to small changes in the input image. A CNN-based model may miss the same polyp appearing in a series of consecutive frames and produce unsubtle detect

Robert Beig

This paper is based on a series of talks given at the ESI program on 'Mathematical Perspectives of Gravitation Beyond the Vacuum Regime' in February 2022. It is meant to be an introduction to the field of relativistic elasticity for readers with a good base in the mathematics of General Relativity with no necessary previous of knowledge of elasticity either

Setareh Medghalchi, Ehsan Karimi, Sang-Hyeok Lee, Benjamin Berkels

High performance sheet metals with a multi-phase microstructure suffer from deformation induced damage formation during forming in the constituent phases but importantly also where these intersect. To capture damage in terms of the physical processes in three dimensions (3D) and its stochastic nature during deformation, two challenges remain to be tackled: F

Klaus Miesenberger, Walther Neuper, Bernhard Stöger, Makarius Wenzel

The paper collects preparatory work for interdisciplinary collaboration between three partners, between (1) expertise in improving accessibility of studies for impaired individuals, (2) expertise in developing educational mathematics software and (3) expertise in designing and implementing interactive proof assistants. The cooperation was started with the go

Ankit Kumar, Andrew Walter, Panagiotis Manolios

Almost all Computer Science programs require students to take a course on the Theory of Computation (ToC) which covers various models of computation such as finite automata, push-down automata and Turing machines. ToC courses tend to give assignments that require paper-and-pencil solutions. Grading such assignments takes time, so students typically receive f

Frederik Krogsdal Jacobsen, Jørgen Villadsen

We present an approach for testing student learning outcomes in a course on automated reasoning using the Isabelle proof assistant. The approach allows us to test both general understanding of formal proofs in various logical proof systems and understanding of proofs in the higher-order logic of Isabelle/HOL in particular. The use of Isabelle enables almost

Joomy Korkut

We have developed a web-based pedagogical proof assistant, the Proof Tree Builder, that lets you apply rules upwards from the initial goal in sequent calculus and Hoare logic for a simple imperative language. We equipped our tool with a basic proof automation feature and Z3 integration. Students in the automated reasoning course at Princeton University used

Davi Romero Vasconcelos

This work presents the system ANITA (Analytic Tableau Proof Assistant) developed for teaching analytic tableaux to computer science students. The tool is written in Python and can be used as a desktop application, or in a web platform. This paper describes the logical system of the tool, explains how the tool is used and compares it to several similar tools.

Joana Teles, Vanda Santos, Pedro Quaresma

The introduction of automated deduction systems in secondary schools face several bottlenecks. Beyond the problems related with the curricula and the teachers, the dissonance between the outcomes of the geometry automated theorem provers and the normal practice of conjecturing and proving in schools is a major barrier to a wider use of such tools in an educa

Thierry Noah Dana-Picard

This survey paper is an expanded version of an invited keynote at the ThEdu'22 workshop, August 2022, in Haifa (Israel). After a short introduction on the developments of CAS, DGS and other useful technologies, we show implications in Mathematics Education, and in the broader frame of STEAM Education. In particular, we discuss the transformation of Mathemati

Margherita Bertè, Kyriaki Kalimeri, Daniela Paolotti

Women remain underrepresented in the labour market. Although significant advancements are being made to increase female participation in the workforce, the gender gap is still far from being bridged. We contribute to the growing literature on gender inequalities in the labour market, evaluating the potential of the LinkedIn estimates to monitor the evolution

Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes

Self-supervised models allow (pre-)training on unlabeled data and therefore have the potential to overcome the need for large annotated cohorts. One leading self-supervised model is the masked autoencoder (MAE) which was developed on natural imaging data. The MAE is masking out a high fraction of visual transformer (ViT) input patches, to then recover the un

Meghashrita Das, Tirupati Bolisetti

Quantum machine learning has established as an interdisciplinary field to overcome limitations of classical machine learning and neural networks. This is a field of research which can prove that quantum computers are able to solve problems with complex correlations between inputs that can be hard for classical computers. This suggests that learning models ma

Ferdinando Auricchio, Giuseppe Toscani, Mattia Zanella

We obtain equilibration rates for a one-dimensional nonlocal Fokker-Planck equation with time-dependent diffusion coefficient and drift, modeling the relaxation of a large swarm of robots, feeling each other in terms of their distance, towards the steady profile characterized by uniform spreading over a finite interval of the line. The result follows by comb

Wei Luo, Zhuocheng Xie, Siyuan Zhang, Julien Guénolé

Brittle topologically close-packed precipitates form in many advanced alloys. Due to their complex structures little is known about their plasticity. Here, we present a strategy to understand and tailor the deformability of these complex phases by considering the Nb-Co {\mu}-phase as an archetypal material. The plasticity of the Nb-Co {\mu}-phase is controll

M. Steiner, O. Attia, D. Ehrenreich, M. Lendl

We searched for potential atmospheric species in KELT-10b, focusing on sodium doublet lines (Na i; 589 nm) and the Balmer alpha line (H $\alpha$; 656 nm) in the transmission spectrum. Furthermore, we measured the planet-orbital alignment with the spin of its host star. We used the Rossiter-McLaughlin Revolutions technique to analyze the local stellar lines o

De-Ming Liu, Zhi-Xi Wu, Jian-Yue Guan

Normal life activities between cells rely crucially on the homeostasis of the cellular microenvironment, but aging and cancer will upset this balance. In this paper, we introduce the microenvironmental feedback mechanism to the growth dynamics of multicellular organisms, which changes the cellular competitive ability, and thereby regulates the growth of mult

A. Chernikov, S. S. Sysoev, E. A. Vashukevich, T. Yu. Golubeva

In this paper we present genetic algorithms based search technique for the linear optics schemes, performing two-qubit quantum gates. We successfully applied this technique for finding heralded two-qubit gates and obtained the new schemes with performance parameters equal to the best currently known. The new simple metrics is introduced which enables compari

Michael Rawson, Christoph Wernhard, Zsolt Zombori, Wolfgang Bibel

Noting that lemmas are a key feature of mathematics, we engage in an investigation of the role of lemmas in automated theorem proving. The paper describes experiments with a combined system involving learning technology that generates useful lemmas for automated theorem provers, demonstrating improvement for several representative systems and solving a hard

Raisa-Ioana Biega, Menno Bokdam, Kai Herrmann, John Mohanraj

Ruddlesden-Popper hybrid halide perovskite are quasi-two-dimensional materials with a layered structure and structural dynamics that are determined by the interplay between the organic and inorganic layers. While their optical properties are governed by confinement effects, the atomistic origin of thermal and electronic properties of these materials is yet t

HyeongTark Han, Sungmin Joo, Takahiro Sakaue, Jae-Hyung Jeon

In a viscoelastic environment, the diffusion of a particle becomes non-Markovian due to the memory effect. An open question is to quantitatively explain how self-propulsion particles with directional memory diffuse in such a medium. Based on simulations and analytic theory, we address this issue with active viscoelastic systems where an active particle is co

Vasil Zhelinski, Boyan Zlatanov

We investigate the connections between UC and UC* properties for ordered pairs of subsets (A,B) in metric spaces, which are involved in the study of existence and uniqueness of best proximity points. We show that the $UC^{*}$ property is included into the UC property. We introduce some new notions: bounded UC (BUC) property and uniformly convex set about a f

Fabian Duenkel, Marcus Niechciol, Markus Risse

In extensive air showers induced by ultra-high energy (UHE) cosmic rays, secondary particles are produced with energies far above those accessible by other means. These extreme energies can be used to search for new physics. We study the effects of isotropic, nonbirefringent Lorentz violation in the photon sector. In case of a photon velocity smaller than th

Thom Badings, Thiago D. Simão, Marnix Suilen, Nils Jansen

This position paper reflects on the state-of-the-art in decision-making under uncertainty. A classical assumption is that probabilities can sufficiently capture all uncertainty in a system. In this paper, the focus is on the uncertainty that goes beyond this classical interpretation, particularly by employing a clear distinction between aleatoric and epistem

Simona Ramos, Morshed Mannan

The potential for blockchain technology to eliminate the middleman and replace the top down hierarchical model of governance with a system of distributed cooperation has opened up many new opportunities, as well as dilemmas. Surpassing the level of acceptance by early tech adopters, the market of smart contracts is now moving towards wider acceptance from re

Zhenguang G. Cai, Xufeng Duan, David A. Haslett, Shuqi Wang

Large language models (LLMs) such as ChatGPT and Vicuna have shown remarkable capacities in comprehending and producing language. However, their internal workings remain a black box, and it is unclear whether LLMs and chatbots can develop humanlike characteristics in language use. Cognitive scientists have devised many experiments that probe, and have made g

Xuanhua Yang, Jianxin Zhao, Shaoguo Liu, Liang Wang

Multi-task learning (MTL) has been widely applied in online advertising and recommender systems. To address the negative transfer issue, recent studies have proposed optimization methods that thoroughly focus on the gradient alignment of directions or magnitudes. However, since prior study has proven that both general and specific knowledge exist in the limi

Stefania De Curtis, Luigi Delle Rose, Andrea Guiggiani, Ángel Gil Muyor

The dynamics of the true-vacuum bubbles nucleated during a first-order phase transition is affected by the distribution functions of the particle species in the plasma, driven out-of-equilibrium by the travelling domain wall. An accurate modelling of this phenomenon is relevant for a quantitative description of phase transitions in the early universe and for

Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson

Classifiers based on neural networks (NN) often lack a measure of uncertainty in the predicted class. We propose a method to estimate the probability mass function (PMF) of the different classes, as well as the covariance of the estimated PMF. First, a local linear approach is used during the training phase to recursively compute the covariance of the parame

Niclas Bernhoff

The linearized Boltzmann collision operator has a central role in many important applications of the Boltzmann equation. Recently some important classical properties of the linearized collision operator for monatomic single species were extended to multicomponent monatomic gases and polyatomic single species. For multicomponent polyatomic gases, the case whe

Mouyuan Sun

The determination of supermassive black hole (SMBH) masses is the key to understanding the host galaxy build-up and the SMBH mass assembly histories. The SMBH masses of non-local quasars are frequently estimated via the single-epoch virial black-hole mass estimators, which may suffer from significant biases. Here we demonstrate a new approach to infer the ma

Kajsa Møllersen, Einar Holsbø

State-of-the-art (SOTA) performance refers to the highest performance achieved by some model on a test sample, preferably under controlled conditions such as public data (reproducibility) or public challenges (independent sample). Thousands of classifiers are applied, and the highest performance becomes the new reference point for a particular problem. In ef

Trung Hieu Le, Marc Antonini, Marc Lambert, Karima Alioua

Remote control vehicles require the transmission of large amounts of data, and video is one of the most important sources for the driver. To ensure reliable video transmission, the encoded video stream is transmitted simultaneously over multiple channels. However, this solution incurs a high transmission cost due to the wireless channel's unreliable and rand

Filippo Riva

A quasistatic model for a horizontally loaded thin elastic composite at small strains is studied. The composite consists of two adjacent plates whose interface behaves in a cohesive fashion with respect to the slip of the two layers. We allow for different loading-unloading regimes, distinguished by the presence of an irreversible variable describing the max

Federico Cacciafesta, Elena Danesi, Long Meng

In this paper we study Strichartz estimates for the half wave, the half Klein-Gordon and the Dirac Equations on compact manifolds without boundary, proving in particular for each of these flows local in time estimates both for the wave and Schroedinger admissible couples (in this latter case with an additional loss of regularity). The strategy for the proof

Christian Meyer, Annika Müller

This paper is concerned with the finite element discretization of the data driven approach according to arXiv:1510.04232 for the solution of PDEs with a material law arising from measurement data. To simplify the setting, we focus on a scalar diffusion problem instead of a problem in elasticity. It is proven that the data convergence analysis from arXiv:1708

Weiyi Sun, Yunyun Fan, Mei Zhao, Han Cui

Low Gain Avalanche Detectors (LGAD) for the High-Granularity Timing Detector (HGTD) are crucial in reducing pileups in the High-Luminosity Large Hadron Collider. Numerous studies have been conducted on the bulk irradiation damage of LGADs. However, few studies have been carried out on the surface irradiation damage of LGAD sensors with shallow carbon implant

Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov

In this paper, we establish novel concentration inequalities for additive functionals of geometrically ergodic Markov chains similar to Rosenthal inequalities for sums of independent random variables. We pay special attention to the dependence of our bounds on the mixing time of the corresponding chain. Precisely, we establish explicit bounds that are linked

Ido Cohen, Eli Appleboim

Research on Koopman operator theory has focused on three key areas for several decades: the mathematical structure of the Koopman eigenfunction space, the basis of this space, and the ability to represent nonlinear dynamics as linear. This study provides a thorough and comprehensive framework for these topics, including theoretical, analytical, and numerical

Sarah Leyder, Jakob Raymaekers, Tim Verdonck

Outliers contaminating data sets are a challenge to statistical estimators. Even a small fraction of outlying observations can heavily influence most classical statistical methods. In this paper we propose generalized spherical principal component analysis, a new robust version of principal component analysis that is based on the generalized spatial sign cov

Jaehyeok Kim, Dongyoon Wee, Dan Xu

We introduce You Only Train Once (YOTO), a dynamic human generation framework, which performs free-viewpoint rendering of different human identities with distinct motions, via only one-time training from monocular videos. Most prior works for the task require individualized optimization for each input video that contains a distinct human identity, leading to

Valentin Boboc

We use Lambek's pregroups and the framework of compositional distributional models of language ("DisCoCat") to study translations from Japanese to English as pairs of functors. Adding decorations to pregroups we show how to handle word order changes between languages.

Dario Bercioux, Diego Frustaglia, Alessandro De Martino

We show that the chiral modes in circular graphene $pn$ junctions provide an advantage for spin manipulation via spin-orbit coupling compared to semiconductor platforms. We derive the effective Hamiltonian for the spin dynamics of the junction's zero modes and calculate their quantum phases. We find a sweet spot in parameter space where the spin is fully in-

Lina Ji, Jie Xiong, Xu Yang

In this paper a martingale problem for super-Brownian motion with interactive branching is derived. The uniqueness of the solution to the martingale problem is obtained by using the pathwise uniqueness of the solution to a corresponding system of SPDEs with proper boundary conditions. The existence of the solution to the martingale problem and the local H\"{