July 2022 arXiv papers — page 79

Anup Biswas, Somnath Pradhan

In this article, we study the ergodic risk-sensitive control problem for controlled regime-switching diffusions. Under a blanket stability hypothesis, we solve the associated nonlinear eigenvalue problem for weakly coupled systems and characterize the optimal stationary Markov controls via a suitable verification theorem. We also consider the near-monotone c

Eugene A. Feinberg, Pavlo O. Kasyanov

This paper studies weak continuity of nonlinear filters. It is well-known that Borel measurability of transition probabilities for problems with incomplete state observations is preserved when the original discrete-time process is replaced with the process whose states are belief probabilities. It is also known that the similar preservation may not hold for

Marina Costantini, Nikolaos Liakopoulos, Panayotis Mertikopoulos, Thrasyvoulos Spyropoulos

In decentralized optimization environments, each agent $i$ in a network of $n$ nodes has its own private function $f_i$, and nodes communicate with their neighbors to cooperatively minimize the aggregate objective $\sum_{i=1}^n f_i$. In this setting, synchronizing the nodes' updates incurs significant communication overhead and computational costs, so much o

Wolfgang Dahmen, Harald Monsuur, Rob Stevenson

This paper is concerned with the design and analysis of least squares solvers for ill-posed PDEs that are conditionally stable. The norms and the regularization term used in the least squares functional are determined by the ingredients of the conditional stability assumption. We are then able to establish a general error bound that, in view of the condition

Valerii Pchelintsev, Alexander Ukhlov

We study the weak regularity of mappings inverse to weighted Sobolev homeomorphisms $\varphi:\Omega\to\widetilde{\Omega}$, where $\Omega$ and $\widetilde{\Omega}$ are domains in $\mathbb R^n$. Using the weak regularity of inverse mappings we obtain the composition duality property of composition operators on weighted Sobolev spaces.

Emmanuel Senft, David Porfirio, Katie Winkle

People who need robots are often not the same as people who can program them. This key observation in human-robot interaction (HRI) has lead to a number of challenges when developing robotic applications, since developers must understand the exact needs of end-users. Participatory Design (PD), the process of including stakeholders such as end users early in

Ronghui Mu, Wenjie Ruan, Leandro S. Marcolino, Qiang Ni

3D point cloud models are widely applied in safety-critical scenes, which delivers an urgent need to obtain more solid proofs to verify the robustness of models. Existing verification method for point cloud model is time-expensive and computationally unattainable on large networks. Additionally, they cannot handle the complete PointNet model with joint align

Thomas Meissner, David Albrecht

Debt aversion can have severe adverse effects on financial decision-making. We propose a model of debt aversion, and design an experiment involving real debt and saving contracts, to elicit and jointly estimate debt aversion with preferences over time, risk and losses. Structural estimations reveal that the vast majority of participants (89%) are debt averse

Antonello Pellecchia, Piet Verwilligen, Anna Stamerra

Triple-GEM detectors for the GE2/1 and ME0 stations of the endcap muon system for the Phase-2 upgrade of the CMS Experiment have been operated in a test beam to measure their efficiency and spatial resolution, together with a high spatial resolution triple- GEM tracker. A production module of GE2/1 detectors and a prototype ME0 detector show excellent local

Qi Zhou, Di Guo, Shi-Qing Kuang, Qin-He Yang

In this letter, we perform partial wave decomposition on coupled-channel scattering amplitudes, $J/\psi J/\psi$-$J/\psi \psi(2S)$-$J/\psi \psi(3770)$, to study the resonance appears in these processes. Effective Lagrangians are used to describe the interactions of four charmed vector mesons, and the scattering amplitudes are calculated up to the next-to-lead

Andrea C. Burgess, Robert D. Luther, David A. Pike

A graph or hypergraph is said to be vertex-transitive if its automorphism group acts transitively upon its vertices. A classic theorem of Mader asserts that every connected vertex-transitive graph is maximally edge-connected. We generalise this result to hypergraphs and show that every connected linear uniform vertex-transitive hypergraph is maximally edge-c

Amir Levinson

It is shown that force-free electrodynamics (FFE) breaks down in regions where $B^2 -E^2 <0$ (electric zones) even if $\pmb{E}\cdot\pmb{B} =0$. Spontaneous creation of such regions will inevitably lead to plasma oscillations that will subsequently decay over a few periods via anomalous heating and, under certain conditions, emission of high energy quanta, un

Chong Chen, Ying D. Liu, Bei Zhu

We investigate the source eruption, propagation and expansion characteristics, and heliospheric impacts of the 2020 November 29 coronal mass ejection (CME) and associated shock, using remote sensing and in situ observations from multiple spacecraft. A potential--field source--surface model is employed to examine the coronal magnetic fields surrounding the so

Taeho Kim, Kyoung-kuk Kim, Eunhye Song

We consider an expected-value ranking and selection (R&S) problem where all k solutions' simulation outputs depend on a common parameter whose uncertainty can be modeled by a distribution. We define the most probable best (MPB) to be the solution that has the largest probability of being optimal with respect to the distribution and design an efficient sequen

Xinbu Cheng, Zixiang Xu

Motivated by a problem in theoretical computer science suggested by Wigderson, Alon and Ben-Eliezer studied the following extremal problem systematically one decade ago. Given a graph $H$, let $C(n,H)$ be the minimum number $k$ such that the following holds. There are $n$ colorings of $E(K_{n})$ with $k$ colors, each associated with one of the vertices of $K

Lorenzo Gotta, Leonardo Mazza, Pascal Simon, Guillaume Roux

We construct a 1D model Hamiltonian of spinless fermions for which the spinless analogue of $\eta$-pairing states are quantum many-body scars of the model. These states are excited states and display subvolume entanglement entropy scaling; they form a tower of states that are equally spaced in energy (resulting in periodic oscillations in the Loschmidt echo

Geoffrey Goodell

In this article, we consider the roles of tokens and distributed ledgers in digital payment systems. We present a brief taxonomy of digital payment systems that use tokens, and we address the different models for how distributed ledger technology can support digital payment systems in general. We offer guidance on the salient features of digital payment syst

Wei Zeng, Yi Ling, Qing-Quan Jiang

We investigate the photon sphere and the extremal stable circular orbit (ESCO) for massive particles over a recently proposed regular black holes with sub-Planckian curvature and Minkowskian core. We derive the effective potential for geodesic orbits and determine the radius of circular photon orbits, with an analysis on the stability of these orbits. We ext

Giordano d'Aloisio, Antinisca Di Marco, Giovanni Stilo

The recently increased complexity of Machine Learning (ML) methods, led to the necessity to lighten both the research and industry development processes. ML pipelines have become an essential tool for experts of many domains, data scientists and researchers, allowing them to easily put together several ML models to cover the full analytic process starting fr

Elyes Boughattas

Over the function field of a complex algebraic curve, strong approximation off a non-empty finite set of places holds for the complement of a codimension $2$ closed subset in a homogeneous space under a semisimple algebraic group, and for the complement of a codimension $2$ closed subset in an affine smooth complete intersection of low degree.

Guillermo Lopez-Polin, Hugo Aramberri, Jorge Marques-Marchan, Benjamin I. Weintrub

The anomalous Nernst effect (ANE) is a thermomagnetic phenomenon with potential applications in thermal energy harvesting. While many recent works studied the approaches to increase the ANE coefficient of materials, relatively little effort was devoted to increasing the power supplied by the effect. Here we demonstrate a nanofabricated device with record pow

Alva Bechlenberg, Yanji Wei, Bayu Jayawardhana, Antonis I. Vakis

The aim of this work is to assess the influence of different degrees of adaptability of the power take-off (PTO) system on the power absorption of dense wave energy converter (WEC) arrays. The adaptability is included in simulations through a transmission ratio that scales the force actuating the PTO relative to the force generated by the motion of a floater

Benjamin Alt, Darko Katic, Rainer Jäkel, Michael Beetz

In both industrial and service domains, a central benefit of the use of robots is their ability to quickly and reliably execute repetitive tasks. However, even relatively simple peg-in-hole tasks are typically subject to stochastic variations, requiring search motions to find relevant features such as holes. While search improves robustness, it comes at the

Xiaoyu Dong, Mark Rudelson

An $n \times n$ matrix with $\pm 1$ entries which acts on $\mathbb{R}^n$ as a scaled isometry is called Hadamard. Such matrices exist in some, but not all dimensions. Combining number-theoretic and probabilistic tools we construct matrices with $\pm 1$ entries which act as approximate scaled isometries in $\mathbb{R}^n$ for all $n$. More precisely, the matri

Wencan Cheng, Jong Hwan Ko

Scene flow estimation, which extracts point-wise motion between scenes, is becoming a crucial task in many computer vision tasks. However, all of the existing estimation methods utilize only the unidirectional features, restricting the accuracy and generality. This paper presents a novel scene flow estimation architecture using bidirectional flow embedding l

Marco Zamparo

In this paper we investigate the normal and the large fluctuations of additive functionals associated with a stochastic process under a general non-Poissonian resetting mechanism. Cumulative functionals of regenerative processes are very close to renewal-reward processes and inherit most of the properties of the latter. Here we review and use the classical l

Filip Lemic, Jakob Struye, Jeroen Famaey

Full-immersive multiuser Virtual Reality (VR) envisions supporting unconstrained mobility of the users in the virtual worlds, while at the same time constraining their physical movements inside VR setups through redirected walking. For enabling delivery of high data rate video content in real-time, the supporting wireless networks will leverage highly direct

Sayan Bhattacharya, Peter Kiss, Thatchaphol Saranurak

In the dynamic linear program (LP) problem, we are given an LP undergoing updates and we need to maintain an approximately optimal solution. Recently, significant attention (e.g., [Gupta et al. STOC'17; Arar et al. ICALP'18, Wajc STOC'20]) has been devoted to the study of special cases of dynamic packing and covering LPs, such as the dynamic fractional match

Michele N. Notarnicola, Matteo G. A. Paris, Stefano Olivares

We propose a near-optimum receiver for the discrimination of binary phase-shift-keyed coherent states employing photon-number-resolving detectors. The receiver exploits a discrimination strategy based on both the so-called homodyne-like and the direct detection, thus resulting in a hybrid scheme. We analyse the performance and the robustness of the proposed

Guoxuan Xia, Christos-Savvas Bouganis

The ability to detect Out-of-Distribution (OOD) data is important in safety-critical applications of deep learning. The aim is to separate In-Distribution (ID) data drawn from the training distribution from OOD data using a measure of uncertainty extracted from a deep neural network. Deep Ensembles are a well-established method of improving the quality of un

Fernando Casas, Jesús María Sanz-Serna, Luke Shaw

We study Hamiltonian Monte Carlo (HMC) samplers based on splitting the Hamiltonian $H$ as $H_0(\theta,p)+U_1(\theta)$, where $H_0$ is quadratic and $U_1$ small. We show that, in general, such samplers suffer from stepsize stability restrictions similar to those of algorithms based on the standard leapfrog integrator. The restrictions may be circumvented by p

Rémi Jaoui, Rahim Moosa

A new tool for the model theory of differentially closed fields and of compact complex manifolds is here developed. In such settings, it is shown that a type internal to the field of constants (resp. to the projective line) admits a maximal image whose binding group is an abelian variety. The properties of such "abelian reductions" are investigated in the Ga

Mrityunjay Singh, Saeed Mahmoodpour, Reza Ershadnia, Mohamad Reza Soltanian

Geothermal energy is an infinite energy source for the present human society. Energy extraction from the deep subsurface requires engineering using a working fluid that circulates between well doublet. Due to its thermal properties, CO2 is an ideal option as a heat transfer fluid. By using CO2, working fluid loss is an advantage compared to other working flu

Alex F. Spies, Alessandra Russo, Murray Shanahan

We investigate the composability of soft-rules learned by relational neural architectures when operating over object-centric (slot-based) representations, under a variety of sparsity-inducing constraints. We find that increasing sparsity, especially on features, improves the performance of some models and leads to simpler relations. Additionally, we observe

G. Miniutti, M. Giustini, R. Arcodia, R. D. Saxton

GSN 069 is the first galactic nucleus where quasi-periodic eruptions (QPEs) have been identified. These are high-amplitude, soft X-ray bursts recurring every ~9 hr, lasting ~1 hr, and during which the X-ray count rate increases by up to two orders of magnitude with respect to an otherwise stable quiescent level. The X-ray spectral properties and the long-ter

Xingming Wang, Xiaoyi Qin, Yikang Wang, Yunfei Xu

This paper describes our DKU-OPPO system for the 2022 Spoofing-Aware Speaker Verification (SASV) Challenge. First, we split the joint task into speaker verification (SV) and spoofing countermeasure (CM), these two tasks which are optimized separately. For ASV systems, four state-of-the-art methods are employed. For CM systems, we propose two methods on top o

Erika Janitz, Konstantin Herb, Laura A. Völker, William S. Huxter

Quantum sensing using optically addressable atomic-scale defects, such as the nitrogen--vacancy (NV) center in diamond, provides new opportunities for sensitive and highly localized characterization of chemical functionality. Notably, near-surface defects facilitate detection of the minute magnetic fields generated by nuclear or electron spins outside of the

Joshua Barrow, Kristi L. Engel, Tiffany R. Lewis, Sara M. Simon

In April 2020, the 2019 and 2020 American Physical Society's Division of Particles and Fields (APS DPF) Early Career Executive Committee (ECEC) members were tasked with organizing the formation of a representative body for High-Energy Physics (HEP) early career members for the Snowmass process by the DPF Executive Committee. Here, we outline the structure we

Vyacheslav Lysov, Yasha Neiman

We consider type-A higher-spin gravity in AdS_4, holographically dual to a free U(N) vector model on the boundary. We study the linearized version of the Didenko-Vasiliev "BPS black hole", which we view as this theory's equivalent of the fundamental string. The Didenko-Vasiliev solution consists of gauge fields of all spins generated by a particle-like sourc

Guoxuan Xia, Christos-Savvas Bouganis

Detecting out-of-distribution (OOD) data is a task that is receiving an increasing amount of research attention in the domain of deep learning for computer vision. However, the performance of detection methods is generally evaluated on the task in isolation, rather than also considering potential downstream tasks in tandem. In this work, we examine selective

Mauro Di Nasso, Marco Forti

We introduce axiomatically the ring $\bf{Z}_\kappa$ of the Euclidean integers, that can be viewed as the ``integral part" of the field $\mathbb{E}$ of Euclidean numbers of [4], where the transfinite sum of ordinal indexed $\kappa$-sequences of integers is well defined. In particular any ordinal might be identified with the transfiite sum of its characteristi

Chelsea Edmonds, Angeliki Koutsoukou-Argyraki, Lawrence C. Paulson

We have formalised Szemer\'edi's Regularity Lemma and Roth's Theorem on Arithmetic Progressions, two major results in extremal graph theory and additive combinatorics, using the proof assistant Isabelle/HOL. For the latter formalisation, we used the former to first show the Triangle Counting Lemma and the Triangle Removal Lemma: themselves important technica

Ignacio Carlucho, Arrasy Rahman, William Ard, Elliot Fosong

While research in ad hoc teamwork has great potential for solving real-world robotic applications, most developments so far have been focusing on environments with simple dynamics. In this article, we discuss how the problem of ad hoc teamwork can be of special interest for marine robotics and how it can aid marine operations. Particularly, we present a set

Anderson R. Avila, Khalil Bibi, Rui Heng Yang, Xinlin Li

Deep neural networks (DNN) have achieved impressive success in multiple domains. Over the years, the accuracy of these models has increased with the proliferation of deeper and more complex architectures. Thus, state-of-the-art solutions are often computationally expensive, which makes them unfit to be deployed on edge computing platforms. In order to mitiga

Lilit Avetisyan, Jackie Ayoub, Feng Zhou

With the level of automation increases in vehicles, such as conditional and highly automated vehicles (AVs), drivers are becoming increasingly out of the control loop, especially in unexpected driving scenarios. Although it might be not necessary to require the drivers to intervene on most occasions, it is still important to improve drivers' situation awaren

Pak-Yeung Chan, Shaochuang Huang, Man-Chun Lee

In this work, we construct distance like functions with integral hessian bound on manifolds with small curvature concentration and use it to construct Ricci flows on manifolds with possibly unbounded curvature. As an application, we study the geometric structure of those manifolds without bounded curvature assumption. In particular, we show that manifolds wi

Seyoung Ahn, Soohyeong Kim, Yongseok Kwon, Joohan Park

In 6G mobile communication systems, various AI-based network functions and applications have been standardized. Federated learning (FL) is adopted as the core learning architecture for 6G systems to avoid privacy leakage from mobile user data. However, in FL, users with non-independent and identically distributed (non-IID) datasets can deteriorate the perfor

Pongwit Srisangyingcharoen

We propose a possible modification to the tensionless string model with contact interactions. The proposed model aims to reproduce an expectation value of the non-Abelian Wilson loop in the Yang-Mills theory when integrating out string degrees of freedom with a fixed worldsheet boundary. Lie algebra-valued fields whose dynamics are determined by the topologi

Abdulaziz H. Al-Aswad, Fahhad H. Alharbi

Within ``orbital-free'' density functional theory, it is essential to develop general kinetic energy density (KED), denoted as $t(\mathbf{r})$. This is usually done by empirical corrections and enhancements, gradient expansions, machine learning, or axiomatic approaches to find forms that satisfy physical necessities. In all cases, it is crucial to determine

Jane, Tan, Yong Tan

Conditional thank-you gifts are one of the most widely used incentives for charitable giving. Past studies explored non-monetary thank-you gifts (e.g., mugs and shirts) and monetary thank-you gifts (e.g., rebates that return some of the donations to the giver). Following the rapid growth of blockchain technology, a novel form of thank-you gifts emerged: the

Raphael Zufferey, Jesus Tormo Barbero, Daniel Feliu Talegon, Saeed Rafee Nekoo

Flapping wings are a bio-inspired method to produce lift and thrust in aerial robots, leading to quiet and efficient motion. The advantages of this technology are safety and maneuverability, and physical interaction with the environment, humans, and animals. However, to enable substantial applications, these robots must perch and land. Despite recent progres

Morgan Görtz, Fredrik Hellman, Axel Målqvist

We present and analyze a preconditioned conjugate gradient method (PCG) for solving spatial network problems. Primarily, we consider diffusion and structural mechanics simulations for fiber based materials, but the methodology can be applied to a wide range of models, fulfilling a set of abstract assumptions. The proposed method builds on a classical subspac

Yuren Zhou, Yanmei Chen, Yong Shi, Dmitry Bizyaev

We select 456 gas-star kinematically misaligned galaxies from the internal Product Launch-10 of MaNGA survey, including 74 star-forming (SF), 136 green-valley (GV) and 206 quiescent (QS) galaxies. We find that the distributions of difference between gas and star position angles for galaxies have three local peaks at $\sim0^{\circ}$, $90^{\circ}$, $180^{\circ

Martine S. Lenders, Christian Amsüss, Cenk Gündogan, Marcin Nawrocki

In this paper, we present the design, implementation, and analysis of DNS over CoAP (DoC), a new proposal for secure and privacy-friendly name resolution of constrained IoT devices. We implement different design choices of DoC in RIOT, an open-source operating system for the IoT, evaluate performance measures in a testbed, compare with DNS over UDP and DNS o

Isaac Z. Pesenson

In the setting of the multidimensional Mellin analysis we introduce moduli of continuity and use them to define Besov-Mellin spaces. We prove that Besov-Mellin spaces are the interpolation spaces (in the sense of J.Peetre) between two Sobolev-Mellin spaces. We also introduce Bernstein-Mellin spaces and prove corresponding direct and inverse approximation the

Billy Pik Lik Lau, Brandon Jin Yang Ong, Leonard Kin Yung Loh, Ran Liu

With the increasing need for multi-robot for exploring the unknown region in a challenging environment, efficient collaborative exploration strategies are needed for achieving such feat. A frontier-based Rapidly-Exploring Random Tree (RRT) exploration can be deployed to explore an unknown environment. However, its' greedy behavior causes multiple robots to e

Kumar Saurabh, Tanuj Kumar, Uphar Singh, O. P. Vyas

In the recent years, Distributed Denial of Service (DDoS) attacks on Internet of Things (IoT) devices have become one of the prime concerns to Internet users around the world. One of the sources of the attacks on IoT ecosystems are botnets. Intruders force IoT devices to become unavailable for its legitimate users by sending large number of messages within a

Aleksandr Petrov, Craig Macdonald

BERT4Rec is an effective model for sequential recommendation based on the Transformer architecture. In the original publication, BERT4Rec claimed superiority over other available sequential recommendation approaches (e.g. SASRec), and it is now frequently being used as a state-of-the art baseline for sequential recommendations. However, not all subsequent pu

Axel Schaffland

In this paper the Mechanical Neural Network(MNN) is introduced, a physical implementation of a multilayer perceptron(MLP) with ReLU activation functions, two input neurons, four hidden neurons and two output neurons. This physical model of a MLP is used in education to give a hands on experience and allow students to experience the effect of changing the par

Zhenyu Bai, Hugues Cassé, Thomas Carle, Christine Rochange

Worst-Case Execution Time (WCET) is a key component for the verification of critical real-time applications. Yet, even the simplest microprocessors implement pipelines with concurrently-accessed resources, such as the memory bus shared by fetch and memory stages. Although their in-order pipelines are, by nature, very deterministic, the bus can cause out-of-o

Guy Boistel

This study sums up a major part of the red giant V449 Cygni measurements for the years 1974 through 2022, obtained by visual and CCD GEOS observers, the Unione Astrofili Italiani, and various automatized telescopes. It appears that the light variations of V449 Cyg in the years 1970-1990 corresponded more to an L-type star according to the GCVS classification

Patricia Bouyer, Paul Gastin, Frédéric Herbreteau, Ocan Sankur

Timed automata have been introduced by Rajeev Alur and David Dill in the early 90's. In the last decades, timed automata have become the de facto model for the verification of real-time systems. Algorithms for timed automata are based on the traversal of their state-space using zones as a symbolic representation. Since the state-space is infinite, terminatio

Ziv Epstein, Hause Lin

Existing social media platforms (SMPs) make it incredibly difficult for researchers to conduct studies on social media, which in turn has created a knowledge gap between academia and industry about the effects of platform design on user behavior. To close the gap, we introduce Yourfeed, a research tool for conducting ecologically valid social media research.

Paweł Gawrychowski, Florin Manea, Stefan Siemer

A pattern $\alpha$ is a string of variables and terminal letters. We say that $\alpha$ matches a word $w$, consisting only of terminal letters, if $w$ can be obtained by replacing the variables of $\alpha$ by terminal words. The matching problem, i.e., deciding whether a given pattern matches a given word, was heavily investigated: it is NP-complete in gener

Belle Collaboration, D. Biswas, Sw. Banerjee, I. Adachi

A dark leptophilic scalar $(\phi_L)$ is a hypothetical particle that couples only to leptons rather than quarks. We report on a search for $\phi_L$ in the $e^+e^- \to \tau^+ \tau^- \phi_L, ~\phi_L \to \ell^+ \ell^- ~(\ell = e, \mu)$ process using 626~\invfb of data collected by the Belle experiment near the \Y4S resonance. We validate the backgrounds with mu

Takuya Konishi, Yoshinobu Kawahara

Weight-tied models have attracted attention in the modern development of neural networks. The deep equilibrium model (DEQ) represents infinitely deep neural networks with weight-tying, and recent studies have shown the potential of this type of approach. DEQs are needed to iteratively solve root-finding problems in training and are built on the assumption th

Bogdan-Vasile Matioc, Christoph Walker

We establish the well-posedness of the nonlocal mean curvature flow of order ${\alpha\in(0,1)}$ for periodic graphs on $\mathbb{R}^n$ in all subcritical little H\"older spaces ${\rm h}^{1+\beta}(\mathbb{T}^n)$ with $\beta\in(0,1)$. Furthermore, we prove that if the solution is initially sufficiently close to its integral mean in ${\rm h}^{1+\beta}(\mathbb{T}

Xun Gong, Zhikai Zhou, Yanmin Qian

Modern non-autoregressive~(NAR) speech recognition systems aim to accelerate the inference speed; however, they suffer from performance degradation compared with autoregressive~(AR) models as well as the huge model size issue. We propose a novel knowledge transfer and distillation architecture that leverages knowledge from AR models to improve the NAR perfor

Jian-Feng Cai, Jae Kyu Choi, Ke Wei

Total variation (TV) minimization is one of the most important techniques in modern signal/image processing, and has wide range of applications. While there are numerous recent works on the restoration guarantee of the TV minimization in the framework of compressed sensing, there are few works on the restoration guarantee of the restoration from partial obse

Arnaud Debussche, Berenger Hug, Etienne Memin

In this paper we analyze the theoretical properties of a stochastic representation of the incompressible Navier-Stokes equations defined in the framework of the modeling under location uncertainty (LU). This setup built from a stochastic version of the Reynolds transport theorem incorporates a so-called transport noise and involves several specific additiona

Silvia Ferreres-Solé

Summary of some of the most recent measurements performed by LHCb on rare decays and lepton favour universality tests.

N. T. V. Hang, W. Jung, M. E. Sarabi

Understanding the role that subgradients play in various second-order variational analysis constructions can help us uncover new properties of important classes of functions in variational analysis. Focusing mainly on the behavior of the second subderivative and subgradient proto-derivative of polyhedral functions, functions with polyhedral epigraphs, we dem

Johan Vertens, Wolfram Burgard

In this paper we propose USegScene, a framework for semantically guided unsupervised learning of depth, optical flow and ego-motion estimation for stereo camera images using convolutional neural networks. Our framework leverages semantic information for improved regularization of depth and optical flow maps, multimodal fusion and occlusion filling considerin

Stefano Pozzorini, Natalie Schär, Max F. Zoller

NLO scattering amplitudes are provided by fully automated numerical tools, such as OpenLoops, for a very wide range of processes. In order to match the numerical precision of current and future collider experiments, the higher precision of NNLO calculations is essential, and their automation in a similar tool a highly desirable goal. In our approach, D-dimen

Phillip Murray, Ben Wood, Hans Buehler, Magnus Wiese

We present a method for finding optimal hedging policies for arbitrary initial portfolios and market states. We develop a novel actor-critic algorithm for solving general risk-averse stochastic control problems and use it to learn hedging strategies across multiple risk aversion levels simultaneously. We demonstrate the effectiveness of the approach with a n

Gabriel Kasmi, Laurent Dubus, Philippe Blanc, Yves-Marie Saint-Drenan

Photovoltaic (PV) energy is rapidly growing and key to mitigating the energy crisis. However, distributed PV generation, which amounts to half of the PV installed capacity, is typically unavailable to transmission system operators (TSOs), making it increasingly difficult to balance the load and supply and avoid grid congestions. To assess distributed PV gene

Jesse Ables, Thomas Kirby, William Anderson, Sudip Mittal

Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems (IDS) are complex black boxes. This means that a security analyst will have little to no explanation or clarification on why an IDS model made a particular prediction. A potential solution to this problem is to research and develop Explainable Intrusion Detection Systems (X-IDS) based on

G. Kim, C. Hofmann, A. S. Maxwell, C. Figueira de Morisson Faria

We perform a systematic analysis of how ultrafast photoelectron holography is influenced by an elliptically polarized field, with emphasis on quantum interference effects. We find that the interplay of the external field and the binding potential leads to twisted holographic patterns for low ellipticities and recover well-known angular offsets for high ellip

A. S. Fokas, A. Latifi

We elaborate on a new methodology, which starting with an integrable evolution equation in one spatial dimension, constructs an integrable forced version of this equation. The forcing consists of terms involving quadratic products of certain eigenfunctions of the associated Lax pair. Remarkably, some of these forced equations arise in the modelling of import

Anagha G Rao, Umesh Siddarth U S, Srisha M V Rao

Streamline tracing in conical hypersonic flows is essential for designing high-performance waverider and intake. Conventionally, the streamline equations are solved after obtaining the velocity field from the solution of the axisymmetric conical flow field. The hypersonic waverider shape is generated from the base conical flow field by repeatedly applying th

Jacopo Schino

The existence of ground states and (multiple) bound states to semilinear time-independent Maxwell and Schr\"odinger equations, with or without $L^2$-constraints, is investigated.

Mikel Garcia-de-Andoin, Izaskun Oregi, Esther Villar-Rodriguez, Eneko Osaba

The Bin Packing Problem (BPP) stands out as a paradigmatic combinatorial optimization problem in logistics. Quantum and hybrid quantum-classical algorithms are expected to show an advantage over their classical counterparts in obtaining approximate solutions for optimization problems. We have recently proposed a hybrid approach to the one dimensional BPP in

S. A. Tyul'bashev, I. V. Chashei, I. A. Subaev, M. A. Kitaeva

The search for compact components of strong ($S_{int} \ge 5$ Jy at 102.5 MHz) discrete radio sources from the Pushchino catalogue was carried out using the method of interplanetary scintillation. A total of 3620 sources were examined, and 812 of them were found to compact (scintillating) components. Estimates of fluctuations of the flux density of these comp

Inyoung Jun, Simone Marini, Christina A. Boucher, J. Glenn Morris

Bacterial infections are responsible for high mortality worldwide. Antimicrobial resistance underlying the infection, and multifaceted patient's clinical status can hamper the correct choice of antibiotic treatment. Randomized clinical trials provide average treatment effect estimates but are not ideal for risk stratification and optimization of therapeutic

Dan Crisan, Darryl D. Holm, Oana Lang, Prince Romeo Mensah

This paper investigates the mathematical properties of a stochastic version of the balanced 2D thermal quasigeostrophic (TQG) model of potential vorticity dynamics. This stochastic TQG model is intended as a basis for parametrisation of the dynamical creation of unresolved degrees of freedom in computational simulations of upper ocean dynamics when horizonta

A. Leleu, J. -B. Delisle, S. Udry, R. Mardling

Transit Timing Variations (TTVs) can provide useful information on compact multi-planetary systems observed by transits, by putting constraints on the masses and eccentricities of the observed planets. This is especially helpful when the host star is not bright enough for radial velocity follow-up. However, in the past decades, numerous works have shown that

Cameron Franc, Geoffrey Mason

We postulate axioms for a chiral half of a nonarchimedean 2-dimensional bosonic conformal field theory, that is, a vertex operator algebra in which a p-adic Banach space replaces the traditional Hilbert space. We study some consequences of our axioms leading to the construction of various examples, including p-adic commutative Banach rings and p-adic version

Guillem Braso, Orcun Cetintas, Laura Leal-Taixe

Graphs offer a natural way to formulate Multiple Object Tracking (MOT) and Multiple Object Tracking and Segmentation (MOTS) within the tracking-by-detection paradigm. However, they also introduce a major challenge for learning methods, as defining a model that can operate on such structured domain is not trivial. In this work, we exploit the classical networ

Xiaohui Zhang, Mingying Xue, Xianghua Miao

Blockchain technology enables stakeholders to conduct trusted data sharing and exchange without a trusted centralized institution. These features make blockchain applications attractive to enhance trustworthiness in very different contexts. Due to unique design concepts and outstanding performance, blockchain has become a popular research topic in industry a

Gabriel Andres Piovano, Andrea Maselli, Paolo Pani

We estimate the accuracy in the measurement of the tidal Love number of a supermassive compact object through the detection of an extreme mass ratio inspiral~(EMRI) by the future LISA mission. A nonzero Love number would be a smoking gun for departures from the classical black hole prediction of General Relativity. We find that an EMRI detection by LISA coul

Stephan De Bievre

We provide an in-depth study of the recently introduced notion of completely incompatible observables and its links to the support uncertainty and to the Kirkwood-Dirac nonclassicality of pure quantum states. The latter notion has recently been proven central to a number of issues in quantum information theory and quantum metrology. In this last context, it

Thomas Colcombet, Gaëtan Douéneau-Tabot, Aliaume Lopez

This paper introduces a robust class of functions from finite words to integers that we call Z-polyregular functions. We show that it admits natural characterizations in terms of logics, Z-rational expressions, Z-rational series and transducers. We then study two subclass membership problems. First, we show that the asymptotic growth rate of a function is co

Fedor V. Fomin, Petr A. Golovach, Tuukka Korhonen, Kirill Simonov

We introduce a general method for obtaining fixed-parameter algorithms for problems about finding paths in undirected graphs, where the length of the path could be unbounded in the parameter. The first application of our method is as follows. We give a randomized algorithm, that given a colored $n$-vertex undirected graph, vertices $s$ and $t$, and an intege

A. R. Wildes, J. R. Stewart, M. D. Le, R. A. Ewings

Neutron spectroscopy measurements have been performed on single crystals of the antiferromagnetic van der Waals compound NiPS$_3$. Linear spin wave theory using a Heisenberg Hamiltonian with single-ion anisotropies has been applied to determine the magnetic exchange parameters and the nature of the anisotropy. The analysis reveals that NiPS$_3$ is less two-d

Syu Kato

We exhibit a higher-level analogue of the Bernstein-Gelfand-Gelfand (BGG) reciprocity for twisted current algebras for each positive integer, which recovers the original one (established by Bennett, Berenstein, Chari, Ion, Khoroshkin, Loktev, and Manning) as its level-one case. This work brings theta functions and modular forms into the theory of symmetric p

Ladina Hausmann, Nuriya Nurgalieva, Lídia del Rio

Information is physical, and for a physical theory to be universal, it should model observers as physical systems, with concrete memories where they store the information acquired through experiments and reasoning. Here we address these issues in Spekkens' toy theory, a non-contextual epistemically restricted model that partially mimics the behaviour of quan

Marcin Straczkiewicz, Emily J. Huang, Jukka-Pekka Onnela

The ubiquity of personal digital devices offers unprecedented opportunities to study human behavior. Current state-of-the-art methods quantify physical activity using 'activity counts,' a measure which overlooks specific types of physical activities. We proposed a walking recognition method for sub-second tri-axial accelerometer data, in which activity class

Ioannis Psarros, Dennis Rohde

Modern time series analysis requires the ability to handle datasets that are inherently high-dimensional; examples include applications in climatology, where measurements from numerous sensors must be taken into account, or inventory tracking of large shops, where the dimension is defined by the number of tracked items. The standard way to mitigate computati

Calum Milloy, Giulio Falcioni, Einan Gardi, Niamh Maher

The high-energy limit of $2\to 2$ scattering amplitudes offers an excellent setting to explore the universal features of gauge theories. At Leading Logarithmic (LL) accuracy the partonic amplitude is governed by Regge poles in the complex angular momentum plane. Beyond LL, Regge cuts in this plane begin to play an important role. Specifically, the real part

Xia Chen, Xiangbin Teng, Han Chen, Yafeng Pan

This study examines the efficacy of various neural network (NN) models in interpreting mental constructs via electroencephalogram (EEG) signals. Through the assessment of 16 prevalent NN models and their variants across four brain-computer interface (BCI) paradigms, we gauged their information representation capability. Rooted in comprehensive literature rev