April 2023 arXiv papers — page 46

Jun-Shuai Wang, Yong-Liang Ma

We study the multi-skyrmion states using a Skyrme model with false vacuum potential upto baryon number $B=8$ using the product ansatz. It is found that, both the false vacuum potential and true vacuum potential can yield cluster structure of the multi-skyrmion states. The effect of the explicit chiral breaking on the masses and the contour surfaces of the ba

Fei Guo, Hao-Song Li

In this work, we calculate the magnetic moments of the $P^{N^{0}}_{\psi}$ states and $P^{\Delta^{0}}_{\psi}$ states with valence quark content $\bar{c}cudd $ in molecular model, diquark-diquark-antiquark model and diquark-triquark model, as well as the transition magnetic moments in the molecular model. At the same time, we also calculate magnetic moments an

Kamil Bulinski, Alina Ostafe, Igor E. Shparlinski

We show that if one selects uniformly independently and identically distributed matrices $A_1, \ldots, A_s \in \mathrm{SL}_2(\mathbb{Z})$ from a ball of large radius $X$ then with probability at least $1 - X^{-1 + o(1)}$ the matrices $A_1, \ldots, A_s$ are free generators for a free subgroup of $\mathrm{SL}_2(\mathbb{Z})$. Furthermore, to show the flexibilit

Nicolas Burq, Aurélien Poiret, Laurent Thomann

The purpose of this article is to construct global solutions, in a probabilistic sense, for the nonlinear Schr{\"o}dinger equation posed on $\mathbb{R}^d$, in a supercritical regime. Firstly, we establish Bourgain type bilinear estimates for the harmonic oscillator which yields a gain of half a derivative in space for the local theory with randomised initial

Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger

Conservative inference is a major concern in simulation-based inference. It has been shown that commonly used algorithms can produce overconfident posterior approximations. Balancing has empirically proven to be an effective way to mitigate this issue. However, its application remains limited to neural ratio estimation. In this work, we extend balancing to a

Matteo Muffo, Aldo Cocco, Enrico Bertino

In recent years, Large Language Models such as GPT-3 showed remarkable capabilities in performing NLP tasks in the zero and few shot settings. On the other hand, the experiments highlighted the difficulty of GPT-3 in carrying out tasks that require a certain degree of reasoning, such as arithmetic operations. In this paper we evaluate the ability of Transfor

Karina Zakharova

The search task is one of the most difficult when it comes to execution speed, and reducing the latter is important both when working with large data and with small samples, if they need to be processed frequently and in a limited time. Grover's algorithm gave hope to quantum computing and served as an excellent base for all possible implementations and modi

Pedro Alves, Bruno Pereira Cipriano

We introduce the idea of Centaur Programmer, based on the premise that a collaborative approach between humans and AI will be more effective than AI alone, as demonstrated in centaur chess tournaments where mixed teams of humans and AI beat sole computers. The paper introduces several collaboration models for programming alongside an AI, including the guidan

Gilles Dowek, Olivier Hermant

We give a simple and direct proof that super-consistency implies the cut elimination property in deduction modulo. This proof can be seen as a simplification of the proof that super-consistency implies proof normalization. It also takes ideas from the semantic proofs of cut elimination that proceed by proving the completeness of the cut-free calculus. As an

Keir N Murphy, Mira Naftaly, Alison Nordon, Daniel Markl

Fundamental knowledge of scattering in granular compacts is essential to ensure accuracy of spectroscopic measurements and determine material characteristics such as size and shape of scattering objects. Terahertz time-domain spectroscopy (THz-TDS) was employed to investigate the effect of particle size and concentration on scattering in specially fabricated

Segun Taofeek Aroyehun, Lukas Malik, Hannah Metzler, Nikolas Haimerl

The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the quality of emotion identification methods due to training d

Abhijit Kayal, Veeresh Singh, Claudio Ricci, N. P. S. Mithun

The circumnuclear material around Active Galactic Nuclei (AGN) is one of the essential components of the obscuration-based unification model. However, our understanding of the circumnuclear material in terms of its geometrical shape, structure and its dependence on accretion rate is still debated. In this paper, we present the multi-epoch broadband X-ray spe

Albert Cohen, Matthieu Dolbeault, Agustin Somacal, Wolfgang Dahmen

We consider the parametric elliptic PDE $-{\rm div} (a(y)\nabla u)=f$ on a spatial domain $\Omega$, with $a(y)$ a scalar piecewise constant diffusion coefficient taking any positive values $y=(y_1, \dots, y_d)\in ]0,\infty[^d$ on fixed subdomains $\Omega_1,\dots,\Omega_d$. This problem is not uniformly elliptic as the contrast $\kappa(y)=\frac{\max y_j}{\min

Mingkai Zheng, Xiu Su, Shan You, Fei Wang

We investigate the potential of GPT-4~\cite{gpt4} to perform Neural Architecture Search (NAS) -- the task of designing effective neural architectures. Our proposed approach, \textbf{G}PT-4 \textbf{E}nhanced \textbf{N}eural arch\textbf{I}tect\textbf{U}re \textbf{S}earch (GENIUS), leverages the generative capabilities of GPT-4 as a black-box optimiser to quick

Yanki Lekili, Ed Segal

Given a Hamiltonian torus action on a symplectic manifold, Teleman and Fukaya have proposed that the Fukaya category of each symplectic quotient should be equivalent to an equivariant Fukaya category of the original manifold. We lay out new conjectures that extend this story - in certain situations - to singular values of the moment map. These include a prop

L. Mascotto

The virtual element method was introduced 10 years ago and it has generated a large number of theoretical results and applications ever since. Here, we overview the main mathematical results concerning the stabilization term of the method as an introduction for newcomers in the field. In particular, we summarize the proofs of some results for two dimensional

Seiji Kajita, Alberto Pacini, Gabriele Losi, Nobuaki Kikkawa

Understanding frictional phenomena is a fascinating fundamental problem with huge potential impact on energy saving. Such an understanding requires monitoring what happens at the sliding buried interface, which is almost inaccessible by experiments. Simulations represent powerful tools in this context, yet a methodological step forward is needed to fully cap

Hongwei Chen, Yujia Zhai, Joshua J. Turner, Adrian Feiguin

Atomistic spin dynamics simulations provide valuable information about the energy spectrum of magnetic materials in different phases, allowing one to identify instabilities and the nature of their excitations. However, the time cost of evaluating the dynamical correlation function $S(\mathbf{q}, t)$ increases quadratically as the number of spins $N$, leading

Marco Lauricella, Sauro Succi, Eyal Zussman, Dario Pisignano

Fluid flows hosting electrical phenomena make the subject of a fascinating and highly interdisciplinary scientific field. In recent years, the extraordinary success of electrospinning and solution blowing technologies for the generation of polymer nanofibers has motivated vibrant research aiming at rationalizing the behavior of viscoelastic jets under applie

Joseph E. Lawrence, Jindrich Dusek, Jeremy O. Richardson

We introduce an approach for calculating perturbative corrections to the ring-polymer instanton approximation to tunneling splittings (RPI+PC), by computing higher-order terms in the asymptotic expansion in $\hbar$. The resulting method goes beyond standard instanton theory by using information on the third and fourth derivatives of the potential along the t

Sung-Hwan Kim, Francisco Olivares, Nicola Prezza

Sorting is a fundamental algorithmic pre-processing technique which often allows to represent data more compactly and, at the same time, speeds up search queries on it. In this paper, we focus on the well-studied problem of sorting and indexing string sets. Since the introduction of suffix trees in 1973, dozens of suffix sorting algorithms have been describe

Jiajia Mi

In intelligent transport systems, it is common and inevitable with missing data. While complete and valid traffic speed data is of great importance to intelligent transportation systems. A latent factorization-of-tensors (LFT) model is one of the most attractive approaches to solve missing traffic data recovery due to its well-scalability. A LFT model achiev

Shaoshuai Chu, Olyana A. Kovyrkina, Alexander Kurganov, Vladimir V. Ostapenko

We study experimental convergence rates of three shock-capturing schemes for hyperbolic systems of conservation laws: the second-order central-upwind (CU) scheme, the third-order Rusanov-Burstein-Mirin (RBM), and the fifth-order alternative weighted essentially non-oscillatory (A-WENO) scheme. We use three imbedded grids to define the experimental pointwise,

François Dubois, Hedy César Ramírez-De-{Á}vila, Juan Antonio Rojas-Quintero

In this work, we consider a mechanical system whose mass tensor implements a scalar product in a Riemannian manifold. This system is controlled with the help of forces and torques. A cost functional is minimized to achieve an optimal trajectory. In this contribution, this cost function is supposed to be an arbitrary regular function invariant under a change

Rémi Carles, Louise Gassot

We consider the mass-supercritical, defocusing, nonlinear Schr{\"o}dinger equation. We prove loss of regularity in arbitrarily short times for regularized initial data belonging to a dense set of any fixed Sobolev space for which the nonlinearity is supercritical. The proof relies on the construction of initial data as a superposition of disjoint bubbles at

Philipp L. Kinon, Tobias Thoma, Peter Betsch, Paul Kotyczka

Port-Hamiltonian (PH) systems provide a framework for modeling, analysis and control of complex dynamical systems, where the complexity might result from multi-physical couplings, non-trivial domains and diverse nonlinearities. A major benefit of the PH representation is the explicit formulation of power interfaces, so-called ports, which allow for a power-p

Lingyuan Ye

In this paper, we provide an alternative description of the duality result for distributive lattices and coherent locales using ultraposet. In particular, we show that there are fully faithful embeddings from the opposite of the category of distributive lattices into the category of ultraposets with ultrafunctors, and from the category of coherent locales in

Yang Li, Bo Yang, Xuehua Zhao, Zhejian Yang

Signed network structure discovery has received extensive attention and has become a research focus in the field of network science. However, most of the existing studies are focused on the networks with a single structure, e.g., community or bipartite, while ignoring multiple structures, e.g., the coexistence of community and bipartite structures. Furthermo

Matthias Rowold, Levent Ögretmen, Ulf Kasolowsky, Boris Lohmann

We propose an online planning approach for racing that generates the time-optimal trajectory for the upcoming track section. The resulting trajectory takes the current vehicle state, effects caused by \acl{3D} track geometries, and speed limits dictated by the race rules into account. In each planning step, an optimal control problem is solved, making a quas

ATLAS Collaboration

A search for forward proton scattering in association with light-by-light scattering mediated by an axion-like particle is presented, using the ATLAS Forward Proton spectrometer to detect scattered protons and the central ATLAS detector to detect pairs of outgoing photons. Proton-proton collision data recorded in 2017 at a centre-of-mass energy of $\sqrt{s}

Tomonori Tanizawa, Yuki Takeuchi, Shion Yamashika, Ryosuke Yoshii

Graph states are entangled states useful for several quantum information processing tasks such as measurement-based quantum computation and quantum metrology. As the size of graph states realized in experiments increases, it becomes more essential to devise efficient methods estimating the fidelity between the ideal graph state and an experimentally-realized

Mizhaan Prajit Maniyar, Akash Mondal, Prashanth L. A., Shalabh Bhatnagar

We consider the problem of control in the setting of reinforcement learning (RL), where model information is not available. Policy gradient algorithms are a popular solution approach for this problem and are usually shown to converge to a stationary point of the value function. In this paper, we propose two policy Newton algorithms that incorporate cubic reg

William G. La Cava

Improving the fairness of machine learning models is a nuanced task that requires decision makers to reason about multiple, conflicting criteria. The majority of fair machine learning methods transform the error-fairness trade-off into a single objective problem with a parameter controlling the relative importance of error versus fairness. We propose instead

Yu-Shiang Wong, Niloy J. Mitra

A long-standing goal in scene understanding is to obtain interpretable and editable representations that can be directly constructed from a raw monocular RGB-D video, without requiring specialized hardware setup or priors. The problem is significantly more challenging in the presence of multiple moving and/or deforming objects. Traditional methods have appro

Hiroshi Yano, Naoki Yamamoto

Quantum state estimation (or state tomography) is an indispensable task in quantum information processing. Because full state tomography that determines all elements of the density matrix is computationally demanding, one usually takes the strategy of assuming a certain model of quantum states and identifying the model parameters. However, it is difficult to

Silvia Pappalardi, Laura Foini, Jorge Kurchan

We discuss the construction of a microcanonical projection WOW of a quantum operator O induced by an energy window filter W, its spectrum, and the retrieval of canonical many-time correlations from it.

Antoine Ayache, Ciprian A Tudor

We consider a modified quadratic variation of the Hermite process based on some well-chosen increments of this process. These special increments have the very useful property to be independent and identically distributed up to asymptotically negligible remainders. We prove that this modified quadratic variation satisfies a Central Limit Theorem and we derive

Wolfgang Arendt, Isabelle Chalendar, Robert Eymard

We first give a general error estimate for the nonconforming approximation of a problem for which a Banach-Ne{\v c}as-Babu{\v s}ka (BNB) inequality holds. This framework covers parabolic problems with general conditions in time (initial value problems as well as periodic problems) under minimal regularity assumptions. We consider approximations by two types

Arthur Vesperini

Multipartite quantum states constitute the key resource for quantum computation. The understanding of their internal structure is thus of great importance in the field of quantum information. This paper aims at examining the structure of multipartite maximally entangled pure states, using tools with a simple and intuitive physical meaning, namely, projective

Nadine Große, Mirela Kohr, Victor Nistor

A differential operator $T$ satisfies the $L^2$-unique continuation property if every $L^2$-solution of $T$ that vanishes on an open subset vanishes identically. We study the $L^2$-unique continuation property of an operator $T$ acting on a manifold with bounded geometry. In particular, we establish some connections between this property and the regularity p

Zahra Sartipi, Javad Vahedi

The thermoelectric performance at a given output power of a voltage-probe heat engine, exposed to an external magnetic field, is investigated in linear irreversible thermodynamics. For the model, asymmetric parameter, general figures of merit and efficiency at a given output power are analytically derived. Results show a trade-off between efficiency and outp

Liu Pingping, Liu Zetong, Lang Yijun, Zhou Qiuzhan

Deep metric learning aims to construct an embedding space where samples of the same class are close to each other, while samples of different classes are far away from each other. Most existing deep metric learning methods attempt to maximize the difference of inter-class features. And semantic related information is obtained by increasing the distance betwe

Cheng Tan, Zhangyang Gao, Lirong Wu, Jun Xia

Antibodies are crucial proteins produced by the immune system in response to foreign substances or antigens. The specificity of an antibody is determined by its complementarity-determining regions (CDRs), which are located in the variable domains of the antibody chains and form the antigen-binding site. Previous studies have utilized complex techniques to ge

Simon Rey, Ulle Endriss

We initiate the study of voting rules for participatory budgeting using the so-called epistemic approach, where one interprets votes as noisy reflections of some ground truth regarding the objectively best set of projects to fund. Using this approach, we first show that both the most studied rules in the literature and the most widely used rule in practice c

Marion Neumeier, Andreas Tollkühn, Sebastian Dorn, Michael Botsch

This work provides a comprehensive derivation of the parameter gradients for GATv2 [4], a widely used implementation of Graph Attention Networks (GATs). GATs have proven to be powerful frameworks for processing graph-structured data and, hence, have been used in a range of applications. However, the achieved performance by these attempts has been found to be

Debanjana Kundu, Filippo Alberto Edoardo Nuccio Mortarino Majno Di Capriglio, Sujatha Ramdorai

This paper studies fine Selmer groups of elliptic curves in abelian $p$-adic Lie extensions. A class of elliptic curves are provided where both the Selmer group and the fine Selmer group are trivial in the cyclotomic $\mathbb{Z}_p$-extension. The fine Selmer groups of elliptic curves with complex multiplication are shown to be pseudonull over the trivializin

Mirjana Brdar, Sebastian Franz, Hans-Goerg Roos

A convection-diffusion problem with a large shift in space is considered. Numerical analysis of high order finite element methods on layer-adapted Duran type meshes, as well as on coarser Duran type meshes in places where weak layers appear, is provided. The theoretical results are confirmed by numerical experiments.

Sarbajit Basu, Arthur K. Barnes, Adam Mate, Olga Lavrova

Inverter-interfaced microgrids, owing to the lack of fault current, cannot be protected using traditional over-current protections, while admittance or differential relaying protection schemes are not practical to be implemented. Dynamic state estimation can track and predict power system transients and has been extensively investigated for setting-less prot

D. J. Needham, J. Billingham

In the second part of this series of papers, we address the same Cauchy problem that was considered in part 1, namely the nonlocal Fisher-KPP equation in one spatial dimension, \[ u_t = D u_{xx} + u(1-\phi*u), \] where $\phi*u$ is a spatial convolution with the top hat kernel, $\phi(y) \equiv H\left(\frac{1}{4}-y^2\right)$, except that now the spatial domain

Michela Negro, Milena Crnogorčević, Eric Burns, Eric Charles

With the coincident detections of electromagnetic radiation together with gravitational waves (GW170817) or neutrinos (TXS 0506+056), the new era of multimessenger astrophysics has begun. Of particular interest are the searches for correlation between the high-energy astrophysical neutrinos detected by the IceCube Observatory and gamma-ray photons detected b

Romain Menegaux, Emmanuel Jehanno, Margot Selosse, Julien Mairal

We introduce a novel self-attention mechanism, which we call CSA (Chromatic Self-Attention), which extends the notion of attention scores to attention _filters_, independently modulating the feature channels. We showcase CSA in a fully-attentional graph Transformer CGT (Chromatic Graph Transformer) which integrates both graph structural information and edge

Paul Irofti, Luis Romero-Ben, Florin Stoican, Vicenç Puig

This article presents a leak localization methodology based on state estimation and learning. The first is handled by an interpolation scheme, whereas dictionary learning is considered for the second stage. The novel proposed interpolation technique exploits the physics of the interconnections between hydraulic heads of neighboring nodes in water distributio

E. Aprile, K. Abe, S. Ahmed Maouloud, L. Althueser

Multiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from Multiply-Interacting Massive Particles (MIMPs). Their unique track signature

Ivailo Hartarsky, Lyuben Lichev, Fabio Toninelli

We consider local dynamics of the dimer model (perfect matchings) on hypercubic boxes $[n]^d$. These consist of successively switching the dimers along alternating cycles of prescribed (small) lengths. We study the connectivity properties of the dimer configuration space equipped with these transitions. Answering a question of Freire, Klivans, Milet and Sald

Sanghoon Baek, Rostislav Devyatov

Consider the canonical morphism from the Chow ring of a smooth variety $X$ to the associated graded ring of the topological filtration on the Grothendieck ring of $X$. In general, this morphism is not injective. However, Nikita Karpenko conjectured that these two rings are isomorphic for a generically twisted flag variety $X$ of a semisimple group $G$. The c

Zuhaib Akhtar, Mohammad Omar Khursheed, Dongsu Du, Yuzong Liu

In this work, we present Slimmable Neural Networks applied to the problem of small-footprint keyword spotting. We show that slimmable neural networks allow us to create super-nets from Convolutioanl Neural Networks and Transformers, from which sub-networks of different sizes can be extracted. We demonstrate the usefulness of these models on in-house Alexa da

ALICE Collaboration

The first measurement of the polarisation of coherently photoproduced J$/\psi$ mesons in ultra-peripheral Pb-Pb collisions, using data at $\sqrt{s_{\rm NN}}$ = 5.02 TeV, is presented. The J/$\psi$ meson is measured via its dimuon decay channel in the forward rapidity interval $-4.0 < y < -2.5$ using the ALICE detector at the CERN LHC. An event sample corresp

Angelo Russomanno

In this work we consider the dynamics of a chain of many coupled kicked rotors with dissipation. We map a rich phase diagram with many dynamical regimes. We focus mainly on a regime where the system shows period doubling, and forms patterns that are persistent and depend on the stroboscopic time with period double than that of the driving: The system shows a

Rishabh Duhan, Subhamita Sengupta, Ruchi Tomar, Somak Basistha

We report the formation of a pinned vortex liquid spanning a very large region of the magnetic field-temperature parameter space in a 5 nm thick amorphous superconducting Re_xZr (x~6) (a-ReZr) thin film, using a combination of low-temperature scanning tunnelling spectroscopic (STS) imaging and magnetotransport measurements. The nature of the vortex liquid di

Thiago Castilho de Mello, Manuela da Silva Souza

In this paper we study identities and images of polynomials on null-filiform Leibniz algebras. If $L_n$ is an $n$-dimensional null-filiform Leibniz algebra, we exhibit a finite minimal basis for $\mbox{Id}(L_n)$, the polynomial identities of $L_n$, and we explicitly compute the images of multihomogeneous polynomials on $L_n$. We present necessary and suffici

Florent Balacheff, Wolfgang Pitsch

Consider a finite connected $2$-complex $X$ endowed with a piecewise Riemannian metric and whose fundamental group is freely indecomposable, of rank at least $3$, and in which every $2$-generated subgroup is free. In this paper we show that we can always find a connected graph $\Gamma\subset X$ such that $\pi_1 \Gamma\simeq {\mathbb F}_2 \hookrightarrow\pi_1

Thomas Schmidt, Jule Helena Schütt

We determine the optimal H\"older exponent in Massari's regularity theorem for sets with variational mean curvature in $\mathrm{L}^p$. In fact, we obtain regularity with improved exponents and at the same time provide sharp counterexamples.

D. J. Needham, J. Billingham, N. M. Ladas, J. C. Meyer

We study the Cauchy problem on the real line for the nonlocal Fisher-KPP equation in one spatial dimension, \[ u_t = D u_{xx} + u(1-\phi*u), \] where $\phi*u$ is a spatial convolution with the top hat kernel, $\phi(y) \equiv H\left(\frac{1}{4}-y^2\right)$. After showing that the problem is globally well-posed, we demonstrate that positive, spatially-periodic

Yuto Watanabe, Kazunori Sakurama, Hyo-Sung Ahn

In this study, we propose a design methodology of distributed controllers for multi-agent systems on a class of directed interaction networks by extending the gradient-flow method. Although the gradient-flow method is a common design tool for distributed controllers, it is inapplicable to directed networks. First, we demonstrate how to construct a distribute

Andreas Bluhm, Ion Nechita, Simon Schmidt

Several central problems in quantum information theory (such as measurement compatibility and quantum steering) can be rephrased as membership in the minimal matrix convex set corresponding to special polytopes (such as the hypercube or its dual). In this article, we generalize this idea and introduce the notion of polytope compatibility, by considering arbi

A. Beauville, A. Etesse, A. Höring, J. Liu

Let X be a n-dimensional (smooth) intersection of two quadrics, and let T*X be its cotangent bundle. We show that the algebra of symmetric tensors on X is a polynomial algebra in n variables. The corresponding map F: T*X -- > C^n is a Lagrangian fibration, which admits an explicit geometric description; its general fiber is a Zariski open subset of an abelia

Spyros Pasias

In this Thesis we deal with problems regarding boundary behavior of analytic functions and approximation theory. We will begin by characterizing the set in which Blaschke products fail to have radial limits but have unrestricted limits on its complement. We will then proceed and solve several cases of an open problem posed in \cite{Da}. The goal of the probl

Philip Mummert

Austrian Solitaire is a variation of Bulgarian Solitaire. It may be described as a card game, a method of asset inventory management, or a discrete dynamical system on integer partitions. We prove that the limit cycles in Austrian Solitaire do not depend on the initial configuration; in other words, each state space is connected. We show that a full Farey se

Dorin Bucur, Jimmy Lamboley, Mickaël Nahon, Raphaël Prunier

Let $\Omega\subset\mathbb{R}^n$ be an open set with the same volume as the unit ball $B$ and let $\lambda_k(\Omega)$ be the $k$-th eigenvalue of the Laplace operator of $\Omega$ with Dirichlet boundary conditions on $\partial\Omega$. In this work, we answer the following question: if $\lambda_1(\Omega)-\lambda_1(B)$ is small, how large can $|\lambda_k(\Omega

Liang-Liang Wan, Xin-You Lü

We theoretically predict the squeezing-induced point-gap topology together with a {\it symmetry-protected $\mathbb{Z}_2$ skin effect} in a one-dimensional (1D) quadratic-bosonic system (QBS). Protected by a time-reversal symmetry, such a topology is associated with a novel $\mathbb{Z}_2$ invariant (similar to quantum spin-Hall insulators), which is fully cap

Juha Kontinen, Max Sandström, Jonni Virtema

We introduce and develop a set-based semantics for asynchronous TeamLTL. We consider two canonical logics in this setting: the extensions of TeamLTL by the Boolean disjunction and by the Boolean negation. We establish fascinating connections between the original semantics based on multisets and the new set-based semantics as well as show one of the first pos

Juarez Monteiro, Nathan Gavenski, Felipe Meneguzzi, Rodrigo C. Barros

Behavioural cloning is an imitation learning technique that teaches an agent how to behave via expert demonstrations. Recent approaches use self-supervision of fully-observable unlabelled snapshots of the states to decode state pairs into actions. However, the iterative learning scheme employed by these techniques is prone to get trapped into bad local minim

Elizabeth L. Mansfield

We outline how discrete analogues of the conservation of potential vorticity may be achieved in Finite Element numerical schemes for a variational system which has the particle relabelling symmetry, typically shallow water equations. We show that the discrete analogue of the conservation law for potential vorticity converges to the smooth law for potential v

Ignasi Ventura Nadal, Samuel Chevalier

New generations of power systems, containing high shares of renewable energy resources, require improved data-driven tools which can swiftly adapt to changes in system operation. Many of these tools, such as ones using machine learning, rely on high-quality training datasets to construct probabilistic models. Such models should be able to accurately represen

Viktoria Horn, Claude Draude

Socio-technical design embeds social investigations and inquiries into (Information) Technology Design processes. In this position paper, we propose, by using the aforementioned approach the design of technology and policies can simultaneously inform each other. Additionally we present data economy and particularly anchored online journalism platforms as use

Lukas Lanza, Dario Dennstädt, Thomas Berger, Karl Worthmann

We develop a three-component Model Predictive Control (MPC) algorithm to achieve output-reference tracking with prescribed performance for continuous-time nonlinear systems. One component is so-called funnel MPC, which achieves reference tracking with prescribed performance for the model output for suitable models. Recently, this MPC algorithm has been combi

Joakim Edin, Alexander Junge, Jakob D. Havtorn, Lasse Borgholt

Medical coding is the task of assigning medical codes to clinical free-text documentation. Healthcare professionals manually assign such codes to track patient diagnoses and treatments. Automated medical coding can considerably alleviate this administrative burden. In this paper, we reproduce, compare, and analyze state-of-the-art automated medical coding ma

Ankit Kumar, Manil T. Mohan

The main objective of this paper is to demonstrate the uniform large deviation principle (UDLP) for the solutions of two-dimensional stochastic Navier-Stokes equations (SNSE) in the vorticity form when perturbed by two distinct types of noises. We first consider an infinite-dimensional additive noise that is white in time and colored in space and then consid

Chong-Sun Chu, Himanshu Parihar

We study the entanglement entropy for time-like subsystem in two-dimensional boundary conformal field theory (BCFT) both from the field theory and holographic point of view. In field theory, we compute the time-like entanglement entropy of a pure time-like interval at zero and finite temperature using the replica technique and analytical continuation. We fin

Naïmo Davier, Flavia A. Gómez Albarracín, H. Diego Rosales, Pierre Pujol

Classical spin liquids have been a very active subject of research in the last few years. A very rich variety of cases have been shown to exist, including short-range and algebraic spin liquids displaying dipolar correlations at zero temperature. In this article, we investigate different families of classical spins liquids by combining analytical techniques

Nicholas T. Runcie, Antonia S. J. S. Mey

Computationally generating novel synthetically accessible compounds with high affinity and low toxicity is a great challenge in drug design. Machine-learning models beyond conventional pharmacophoric methods have shown promise in generating novel small molecule compounds, but require significant tuning for a specific protein target. Here, we introduce a meth

Yuto Watanabe, Kazunori Sakurama

This study addresses a distributed optimization with a novel class of coupling of variables, called clique-wise coupling. A clique is a node set of a complete subgraph of an undirected graph. This setup is an extension of pairwise coupled optimization problems (e.g., consensus optimization) and allows us to handle coupling of variables consisting of more tha

Eemeli Tomberg

Stochastic inflation resolves primordial perturbations non-linearly, probing their probability distribution deep into its non-Gaussian tail. The strongest perturbations collapse into primordial black holes. In typical black-hole-producing single-field inflation, the strongest stochastic kicks occur during a period of constant roll. In this paper, I solve the

Feihu Huang, Songcan Chen

Minimax optimization plays an important role in many machine learning tasks such as generative adversarial networks (GANs) and adversarial training. Although recently a wide variety of optimization methods have been proposed to solve the minimax problems, most of them ignore the distributed setting where the data is distributed on multiple workers. Meanwhile

T. Alissa Schenck, Christian A. Hans

Microgrids are autonomous clusters of generators, storage units and loads. Special requirements arise in interconnected operation: control schemes that do not require individual microgrids to disclose information about their internal structure and operating objectives are preferred for privacy reasons. Moreover, a safe and economically meaningful operation s

Olivier Jeunen

Online experiments such as Randomised Controlled Trials (RCTs) or A/B-tests are the bread and butter of modern platforms on the web. They are conducted continuously to allow platforms to estimate the causal effect of replacing system variant "A" with variant "B", on some metric of interest. These variants can differ in many aspects. In this paper, we focus o

Thomas Wolgast, Nils Wenninghoff, Stephan Balduin, Eric Veith

The ongoing penetration of energy systems with information and communications technology (ICT) and the introduction of new markets increase the potential for malicious or profit-driven attacks that endanger system stability. To ensure security-of-supply, it is necessary to analyze such attacks and their underlying vulnerabilities, to develop countermeasures

Zixi Zhang, Yuriy V. Pershin, Ivar Martin

In this article, we introduce a new nanoscale electromechanical device -- a leaky memcapacitor -- and show that it may be useful for the hardware implementation of spiking neurons. The leaky memcapacitor is a movable-plate capacitor that becomes quite conductive when the plates come close to each other. The equivalent circuit of the leaky memcapacitor involv

Tran Ngoc Thang, Dao Minh Hoang, Nguyen Viet Dung

The article proposes an exact approach to find the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudoconvex, and the constraints are quasiconvex. Due to its non-convexity, this problem is challenging, but it attracts more and more interest because of its practical applications. Th

Thang Pham

The first goal of this paper is to prove a sharp condition to guarantee of having a positive proportion of all congruence classes of triangles in given sets in $\mathbb{F}_q^2$. More precisely, for $A, B, C\subset \mathbb{F}_q^2$, if $|A||B||C|^{1/2}\gg q^4$, then for any $\lambda\in \mathbb{F}_q\setminus \{0\}$, the number of congruence classes of triangles

Andrea Cavallo, Claas Grohnfeldt, Michele Russo, Giulio Lovisotto

Graph Neural Networks (GNNs) are well-suited for learning on homophilous graphs, i.e., graphs in which edges tend to connect nodes of the same type. Yet, achievement of consistent GNN performance on heterophilous graphs remains an open research problem. Recent works have proposed extensions to standard GNN architectures to improve performance on heterophilou

Marco Holzer, Tina Waurischk, Janine George, Robert Maaß

We present a novel method to predict the fracture surface energy, {\gamma}, of isochemically crystallizing silicate glasses using readily available crystallographic structure data of their crystalline counterpart and tabled diatomic chemical bond energies, D0. The method assumes that {\gamma} equals the fracture surface energy of the most likely cleavage pla

Elifnaz Saglamkaya, Artem Musiienko, Mohammad Saeed Shadabroo, Bowen Sun

Non-fullerene acceptors (NFA) have delivered advance in bulk heterojunction organic solar cell efficiencies, with the significant milestone of 20% now in sight. However, these materials challenge the accepted wisdom of how organic solar cells work. In this work we present neat Y6 device with efficiency above 4.5%. We thoroughly investigate mechanisms of char

Runwei Guan, Ka Lok Man, Feifan Chen, Shanliang Yao

Natural language (NL) based vehicle retrieval is a task aiming to retrieve a vehicle that is most consistent with a given NL query from among all candidate vehicles. Because NL query can be easily obtained, such a task has a promising prospect in building an interactive intelligent traffic system (ITS). Current solutions mainly focus on extracting both text

Mehran Salmani, Saeid Ghafouri, Alireza Sanaee, Kamran Razavi

The use of machine learning (ML) inference for various applications is growing drastically. ML inference services engage with users directly, requiring fast and accurate responses. Moreover, these services face dynamic workloads of requests, imposing changes in their computing resources. Failing to right-size computing resources results in either latency ser

J. Khatua, Q. P. Ding, M. S. Ramachandra Rao, K. Y. Choi

The interplay between spin-orbit coupling, anisotropic magnetic interaction, frustration-induced quantum fluctuations and spin correlations can lead to novel quantum states with exotic excitations in rare-earth-based quantum magnets. Herein, we present the crystal structure, magnetization, electron spin resonance (ESR), specific heat, and nuclear magnetic re

A. Alochukwu, M. Dorfling, E. Jonck

An $i$-packing in a graph $G$ is a set of vertices that are pairwise distance more than $i$ apart. A \emph{packing colouring} of $G$ is a partition $X=\{X_{1},X_{2},\ldots,X_{k}\}$ of $V(G)$ such that each colour class $X_{i}$ is an $i$-packing. The minimum order $k$ of a packing colouring is called the packing chromatic number of $G$, denoted by $\chi_{\rho

Yikai Wang, Zheyuan Jiang, Jianyu Chen

Recently, reinforcement learning has become a promising and polular solution for robot legged locomotion. Compared to model-based control, reinforcement learning based controllers can achieve better robustness against uncertainties of environments through sim-to-real learning. However, the corresponding learned gaits are in general overly conservative and un

R. Dhanya, Ritabrata Jana, Uttam Kumar, Sweta Tiwari

We consider a semipositone problem involving the fractional $p$ Laplace operator of the form \begin{equation*} \begin{aligned} (-\Delta)_p^s u &=\mu( u^{r}-1) \text{ in } \Omega,\\ u &>0 \text{ in }\Omega,\\ u &=0 \text{ on }\Omega^{c}, \end{aligned} \end{equation*} where $\Omega$ is a smooth bounded convex domain in $\mathbb{R}^N$, $p-1<r<p^{*}_{s}-1$, wher

Wen Chen, Bo Zhang, Jingdong Zhang, Jun Yang

To accurately link the radio and optical Celestial Reference Frames (CRFs) at optical bright end, i.e., with Gaia G band magnitude < 13, increasing number and improving sky distribution of radio stars with accurate astrometric parameters from both Very Long Baseline Interferometry (VLBI) and Gaia measurements are mandatory. We selected two radio stars HD 199