March 2023 arXiv papers — page 144

V. I. Yukalov, E. P. Yukalova

The review considers statistical systems composed of several phases that are intermixed in space at mesoscopic scale and systems representing a mixture of several components of microscopic objects. These types of mixtures should be distinguished from the Gibbs phase mixture, where the system is filled by macroscopic pieces of phases. The description of the m

M. A. Velez, K. D. Retherford, V. Hue, J. A. Kammer

Ultraviolet spectroscopy is a powerful method to study planetary surface composition through reflectance measurements and atmospheric composition through stellar/solar occultations, transits of other planetary bodies, and direct imaging of airglow and auroral emissions. The next generation of ultraviolet spectrographs (UVS) on board ESA's JUICE (Jupiter Icy

Roman Gansch, Ahmad Adee

The complexity of the operating environment and required technologies for highly automated driving is unprecedented. A different type of threat to safe operation besides the fault-error-failure model by Laprie et al. arises in the form of performance limitations. We propose a system theoretic approach to handle these and derive a taxonomy based on uncertaint

Andrzej Grzesik, Daniel Kral, Oleg Pikhurko

We study generalized quasirandom graphs whose vertex set consists of $q$ parts (of not necessarily the same sizes) with edges within each part and between each pair of parts distributed quasirandomly; such graphs correspond to the stochastic block model studied in statistics and network science. Lov\'asz and S\'os showed that the structure of such graphs is

Qingyi Wang, Shenhao Wang, Dingyi Zhuang, Haris Koutsopoulos

Recent studies have significantly improved the prediction accuracy of travel demand using graph neural networks. However, these studies largely ignored uncertainty that inevitably exists in travel demand prediction. To fill this gap, this study proposes a framework of probabilistic graph neural networks (Prob-GNN) to quantify the spatiotemporal uncertainty o

Pallab Basu, Haridev S R, Prasant Samantray

In this short paper, we investigate the consequences of observer dependence of the quantum effective potential for an interacting field theory. Specializing to $d+2$ dimensional Euclidean Rindler space, we develop the formalism to calculate the effective potential. While the free energy diverges due to the presence of the Rindler horizon, the effective poten

Charles K. Assaad, Imad Ez-zejjari, Lei Zan

This paper presents an approach for identifying the root causes of collective anomalies given observational time series and an acyclic summary causal graph which depicts an abstraction of causal relations present in a dynamic system at its normal regime. The paper first shows how the problem of root cause identification can be divided into many independent s

Ahmad Adee, Roman Gansch, Peter Liggesmeyer, Claudius Glaeser

Highly automated driving (HAD) vehicles are complex systems operating in an open context. Performance limitations originating from sensing and understanding the open context under triggering conditions may result in unsafe behavior, thus, need to be identified and modeled. This aspect of safety is also discussed in standardization activities such as ISO 2144

Robin Herkert, Patrick Buchfink, Bernard Haasdonk, Johannes Rettberg

Simulations of large scale dynamical systems in multi-query or real-time contexts require efficient surrogate modelling techniques, as e.g. achieved via Model Order Reduction (MOR). Recently, symplectic methods like the complex singular value decomposition (cSVD) or the SVD-like decomposition have been developed for preserving Hamiltonian structure during MO

Tarek Diaa-Eldeen, Marcus Krogh Nielsen, Carl Fredrik Berg, Morten Hovd

Data assimilation (DA) provides a general framework for estimation in dynamical systems based on the concepts of Bayesian inference. This constitutes a common basis for the different linear and nonlinear filtering and smoothing techniques which gives a better understanding of the characteristics and limitations of each approach. In this study, four nonlinear

Dell Zhang, Frank Schilder, Jack G. Conrad, Masoud Makrehchi

This "blue sky idea" paper outlines the opportunities and challenges in data mining and machine learning involving making a computational attorney -- an intelligent software agent capable of helping human lawyers with a wide range of complex high-level legal tasks such as drafting legal briefs for the prosecution or defense in court. In particular, we discus

Anca Iuliana Bonciocat, Nicolae Ciprian Bonciocat, Yann Bugeaud, Mihai Cipu

We provide upper bounds for the sum of the multiplicities of the non-constant irreducible factors that appear in the canonical decomposition of a polynomial $f(X)\in\mathbb{Z}[X]$, in case all the roots of $f$ lie inside an Apollonius circle associated to two points on the real axis with integer abscissae $a$ and $b$, with ratio of the distances to these poi

Michael Gentner, Prajval Kumar Murali, Mohsen Kaboli

Point cloud registration is a fundamental and challenging problem for autonomous robots interacting in unstructured environments for applications such as object pose estimation, simultaneous localization and mapping, robot-sensor calibration, and so on. In global correspondence-based point cloud registration, data association is a highly brittle task and com

Yi-Chun Hung, Baokai Wang, Chen-Hsuan Hsu, Arun Bansil

Solitons formed through the one-dimensional mass-kink mechanism on the edges of two-dimensional systems with non-trivial topology play an important role in the emergence of higher-order (HO) topological phases. In this connection, the existing work in time-reversal symmetric systems has focused on gapping the edge Dirac cones in the presence of particle-hole

Wenjie Li, Haoze Li, Jean Honorio, Qifan Song

We introduce a Python open-source library for $\mathcal{X}$-armed bandit and online blackbox optimization named PyXAB. PyXAB contains the implementations for more than 10 $\mathcal{X}$-armed bandit algorithms, such as HOO, StoSOO, HCT, and the most recent works GPO and VHCT. PyXAB also provides the most commonly-used synthetic objectives to evaluate the perf

Ahmad Adee, Roman Gansch, Peter Liggesmeyer

Highly automated driving (HAD) vehicles are complex systems operating in an open context. Complexity of these systems as well as limitations and insufficiencies in sensing and understanding the open context may result in unsafe and uncertain behavior. The safety critical nature of the HAD vehicles demands to model limitations, insufficiencies and triggering

Durga Prasad Karothu, Rodrigo Ferreira, Ghada Dushaq, Ejaz Ahmed

Following a well-established practice of publishing commentaries to articles of other authors who work on materials that were earlier studied by them (n.b. six published comments[1-6]), Marek Szafra\'nski(MS) and Andrzej Katrusiak (AK) have filed on the preprint server arXiv a manuscript entitled "On the giant deformation and ferroelectricity of guanidinium

Chia-Sheng Liu, Jia-Fong Yeh, Hao Hsu, Hung-Ting Su

The large amount of data collected by LiDAR sensors brings the issue of LiDAR point cloud compression (PCC). Previous works on LiDAR PCC have used range image representations and followed the predictive coding paradigm to create a basic prototype of a coding framework. However, their prediction methods give an inaccurate result due to the negligence of inval

Anatole Gaudin

In this article, the Hodge decomposition for any degree of differential forms is investigated on the whole space $\mathbb{R}^n$ and the half-space $\mathbb{R}^n_+$ on different scale of function spaces namely homogeneous and inhomogeneous Besov and Sobolev space, $\dot{\mathrm{H}}^{s,p}$, $\dot{\mathrm{B}}^{s}_{p,q}$, ${\mathrm{H}}^{s,p}$ and ${\mathrm{B}}^{

Stewart Jamieson, Jonathan P. How, Yogesh Girdhar

Successful applications of complex vision-based behaviours underwater have lagged behind progress in terrestrial and aerial domains. This is largely due to the degraded image quality resulting from the physical phenomena involved in underwater image formation. Spectrally-selective light attenuation drains some colors from underwater images while backscatteri

Xun Zeng, Chuanlai Liu, Chaoyu Zhao, Jie Dong

Tensile twinning is a main deformation mode in hexagonal close packed structure metals, so it is important to comprehensively understand twinning mechanisms which are not fully disclosed using 2D or small volume 3D characterization techniques. A large area 3D electron backscatter diffraction (EBSD) measurement and crystal plasticity modeling were carried out

Gyan Tatiya, Jonathan Francis, Jivko Sinapov

Humans learn about objects via interaction and using multiple perceptions, such as vision, sound, and touch. While vision can provide information about an object's appearance, non-visual sensors, such as audio and haptics, can provide information about its intrinsic properties, such as weight, temperature, hardness, and the object's sound. Using tools to int

Si-Qiang Luo, Xiang Liu

The newly observed $\Omega_c(3327)$ gives us a good chance to construct the $\Omega_c$ charmed baryon family. In this work, we carry out the mass spectrum analysis by a non-relativistic potential model using Gaussian Expansion Method, and the study of its two-body Okubo-Zweig-Iizuka allowed strong decay behavior. Our results imply that the $\Omega_c(3327)$ i

Gianira N. Alfarano, Altan B. Kilic, Alberto Ravagnani, Emina Soljanin

We investigate the properties of a family of polytopes that naturally arise in connection with a problem in distributed data storage, namely service rate region polytopes. The service rate region of a distributed coded system describes the data access requests that the underlying system can support. In this paper, we study the polytope structure of the servi

Davit Gogolashvili, Matteo Zecchin, Motonobu Kanagawa, Marios Kountouris

This paper investigates when the importance weighting (IW) correction is needed to address covariate shift, a common situation in supervised learning where the input distributions of training and test data differ. Classic results show that the IW correction is needed when the model is parametric and misspecified. In contrast, recent results indicate that the

Ella Hamonic, Anja Hopma, Baptiste Gaultier, Denis Moalic

Teaching digital manufacturing at scale using MOOCs has opened opportunities for IMT, a network of French graduate engineering schools, to work closely with a community of learners and educators in physical spaces called Fab Labs. By setting up a cohort of lifelong learning trainees taking the MOOC online and attending hands-on in-person workshops, IMT to ex

Michal Benes, Miroslav Kolar, Jan M. Sischka, Axel Voigt

We consider formal matched asymptotics to show the convergence of a degenerate area preserving surface Allen-Cahn equation to its sharp interface limit of area preserving geodesic curvature flow. The degeneracy results from a surface de Gennes-Cahn-Hilliard energy and turns out to be essential to numerically resolve the dependency of the solution on geometri

Rahul Srinivasan, Astrid Lamberts, Marie Anne Bizouard, Tristan Bruel

With nearly a hundred gravitational wave detections, the origin of black hole mergers has become a key question. Here, we focus on understanding the typical galactic environment in which binary black hole mergers arise. To this end, we synthesize progenitors of binary black hole mergers as a function of the redshift of progenitor formation, present-day forma

Kai Lu, Bo Yang, Bing Wang, Andrew Markham

Recent works in robotic manipulation through reinforcement learning (RL) or imitation learning (IL) have shown potential for tackling a range of tasks e.g., opening a drawer or a cupboard. However, these techniques generalize poorly to unseen objects. We conjecture that this is due to the high-dimensional action space for joint control. In this paper, we tak

Zengjie Zhang, Yingwei Du, Tong Liu, Fangzhou Liu

A novel procedure for the online identification of a class of discrete-time switched linear systems, which simultaneously estimates the parameters and switching manifolds of the systems, is proposed in this paper. Firstly, to estimate the parameters of the subsystems, a discrete-time concurrent learning-based recursive parameter estimator is designed to guar

André Lieutier, Mathijs Wintraecken

In this paper we introduce a pruning of the medial axis called the $(\lambda,\alpha)$-medial axis ($\textrm{ax}_\lambda^\alpha $). We prove that the $(\lambda,\alpha)$-medial axis of a set $K$ is stable in a Gromov-Hausdorff sense under weak assumptions. More formally we prove that if $K$ and $K'$ are close in the Hausdorff ($d_H$) sense then the $(\lambda,\

Georges Habib, Sylvie Paycha

Inspired by Gilkey's invariance theory, Getzler's rescaling method and Scott's approach to the index via Wodzicki residues, we give a localisation formula for the $\mathbb Z_2$-graded Wodzicki residue of the logarithm of a class of differential operators acting on sections of a spinor bundle over an even-dimensional manifold. This formula is expressed in ter

Simon Schmitt, John Shawe-Taylor, Hado van Hasselt

How to efficiently explore in reinforcement learning is an open problem. Many exploration algorithms employ the epistemic uncertainty of their own value predictions -- for instance to compute an exploration bonus or upper confidence bound. Unfortunately the required uncertainty is difficult to estimate in general with function approximation. We propose epist

Sacha Morin, Miguel Saavedra-Ruiz, Liam Paull

A fundamental task in robotics is to navigate between two locations. In particular, real-world navigation can require long-horizon planning using high-dimensional RGB images, which poses a substantial challenge for end-to-end learning-based approaches. Current semi-parametric methods instead achieve long-horizon navigation by combining learned modules with a

Xuanye Zhang, Jinyu Zou, Gang Xu

We develop an unrestricted Hartree-Fock mean-field method including Coulomb repulsion $U$, $V$ and spin-orbital coupling $\lambda$ self-consistently to investigate the mechanism of structural instability and magnetic ordering in Ba$_2$MgReO$_6$. A comprehensive quadrupole phase diagram versus $U$ and $V$ with $\lambda$=0.28eV is calculated. Our results demon

Zengjie Zhang, Dirk Wollherr

This paper proposes a novel observer-based disturbance estimation method for high degree-of-freedom Euler-Lagrangian systems using an unknown input-output (UIO) sliding mode observer (SMO). Different from the previous SMO methods, this approach does not assume the matching condition of the disturbances. Besides, compared to the conventional disturbance estim

David Brizuela, Marco de Cesare

Considering a generalization of the Gibbons-Hawking-York covariant boundary action that depends on both the extrinsic and the intrinsic geometry of the boundary, we derive boundary conditions for the cosmological background and tensor perturbations in a closed universe with space-like boundaries. We also give a general method to reconstruct the covariant bou

Juska E. Soljento, Simon W. Good, Adnane Osmane, Emilia K. J. Kilpua

We have investigated how the degree of imbalance in solar wind turbulence is modified by large-scale velocity shears in the solar wind plasma. The balance between counterpropagating Alfv\'enic fluctuations, which interact nonlinearly to generate the turbulence, has been quantified by the cross helicity and Elsasser ratio. Velocity shears at a 30-min timescal

René Wittmann, Paul A. Monderkamp, Hartmut Löwen

We explore the statistics of assembling soft-matter building blocks to investigate the uptake and encapsulation of cargo particles by carriers engulfing their load. While the such carrier-cargo complexes are important for many applications out of equilibrium, such as drug delivery and synthetic cell encapsulation, we uncover here the basic statistical physic

Wanpeng Han, Xingchuan Zhu, Shiping Feng, Huaiming Guo

Spin-triplet superconductivity is actively pursued in condensed matter physics due to the potential applications in topological quantum computations. The related pairing mechanism involving the interaction remains an important research topic. Here we propose a universal approach to obtain p-wave triplet superconductivity in the Hubbard models by simply chang

Kai Liu, Yarui Cao

Recent technology and equipment advancements provide with us opportunities to better analyze Alzheimer's disease (AD), where we could collect and employ the data from different image and genetic modalities that may potentially enhance the predictive performance. To perform better clustering in AD analysis, in this paper we propose a novel model to leverage d

Yuanwei Liu, Jiaqi Xu, Zhaolin Wang, Xidong Mu

The design dilemma of "What will be different between near-field communications (NFC) and far-field communications (FFC)?" is addressed from four perspectives. 1) From the channel modelling perspective, the differences between near-field and far-field channel models are discussed. A novel Green's function-based channel model is proposed for continuous-apertu

Alessandro Pacco, Valentina Ros

We consider pairs of GOE (Gaussian Orthogonal Ensemble) matrices which are correlated with each others, and subject to additive and multiplicative rank-one perturbations. We focus on the regime of parameters in which the finite-rank perturbations generate outliers in the spectrum of the matrices. We investigate the statistical correlation (i.e., the typical

Rodrigo Mello, Filipe Calegario, Geber Ramalho

Despite recent advancements, the field of text-to-image synthesis still suffers from lack of fine-grained control. Using only text, it remains challenging to deal with issues such as concept coherence and concept contamination. We propose a method to enhance control by generating specific concepts that can be reused throughout multiple images, effectively ex

Johannes Janicka, Paulo Debiagi, Arne Scholtissek, Andreas Dreizler

Storing electrical energy for long periods and transporting it over long distances is an essential task of the necessary transition to a CO$_2$-free energy economy. An oxidation-reduction cycle based on iron and its oxides represents a very promising technology in this regard. The present work assesses the potential of converting an existing modern coal-fire

Guilhem Lacombe, David Feliot, Etienne Boespflug, Marie-Laure Potet

Certification through auditing allows to ensure that critical embedded systems are secure. This entails reviewing their critical components and checking for dangerous execution paths. This latter task requires the use of specialized tools which allow to explore and replay executions but are also difficult to use effectively within the context of the audit, w

L. Mignon, N. Meunier, X. Delfosse, X. Bonfils

M dwarfs are active stars that exhibit variability in chromospheric emission and photometry at short and long timescales, including long cycles that are related to dynamo processes. This activity also impacts the search for exoplanets because it affects the radial velocities. We analysed a large sample of 177 M dwarfs observed with HARPS (2003-2020) in order

Javier De Miguel, Juan F. Hernández-Cabrera, Elvio Hernández-Suárez, Enrique Joven-Álvarez

We discuss the discovery potential of the Dark-photons & Axion-Like particles Interferometer (DALI) in this letter. The apparatus, currently in a design and prototyping phase, will probe axion dark matter from the Teide Observatory, an environment protected from terrestrial microwave sources, reaching Dine--Fischler--Srednicki--Zhitnitsky-like axion sensitiv

Adam Burgess, Marian Florescu, Dominic Michael Rouse

Many optically active systems possess spatially asymmetric electron orbitals. These generate permanent dipole moments, which can be stronger than the corresponding transition dipole moments, significantly affecting the system dynamics and creating polarised Fock states of light. We derive a master equation for these systems by employing an optical polaron tr

Samuel Deng, Navid Ardeshir, Daniel Hsu

We consider the problem of distribution-free conformal prediction and the criterion of group conditional validity. This criterion is motivated by many practical scenarios including hidden stratification and group fairness. Existing methods achieve such guarantees under either restrictive grouping structure or distributional assumptions, or they are overly-co

Aman Abhishek, Sayantan Sharma

Mean-field model quantum field theories of hadrons were traditionally developed to describe cold and dense nuclear matter and are by now very well constrained from the recent neutron star merger observations. We show that when augmented with additional known hadrons and resonances but not included earlier, these mean-field models can be extended beyond its r

D. Kinzebulatov, Yu. A. Semenov

We obtain gradient estimates on solutions to parabolic Kolmogorov equation with singular drift in a large class. Such estimates allow to construct a Feller evolution family, which is used to construct unique weak solutions to the corresponding stochastic differential equation.

Javier Gómez-Serrano, Alexandru D. Ionescu, Jaemin Park

This monograph addresses an important problem in mathematical fluid dynamics: constructing stable, long-term solutions to certain quasilinear evolution equations. We implement an elaborate scheme for building global quasiperiodic solutions without relying on external parameters. Instead of relying on artificial external parameters, we exploit the natural str

Xiaofeng Wang, Zheng Zhu, Wenbo Xu, Yunpeng Zhang

Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant benchmarks lack diversity in urban scenes, and they only evaluate front-view predictions. Towards a comprehensive benchmarking of surrounding perception algorithms, we propose OpenOc

Miguel Chamorro-Burgos, Adolfo Guarino, Colin Sterckx

We use holography and four-dimensional $\,\mathcal{N}=4\,$ gauged supergravity to collect evidence for a large class of interconnected three-dimensional $\,\mathcal{N}=2\,$ conformal field theories. On the gravity side, we construct a one-parameter family of $\,{\textrm{ISO}(3) \times \textrm{ISO}(3)}$ gaugings of half-maximal supergravity containing a rich

D. Pauli, L. M. Oskinova, W. -R. Hamann, D. M. Bowman

The origin of the observed population of Wolf-Rayet (WR) stars in low-metallicity (low-Z) galaxies, such as the Small Magellanic Cloud (SMC), is not yet understood. Standard, single-star evolutionary models predict that WR stars should stem from very massive O-type star progenitors, but these are very rare. On the other hand, binary evolutionary models predi

Zhimeng Zhang, Zhipeng Hu, Wenjin Deng, Changjie Fan

For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity dubbing results. To address the above problem, this paper proposes a Deformation Inpainting Network (DINet) for high-resolution face visually dubbing. Different from previous works r

Holger . B. Nielsen, Colin D. Froggatt

We briefly review and update our earlier published model for dark matter consisting of nanometer size bubbles of a new speculated vacuum phase in which some ordinary material, e.g. carbon, is present under high pressure caused by the surface tension of the domain wall surrounding the bubble. These bubbles or pearls are surrounded by dust grains, and it is on

Tristan Rigaut, Pierre Carpentier, Jean-Philippe Chancelier, Michel de Lara

In energy management, it is common that strategic investment decisions (storage capacity, production units) are made at a slow time scale, whereas operational decisions (storage, production) are made at a fast time scale: for such problems, the total number of decision stages may be huge. In this paper, we consider multistage stochastic optimization problems

Feihu Huang, Chunyu Xuan, Xinrui Wang, Siqi Zhang

Minimax optimization recently is widely applied in many machine learning tasks such as generative adversarial networks, robust learning and reinforcement learning. In the paper, we study a class of nonconvex-nonconcave minimax optimization with nonsmooth regularization, where the objective function is possibly nonconvex on primal variable $x$, and it is nonc

Lovro Lugović, Fabrizio Montesi

In the paradigm of choreographic programming, the overall behaviour of a distributed system is coded as a choreography from a global viewpoint. The choreography can then be automatically projected (compiled) to a correct implementation for each participant. This paradigm is interesting because it relieves the programmer from manually writing the separate sen

Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto

Structured state space sequence (S4) models have recently achieved state-of-the-art performance on long-range sequence modeling tasks. These models also have fast inference speeds and parallelisable training, making them potentially useful in many reinforcement learning settings. We propose a modification to a variant of S4 that enables us to initialise and

Anne Kathrine Petersen Bach, Trine Munch Nørgaard, Jens Christian Brok, Niels van Berkel

Clinical needs and technological advances have resulted in increased use of Artificial Intelligence (AI) in clinical decision support. However, such support can introduce new and amplify existing cognitive biases. Through contextual inquiry and interviews, we set out to understand the use of an existing AI support system by ophthalmologists. We identified co

Karl-G. Grosse-Erdmann, Dimitris Papathanasiou

We study the dynamical behaviour of weighted backward shift operators defined on sequence spaces over a directed tree. We provide a characterization of chaos on very general Fr\'echet sequence spaces in terms of the existence of a large supply of periodic points, or of fixed points. In the special case of the space $\ell^p$, $1\leq p<\infty$, or the space $c

Sarah Scheffler, Jonathan Mayer

Popular messaging applications now enable end-to-end-encryption (E2EE) by default, and E2EE data storage is becoming common. These important advances for security and privacy create new content moderation challenges for online services, because services can no longer directly access plaintext content. While ongoing public policy debates about E2EE and conten

Razvan Barbulescu, Adrien Poulalion

Unit group computations are a cryptographic primitive for which one has a fast quantum algorithm, but the required number of qubits is $\tilde O(m^5)$. In this work we propose a modification of the algorithm for which the number of qubits is $\tilde O(m^2)$ in the case of cyclotomic fields. Moreover, under a recent conjecture on the size of the class group o

Anna Sieben, Armin Seyfried

During the Love Parade disaster in 2011 in Duisburg, Germany, twenty one visitors were killed and more than five hundred injured in a very dense crowd on the route to and from the festival area. Approximately nine hundred visitors who had been among this crowd were subsequently interviewed by police officers as eyewitnesses. This paper content analyses a ran

C. Gehan, T. L. Campante, M. S. Cunha, F. Pereira

We developed, tested and validated a new Fast, Robust and Automated (FRA) tool to detect solar-like oscillations. FRA is based on the detection and measurement of the frequency of maximum oscillation power $\nu_{max}$, without relying on the detection of a regular frequency spacing to guide the search. We applied the FRA pipeline to 254 synthetic power spect

Spencer Rarrick, Ranjita Naik, Varun Mathur, Sundar Poudel

Although recent years have brought significant progress in improving translation of unambiguously gendered sentences, translation of ambiguously gendered input remains relatively unexplored. When source gender is ambiguous, machine translation models typically default to stereotypical gender roles, perpetuating harmful bias. Recent work has led to the develo

Udo Ausserlechner

This note is about uniform, plane, singly connected, regular Hall-plates with an arbitrary number of contacts exposed to a uniform magnetic field of arbitrary strength. In practice, the regular symmetry is the most common one. If the Hall-plates are mapped conformally to the unit disk, regular symmetry means that all contacts are equally large and all contac

Fang-Yu Li, Hao Yu, Jin Li, Lian-Fu Wei

We consider the perturbative photon flows (PPFs, i.e., electromagnetic (EM) counterparts) generated by the EM resonance response to high-frequency gravitational waves (HFGWs) with additional polarization states in a rotating laboratory frame system. It is found that when the propagating direction of HFGWs and the symmetrical axis of the laboratory frame syst

Xuecheng Wang

Motivated by the study of uniaxial crystal optics, we consider a coupled system of $3D$ anisotropic wave equations, in which they have the same speed only in one direction but distinct speeds in the other directions. Moreover, this system has a $1D$-type null structure along the common direction. Unlike the isotropic case, in which the celebrated Klainerman

Luís Cruz-Filipe, Lovro Lugović, Fabrizio Montesi

Programming communicating processes is challenging, because it requires writing separate programs that perform compatible send and receive actions at the right time during execution. Leaving this task to the programmer can easily lead to bugs. Choreographic programming addresses this challenge by equipping developers with high-level abstractions for codifyin

Diego Fonseca, Mauricio Junca

This work presents a new Distributionally Robust Optimization approach, using $p$-Wasserstein metrics, to analyze a stochastic program in a general context. The ambiguity set in this approach depends on the decision variable and is represented as a ball where both the center and the radius depend on the decision variable. We show that, under Lipschitz's assu

Bradd Hart

We present an introduction to modern continuous model theory with an emphasis on its interactions with topics covered in this volume such as $C^*$-algebras and von Neumann algebras. The role of ultraproducts is highlighted and expositions of definable sets, imaginaries, quantifier elimination and separable categoricity are included.

James K. Williams, Mario Gliozzi, Kyle A. Bockwoldt, Onic I. Shuvo

Accurately determining the black hole mass ($M_\mathrm{BH}$) in active galactic nuclei (AGN) is crucial to constraining their properties and to studying their evolution. While direct methods yield reliable measurements of $M_\mathrm{BH}$ in unobscured type 1 AGN, where the dynamics of stellar or gas components can be directly observed, only indirect methods

Fulong Wang, Huimin Wang, Binglin Zeng, Chenliang Xia

Laser triggered and photothermally induced vapor bubbles have emerged as promising approaches to facilitate optomechanical energy conversion for numerous relevant applications in micro/nanofluidics. Here we report the observation of a sub-megahertz spontaneous nucleation of explosive plasmonic bubbles, triggered by a continuous wave laser. The periodic nucle

Luis Camacho

Mainly due to lack of support, most under-resourced languages have a reduced lexicon in most realms and domains of increasing importance, then their speakers need to significantly augment it. Although neologisms should arise from the languages themselves, external sources are widely accepted. However, we dispute the "common sense" of using the imposed offici

Alessandro Basile, Riccardo Crupi, Michele Grasso, Alessandro Mercanti

Name Entity Disambiguation is the Natural Language Processing task of identifying textual records corresponding to the same Named Entity, i.e. real-world entities represented as a list of attributes (names, places, organisations, etc.). In this work, we face the task of disambiguating companies on the basis of their written names. We propose a Siamese LSTM N

William Trung Le, Chulmin Bang, Philippine Cordelle, Daniel Markel

Adaptive radiotherapy is a growing field of study in cancer treatment due to it's objective in sparing healthy tissue. The standard of care in several institutions includes longitudinal cone-beam computed tomography (CBCT) acquisitions to monitor changes, but have yet to be used to improve tumor control while managing side-effects. The aim of this study is t

Luciene da Silva Coelho, Edgar Mendoza, Amancio Cesar dos Santos Friaça

This work presents the results of a theoretical study that analyzed the possibility of nucleobases to form in the interstellar medium, in the Horsehead nebula, which is a region considered an archetype of molecular cloud. Performing the Meudon PDR code, the reactions of the nitrogen bases formation from formamide, which is a precursor compound identified in

Jessica Enright, Kitty Meeks, William Pettersson, John Sylvester

We generalise the popular cops and robbers game to multi-layer graphs, where each cop and the robber are restricted to a single layer (or set of edges). We show that initial intuition about the best way to allocate cops to layers is not always correct, and prove that the multi-layer cop number is neither bounded from above nor below by any increasing functio

Beate Scheibel, Stefanie Rinderle-Ma

Decision mining enables the discovery of decision rules from event logs or streams, and constitutes an important part of in-depth analysis and optimisation of business processes. So far, decision mining has been merely applied in an ex-post way resulting in a snapshot of decision rules for the given chunk of log data. Online decision mining, by contrast, ena

Allison McClure, Anne Shiu

A multistationarity region is the part of a reaction network's parameter space that gives rise to multiple steady states. Mathematically, this region consists of the positive parameters for which a parametrized family of polynomial equations admits two or more positive roots. Much recent work has focused on analyzing multistationarity regions of biologically

Satyajit Ghosh, Mousumi Dutta

Recent technological advancements have led to the development of new methods for managing organ donation systems, which aim to overcome the limitations of traditional centralized systems. To achieve increased transparency, security, and efficiency in the organ donation process, blockchain technology is being proposed as a replacement for these centralized sy

Frank Uhlig

We assess the situation of our elementary Linear Algebra classes in the US holistically and through personal history recollections. Possible remedies for our elementary Linear Algebra's teaching problems are discussed and a change from abstract algebraic taught classes to a concrete matrix based first course is considered. The challenges of such modernizatio

Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters

Model-based reinforcement learning is one approach to increase sample efficiency. However, the accuracy of the dynamics model and the resulting compounding error over modelled trajectories are commonly regarded as key limitations. A natural question to ask is: How much more sample efficiency can be gained by improving the learned dynamics models? Our paper e

Manoochehr Shirzaei

The availability of Synthetic Aperture Radar (SAR) data from different sensors and observation of the Global Navigation Satellite System (GNSS) has been growing worldwide. The complementary nature of InSAR and GNSS observations demands methodological advancements for integrating these datasets of variable accuracy, spatiotemporal sampling rate, and geometrie

Taja Kuzman, Igor Mozetič, Nikola Ljubešić

ChatGPT has shown strong capabilities in natural language generation tasks, which naturally leads researchers to explore where its abilities end. In this paper, we examine whether ChatGPT can be used for zero-shot text classification, more specifically, automatic genre identification. We compare ChatGPT with a multilingual XLM-RoBERTa language model that was

Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski

Today we have a good theoretical understanding of the representational power of Graph Neural Networks (GNNs). For example, their limitations have been characterized in relation to a hierarchy of Weisfeiler-Lehman (WL) isomorphism tests. However, we do not know what is encoded in the learned representations. This is our main question. We answer it using a pro

Griffin Adams, Jason Zucker, Noémie Elhadad

Long-form clinical summarization of hospital admissions has real-world significance because of its potential to help both clinicians and patients. The faithfulness of summaries is critical to their safe usage in clinical settings. To better understand the limitations of abstractive systems, as well as the suitability of existing evaluation metrics, we benchm

Anton Tkachuk, Tim Krake, Jan Gade, Malte von Scheven

Large statically indeterminate truss and frame structures exhibit complex load-bearing behavior, and redundancy matrices are helpful for their analysis and design. Depending on the task, the full redundancy matrix or only its diagonal entries are required. The standard computation procedure has a high computational effort. Many structures fall in the categor

Feihu Huang

Bilevel optimization is a popular two-level hierarchical optimization, which has been widely applied to many machine learning tasks such as hyperparameter learning, meta learning and continual learning. Although many bilevel optimization methods recently have been developed, the bilevel methods are not well studied when the lower-level problem is nonconvex.

Yogesh Girdhar, Nathan McGuire, Levi Cai, Stewart Jamieson

The current approach to exploring and monitoring complex underwater ecosystems, such as coral reefs, is to conduct surveys using diver-held or static cameras, or deploying sensor buoys. These approaches often fail to capture the full variation and complexity of interactions between different reef organisms and their habitat. The CUREE platform presented in t

Li Jinli, Yuan Ye

A high-dimensional and incomplete (HDI) matrix can describe the complex interactions among numerous nodes in various big data-related applications. A stochastic gradient descent (SGD)-based latent factor analysis (LFA) model is remarkably effective in extracting valuable information from an HDI matrix. However, such a model commonly encounters the problem of

Heeyuen Koh

The gradient information of multilayer perceptron with a linear neuron is modified with functional derivative for the global minimum search benchmarking problems. From this approach, we show that the landscape of the gradient derived from given continuous function using functional derivative can be the MLP-like form with ax+b neurons. In this extent, the sug

Narinder Singh, Anikesh Pal

The effect of the rotation on the turbulent mixing of two miscible fluids of small contrasting density, induced by Faraday instability, is investigated using direct numerical simulations (DNS). We quantify the irreversible mixing which depicts the conversion of the available potential energy (APE) to the background potential energy (BPE) through irreversible

Ye Tian, Zhengshuo Li, Wenchuan Wu, Miao Fan

The issues of uncertainty and frequency security could become significantly serious in power systems with the high penetration of volatile inverter-based renewables (IBRs). These issues make it necessary to consider the uncertainty and frequency-related constraints in the economic dispatch (ED) programs. However, existing ED studies rarely proactively optimi

Pritam Chatterjee, Sayan Banik, Sandip Bera, Arnob Kumar Ghosh

We report on a realistic and rather general scheme where noncollinear magnetic textures proximitized with the most common $s$-wave superconductor can appear as the alternative to $p$-wave superconductor{--}the prime proposal to realize two-dimensional (2D) Kitaev model for topological superconductors (TSCs) hosting Majorana flat edge mode (MFEM). A general m

Jan A. P. Reuter, Max Mäusezahl, Felix Moumtsilis, Tilman Pfau

An ensemble of Rubidum atoms can be excited with lasers such that it evolves into an entangled state with just one collective excitation within the Rydberg blockade radius. The decay of this state leads to the emission of a single, antibunched photon. For a hot vapor of Rubidium atoms in a micro cell we numerically study the feasibility of such a single-phot