July 2023 arXiv papers — page 117

Simone Cecchini, Martin Lesourd, Rudolf Zeidler

We prove a positive mass theorem for spin initial data sets $(M,g,k)$ that contain an asymptotically flat end and a shield of dominant energy (a subset of $M$ on which the dominant energy scalar $\mu-|J|$ has a positive lower bound). In a similar vein, we show that for an asymptotically flat end $\mathcal{E}$ that violates the positive mass theorem (i.e. $\m

Shuzhou Sun, Shuaifeng Zhi, Qing Liao, Janne Heikkilä

Despite the impressive performance of recent unbiased Scene Graph Generation (SGG) methods, the current debiasing literature mainly focuses on the long-tailed distribution problem, whereas it overlooks another source of bias, i.e., semantic confusion, which makes the SGG model prone to yield false predictions for similar relationships. In this paper, we expl

Juan Carlos Ruiz-Garcia, Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Moro

The aging population has led to a growing number of falls in our society, affecting global public health worldwide. This paper presents CareFall, an automatic Fall Detection System (FDS) based on wearable devices and Artificial Intelligence (AI) methods. CareFall considers the accelerometer and gyroscope time signals extracted from a smartwatch. Two differen

Martin Houde, Fereshteh Rajabi, Gordon C. MacLeod, Sharmila Goedhart

We discuss the role that coherence phenomena can have on the intensity variability of spectral lines associated with maser radiation. We do so by introducing the fundamental cooperative radiation phenomenon of (Dicke's) superradiance and discuss its complementary nature to the maser action, as well as its role in the flaring behaviour of some maser sources.

P. Babaev, F. Akhmetov, S. Gorbunov, N. Medvedev

We describe the formation of swift heavy ion tracks in polyethylene (PE) by combining the Monte Carlo code TREKIS, which models electronic excitation in nanometric proximity of the ion trajectory, with the molecular dynamics simulating a response of the atomic system to the perturbation. The model predicts circular tracks in amorphous PE but elliptical ones

Kamala Kanta Jena, Bidhubhusan Sahu, Jajati K. Nayak, Raj Preethi P

A phenomenological optical potential is used to study the elastic angular distributions for the system $^{19}F+^{208}Pb$ close to the Coulomb barrier. This potential is constructed by taking into account the flexible potential developed by Ginocchio. The fluctuations in the real and imaginary parts of the optical model potential follow the trends of the thre

Antonio Avilés, Mikołaj Krupski

The class of $L\Sigma(\leq\omega)$-spaces was introduced in 2006 by Kubi\'s, Okunev and Szeptycki as a natural refinement of the classical and important notion of Lindel\"of $\Sigma$-spaces. Compact $L\Sigma(\leq\omega)$-spaces were considered earlier, under different names, in the works of Tkachuk and Tkachenko in relation to metrizably fibered compacta. In

Zixuan Chen, Lingxiao Yang, Jianhuang Lai, Xiaohua Xie

Sparse-view Computed Tomography (SVCT) reconstruction is an ill-posed inverse problem in imaging that aims to acquire high-quality CT images based on sparsely-sampled measurements. Recent works use Implicit Neural Representations (INRs) to build the coordinate-based mapping between sinograms and CT images. However, these methods have not considered the corre

Marc Barthelemy

Stochastic equations constitute a major ingredient in many branches of science, from physics to biology and engineering. Not surprisingly, they appear in many quantitative studies of complex systems. In particular, this type of equation is useful for understanding the dynamics of urban population. Empirically, the population of cities follows a seemingly uni

Teddy Lazebnik, Or Iny

Temporal graphs have become an essential tool for analyzing complex dynamic systems with multiple agents. Detecting anomalies in temporal graphs is crucial for various applications, including identifying emerging trends, monitoring network security, understanding social dynamics, tracking disease outbreaks, and understanding financial dynamics. In this paper

Amaury Trujillo

Monetizing user-generated content in social media such as Reddit, in which users are both content creators and consumers, is challenging. Among the platform's strategies we find Reddit Awards, paid tokens of appreciation given by peer users who markedly enjoyed a particular posted content. Initially, there were only three awards, but the platform later great

Shuwei Zhou, Xiaoying Zhuang, Timon Rabczuk

Phase field model (PFM) is an efficient fracture modeling method and has high potential for hydraulic fracturing (HF). However, the current PFMs in HF do not consider well the effect of in-situ stress field and the numerical examples of porous media with stress boundary conditions were rarely presented. The main reason is that if the remote stress is applied

Vladislav Pimanov, Oleg Iliev, Ivan Oseledets, Ekaterina Muravleva

If the Stokes equations are properly discretized, it is known that the Schur complement matrix is spectrally equivalent to the identity matrix. Moreover, in the case of simple geometries, it is often observed that most of its eigenvalues are equal to one. These facts form the basis for the famous Uzawa algorithm. Despite recent progress in developing efficie

Jan Martens, Jan Friso Groote

We study the problem of computing minimal distinguishing formulas for non-bisimilar states in finite LTSs. We show that this is NP-hard if the size of the formula must be minimal. Similarly, the existence of a short distinguishing trace is NP-complete. However, we can provide polynomial algorithms, if minimality is formulated as the minimal number of nested

William L. Blair

We extend representation formulas that generalize the similarity principle of solutions to the Vekua equation to certain classes of meta-analytic functions. Also, we solve a generalization of the higher-order Schwarz boundary value problem in the context of meta-analytic functions with boundary conditions that are boundary values in the sense of distribution

Marcelo Jacinto, João Pinto, Jay Patrikar, John Keller

Developing and testing novel control and motion planning algorithms for aerial vehicles can be a challenging task, with the robotics community relying more than ever on 3D simulation technologies to evaluate the performance of new algorithms in a variety of conditions and environments. In this work, we introduce the Pegasus Simulator, a modular framework imp

Hsiu-Hsien Lin, Paul Scholz, Cherry Ng, Ue-Li Pen

We study the 10 fast radio bursts (FRBs) detected in the far side-lobe region of the CHIME telescope from 2018 August 28 to 2021 August 31. We find that the far side-lobe events have on average $\sim$500 times greater fluxes than events detected in CHIME's main lobe. We show that the side-lobe sample is therefore statistically $\sim$20 times closer than the

Hsiu-Hsien Lin, Paul Scholz, Cherry Ng, Ue-Li Pen

We report ten fast radio bursts (FRBs) detected in the far side-lobe region (i.e., $\geq 5^\circ$ off-meridian) of the Canadian Hydrogen Intensity Mapping Experiment (CHIME) from 2018 August 28 to 2021 August 31. We localize the bursts by fitting their spectra with a model of the CHIME/FRB synthesized beam response. We find that the far side-lobe events have

Abhinav Joshi, Akshat Sharma, Sai Kiran Tanikella, Ashutosh Modi

The task of Prior Case Retrieval (PCR) in the legal domain is about automatically citing relevant (based on facts and precedence) prior legal cases in a given query case. To further promote research in PCR, in this paper, we propose a new large benchmark (in English) for the PCR task: IL-PCR (Indian Legal Prior Case Retrieval) corpus. Given the complex natur

Emi Tanaka

Experiments require human decisions in the design process, which in turn are reformulated and summarized as inputs into a system (computational or otherwise) to generate the experimental design. I leverage this system to promote a language of experimental designs by proposing a novel computational framework, called "the grammar of experimental designs", to s

Francesco Nalin, Maria Celeste Tirelli, Piotr Garstecki, Witold Postek

We present Tuna-step, a novel microfluidic module based on step emulsification that allows for reliable generation of droplets of different sizes. Until now, sizes of droplets generated with step emulsification were hard-wired into the geometry of the step emulsification nozzle. To overcome this, we incorporate a thin membrane underneath the step nozzle that

Sebastian Rachuba, Melanie Reuter-Oppermann, Clemens Thielen

Efficient planning of scarce resources in hospitals is a challenging task for which a large variety of Operations Research and Management Science approaches have been developed since the 1950s. While efficient planning of single resources such as operating rooms, beds, or specific types of staff can already lead to enormous efficiency gains, integrated plann

Wenkui Ding, Xingyu Zhang, Jing Liu, Xiaoguang Wang

We propose a novel quantum sensing protocol that leverages the dynamical response of physical observables to quenches in quantum systems. Specifically, we use the nitrogen-vacancy (NV) color center in diamond to realize both scalar and vector magnetometry via quantum response. Furthermore, we suggest a method for detecting the motion of magnetic nanoparticle

Linhao Qu, Yingfan Ma, Zhiwei Yang, Manning Wang

Active learning (AL) is an effective approach to select the most informative samples to label so as to reduce the annotation cost. Existing AL methods typically work under the closed-set assumption, i.e., all classes existing in the unlabeled sample pool need to be classified by the target model. However, in some practical clinical tasks, the unlabeled pool

Florian Rehm, Sofia Vallecorsa, Kerstin Borras, Dirk Krücker

The Quantum Angle Generator (QAG) is a new full Quantum Machine Learning model designed to generate accurate images on current Noise Intermediate Scale (NISQ) Quantum devices. Variational quantum circuits form the core of the QAG model, and various circuit architectures are evaluated. In combination with the so-called MERA-upsampling architecture, the QAG mo

Hans Ulrich Simon, Jan Arne Telle

Imagine a learner L who tries to infer a hidden concept from a collection of observations. Building on the work [4] of Ferri et al., we assume the learner to be parameterized by priors P(c) and by c-conditional likelihoods P(z|c) where c ranges over all concepts in a given class C and z ranges over all observations in an observation set Z. L is called a MAP-

Akifumi Okuno

Density power divergence (DPD) is designed to robustly estimate the underlying distribution of observations, in the presence of outliers. However, DPD involves an integral of the power of the parametric density models to be estimated; the explicit form of the integral term can be derived only for specific densities, such as normal and exponential densities.

Damiano Rossi

In this paper we study the simplicial complex induced by the poset of Brauer pairs ordered by inclusion for the family of finite reductive groups. In the defining characteristic case, the homotopy type of this simplicial complex coincides with that of the Tits building thanks to a well-known result of Quillen. On the other hand, in the non-defining character

Száva Bánsághi, Viola Sári, Péter Szerémy, Ákos Lehotsky

Healthcare-Associated Infections present a major threat to patient safety globally. According to studies, more than 50% of HAI could be prevented by proper hand hygiene. Effectiveness of hand hygiene is regularly evaluated with the fluorescent method: performing hand hygiene with a handrub containing an ultra violet (UV) fluorescent marker. Typically, human

Zhiwen Yang, Yang Zhou, Hui Zhang, Bingzheng Wei

Multi-center positron emission tomography (PET) image synthesis aims at recovering low-dose PET images from multiple different centers. The generalizability of existing methods can still be suboptimal for a multi-center study due to domain shifts, which result from non-identical data distribution among centers with different imaging systems/protocols. While

Pascal Viot, Aykut Argun, Giovanni Volpe, Alberto Imparato

The Brownian gyrator (BG) is often called a minimal model of a nano-engine performing a rotational motion, judging solely upon the fact that in non-equilibrium conditions its torque, angular momentum ${\cal L}$ and angular velocity $\cal W$ have non-zero mean values. For a time-discretized model, which is most adapted for the analysis of an essentially discr

Wei Zhang, Antonietta Mira, Ernst C. Wit

COVID-19 has led to excess deaths around the world, however it remains unclear how the mortality of other causes of death has changed during the pandemic. Aiming at understanding the wider impact of COVID-19 on other death causes, we study Italian data set that consists of monthly mortality counts of different causes from January 2015 to December 2020. Due t

Renzo Angles, Georg Gottlob, Aleksandar Pavlovic, Reinhard Pichler

Over the past decade, Knowledge Graphs have received enormous interest both from industry and from academia. Research in this area has been driven, above all, by the Database (DB) community and the Semantic Web (SW) community. However, there still remains a certain divide between approaches coming from these two communities. For instance, while languages suc

Alexander J. H. Houston, Gareth P. Alexander

A major challenge in the study of active systems is to harness their non-equilibrium dynamics into useful work. We address this by showing how to design colloids with controllable spontaneous propulsion or rotation when immersed in active nematics. This is illustrated for discs with tilted anchoring and chiral cogs, for which we determine the nematic directo

Volker Kaibel, Kirill Kukharenko

We describe constructions of extended formulations that establish a certain relaxed version of the Hirsch conjecture and prove that if there is a pivot rule for the simplex algorithm for which one can bound the number of steps by a polynomial in the diameter plus the number of facets of the polyhedron of feasible solutions then the general linear programming

Andreas Debrouwere, Lenny Neyt

We study an extension problem for continuous linear maps in the setting of $(LB)$-spaces. More precisely, we characterize the pairs $(E,Z)$, where $E$ is a locally complete space with a fundamental sequence of bounded sets and $Z$ is an $(LB)$-space, such that for every exact sequence of $(LB)$-spaces $$ 0 \rightarrow X \xrightarrow{\iota} Y \rightarrow Z \r

Mariia Dospolova, Ekaterina Kochetkova, Eric T. Mortenson

Using a higher-dimensional analog of an identity known to Kronecker, we discover a new Andrews--Crandall-type identity and use it to count the number of integer solutions to $x^2+2y^2+2z^2=n$.

Marius Kadek, Lukas Konecny, Michal Repisky

Recent advances in laser technology enable to follow electronic motion at its natural time-scale with ultrafast pulses, leading the way towards atto- and femtosecond spectroscopic experiments of unprecedented resolution. Understanding of these laser-driven processes, which almost inevitably involve non-linear light-matter interactions and non-equilibrium ele

Bruno Machado Pacheco, Victor Hugo Rocha de Oliveira, Augusto Braga Fernandes Antunes, Saulo Domingos de Souza Pedro

Brain age prediction using neuroimaging data has shown great potential as an indicator of overall brain health and successful aging, as well as a disease biomarker. Deep learning models have been established as reliable and efficient brain age estimators, being trained to predict the chronological age of healthy subjects. In this paper, we investigate the im

Daria Zakharova, Benedetta Vulcani, Gabriella De Lucia, Lizhi Xie

Filaments are elongated structures that connect groups and clusters of galaxies and are visually the striking feature in cosmological maps. In the literature, typically filaments are defined only using galaxies, assuming that these are good tracers of the dark matter distribution, despite the fact that galaxies are a biased indicator. Here we apply the topol

Baiqing Zhu

For a prime number $p>2$, we explain the construction of the difference divisors on the unitary Rapoport-Zink spaces of hyperspecial level and the GSpin Rapoport-Zink spaces of hyperspecial level associated to a minuscule cocharacter $\mu$ and a basic element $b$. We prove the regularity of the difference divisors, find the formally smooth locus of both the

Samuel Grushevsky, Riccardo Salvati Manni

We study various naturally defined subvarieties of the moduli space ${\mathcal A}_g$ of complex principally polarized abelian varieties (ppav) in a neighborhood of the locus of products of $g$ elliptic curves. In this neighborhood, we obtain a local description for the locus of hyperelliptic curves, reproving the recent result of Shepherd-Barron that the hyp

De-Bing Long, Nikolay V. Tkachenko, Qingqing Feng, Xingxing Li

The expanded phthalocyanine (EPc) single-layer sheets with double transition metals (labeled as TM2EPc, TM = Sc-Zn) are predicted to be a new class of two-dimensional (2D) metal-organic materials with a series of favorable functional properties by means of systematic first-principle calculations and molecular dynamics simulations. The strong coordination bet

Xin-Kai Wen, Bin Yan, Zhite Yu, C. -P. Yuan

Electroweak dipole operators in the Standard Model Effective Field Theory (SMEFT) are important indirect probes of quantum effects of new physics beyond the Standard Model (SM), yet they remain poorly constrained by current experimental analyses for lack of interference with the SM amplitudes in constructing cross section observables. In this Letter, we poin

Hanitriniala Malalatiana Rakotondrasoa, Martin Bucher, Ilya Sinayskiy

We compare the performance of three nearest neighbor search algorithms: the Orchard, ball tree, and VP-tree algorithms. These algorithms are commonly used for nearest-neighbor searches and are known for their efficiency in large datasets. We analyze the fraction of distances computed in relation to the size of the dataset and its dimension. For each algorith

Peng Su, Garth Tarr, Samuel Muller, Suojin Wang

Cellwise contamination remains a challenging problem for data scientists, particularly in research fields that require the selection of sparse features. Traditional robust methods may not be feasible nor efficient in dealing with such contaminated datasets. We propose CR-Lasso, a robust Lasso-type cellwise regularization procedure that performs feature selec

A. J. Crilly, D. J. Schlossberg, B. D. Appelbe, A. S. Moore

The hydrodynamics of the dense confining fuel shell is of great importance in defining the behaviour of the burning plasma and burn propagation regimes of inertial confinement fusion experiments. However, it is difficult to probe due to its low emissivity in comparison to the central fusion core. In this work, we utilise the backscattered neutron spectroscop

Mohammad Dehghani, Zahra Yazdanparast

Artificial intelligence has made remarkable progress in handling complex tasks, thanks to advances in hardware acceleration and machine learning algorithms. However, to acquire more accurate outcomes and solve more complex issues, algorithms should be trained with more data. Processing this huge amount of data could be time-consuming and require a great deal

Kristóf Takács, Renáta Nagyné Elek, Tamás Haidegger

Image processing techniques have huge impact on most fields of robotics and industrial automation. Real time methods are usually employed in complex automation tasks, assisting with decision making or directly guiding robots and machinery, while post-processing is usually used for retrospective assessment of systems and processes. While artificial intelligen

Hyun Seung Choi

In this article, we show that Mori domains, pseudo-valuation domains, and $n$-absorbing ideals, the three seemingly unrelated notions in commutative ring theory, are interconnected. In particular, we prove that an integral domain $R$ is a Mori locally pseudo-valuation domain if and only if each proper ideal of $R$ is a finite product of 2-absorbing ideals of

Hongyu Hè, Michal Friedman, Theodoros Rekatsinas

In the post-Moore's Law era, relying solely on hardware advancements for automatic performance gains is no longer feasible without increased energy consumption, due to the end of Dennard scaling. Consequently, computing accounts for an increasing amount of global energy usage, contradicting the objective of sustainable computing. The lack of hardware support

O. Chrenko, R. O. Chametla

We investigate the migration of Mars- to super-Earth-sized planets in the vicinity of a pressure bump in a 3D radiative protoplanetary disc while accounting for the effect of accretion heat release. Pressure bumps have often been assumed to act as efficient migration traps, but we show that the situation changes when the thermal forces are taken into account

Gaetano Lambiase, Tanmay Kumar Poddar

The interaction of neutrinos with ultralight scalar and vector dark matter backgrounds induce a modification of the neutrino dispersion relation. The effects of this modification are reviewed in the framework of asymmetric emission of neutrinos from the supernova core, and, in turn, of pulsar kicks. We consider the neutrino oscillations, focusing in particul

Runcheng Liu, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh

Prompt-tuning has become an increasingly popular parameter-efficient method for adapting large pretrained language models to downstream tasks. However, both discrete prompting and continuous prompting assume fixed prompts for all data samples within a task, neglecting the fact that inputs vary greatly in some tasks such as open-domain dialogue generation. In

J. R. Bravo, G. Stabile, M. Hess, J. A. Hernandez

This article presents a general reduced order model (ROM) framework for addressing fluid dynamics problems involving time-dependent geometric parametrisations. The framework integrates Proper Orthogonal Decomposition (POD) and Empirical Cubature Method (ECM) hyper-reduction techniques to effectively approximate incompressible computational fluid dynamics sim

Muhammad Aitsam, Alessandro Di Nuovo

Hand gestures are a form of non-verbal communication that is used in social interaction and it is therefore required for more natural human-robot interaction. Neuromorphic (brain-inspired) computing offers a low-power solution for Spiking neural networks (SNNs) that can be used for the classification and recognition of gestures. This article introduces the p

Yuyang Du, Soung Chang Liew

This paper reexamines and fundamentally improves the Schmidl-and-Cox (S&C) algorithm, which is extensively used for packet detection in wireless networks, and enhances its adaptability for multi-antenna receivers. First, we introduce a new "compensated autocorrelation" metric, providing a more analytically tractable solution with precise expressions for fals

Christoph Emeis, Sanjoy Kr Mahatha, Sebastian Rohlf, Kai Rossnagel

We combine ab-initio calculations based on many-body perturbation theory and the cumulant expansion with angle-resolved photoemission spectroscopy (ARPES) to quantify the electron-plasmon interaction in the highly-doped semiconducting transition metal dichalcogenide 1$T$-HfS$_2$. ARPES reveals the emergence of satellite spectral features in the vicinity of q

Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang

We present Emu, a Transformer-based multimodal foundation model, which can seamlessly generate images and texts in multimodal context. This omnivore model can take in any single-modality or multimodal data input indiscriminately (e.g., interleaved image, text and video) through a one-model-for-all autoregressive training process. First, visual signals are en

Nahid Hosseini, Matthias Neuenschwander, Jonathan D. Adams, Santiago H. Andany

Active microelectromechanical systems can couple the nanomechanical domain with the electronic domain by integrating electronic sensing and actuation mechanisms into the micromechanical device. This enables very fast and sensitive measurements of force, acceleration, or the presence of biological analytes. In particular, strain sensors integrated onto MEMS c

Razu Ahmed, Md. Sajidul Islam, M. M. Hossain, M. A. Ali

We have looked into the structural, mechanical, optoelectronic, superconducting state and thermophysical aspects of intermetallic compound Zr$_3$Ir using the density functional theory (DFT). Many of the physical properties, including direction dependent mechanical properties, Vickers hardness, optical properties, chemical bonding nature, and charge density d

David Rapado-Rincon, Eldert J. van Henten, Gert Kootstra

The agro-food industry is turning to robots to address the challenge of labour shortage. However, agro-food environments pose difficulties for robots due to high variation and occlusions. In the presence of these challenges, accurate world models, with information about object location, shape, and properties, are crucial for robots to perform tasks accuratel

Anna Schmitt, Kirstin Peters

Encodings are the main way to compare process calculi. By applying quality criteria to encodings we analyse their quality and rule out trivial or meaningless encodings. Thereby, operational correspondence is one of the most common and most important quality criteria. It ensures that processes and their translations have the same abstract behaviour. We analys

Dhruv Mullick, Bilal Ghanem, Alona Fyshe

Customer feedback is invaluable to companies as they refine their products. Monitoring customer feedback can be automated with Aspect Level Sentiment Classification (ALSC) which allows us to analyse specific aspects of the products in reviews. Large Language Models (LLMs) are the heart of many state-of-the-art ALSC solutions, but they perform poorly in some

Michail Chatzianastasis, Giannis Nikolentzos, Michalis Vazirgiannis

Graph neural networks have become the standard approach for dealing with learning problems on graphs. Among the different variants of graph neural networks, graph attention networks (GATs) have been applied with great success to different tasks. In the GAT model, each node assigns an importance score to its neighbors using an attention mechanism. However, si

Maximilien Gadouleau, David C. Kutner

The simple greedy algorithm to find a maximal independent set of a graph can be viewed as a sequential update of a Boolean network, where the update function at each vertex is the conjunction of all the negated variables in its neighbourhood. In general, the convergence of the so-called kernel network is complex. A word (sequence of vertices) fixes the kerne

Kingshook Biswas, Utsav Dewan

A well studied classical problem is the harmonicity of functions satisfying the restricted mean-value property (RMVP). While this has so far been studied mainly for domains in $\mathbb{R}^n$, we consider this problem in the general setting of domains in Riemannian manifolds, and obtain results generalizing classical results of Fenton. We also obtain a result

John J. McCord, Shruti Dogra, Gheorghe Sorin Paraoanu

Quantum physics allows an object to be detected even in the absence of photon absorption by the use of so-called interaction-free measurements. We provide a formulation of this protocol using a three-level system, where the object to be detected is a pulse coupled resonantly to the second transition. In the original formulation of interaction-free measuremen

Sumedha Biswas, Zuzanna Kostrzewa-Rutkowska, Peter G. Jonker, Paul Vreeswijk

The discovery of gravitational wave (GW) events and the detection of electromagnetic counterparts from GW170817 has started the era of multimessenger GW astronomy.The field has been developing rapidly and in this paper,we discuss the preparation for detecting these events with the ESA Gaia satellite,during the 4th observing run of the LIGO-Virgo-KAGRA (LVK)

Abhinav Chandraker, Sampad Barik, Nichenametla Jai Sai, Ankur Chauhan

Traditionally, yield strength prediction relies on detailed and resource-intensive microstructural characterization combined with empirical equations. However, quantifying microstructural feature length scales for novel processes like additive manufacturing, which involves inhomogeneous hierarchical features, poses a challenge. The lack of accurate material

Erik Burman, Janosch Preuss

We study unique continuation over an interface using a stabilized unfitted finite element method tailored to the conditional stability of the problem. The interface is approximated using an isoparametric transformation of the background mesh and the corresponding geometrical error is included in our error analysis. To counter possible destabilizing effects c

Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren

Recent studies show that deep reinforcement learning (DRL) agents tend to overfit to the task on which they were trained and fail to adapt to minor environment changes. To expedite learning when transferring to unseen tasks, we propose a novel approach to representing the current task using reward machines (RMs), state machine abstractions that induce subtas

Lena Eichermüller, Gaurang Chaudhari, Ioannis Katsavounidis, Zhijun Lei

Current developments in video encoding technology lead to continuously improving compression performance but at the expense of increasingly higher computational demands. Regarding the online video traffic increases during the last years and the concomitant need for video encoding, encoder complexity control mechanisms are required to restrict the processing

Ze-Sheng Xu, Jun Gao, Adrian Iovan, Ivan M. Khaymovich

The interrelationship between localization, quantum transport, and disorder has remained a fascinating focus in scientific research. Traditionally, it has been widely accepted in the physics community that in one-dimensional systems, as disorder increases, localization intensifies, triggering a metal-insulator transition. However, a recent theoretical invest

Chetna Singhal, Thiemo Voigt, Luca Mottola

We study how to mitigate the effects of energy attacks in the batteryless Internet of Things (IoT). Battery-less IoT devices live and die with ambient energy, as they use energy harvesting to power their operation. They are employed in a multitude of applications, including safety-critical ones such as biomedical implants. Due to scarce energy intakes and li

A. Bernal, J. A. Casas, J. M. Moreno

Quantum entanglement and quantum entropy are crucial concepts in the study of multipartite quantum systems. In this work we show how the notion of concurrence vector, re-expressed in a particularly useful form, provides new insights and computational tools for the analysis of both. In particular, using this approach for a general multipartite pure state, one

Jan Niklas Reinhardt, Martin Staab, Kohei Yamamoto, Jean-Baptiste Bayle

Interspacecraft ranging is crucial for the suppression of laser frequency noise via time-delay interferometry (TDI). So far, the effects of on-board delays and ambiguities on the LISA ranging observables were neglected in LISA modelling and data processing investigations. In reality, on-board delays cause offsets and timestamping delays in the LISA measureme

Can Xu, Tao Wang, Qiusheng Gu, Anita Zanella

Structural properties of cluster galaxies during their peak formation epoch, $z \sim 2-4$ provide key information on whether and how environment affects galaxy formation and evolution. Based on deep HST/WFC3 imaging towards the z=2.51 cluster, J1001, we explore environmental effects on the structure, color gradients, and stellar populations of a statistical

Chao Wang, Zheng Tang

In the context of label-efficient learning on video data, the distillation method and the structural design of the teacher-student architecture have a significant impact on knowledge distillation. However, the relationship between these factors has been overlooked in previous research. To address this gap, we propose a new weakly supervised learning framewor

Kshiti Sneh Rai, J. Ignacio Cirac, Álvaro M. Alhambra

We show how to efficiently simulate pure quantum states in one dimensional systems that have both finite energy density and vanishingly small energy fluctuations. We do so by studying the performance of a tensor network algorithm that produces matrix product states whose energy variance decreases as the bond dimension increases. Our results imply that varian

Vojtech Franc, Daniel Prusa, Jakub Paplham

The optimal prediction strategy for out-of-distribution (OOD) setups is a fundamental question in machine learning. In this paper, we address this question and present several contributions. We propose three reject option models for OOD setups: the Cost-based model, the Bounded TPR-FPR model, and the Bounded Precision-Recall model. These models extend the st

Hasan Arslan, Alnour Altoum, Hilal Karakus Arslan

In this paper, we introduce an inversion statistic on the hyperoctahedral group $B_n$ by using an decomposition of a positive root system of this reflection group. Then we prove some combinatorial properties for the inversion statistic. We establish an enumeration system on the group $B_n$ and give an efficient method to uniquely derive any group element kno

A. Pérez-Obiol, S. Masot-Llima, A. M. Romero, J. Menéndez

Quantum entanglement offers a unique perspective into the underlying structure of strongly-correlated systems such as atomic nuclei. In this paper, we use quantum information tools to analyze the structure of light and medium-mass berillyum, oxygen, neon and calcium isotopes within the nuclear shell model. We use different entanglement metrics, including sin

Swarnak Ray, Arun Roy

We propose a simple active hydrodynamic model for the self-propulsion of a liquid droplet suspended in micellar solutions. The self-propulsion of the droplet occurs by spontaneous breaking of isotropic symmetry and is studied using both analytical and numerical methods. The emergence of self-propulsion arises from the slow dissolution of the inner fluid into

Seyed Hassan Alavi

In this article, we study $2$-designs with $\lambda=2$ admitting a flag-transitive almost simple automorphism group with socle a finite simple exceptional group of Lie type, and we prove that such a $2$-design does not exist. In conclusion, we present a classification of $2$-designs with $\lambda=2$ admitting flag-transitive and point-primitive automorphism

Jack Jewson, Sahra Ghalebikesabi, Chris Holmes

Differential privacy guarantees allow the results of a statistical analysis involving sensitive data to be released without compromising the privacy of any individual taking part. Achieving such guarantees generally requires the injection of noise, either directly into parameter estimates or into the estimation process. Instead of artificially introducing pe

Hassan Ali, Adnan Qayyum, Ala Al-Fuqaha, Junaid Qadir

Several membership inference (MI) attacks have been proposed to audit a target DNN. Given a set of subjects, MI attacks tell which subjects the target DNN has seen during training. This work focuses on the post-training MI attacks emphasizing high confidence membership detection -- True Positive Rates (TPR) at low False Positive Rates (FPR). Current works in

David Gunn, Martin Hebenstreit, Cornelia Spee, Julio I. de Vicente

Understanding multipartite entanglement is a key goal in quantum information. Entanglement in pure states can be characterised by considering transformations under Local Operations assisted by Classical Communication (LOCC). However, it has been shown that, for $n\ge5$ parties, multipartite pure states are generically isolated, i.e., they can neither be reac

J. Orell-Miquel, M. Lampón, M. López-Puertas, M. Mallorquín

HD235088 (TOI-1430) is a young star known to host a sub-Neptune-sized planet candidate. We validated the planetary nature of HD235088 b with multiband photometry, refined its planetary parameters, and obtained a new age estimate of the host star, placing it at 600-800 Myr. Previous spectroscopic observations of a single transit detected an excess absorption

Ashraf Daneshkhah

In this article, we prove that if $\mathcal{D}$ is a $2$-design with $k=7$ admitting flag-transitive almost simple automorphism group with socle an alternating group, then $\mathcal{D}$ is $PG_{2}(3,2)$ with parameter set $(15,7,3)$ and $G=A_7$, or $\mathcal{D}$ is the $2$-design with parameter set $(55, 7, 1680)$ and $G=A_{11}$ or $S_{11}$.

Harshad Khadilkar

We present a simple linear regression based approach for learning the weights and biases of a neural network, as an alternative to standard gradient based backpropagation. The present work is exploratory in nature, and we restrict the description and experiments to (i) simple feedforward neural networks, (ii) scalar (single output) regression problems, and (

Malte Algren, John Andrew Raine, Tobias Golling

Being able to decorrelate a feature space from protected attributes is an area of active research and study in ethics, fairness, and also natural sciences. We introduce a novel decorrelation method using Convex Neural Optimal Transport Solvers (Cnots) that is able to decorrelate a continuous feature space against protected attributes with optimal transport.

Stefano Cipolla, Jacek Gondzio, Filippo Zanetti

In this work, the authors address the Optimal Transport (OT) problem on graphs using a proximal stabilized Interior Point Method (IPM). In particular, strongly leveraging on the induced primal-dual regularization, the authors propose to solve large scale OT problems on sparse graphs using a bespoke IPM algorithm able to suitably exploit primal-dual regulariz

Nitisha Aggarwal, Geetika Jain Saxena, Sanjeev Singh, Amit Pundir

Generative AI techniques have opened the path for new generations of machines in diverse domains. These machines have various capabilities for example, they can produce images, generate answers or stories, and write codes based on the "prompts" only provided by users. These machines are considered 'thinking minds' because they have the ability to generate hu

Yuval Abulafia, Amit Goft, Nadav Orion, Eric Akkermans

We present a general method to identify topological materials by studying the local electronic density $\delta \rho \left(\boldsymbol{r}\right)$. More specifically, certain types of defects or spatial textures such as vacancies, turn graphene into a topological material characterised by invariant Chern or winding numbers. We show that these numbers are direc

Seyed Hassan Alavi, Ashraf Daneshkhah

In this article, we study symmetric designs admitting flag-transitive, point-imprimitive almost simple automorphism groups with socle sporadic simple groups. As a corollary, we present a classification of symmetric designs admitting flag-transitive automorphism group whose socle is a sporadic simple group, and in conclusion, there are exactly seven such desi

Shuhe Wu, Dong Zhang, Zhengchun Li, Minwei Shi

Rydberg atoms have been shown remarkable performance in sensing microwave field. The sensitivity of such an electrometer based on optical readout of atomic ensemble has been demonstrated to approach the photon-shot-noise limit. However, the sensitivity can not be promoted infinitely by increasing the power of probe light due to the increased collision rates

Long Bai, Mobarakol Islam, Hongliang Ren

Medical students and junior surgeons often rely on senior surgeons and specialists to answer their questions when learning surgery. However, experts are often busy with clinical and academic work, and have little time to give guidance. Meanwhile, existing deep learning (DL)-based surgical Visual Question Answering (VQA) systems can only provide simple answer

Tobias van der Werff, Maruf A. Dhali, Lambert Schomaker

Handwriting recognition has seen significant success with the use of deep learning. However, a persistent shortcoming of neural networks is that they are not well-equipped to deal with shifting data distributions. In the field of handwritten text recognition (HTR), this shows itself in poor recognition accuracy for writers that are not similar to those seen

Yan Cao, Yong Tang

Ultralight bosons are well-motivated particles from various physical and cosmological theories, and can be spontaneously produced during the superradiant process, forming a dense hydrogen-like cloud around the spinning black hole. After the growth saturates, the cloud slowly depletes its mass through gravitational-wave emission. In this work we study the orb