April 2024 arXiv papers — page 160

Mauricio Marcano, Joseba Sarabia, Asier Zubizarreta, Sergio Díaz

This paper presents the validation of shared control strategies for critical maneuvers in automated driving systems. Shared control involves collaboration between the driver and automation, allowing both parties to actively engage and cooperate at different levels of the driving task. The involvement of the driver adds complexity to the control loop, necessi

O. L. Creevey, S. Cassisi, F. Thévenin, M. Salaris

There is plenty of evidence in the literature of significant discrepancies between the observations and models of metal-poor red giant branch stars, in particular regarding the effective temperature, teff, scale. We revisit the benchmark star HD 122563 using the most recent observations from Gaia Data Release 3, to investigate if these new constraints may he

Muhammed Shafeeque, Arun Mathew, Malay K. Nandy

The nature of equation of state for the matter in the neutron star plays an important role in determining its maximal mass. In addition, it must comply with the condition of causality. Noting that the central density of a maximally massive neutron star is well above the nuclear saturation density, a deconfined quark core in the central region is motivated in

Yun Sun, Bing Li

Let $f$ be an expansive Lorenz map on $[0,1]$ and $c$ be the critical point. The survivor set we are discussing here is denoted as $S^+_{f}(a,b):=\{x\in[0,1]:f(b)\leq f^{n}(x) \leq f(a)\ \forall n\geq0\}$, where the hole $(a,b)\subseteq [0,1]$ satisfies $a\leq c \leq b$ and $a\neq b$. Let $a\in[0,c]$ be fixed, we mainly focus on the following two bifurcation

Lili Liang, Guanglu Sun, Jin Qiu, Lizhong Zhang

Compositional spatio-temporal reasoning poses a significant challenge in the field of video question answering (VideoQA). Existing approaches struggle to establish effective symbolic reasoning structures, which are crucial for answering compositional spatio-temporal questions. To address this challenge, we propose a neural-symbolic framework called Neural-Sy

Saskia Nuñez von Voigt, Luise Mehner, Florian Tschorsch

The notion of $\varepsilon$-differential privacy is a widely used concept of providing quantifiable privacy to individuals. However, it is unclear how to explain the level of privacy protection provided by a differential privacy mechanism with a set $\varepsilon$. In this study, we focus on users' comprehension of the privacy protection provided by a differe

Nikolay Kalmykov, Rishat Zagidullin, Oleg Rogov, Sergey Rykovanov

Modulation instability is a phenomenon of spontaneous pattern formation in nonlinear media, oftentimes leading to an unpredictable behaviour and a degradation of a signal of interest. We propose an approach based on reinforcement learning to suppress the unstable modes by optimizing the parameters for the time modulation of the potential in the nonlinear sys

Andrew Jreissaty, Juan Carrasquilla

We study the statistical physics of the classical Ising model in the so-called $\alpha$-R\'enyi ensemble, a finite-temperature thermal state approximation that minimizes a modified free energy based on the $\alpha$-R\'enyi entropy. We begin by characterizing its critical behavior in mean-field theory in different regimes of the R\'enyi index $\alpha$. Next,

Robin Jeanne Kirschner, Carina M. Micheler, Yangcan Zhou, Sebastian Siegner

The use of pointed or edged tools or objects is one of the most challenging aspects of today's application of physical human-robot interaction (pHRI). One reason for this is that the severity of harm caused by such edged or pointed impactors is less well studied than for blunt impactors. Consequently, the standards specify well-reasoned force and pressure th

Ran Zmigrod, Dongsheng Wang, Mathieu Sibue, Yulong Pei

The field of visually rich document understanding (VRDU) aims to solve a multitude of well-researched NLP tasks in a multi-modal domain. Several datasets exist for research on specific tasks of VRDU such as document classification (DC), key entity extraction (KEE), entity linking, visual question answering (VQA), inter alia. These datasets cover documents li

Jędrzej Kozal, Jan Wasilewski, Bartosz Krawczyk, Michał Woźniak

Continual learning poses a fundamental challenge for modern machine learning systems, requiring models to adapt to new tasks while retaining knowledge from previous ones. Addressing this challenge necessitates the development of efficient algorithms capable of learning from data streams and accumulating knowledge over time. This paper proposes a novel approa

Peter Wassenaar, Pierre Guetschel, Michael Tangermann

In the BCI field, introspection and interpretation of brain signals are desired for providing feedback or to guide rapid paradigm prototyping but are challenging due to the high noise level and dimensionality of the signals. Deep neural networks are often introspected by transforming their learned feature representations into 2- or 3-dimensional subspace vis

Tong Wu, Haoran Chen, Tianping Ma, Jia Xu

Efficient control of antiferromagnetic (AFM) domain switching in thin films is vital for advancing antiferromagnet-based memory devices. In this study, we directly observed the current-driven switching process of CoO AFM domains in the Pt/CoO(001) bilayer by the magneto-optical birefringence effect. The observed critical current density for AFM domain switch

Simon Weber, Thomas Dagès, Maolin Gao, Daniel Cremers

The Laplace-Beltrami operator (LBO) emerges from studying manifolds equipped with a Riemannian metric. It is often called the Swiss army knife of geometry processing as it allows to capture intrinsic shape information and gives rise to heat diffusion, geodesic distances, and a multitude of shape descriptors. It also plays a central role in geometric deep lea

Reina Kaneko, Takumi Ueda, Hiroshi Higashi, Yuichi Tanaka

This paper introduces the physics-inspired synthesized underwater image dataset (PHISWID), a dataset tailored for enhancing underwater image processing through physics-inspired image synthesis. For underwater image enhancement, data-driven approaches (e.g., deep neural networks) typically demand extensive datasets, yet acquiring paired clean atmospheric imag

Yuhao Liu, Keita Yoshioka, Tao You, Hanzhang Li

This work extends the hydro-mechanical phase-field fracture model to non-isothermal conditions with micromechanics based poroelasticity, which degrades Biot's coefficient not only with the phase-field variable (damage) but also with the energy decomposition scheme. Furthermore, we propose a new approach to update porosity solely determined by the strain chan

Junlin Lu, Patrick Mannion, Karl Mason

Multi-objective reinforcement learning (MORL) is increasingly relevant due to its resemblance to real-world scenarios requiring trade-offs between multiple objectives. Catering to diverse user preferences, traditional reinforcement learning faces amplified challenges in MORL. To address the difficulty of training policies from scratch in MORL, we introduce d

Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi

Evolutionary Algorithms (EAs) are often challenging to apply in real-world settings since evolutionary computations involve a large number of evaluations of a typically expensive fitness function. For example, an evaluation could involve training a new machine learning model. An approximation (also known as meta-model or a surrogate) of the true function can

Apoorva Nalini Pradeep Kumar, Justus Bogner, Markus Funke, Patricia Lago

Recent advances in artificial intelligence (AI) capabilities have increased the eagerness of companies to integrate AI into software systems. While AI can be used to have a positive impact on several dimensions of sustainability, this is often overshadowed by its potential negative influence. While many studies have explored sustainability factors in isolati

Samiya A Alkhairy

We present filters with rational exponents in order to provide a continuum of filter behavior not classically achievable. We discuss their stability, the flexibility they afford, and various representations useful for analysis, design and implementations. We do this for a generalization of second-order filters which we refer to as rational-exponent Generaliz

Xin Yin

This paper proposes a pipeline for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available dataset. We carry out an extensive technical evaluation of ChatGPT using Big-Vul covering five different common software vulnerability tasks. We evaluate the multitask and multilingual aspects of ChatGPT based on this dataset. We found that

Stefano Longhi

The localization and scattering properties of potential wells or barriers uniformly moving on a lattice are strongly dependent on the drift velocity owing to violation of the Galilean invariance of the discrete Schr\"odinger equation. Here a type of localization-delocalization phase transition of algebraic type is unravelled, which does not require any kind

Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami, Peyman Sheikholharam Mashhadi

This paper investigates how various randomization techniques impact Deep Neural Networks (DNNs). Randomization, like weight noise and dropout, aids in reducing overfitting and enhancing generalization, but their interactions are poorly understood. The study categorizes randomness techniques into four types and proposes new methods: adding noise to the loss f

Shahzad Ali, Yu Rim Lee, Soo Young Park, Won Young Tak

Downsampling images and labels, often necessitated by limited resources or to expedite network training, leads to the loss of small objects and thin boundaries. This undermines the segmentation network's capacity to interpret images accurately and predict detailed labels, resulting in diminished performance compared to processing at original resolutions. Thi

J. Taery Kim, Archit Naik, Isuru Jayarathne, Sehoon Ha

Integrating intelligent systems, such as robots, into dynamic group settings poses challenges due to the mutual influence of human behaviors and internal states. A robust representation of social interaction dynamics is essential for effective human-robot collaboration. Existing approaches often narrow their focus to facial expressions or speech, overlooking

Rainey Lyons, Grigor Nika, Adrian Muntean

We present a finite-volume based numerical scheme for a nonlocal Cahn-Hilliard equation which combines ideas from recent numerical schemes for gradient flow equations and nonlocal Cahn-Hilliard equations. The equation of interest is a special case of a previously derived and studied system of equations which describes phase separation in ternary mixtures. We

Ali Dogdu, Murad Kayacan

In this study, we aimed to examine the effect of VAT revenues and Deposit Interest Rates on Inflation in Turkey between 1985-2022. Within the framework of econometric analysis of the obtained data, the analysis was carried out using ADF unit root test, Johansen Co-Integration Test, Error Terms and VECM (Vector Error Correction Model) models. According to the

Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla

Pre-trained deep learning (DL) models are increasingly accessible in public repositories, i.e., model zoos. Given a new prediction task, finding the best model to fine-tune can be computationally intensive and costly, especially when the number of pre-trained models is large. Selecting the right pre-trained models is crucial, yet complicated by the diversity

Myrthe Reuver, Suzan Verberne, Antske Fokkens

For a viewpoint-diverse news recommender, identifying whether two news articles express the same viewpoint is essential. One way to determine "same or different" viewpoint is stance detection. In this paper, we investigate the robustness of operationalization choices for few-shot stance detection, with special attention to modelling stance across different t

Lukas Rodda, Ben M. Burridge, Jorge Barreto, Imad I. Faruque

Photonic Integrated Circuits (PIC)s are a promising contender for quantum information technologies. The spectral purity of photons is one of the key attributes of PIC photon-pair sources. The dual-pulse pump manipulation technique [1] showed >99% purity in ring-resonator photon-pair sources. Here, we have developed a PIC to shape a pulse into dual, triple an

Cécilia Pradic, Ian Price

We prove a characterization of first-order string-to-string transduction via $\lambda$-terms typed in non-commutative affine logic that compute with Church encoding, extending the analogous known characterization of star-free languages. We show that every first-order transduction can be computed by a $\lambda$-term using a known Krohn-Rhodes-style decomposit

Chi-Hui Lin, Joewie J. Koh, Alessandro Roncone, Lijun Chen

Effective multi-agent collaboration is imperative for solving complex, distributed problems. In this context, two key challenges must be addressed: first, autonomously identifying optimal objectives for collective outcomes; second, aligning these objectives among agents. Traditional frameworks, often reliant on centralized learning, struggle with scalability

Chun-Hui Wang

Let F be a local field. In the case of F being the real field, Pierre Cartier constructed Heisenberg-Weil representations of a Heisenberg group in families using non-self-dual lattices. This result was later reformulated by Jae-Hyun Yang in another paper. We extend this family of representations to a representation of a Jacobi subgroup by incorporating a rat

R. A. J. Eyles-Ferris, C. J. Nixon, E. R. Coughlin, P. T. O'Brien

Gamma-ray bursts (GRBs) are traditionally classified as either short GRBs with durations $\lesssim 2$ s that are powered by compact object mergers, or long GRBs with durations $\gtrsim 2$ s that powered by the deaths of massive stars. Recent results, however, have challenged this dichotomy and suggest that there exists a population of merger-driven long burs

Pritam Acharya, Sujoy Bhore, Aaryan Gupta, Arindam Khan

We study the geometric knapsack problem in which we are given a set of $d$-dimensional objects (each with associated profits) and the goal is to find the maximum profit subset that can be packed non-overlappingly into a given $d$-dimensional (unit hypercube) knapsack. Even if $d=2$ and all input objects are disks, this problem is known to be \textsf{NP}-hard

Aileen A. T. Durst, Matthew T. Eiles

We investigate the absorption spectrum of a Rydberg impurity immersed in and interacting with an ideal Bose-Einstein condensate. Here, the impurity-bath interaction can greatly exceed the mean interparticle distance; this discrepancy in length scales challenges the assumptions underlying the universal aspects of impurity atoms in dilute bosonic environments.

Fedor V. Fomin, Petr A. Golovach, Tuukka Korhonen, Saket Saurabh

We study the following Independent Stable Set problem. Let G be an undirected graph and M = (V(G),I) be a matroid whose elements are the vertices of G. For an integer k\geq 1, the task is to decide whether G contains a set S\subseteq V(G) of size at least k which is independent (stable) in G and independent in M. This problem generalizes several well-studied

Jiefeng Zhou, Zhen Li, Yong Deng

Random walk is an explainable approach for modeling natural processes at the molecular level. The Random Permutation Set Theory (RPST) serves as a framework for uncertainty reasoning, extending the applicability of Dempster-Shafer Theory. Recent explorations indicate a promising link between RPST and random walk. In this study, we conduct an analysis and con

Mathilde Aguiar, Pierre Zweigenbaum, Nona Naderi

This paper describes our submission to Task 2 of SemEval-2024: Safe Biomedical Natural Language Inference for Clinical Trials. The Multi-evidence Natural Language Inference for Clinical Trial Data (NLI4CT) consists of a Textual Entailment (TE) task focused on the evaluation of the consistency and faithfulness of Natural Language Inference (NLI) models applie

Abe Alexander, Lars Fritz

In the ever evolving landscape of decentralized finance automated market makers (AMMs) play a key role: they provide a market place for trading assets in a decentralized manner. For so-called bluechip pairs, arbitrage activity provides a major part of the revenue generation of AMMs but also a major source of loss due to the so-called informed orderflow. Find

Vadym Kurylenko

The local $h^*$-polynomial is a natural invariant of a lattice polytope appearing in Ehrhart theory and Hodge theory. In this work, we study the question posed in [GKZ94] concerning the classification of lattice simplices with vanishing local $h^*$-polynomial. Such simplices are called thin. We relate this question to linear codes and hyperplane arrangements

Weiyi Yang, Xiaolu Liu, Lei He, Yonghao Du

This paper investigates heterogeneous-cost task allocation with budget constraints (HCTAB), wherein heterogeneity is manifested through the varying capabilities and costs associated with different agents for task execution. Different from the centralized optimization-based method, the HCTAB problem is solved using a fully distributed framework, and a coaliti

Anders Strømberg, Einar Digernes, Rajesh Vilas Chopdekar, Jostein Grepstad

Nanopatterned magnetic thin films offer a platform for exploration of tailored magnetic properties such as emergent long-range order. A prominent example is artificial spin ice (ASI), where an arrangement of nanoscale magnetic elements, acting as macrospins, interact via their dipolar fields. In this study, we discuss the transition from antiferromagnetic (A

Simon Jeffery, Laura Scott, Asish Philip Monai, Brent Miszalski

EC 19529-4430 was identified as a helium-rich star in the Edinburgh-Cape Survey of faint-blue objects and subsequently resolved as a metal-poor extreme helium (EHe) star in the SALT survey of chemically-peculiar hot subdwarfs. This paper presents a fine analysis of the SALT high-resolution spectrum. EC 19529-4430 has $T_{\rm eff} = 20\,700 \pm250$\,K, $\log

Fernando Abellán, Andrea Gagna, Rune Haugseng

We prove an unstraightening result for lax transformations between functors from an arbitrary $(\infty,2)$-category to that of $(\infty,2)$-categories. We apply this to study partially (op)lax and weighted (co)limits, giving fibrational descriptions of such (co)limits for diagrams valued in $(\infty,2)$-categories, to characterize adjoints in $(\infty,2)$-ca

P. G. Walsh

We describe how the Mordell-Weil group of rational points on a certain family of elliptic curves give rise to solutions to a conjecture of Erd\"{o}s on $3$-powerful numbers, and state a related conjecture which can be viewed as an elliptic curve analogue of the Ankeny-Artin-Chowla conjecture.

Samiya A Alkhairy

We develop characteristics-based filter design methods for a class of IIR bandpass filters, which we refer to as Generalized-Exponent Filters (GEFs) and that are represented as second-order filters raised to non-unitary exponents. GEFs have a peak, are effectively linear phase, and are useful for seismic signal phase-picking, cochlear implants, and equalizer

Afnan Sultan, Jochen Sieg, Miriam Mathea, Andrea Volkamer

Molecular Property Prediction (MPP) is vital for drug discovery, crop protection, and environmental science. Over the last decades, diverse computational techniques have been developed, from using simple physical and chemical properties and molecular fingerprints in statistical models and classical machine learning to advanced deep learning approaches. In th

Bartosz Uniejewski

The most commonly used form of regularization typically involves defining the penalty function as a L1 or L2 norm. However, numerous alternative approaches remain untested in practical applications. In this study, we apply ten different penalty functions to predict electricity prices and evaluate their performance under two different model structures and in

H. Bogatyryova, V. Chornous, L. Lisetski, I. Gvozdovskyy

For the oblique helicoidal structure of the chiral twist-bend nematic-forming mixture of CB7CB/CB6OCB/5CB doped by light-sensitive chiral compound based on azo-fragment, two consequent states of Bragg reflection of the light in the visible spectral range from 400 to 750 nm were experimentally observed in the course of decreasing the applied electric field. T

Saeid Hedayatrasa, Olga Fink, Wim Van Paepegem, Mathias Kersemans

The vibrational response of structural components carries valuable information about their underlying mechanical properties, health status and operational conditions. This underscores the need for the development of efficient physics-based inversion algorithms which, given a limited set of sensing data points and in the presence of measurement noise, can rec

Christian Knoll, Laura Koesten, Isotta Rigoni, Serge Vulliémoz

The analysis of complex high-dimensional data is a common task in many domains, resulting in bespoke visual exploration tools. Expectations and practices of domain experts as users do not always align with visualization theory. In this paper, we report on a design study in the medical domain where we developed two high-fidelity prototypes encoding EEG-derive

Timothy C. Andrews, Beth A. Wingate

This paper introduces a new algorithm to improve the accuracy of numerical phase-averaging in oscillatory, multiscale, differential equations. Phase-averaging is a timestepping method which averages a mapped variable to remove highly oscillatory linear terms from the differential equation. This retains the main contribution of fast waves on the low frequenci

Tilen Cadez, Dillip Nandy, Dario Rosa, Alexei Andreanov

We present numerical results for the Rosenzweig Porter model for all symmetry classes of the Dyson threefold way. We analyzed the fluctuation properties in the eigenvalue spectra, and compared them with existing and new analytical results. Based on these results we propose characteristics of the spectral properties as measures to explore the transition from

Tomohiro Abe, Ryosuke Sato, Takumu Yamanaka

A dark matter model based on QCD-like $SU(N_c)$ gauge theory with electroweakly interacting dark quarks is discussed. Assuming the dark quark mass $m$ is smaller than the dynamical scale $\Lambda_d \sim 4\pi f_d$, the main component of the dark matter is the lightest $G$-parity odd dark pion associated with chiral symmetry breaking in the dark sector. We sho

Xingyu Liu, Chenyangguang Zhang, Gu Wang, Ruida Zhang

In robotic vision, a de-facto paradigm is to learn in simulated environments and then transfer to real-world applications, which poses an essential challenge in bridging the sim-to-real domain gap. While mainstream works tackle this problem in the RGB domain, we focus on depth data synthesis and develop a range-aware RGB-D data simulation pipeline (RaSim). I

Bernd Heide

A statistical model for the calculation of the ionisation-cluster size distribution in nanodosimetry is proposed. It is based on a canonical ensemble and derives from the well-known nuclear droplet model. The model especially can be applied to the scenario 'low energy primaries (smaller than 100 eV) moving in nanovolumes (in the order of a few nanometers)';

M. Pranav, A. Shukla, D. Moser, J. Rumeney

In this era of non-fullerene acceptor (NFA) based organic solar cells, reducing voltage losses while maintaining high photocurrents is the holy grail of current research. Recent focus lies in understanding the manifold fundamental mechanisms in organic blends with minimal energy offsets - particularly the relationship between ionization energy offset ({\Delt

Stam Nicolis

The Parisi-Sourlas approach to supersymmetry implies that, in spacetime dimensions greater than 1, there is a constraint on the minimal number of flavors, in order for a field theory to define a closed system. In particular, this number is greater than 1. This does not preclude that supersymmetry can be broken, however, and the known ways of breaking supersy

Tuukka Korhonen, Michał Pilipczuk, Giannos Stamoulis

We give an algorithm that, given graphs $G$ and $H$, tests whether $H$ is a minor of $G$ in time ${\cal O}_H(n^{1+o(1)})$; here, $n$ is the number of vertices of $G$ and the ${\cal O}_H(\cdot)$-notation hides factors that depend on $H$ and are computable. By the Graph Minor Theorem, this implies the existence of an $n^{1+o(1)}$-time membership test for every

Preetha Ramiah, James Q. Smith, Oliver Bunnin, Silvia Liverani

Probabilistic Graphical Bayesian models of causation have continued to impact on strategic analyses designed to help evaluate the efficacy of different interventions on systems. However, the standard causal algebras upon which these inferences are based typically assume that the intervened population does not react intelligently to frustrate an intervention.

Boris Nasedkin, Azat Ismagilov, Vladimir Chistiakov, Andrei Gaidash

In this paper we investigate spectral vulnerabilities in quantum key distribution systems arising from the use of shorter-wavelength radiation in the 400-800 nm range, with particular focus on the induced photorefraction attack (IPA). Crucial elements influenced by IPA include various types of modulators, both phase and intensity modulators. In the following

Arpan Das, Wojciech Gorecki, Rafal Demkowicz-Dobrzanski

Assuming Markovian time evolution of a quantum sensing system, we study the general characterization of the optimal sensitivity scalings with time, under most general quantum control protocols. We allow the estimated parameter to influence both the Hamiltonian as well as the dissipative part of the quantum master equation and focus on the asymptotic-time alo

Thomas Karanikiotis, Andreas L. Symeonidis

Context: In the realm of software development, maintaining high software quality is a persistent challenge. However, this challenge is often impeded by the lack of comprehensive understanding of how specific code modifications influence quality metrics. Objective: This study ventures to bridge this gap through an approach that aspires to assess and interpret

Derek F. Holt, Gareth Tracey

We present a randomised variant of an algorithm of Lucchini and Thakkar for finding a smallest sized generating set in a finite group, which has polynomial time expected running time in finite permutation groups.

Vasile Berinde

We obtain results on the existence and approximation of fixed points of enriched contractions in quasi-Banach spaces and thus extend the results obtained in the case of contractions defined on Banach spaces [Berinde, V.; P\u{a}curar, M. Approximating fixed points of enriched contractions in Banach spaces. J. Fixed Point Theory Appl. 22 (2020), no. 2, Paper N

Dennis Barzanoff, Amna Asif

The gaming industry is earning huge revenues from incorporating virtual currencies into the game design experience. Even if it is a useful approach for the game industry to boost up their earnings, the unidirectional and bidirectional in-game virtual currencies can invoke inadequate gaming behaviors and additions among players. The market lacks gaming and cu

I. Septembre, C. Leblanc, D. D. Solnyshkov, G. Malpuech

The combination of an in-plane honeycomb potential and of a photonic spin-orbit coupling (SOC) emulates a photonic/polaritonic analog of bilayer graphene. We show that modulating the SOC magnitude allows to change the overall lattice periodicity, emulating any type of moir\'e-arranged bilayer graphene with a unique all-optical access to the moir\'e band topo

Ana-Maria Cretu, Miruna Rusu, Yves-Alexandre de Montjoye

Smart meters, devices measuring the electricity and gas consumption of a household, are currently being deployed at a fast rate throughout the world. The data they collect are extremely useful, including in the fight against climate change. However, these data and the information that can be inferred from them are highly sensitive. Re-pseudonymization, i.e.,

Naba Jyoti Gogoi, Saumen Acharjee, Prabwal Phukon

In this paper, we study the relationship between the phase transition and Lyapunov exponents for 4D Hayward anti-de Sitter (AdS) black hole. We consider the motion of massless and massive particles around an unstable circular orbit of the Hayward AdS black hole in the equatorial plane and calculate the corresponding Lyapunov exponents. The phase transition i

Lukas Lanza, Timm Faulwasser, Karl Worthmann

The ongoing transition towards energy and power systems dominated by a large number of renewable power injections to the distribution grid poses substantial challenges for system operation, coordination, and control. Optimization-based methods for coordination and control are of substantial research interest in this context. Hence, this chapter provides a tu

Agnieszka Dziurda, Felix Erben, Marc Quentin Führing, Thibaud Humair

This summary reviews contributions to the CKM 2023 workshop in Working Group 4: mixing and mixing-related $CP$ violation in B system. The theoretical and experimental progress is discussed.

S. P. Sikhosana, M. Hilton, G. Bernardi, K. Kesebonye

In the current paradigm, high redshift radio halos are expected to be scarce due to inverse Compton energy losses and redshift dimming, which cause them to be intrinsically faint. This low occurrence fraction is predicted by cosmic ray electron turbulent re-acceleration models. To date, only a handful of radio halos have been detected at redshift z > 0.8. We

Chen Wang, Haoxiang Luo, Kun Zhang, Hua Chen

In robotic insertion tasks where the uncertainty exceeds the allowable tolerance, a good search strategy is essential for successful insertion and significantly influences efficiency. The commonly used blind search method is time-consuming and does not exploit the rich contact information. In this paper, we propose a novel search strategy that actively utili

Federico Caucci

In this note, we relate the basepoint-freeness threshold of a polarized abelian variety, introduced by Jiang and Pareschi, with $k$-jet very ampleness. Then, we derive several applications of this fact, including a criterion for the $k$-very ampleness of Kummer varieties.

Lorenzo Brasco

The Cheeger constant of an open set of the Euclidean space is defined by minimizing the ratio "perimeter over volume", among all its smooth compactly contained subsets. We consider a natural variant of this problem, where the volume of admissible sets is raised to any positive power. We show that for {\it sublinear} powers, all these generalized Cheeger cons

Maximilian Hilger, Vladimír Kubelka, Daniel Adolfsson, Henrik Andreasson

Imaging radar is an emerging sensor modality in the context of Localization and Mapping (SLAM), especially suitable for vision-obstructed environments. This article investigates the use of 4D imaging radars for SLAM and analyzes the challenges in robust loop closure. Previous work indicates that 4D radars, together with inertial measurements, offer ample inf

Mark den Brok, Davor Krajnović, Eric Emsellem, Wilfried Mercier

Star formation in the early Universe has left its imprint on the chemistry of observable stars in galaxies. We derive elemental abundances and the slope of the low-mass end of the initial mass function (IMF) for a sample of 25 very massive galaxies, separated into brightest cluster galaxies (BCGs) and their massive satellites. The elemental abundances of BGC

Vasile Berinde

We give a brief account on a basic result (Lemma \ref{lem2}) which is a very useful tool in proving various convergence theorems in the framework of the iterative approximation of fixed points of demicontractive mappings in Hilbert spaces. This Lemma relates the class of quasi-nonexpansive mappings, by one hand, and the class of $k$-demicontractive mappings

Gulsum Yigit, Mehmet Fatih Amasyali

Math Word Problem (MWP) solving presents a challenging task in Natural Language Processing (NLP). This study aims to provide MWP solvers with a more diverse training set, ultimately improving their ability to solve various math problems. We propose several methods for data augmentation by modifying the problem texts and equations, such as synonym replacement

Shingo Kukita, Haruki Kiya, Yasushi Kondo

Environmental noises cause the relaxation of quantum systems and decrease the precision of operations. Apprehending the relaxation mechanism via environmental noises is essential for building quantum technologies. Relaxations can be considered a process of information dissipation from the system into an environment with infinite degrees of freedom (DoF). Acc

Lynn Miller, Charlotte Pelletier, Geoffrey I. Webb

Earth observation (EO) satellite missions have been providing detailed images about the state of the Earth and its land cover for over 50 years. Long term missions, such as NASA's Landsat, Terra, and Aqua satellites, and more recently, the ESA's Sentinel missions, record images of the entire world every few days. Although single images provide point-in-time

Zheng Hua, Alexander Polishchuk

We establish a link between open positroid varieties in the Grassmannians $G(k,n)$ and certain moduli spaces of complexes of vector bundles over Kodaira cycle $C^n$, using the shifted Poisson structure on the latter moduli spaces and relating them to a certain twist of the standard Poisson structure on $G(k,n)$. %by a bivector field on its maximal torus. Thi

Soumik Aon, Abu Bakkar Miah, Arpita Mandal, Harekrishna Bhunia

The phenomenon of Spin Hall Effect (SHE) generates a pure spin current transverse to an applied current in materials with strong spin-orbit coupling, although not detectable through conventional electrical measurement. An intuitive Hall effect like measurement configuration is implemented to directly measure pure spin chemical potential of the accumulated sp

Anna Lachowska, Olga Postnova, Nicolai Reshetikhin, Dmitry Solovyev

We study the decomposition of tensor powers of two dimensional irreducible representations of quantum $\mathfrak{sl}_2$ at even roots of unity into direct sums of tilting modules. We derive a combinatorial formula for multiplicity of tilting modules in the $N$-th tensor power of two dimensional irreducible representations, interpret it in terms of lattice pa

Vasile Berinde, Khairul Saleh

In this paper we propose new averaged iterative algorithms designed for solving a split common fixed-point problem in the class of demicontractive mappings. The algorithms are obtained by inserting an averaged term into the algorithms used in [Li, R. and He, Z., A new iterative algorithm for split solution problems of quasi-nonexpansive mappings {\it J. Ineq

Minkyu Kim, Panjin Kim

Quantum algorithms for solving noisy linear problems are reexamined, under the same assumptions taken from the existing literature. The findings of this work include on the one hand extended applicability of the quantum Fourier transform to the ring learning with errors problem which has been left open by Grilo et al., who first devised a polynomial-time qua

Vasile Berinde

We propose a hybrid inertial self-adaptive algorithm for solving the split feasibility problem and fixed point problem in the class of demicontractive mappings. Our results are very general and extend several related results existing in literature from the class of nonexpansive or quasi-nonexpansive mappings to the larger class of demicontractive mappings. E

Wenguan Wang, Yi Yang, Yunhe Pan

Visual knowledge is a new form of knowledge representation that can encapsulate visual concepts and their relations in a succinct, comprehensive, and interpretable manner, with a deep root in cognitive psychology. As the knowledge about the visual world has been identified as an indispensable component of human cognition and intelligence, visual knowledge is

Seun Osonuga, Ali Chouman, Muhammad-Salman Shahid, Benoit Delinchant

Tertiary buildings could be an important lever to meet the goals necessitated by the energy transition. The availability of high-quality datasets from this sector will be a crucial enabler in meeting these goals by developing and testing new energy management approaches in the buildings. In this paper, we present the thermal energy datasets available and pub

Laurent Decreusefond, Christophe Vuong

On any denumerable product of probability spaces, we extend the discrete Malliavin structure for conditionally independent random variables. As a consequence, we obtain the chaos decomposition for functionals of conditionally independent random variables. We also show how to derive some concentration results in that framework. The Malliavin-Stein method yiel

Daniel Panangian, Ksenia Bittner

A low-resolution digital surface model (DSM) features distinctive attributes impacted by noise, sensor limitations and data acquisition conditions, which failed to be replicated using simple interpolation methods like bicubic. This causes super-resolution models trained on synthetic data does not perform effectively on real ones. Training a model on real low

Zhilin Zeng, Hui Li, Xiyue Gao, Hui Zhang

By introducing intermediate states for metadata changes and ensuring that at most two versions of metadata exist in the cluster at the same time, shared-nothing databases are capable of making online, asynchronous schema changes. However, this method leads to delays in the deployment of new schemas since it requires waiting for massive data backfill. To shor

Lucas Fresse, Ivan Penkov

Ind-varieties of generalized flags have been studied for two decades. However, a precise statement of when two such ind-varieties, one or both being possibly ind-varieties of isotropic generalized flags, are isomorphic, has been missing in the literature. Using some recent results on the structure of ind-varieties of generalized flags, we establish a criteri

Shihao Xia, Shuai Shao, Mengting He, Tingting Yu

To govern smart contracts running on Ethereum, multiple Ethereum Request for Comment (ERC) standards have been developed, each containing a set of rules to guide the behaviors of smart contracts. Violating the ERC rules could cause serious security issues and financial loss, signifying the importance of verifying smart contracts follow ERCs. Today's practice

Fabian Neumann, Johannes Hampp, Tom Brown

Importing renewable energy to Europe offers many potential benefits, including reduced energy costs, lower pressure on infrastructure development, and less land-use within Europe. However, there remain many open questions: on the achievable cost reductions, how much should be imported, whether the energy vector should be electricity, hydrogen or hydrogen der

Kun Wang, Zheng Chen, Jun Li

In this paper, we consider a trajectory planning problem arising from a lunar vertical landing with minimum fuel consumption. The vertical landing requirement is written as a final steering angle constraint, and a nonnegative regularization term is proposed to modify the cost functional. In this way, the final steering angle constraint will be inherently sat

Xuecan Wang, Shibang Xiao, Xiaohui Liang

We present a lightweight solution for estimating spatially-coherent indoor lighting from a single RGB image. Previous methods for estimating illumination using volumetric representations have overlooked the sparse distribution of light sources in space, necessitating substantial memory and computational resources for achieving high-quality results. We introd

Manjin Kim, Paul Hongsuck Seo, Cordelia Schmid, Minsu Cho

We introduce a new attention mechanism, dubbed structural self-attention (StructSA), that leverages rich correlation patterns naturally emerging in key-query interactions of attention. StructSA generates attention maps by recognizing space-time structures of key-query correlations via convolution and uses them to dynamically aggregate local contexts of value

Gaëtan Robillard

In Search of the Wave is a computer-generated film made in 2013, highlighting the computation of images through computer simulation, and through text and voice. Originating from a screening of the film at the Gustave Eiffel University, the article presents a reflection on research-creation in and from algorithmic images. Fundamentally, what is it in this res