February 2024 arXiv papers — page 132

Maria C. Babiuc Hamilton, Joseph I. Powell

Neutron star mergers are astrophysical `gold mines,' synthesizing over half of the elements heavier than iron through rapid neutron capture nucleosynthesis. The observation of the binary neutron star merger GW170817, detected both in gravitational waves and electromagnetic radiation, marked a breakthrough. One electromagnetic component of this event, the gam

Parisa Farmanifard, Arun Ross

Iris segmentation is a critical component of an iris biometric system and it involves extracting the annular iris region from an ocular image. In this work, we develop a pixel-level iris segmentation model from a foundational model, viz., Segment Anything Model (SAM), that has been successfully used for segmenting arbitrary objects. The primary contribution

Guohua Liu, Yan Peng

We study properties of the innermost photonsphere in the regular compact star background. We take the traceless energy-momentum tensor and dominant energy conditions. In the regular compact star background, we analytically obtain an upper bound on the radius of the innermost photonsphere as $r_{\gamma}^{in}\leqslant \frac{12}{5}M$, where $r_{\gamma}^{in}$ is

Marta Gałyńska, Katharina Boguslawski

The ionization potential (IP) is an important parameter providing essential insights into the reactivity of chemical systems. IPs are also crucial for designing, optimizing, and understanding the functionality of modern technological devices. We recently showed that limiting the CC ansatz to the seniority-zero sector proves insufficient in predicting reliabl

Kirill S. Evdokimov

An agenda-setter repeatedly proposes a spatial policy to voters until some proposal is accepted. Voters have distinct but correlated preferences and receive private signals about the common state. I investigate whether the agenda-setter retains the power to screen voters as players become perfectly patient and private signals become perfectly precise. I show

Ricardo Coimbra Brioso, Damiano Dei, Nicola Lambri, Daniele Loiacono

In order to optimize the radiotherapy delivery for cancer treatment, especially when dealing with complex treatments such as Total Marrow and Lymph Node Irradiation (TMLI), the accurate contouring of the Planning Target Volume (PTV) is crucial. Unfortunately, relying on manual contouring for such treatments is time-consuming and prone to errors. In this pape

CMS Collaboration

A search for pair production of scalar and vector leptoquarks (LQs) each decaying to a muon and a bottom quark is performed using proton-proton collision data collected at $\sqrt{s}$ = 13 TeV with the CMS detector at the CERN LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. No excess above standard model expectation is observed. Scalar (vecto

Stefan Schnake, Coleman Kendrick, Eirik Endeve, Miroslav Stoyanov

Sparse-grid methods have recently gained interest in reducing the computational cost of solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid sparse-grid methods for the Vlasov-Poisson-Lenard-Bernstein (VPLB) model. This model has applications to plasma physics and is simulated in two reduced geometries: a 0x3v space hom

Yichen Jiang, Xiang Zhou, Mohit Bansal

Transformers generalize to novel compositions of structures and entities after being trained on a complex dataset, but easily overfit on datasets of insufficient complexity. We observe that when the training set is sufficiently complex, the model encodes sentences that have a common syntactic structure using a systematic attention pattern. Inspired by this o

Juan A. Acebron, Angel Rodriguez-Rozas

A probabilistic representation for initial value semilinear parabolic problems based on generalized random trees has been derived. Two different strategies have been proposed, both requiring generating suitable random trees combined with a Pade approximant for approximating accurately a given divergent series. Such series are obtained by summing the partial

J. Schiappacasse-Ulloa, S. Lucatello, G. Cescutti, E. Carretta

Context. Globular clusters are considered key objects for understanding the formation and evolution of the Milky Way. In this sense, their characterisation in terms of their chemical and orbital parameters can provide constraints to the chemical evolution models of the Galaxy. Aims. We use the heavy element abundances of globular clusters to trace their over

Bárbara Andrade, Utso Bhattacharya, Ravindra W. Chhajlany, Tobias Graß

The Schwinger model describes quantum electrodynamics in 1+1-dimensions, it is a prototype for quantum chromodynamics, and its lattice version allows for a quantum link model description that can be simulated using modern quantum devices. In this work, we devise quantum simulations to investigate the dynamics of this model in its low dimensional form, where

Luke Booth, Subhajit Sarkar, Matt Griffin, Billy Edwards

Cool gaseous exoplanets ($1.75\ R_\oplus < R_\text{p} < 3\ R_\text{J}$, $200$ K $<T_\text{eq} < 1000$~K) are an as-yet understudied population, with great potential to expand our understanding of planetary atmospheres and formation mechanisms. In this paper, we outline the basis for a homogeneous survey of cool gaseous planets with Twinkle, a 0.45-m diameter

Joost J. Joosten, Manuela Montoya García

An important aim of this paper is to convey some basics of mathematical logic to the legal community working with Artificial Intelligence. After analysing what AI is, we decide to delimit ourselves to rule-based AI leaving Neural Networks and Machine Learning aside. Rule based AI allows for Formal methods which are described in a rudimentary form. We will th

Andrea Mondino, Vanessa Ryborz

The goal of the paper is to prove the equivalence of distributional and synthetic Ricci curvature lower bounds for a weighted Riemannian manifold with continuous metric tensor having Christoffel symbols in $L^2_{{\rm loc}}$, and with weight in $C^0\cap W^{1,2}_{{\rm loc}}$.

Marco Mancastroppa, Iacopo Iacopini, Giovanni Petri, Alain Barrat

The richness of many complex systems stems from the interactions among their components. The higher-order nature of these interactions, involving many units at once, and their temporal dynamics constitute crucial properties that shape the behaviour of the system itself. An adequate description of these systems is offered by temporal hypergraphs, that integra

M'hamed Essafri, Luca Calatroni, Emmanuel Soubies

We propose a new class of exact continuous relaxations of l0-regularized criteria involving non-quadratic data terms such as the Kullback-Leibler divergence and the logistic regression, possibly combined with an l2 regularization. We first prove the existence of global minimizers for such problems and characterize their local minimizers.Then, we propose the

M. Aguayo, L. Bellido, C. M. Lentisco, E. Pastor

The wide adoption of multimedia service capable mobile devices, the availability of better networks with higher bandwidths, and the availability of platforms offering digital content has led to an increasing popularity of multimedia streaming services. However, multimedia streaming services can be subject to different factors that affect the quality perceive

Zhipeng Liang, Zicheng Wang, Zhengzhong Yi, Yulin Wu

Code distance is an important parameter for quantum stabilizer codes (QSCs). Directly precisely computing it is an NP-complete problem. However, the upper bound of code distance can be computed by some efficient methods. In this paper, employing the idea of Monte Carlo method, we propose the algorithm of determining the upper bound of code distance of QSCs b

Jan Kloppenborg Møller, Peter Nystrup, Poul G. Hjorth, Henrik Madsen

We propose to estimate the weight matrix used for forecast reconciliation as parameters in a general linear model in order to quantify its uncertainty. This implies that forecast reconciliation can be formulated as an orthogonal projection from the space of base-forecast errors into a coherent linear subspace. We use variance decomposition together with the

Paolo Pegolo, Federico Grasselli

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the chemical and morphological complexity of glasses calls for atomistic simulations where the interatomic pote

Gliia Braek, Mondher Chouikhi, Faouzi Thabet

In this paper, we give a full description of the critical graph of the quadratic differential $\varpi_{a,\theta}$ defined on the Riemann sphere $\widehat{% %TCIMACRO{\U{2102} }% %BeginExpansion \mathbb{C} %EndExpansion }$ by $\varpi_{a,\theta}=-e^{2i\theta}\left( z-a\right) \left( z^{2}-1\right) dz^{2},$ where $\theta\in% %TCIMACRO{\U{211d} }% %BeginExpansio

Jayadev Athreya, Semyon Dyatlov, Nicholas Miller

We study semiclassical measures for Laplacian eigenfunctions on compact complex hyperbolic quotients. Geodesic flows on these quotients are a model case of hyperbolic dynamical systems with different expansion/contraction rates in different directions. We show that the support of any semiclassical measure is either equal to the entire cosphere bundle or cont

Joseph W. Eatson, Tim Lichtenberg, Richard J. Parker, Taras V. Gerya

Whilst the formation of Solar system planets is constrained by meteoritic evidence, the geophysical history of low-mass exoplanets is much less clear. The bulk composition and climate states of rocky exoplanets may vary significantly based on the composition and properties of the planetesimals they form from. An important factor influenced by planetesimal co

João Daniel Silva, João Magalhães, Devis Tuia, Bruno Martins

Image captioning and cross-modal retrieval are examples of tasks that involve the joint analysis of visual and linguistic information. In connection to remote sensing imagery, these tasks can help non-expert users in extracting relevant Earth observation information for a variety of applications. Still, despite some previous efforts, the development and appl

G. A. Gontcharov, A. A. Marchuk, M. Yu. Khovrichev, A. V. Mosenkov

We present new three-dimensional (3D) interstellar extinction maps in the $V$ and Gaia $G$ filters within 2 kpc of the Sun, a 3D differential extinction (dust spatial distribution density) map along the lines of sight in the same space, a 3D map of variations in the ratio of the extinctions in the $V$ and Gaia $G$ filters within 800 pc of the Sun, and a 2D m

Tino Laidin, Lorenzo Pareschi

We address the problem of constructing approximations based on orthogonal polynomials that preserve an arbitrary set of moments of a given function without loosing the spectral convergence property. To this aim, we compute the constrained polynomial of best approximation for a generic basis of orthogonal polynomials. The construction is entirely general and

Di Liu, Hanqing Zhou, Pengcheng An

Storymaking, as an integrative form of expressive arts therapy, is an effective means to foster family communication. Yet, the integration of generative AI as expressive materials in therapeutic storymaking remains underexplored. And there is a lack of HCI implications on how to support families and therapists in this context. Addressing this, our study invo

Gregor Bankhamer, Petra Berenbrink, Felix Biermeier, Robert Elsässer

We consider the \emph{exact plurality consensus} problem for \emph{population protocols}. Here, $n$ anonymous agents start each with one of $k$ opinions. Their goal is to agree on the initially most frequent opinion (the \emph{plurality opinion}) via random, pairwise interactions. The case of $k = 2$ opinions is known as the \emph{majority problem}. Recent b

Gerasimos Damigos, Akshit Saradagi, Sara Sandberg, George Nikolakopoulos

The fifth generation (5G) cellular network technology is mature and increasingly utilized in many industrial and robotics applications, while an important functionality is the advanced Quality of Service (QoS) features. Despite the prevalence of 5G QoS discussions in the related literature, there is a notable absence of real-life implementations and studies

Steve K. Lamoreaux

The synthesis and application of deuterated polystyrene (dps) films is discussed. Ultracold neutron storage properties and the Fermi potential of dps films is measured with the result that Tstore=700 +/- 200 sec for dps in the bottle used and the Fermi potential is about 165neV. The behavior under application of high electric fields in vacuum is measured; th

Diogo V. Saraiva, Steven N. Remiëns, Ethan I. L. Jull, Ivo R. Vermaire

Most paints contain pigments that absorb light and fade over time. A robust alternative can be found in nature, where structural coloration arises from the interference of light with submicron features. Plant-derived, cellulose nanocrystals (CNCs) mimic these features by self-assembling into a cholesteric liquid crystal that exhibits structural coloration wh

Francisco Javier Nunez Cornu, Juan Manuel Sandoval, Edgar Alarcon, Adan Gomez

The Jalisco region of western Mexico is the locus of interaction among the North America, Cocos, and Rivera plates, giving rise to the Jalisco block. This region is one of the most tectonically active in Mexico, and here took place the largest instrumentally recorded earthquake in Mexico the twentieth century, on 3 June 1932 (M 8.2), three important tsunamis

Yanna J. Kraakman, Clara Stegehuis

Many complex systems show non-pairwise interactions, which can be captured by hypergraphs. In this work, we propose an edge-swapping method to sample random directed hypergraphs with fixed vertex and hyperarc degrees, which can be applied to different classes of directed hypergraphs (containing self-loops, degenerate hyperarcs and/or multi-hyperarcs). We pro

Ciaran O'Connor, Joseph Collins, Steven Prestwich, Andrea Visentin

Short-term electricity markets are becoming more relevant due to less-predictable renewable energy sources, attracting considerable attention from the industry. The balancing market is the closest to real-time and the most volatile among them. Its price forecasting literature is limited, inconsistent and outdated, with few deep learning attempts and no publi

Eliad Tsfadia

Private data analysis faces a significant challenge known as the curse of dimensionality, leading to increased costs. However, many datasets possess an inherent low-dimensional structure. For instance, during optimization via gradient descent, the gradients frequently reside near a low-dimensional subspace. If the low-dimensional structure could be privately

Christoph Schweiger, Martin Braß, Vincent Debierre, Menno Door

The investigation of the absolute scale of the effective neutrino mass remains challenging due to the exclusively weak interaction of neutrinos with all known particles in the standard model of particle physics. Currently, the most precise and least model-dependent upper limit on the electron antineutrino mass is set by the KATRIN experiment from the analysi

Arnaud Münch, Diego A. Souza

This paper deals with the numerical computation of null controls for the linear heat equation. The goal is to compute approximations of controls that drive the solution from a prescribed initial state to zero at a given positive time. In [Fernandez-Cara \& M\"unch, Strong convergence approximations of null controls for the 1D heat equation, 2013], a so-calle

Abdoul Aziz Amadou, Laura Peralta, Paul Dryburgh, Paul Klein

Ultrasound is well-established as an imaging modality for diagnostic and interventional purposes. However, the image quality varies with operator skills as acquiring and interpreting ultrasound images requires extensive training due to the imaging artefacts, the range of acquisition parameters and the variability of patient anatomies. Automating the image ac

Luis Alfredo Madrigal, Diana Nunez, Felipe de Jesus Escalona-Alcazar, Francisco Javier Nunez-Cornu

The tectonic interaction between the Rivera and North American plates north of the Bahia de Banderas is poorly understood. The nature of the crust and where the subduction ends in the western part of the Islas Marias Archipelago are still controversial. Based on new geophysical data provided by the TsuJal project, we present the shallow and deep crustal stru

Diogo L. M. Souza, Enrique C. Gabrick, Paulo R. Protachevicz, Fernando S. Borges

The description of neuronal activity has been of great importance in neuroscience. In this field, mathematical models are useful to describe the electrophysical behaviour of neurons. One successful model used for this purpose is the Adaptive Exponential Integrate-and-Fire (Adex), which is composed of two ordinary differential equations. Usually, this model i

Jongmin Yoon, Juho Lee

Straightening the probability flow of the continuous-time generative models, such as diffusion models or flow-based models, is the key to fast sampling through the numerical solvers, existing methods learn a linear path by directly generating the probability path the joint distribution between the noise and data distribution. One key reason for the slow samp

Khaled Mosharraf Mukut, Anindya Ganguly, Eirini Goudeli, Georgios A. Kelesidis

Incipient soot particles obtained from a series of reactive molecular dynamics simulations were studied to understand the evolution of physical, chemical, and morphological properties of incipient soot. Reactive molecular dynamics simulations of acetylene pyrolysis were performed using ReaxFF potential at 1350, 1500, 1650, and 1800 K. A total of 3324 incipie

Guangsheng Yu, Qin Wang, Caijun Sun, Lam Duc Nguyen

In this paper, we study how to optimize existing Non-Fungible Token (NFT) incentives. Upon exploring a large number of NFT-related standards and real-world projects, we come across an unexpected finding. That is, the current NFT incentive mechanisms, often organized in an isolated and one-time-use fashion, tend to overlook their potential for scalable organi

Yavdat Il'yasov, Nurmukhamet Valeev

We develop the Perron-Frobenius theory using a variational approach and extend it to a set of arbitrary matrices, including those that are neither irreducible nor essentially positive, and non-preserved cones. We introduce a new concept called a quasi-eigenvalue of a matrix, which is invariant under orthogonal transformations of variables, and has various us

Arian Hosseini, Xingdi Yuan, Nikolay Malkin, Aaron Courville

Common self-improvement approaches for large language models (LLMs), such as STaR, iteratively fine-tune LLMs on self-generated solutions to improve their problem-solving ability. However, these approaches discard the large amounts of incorrect solutions generated during this process, potentially neglecting valuable information in such solutions. To address

Khaled Mosharraf Mukut, Anindya Ganguly, Eirini Goudeli, Georgios A. Kelesidis

A series of reactive molecular dynamics simulations is used to study the internal structure of incipient soot particles obtained from acetylene pyrolysis. The simulations were performed using ReaxFF potential at four different temperatures. The resulting soot particles are cataloged and analyzed to obtain statistics of their mass, volume, density, C/H ratio,

Arne Wulff, Boyang Chen, Matthew Steinberg, Yinglu Tang

As with many tasks in engineering, structural design frequently involves navigating complex and computationally expensive problems. A prime example is the weight optimization of laminated composite materials, which to this day remains a formidable task, due to an exponentially large configuration space and non-linear constraints. The rapidly developing field

Hiroyuki Tajima, Hideo Aoki, Andrea Perali, Antonio Bianconi

In superconductivity, a surge of interests in enhancing $T_{\rm c}$ is ever mounting, where a recent focus is toward multi-band superconductivity. In $T_{\rm c}$ enhancements specific to two-band cases, especially around the Bardeen-Cooper-Schrieffer (BCS) to Bose-Einstein condensate (BEC) crossover considered here, we have to be careful about how quantum fl

M. L. Savchenko, A. A. Bykov, A. Shuvaev, A. K. Bakarov

We report on the optical realization of the magneto-intersubband oscillations that have been measured in the sub-terahertz transmittance of a GaAs quantum well with two subbands occupied. Following their dc analogue, the oscillations are periodic in the inverse magnetic field with the period governed by the subband gap. Their magnitude and polarization depen

Keito Tajima, Naoki Ichijo, Yuta Nakahara, Toshiyasu Matsushima

Predictions using a combination of decision trees are known to be effective in machine learning. Typical ideas for constructing a combination of decision trees for prediction are bagging and boosting. Bagging independently constructs decision trees without evaluating their combination performance and averages them afterward. Boosting constructs decision tree

Zhaohua Guo, Rui Miao, Jin-Li Guo, Yuan Yuan

A simplex-based network is referred to as a higher-order network, in which describe that the interactions can include more than two nodes. Many multicomponent interactions can be grasped through simplicial complexes, which have recently found applications in social, technological, and biological contexts. The paper first proposes a competitive evolving model

Chen Lu, Zhiming Pan, Fan Yang, Congjun Wu

The discovery of superconductivity (SC) in the trilayer nickelate compound La$_{4}$Ni$_3$O$_{10}$ under pressure has generated significant interest. In this work, we propose a trilayer two $E_g$-orbital $t$-$J_{\parallel}$-$J_{\perp}$ model to investigate the microscopic origin of SC in this system. In the strong-coupling regime, each layer is governed by a

D. Sebastian, A. H. M. J. Triaud, M. Brogi, T. A. Baycroft

High-contrast eclipsing binaries with low mass M-dwarf secondaries are precise benchmark stars to build empirical mass-radius relationships for fully convective low-mass ($\rm M_{*} < 0.35\,M_{\rm sun}$) dwarf stars. The contributed light of the M-dwarf in such binaries is usually much less than one~per~cent at optical wavelengths. This enables the detection

Sergio Conti, Georg Dolzmann, Stefan Müller

Let $M$ be a smooth, compact, connected, oriented Riemannian manifold, and let $\imath: M \to \mathbb R^d$ be an isometric embedding. We show that a Sobolev map $f: M \to M$ which has the property that the differential $df(q)$ is close to the set $SO(T_q M, T_{f(q)} M)$ of orientation preserving isometries (in an $L^p$ sense) is already $W^{1,p}$ close to a

Armand Gissler, Alain Durmus, Anne Auger

In this paper, we analyze a large class of general nonlinear state-space models on a state-space X, defined by the recursion $\phi_{k+1} = F(\phi_k,\alpha(\phi_k,U_{k+1}))$, $k \in\mathbb N$, where $F,\alpha$ are some functions and $\{U_{k+1}\}_{k\in\mathbb N}$ is a sequence of i.i.d. random variables. More precisely, we extend conditions under which this cl

Fengyi Shen, Li Zhou, Kagan Kucukaytekin, Ziyuan Liu

Data generation is recognized as a potent strategy for unsupervised domain adaptation (UDA) pertaining semantic segmentation in adverse weathers. Nevertheless, these adverse weather scenarios encompass multiple possibilities, and high-fidelity data synthesis with controllable weather is under-researched in previous UDA works. The recent strides in large-scal

Dobrik Georgiev, Pietro Liò, Davide Buffelli

Recent work on neural algorithmic reasoning has demonstrated that graph neural networks (GNNs) could learn to execute classical algorithms. Doing so, however, has always used a recurrent architecture, where each iteration of the GNN aligns with an algorithm's iteration. Since an algorithm's solution is often an equilibrium, we conjecture and empirically vali

Victor Jaeck

The character variety $\Xi$ of a finitely generated group $\Gamma$ in $\mathrm{PSL}_2(\mathbb{R})$ has many compactifications. We construct a continuous surjection from the real spectrum compactification $\Xi^{\mathrm{RSp}}$ to the oriented Gromov equivariant compactification. Our construction is based on a geometric interpretation of the elements of $\parti

Merel A Schalkers, Kamiel Dankers, Michael Wimmer, Pieter Vermaas

The rapid growth of quantum technologies requires an increasing number of physicists, computer scientists, and engineers who can work on these technologies. For educating these professionals, quantum mechanics should stop being perceived as incomprehensible. In this paper we contribute to this change by presenting a pedagogical model for explaining Grover's

Recep Firat Cekinel, Pinar Karagoz

The rapid dissemination of misinformation through social media increased the importance of automated fact-checking. Furthermore, studies on what deep neural models pay attention to when making predictions have increased in recent years. While significant progress has been made in this field, it has not yet reached a level of reasoning comparable to human rea

Artem Alexandrov, Alexander Gorsky

Using the Penrose method of instability analysis, we consider the synchronization transition in the Kuramoto model with inertia and noise with all-to-all couplings. Analyzing the Penrose curves, we identify the appearance of cluster and chimera states in the presence of noise. We observe that noise can destroy chimera and biclusters states. The critical coup

Jarrod Mau, Kevin Moon

Time series analysis is relevant in various disciplines such as physics, biology, chemistry, and finance. In this paper, we present a novel neural network architecture that integrates elements from ResNet structures, while introducing the innovative incorporation of the Taylor series framework. This approach demonstrates notable enhancements in test accuracy

Giyoon Kim, Soojin Kang, Seungjun Baek, Kimoon Kim

Ransomware is malicious software that is a prominent global cybersecurity threat. Typically, ransomware encrypts data on a system, rendering the victim unable to decrypt it without the attacker's private key. Subsequently, victims often pay a substantial ransom to recover their data, yet some may still incur damage or loss. This study examines Rhysida ransom

Charlie-Ray Mann, Francesco Andreoli, Vladimir Protsenko, Zala Lenarčič

A novel way to create efficient atom-light interfaces is to engineer collective atomic states that selectively radiate into a target optical mode by suppressing emission into undesired modes through destructive interference. While it is generally assumed that this approach requires dense atomic arrays with sub-wavelength lattice constants, here we show that

ATLAS Collaboration

We present performance studies of the Time-of-Flight (ToF) subdetector of the ATLAS Forward Proton (AFP) detector at the LHC. Efficiencies and resolutions are measured using high-statistics data samples collected at low and moderate pile-up in 2017, the first year when the detectors were installed on both sides of the interaction region. While low efficienci

C. M. Lentisco, L. Bellido, A. Cárdenas, R. F. Moyano

The demand for mobile multimedia streaming services has been steadily growing in recent years. Mobile multimedia broadcasting addresses the shortage of radio resources but introduces a network error recovery problem. Retransmitting multimedia segments that are not correctly broadcast can cause service disruptions and increased service latency, affecting the

Peter Hönig, Stefan Thalhammer, Markus Vincze

Estimating 2D-3D correspondences between RGB images and 3D space is a fundamental problem in 6D object pose estimation. Recent pose estimators use dense correspondence maps and Point-to-Point algorithms to estimate object poses. The accuracy of pose estimation depends heavily on the quality of the dense correspondence maps and their ability to withstand occl

Matheus Cheque Bortolan, Alexandre Nolasco de Carvalho, Pedro Marín-Rubio, José Valero

In this paper we obtain the existence of a weak global attractor for the three-dimensional Navier-Stokes equations, that is, a weakly compact set with an invariance property, that uniformly attracts solutions, with respect to the weak topology, for initial data in bounded sets. To that end, we define this weak global attractor in terms of limits of solutions

Florian Peter Busch, Roshni Kamath, Rupert Mitchell, Wolfgang Stammer

A dataset is confounded if it is most easily solved via a spurious correlation, which fails to generalize to new data. In this work, we show that, in a continual learning setting where confounders may vary in time across tasks, the challenge of mitigating the effect of confounders far exceeds the standard forgetting problem normally considered. In particular

S. B. Dubovichenko, N. A. Burkova, A. S. Tkachenko, D. M. Zazulin

The 10B(p,{\gamma})11C reaction is of significant interest in nuclear astrophysics and in the field of controlled thermonuclear fusion. This reaction is one of the reactions of 11B production, which is carried out through the 10B(p,{\gamma})11C(\b{eta}+{\nu})11B chain. The rate of the 10B(p,{\gamma})11C reaction (occurring in the interiors of first-generatio

B. S. Jacobs, Abhishek Pandey

We report the growth of high-quality single crystals of ThCr$_2$Si$_2$-type tetragonal BaMn$_2$P$_2$ and investigation of its structural, electrical transport, thermal and magnetic properties. Our results of basal plane electrical resistivity and heat capacity measurements show that the compound has an insulating ground state with a small band gap. Anisotrop

Gassiat Elisabeth, Stoltz Gilles

We work out a version of the van Trees inequality in a Hajek--Le Cam spirit, i.e., under minimal assumptions that, in particular, involve no direct pointwise regularity assumptions on densities but rather almost-everywhere differentiability in quadratic mean of the model. Surprisingly, it suffices that the latter differentiability holds along canonical direc

Gábor Geréb, András Sándor

Complex interval arithmetic is a powerful tool for the analysis of computational errors. The naturally arising rectangular, polar, and circular (together called primitive) interval types are not closed under simple arithmetic operations, and their use yields overly relaxed bounds. The later introduced polygonal type, on the other hand, allows for arbitrarily

Sören Bartels, Alex Kaltenbach

A posteriori error estimates are an important tool to bound discretization errors in terms of computable quantities avoiding regularity conditions that are often difficult to establish. For non-linear and non-differentiable problems, problems involving jumping coefficients, and finite element methods using anisotropic triangulations, such estimates often inv

Marek Foltyn, Konrad Norowski, Alexander Savin, Maciej Zgirski

We demonstrate complete control over dynamics of a single superconducting vortex in a nanostructure which we coin the Single Vortex Box (SVB). Our device allows us to trap the vortex in a field-cooled aluminum nanosquare and expel it on demand with a nanosecond pulse of electrical current. We read-out the vortex state of the box by testing the switching curr

Rachid Caich

We examine the conditions under which the sum of random multiplicative functions in short intervals, given by $\sum_{x<n \leqslant x+y} f(n)$, exhibits the phenomenon of \textit{better than square-root cancellation}. We establish that the point at which the square-root cancellation diminishes significantly is approximately when the ratio $\log\big(\frac{x}{y

Jesus-Pablo Toledo-Zucco, Denis Matignon, Charles Poussot-Vassal, Yann Le Gorrec

This paper presents a systematic methodology for the discretization and reduction of a class of one-dimensional Partial Differential Equations (PDEs) with inputs and outputs collocated at the spatial boundaries. The class of system that we consider is known as Boundary-Controlled Port-Hamiltonian Systems (BC-PHSs) and covers a wide class of Hyperbolic PDEs w

C. M. Lentisco, L. Bellido, A. Cárdenas, R. F. Moyano

Multimedia services over mobile networks pose several challenges, such as the efficient management of radio resources or the latency induced by network delays and buffering requirements on the multimedia players. In Long Term Evolution (LTE) networks, the definition of multimedia broadcast services over a common radio channel addresses the shortage of radio

Yifeng Bai, Zhirong Chen, Pengpeng Liang, Bo Song

In autonomous driving, accurate 3D lane detection using monocular cameras is important for downstream tasks. Recent CNN and Transformer approaches usually apply a two-stage model design. The first stage transforms the image feature from a front image into a bird's-eye-view (BEV) representation. Subsequently, a sub-network processes the BEV feature to generat

M. Sahnawaz Alam, Federico Gorrini, Michał Gawełczyk, Daniel Wigger

The negatively charged nitrogen-vacancy (NV$^{-}$) center in diamond has shown great potential in nanoscale sensing and quantum information processing due to its rich spin physics. An efficient coupling with light, providing strong luminescence, is crucial for realizing these applications. Laser-written waveguides in diamond promote NV$^{-}$ creation and imp

Jesse David Dinneen, Charles-Antoine Julien

Thoughtfully designing services and rigorously testing software to support personal information management (PIM) requires understanding the relevant collections, but relatively little is known about what people keep in their file collections, especially personal collections. Complementing recent work on the structure of 348 file collections, we examine those

Yvette Graham, Mohammed Rameez Qureshi, Haider Khalid, Gerasimos Lampouras

The aim of the workshop was to bring together experts working on open-domain dialogue research. In this speedily advancing research area many challenges still exist, such as learning information from conversations, and engaging in a realistic and convincing simulation of human intelligence and reasoning. SCI-CHAT follows previous workshops on open domain dia

Florian Trinter, Ludger Inhester, Ralph Püttner, Sebastian Malerz

We present a combined experimental and theoretical investigation of the radiationless decay spectrum of an O 1s double core hole in liquid water. Our experiments were carried out using liquid-jet electron spectroscopy from cylindrical microjets of normal and deuterated water. The signal of the double-core-hole spectral fingerprints (hypersatellites) of liqui

D. H. Jakubassa-Amundsen

A formal derivation of the polarization correlations between the incident electron and the scattered electron is given for a general class of transition operators. In correspondence to the case of bremsstrahlung emission, three sum rules for the polarization correlations are predicted, which reduce to the known one for potential scattering. Further examples,

D. Aristizabal Sierra, Valentina De Romeri, Christoph A. Ternes

Third-generation dark matter detectors will be fully sensitive to the boron-8 solar neutrino flux. Because of this, the characterization of such a background has been the subject of extensive analyses over the last few years. In contrast, little is known about the impact of reactor neutrinos. In this letter we report on the implications of such a flux for da

Songtai Lv, Yang Liang, Yuchen Meng, Xiaochen Yao

A new implementation of many-body calculations is of paramount importance in the field of computational physics. In this study, we leverage the capabilities of Field Programmable Gate Arrays (FPGAs) for conducting quantum many-body calculations. Through the design of appropriate schemes for Monte Carlo and tensor network methods, we effectively utilize the p

Bianca-Mihaela Ganescu, Jonathan Passerat-Palmbach

Generative AI, exemplified by models like transformers, has opened up new possibilities in various domains but also raised concerns about fairness, transparency and reliability, especially in fields like medicine and law. This paper emphasizes the urgency of ensuring fairness and quality in these domains through generative AI. It explores using cryptographic

Tianshu Wu, Yiqian Chen

This paper delves into observable signatures of hot spots orbiting Reissner-Nordstr\"om (RN) black holes and naked singularities. In a RN black hole case, we find two discernible lensing image tracks in time integrated images capturing a complete orbit of hot spots, and a image shadow within the critical curve where photons with a small impact parameter fall

Felix Ott, Lucas Heublein, Nisha Lakshmana Raichur, Tobias Feigl

Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting anomalies in frequency snapshots is crucial to counteract these interferences effectively. The ability to adapt to diverse, unseen interference characteristics is essential for ensu

Kaja Gruntkowska, Alexander Tyurin, Peter Richtárik

Effective communication between the server and workers plays a key role in distributed optimization. In this paper, we focus on optimizing the server-to-worker communication, uncovering inefficiencies in prevalent downlink compression approaches. Considering first the pure setup where the uplink communication costs are negligible, we introduce MARINA-P, a no

Guillermo Garcia-Barrios, Eduardo Latorre Iglesias, Juana M. Gutierrez-Arriola, Ruben Fraile

Acoustic reverberation is one of the most relevant factors that hampers the localization of a sound source inside a room. To date, several approaches have been proposed to deal with it, but have not always been evaluated under realistic conditions. This paper proposes exploiting spatial diversity as an alternative approach to achieve robustness against rever

Tao Ding, Tom M. W. Nye, Yujiang Wang

We propose a model for time series taking values on a Riemannian manifold and fit it to time series of covariance matrices derived from EEG data for patients suffering from epilepsy. The aim of the study is two-fold: to develop a model with interpretable parameters for different possible modes of EEG dynamics, and to explore the extent to which modelling res

Pablo Pavón-Domínguez, Soledad Moreno-Pulido

Complex networks have been studied in recent years due to their relevance in biological, social and technical real systems, such as the world wide web, social networks and biochemical interactions. One of the most current features of complex networks is the presence of (multi-)fractal properties. In spite of the amount of contributions that have been develop

Jochem G. Meijer, Duarte Rocha, Annemarie M. Linnenbank, Christian Diddens

Frozen water might appear opaque since gas bubbles can get trapped in the ice during the freezing process. They nucleate and then grow near the advancing solidification front, due to the formation of a gas supersaturation region in its vicinity. A delicate interplay between the rate of mass transfer and the rate of freezing dictates the final shapes and size

Colin Davalo, J. Maxwell Riestenberg

We introduce a sufficient condition for a finitely generated subgroup $\Gamma$ of a semisimple Lie group $G$ to admit finite-sided Dirichlet domains for polyhedral Finsler metrics on the symmetric space $G/K$. The condition always implies the $\Theta$-Anosov condition for some $\Theta$, and can be arranged to be equivalent to the $\Theta$-Anosov condition wh

Sushmita Gupta, Sounak Modak, Saket Saurabh, Sanjay Seetharaman

A feedback vertex set (FVS) in a digraph is a subset of vertices whose removal makes the digraph acyclic. In other words, it hits all cycles in the digraph. Lokshtanov et al. [TALG '21] gave a factor 2 randomized approximation algorithm for finding a minimum weight FVS in tournaments. We generalize the result by presenting a factor $2\alpha$ randomized appro

Patricia C. Magalhães, Tara Nanut Petrič, Stefan Schacht

We summarize the results of Working Group 7 at the 12th International Workshop on the CKM Unitarity Triangle (CKM 2023) which took place in Santiago de Compostela, Spain, 18--22 September 2023.

Mamta Aggarwal, G. Saxena, Pranali Parab

In a rapidly changing shape phase region, the presence of shape coexistence and its possible impact on the decay modes and half$-$lives, has been explored in astrophysically interesting Mo and Ru isotopes, in an extensive study within the microscopic theoretical framework using Nilsson Strutinsky Method and Relativistic Mean Field Model. The isotopic chains

Gresa Shala, André Biedenkapp, Josif Grabocka

We introduce Hierarchical Transformers for Meta-Reinforcement Learning (HTrMRL), a powerful online meta-reinforcement learning approach. HTrMRL aims to address the challenge of enabling reinforcement learning agents to perform effectively in previously unseen tasks. We demonstrate how past episodes serve as a rich source of information, which our model effec