July 2023 arXiv papers — page 45

Josh A. Zuber, Minghao Li, Marcel. li Grimau Puigibert, Jodok Happacher

The negatively charged silicon vacancy center (SiV$^-$) in diamond is a promising, yet underexplored candidate for single-spin quantum sensing at sub-kelvin temperatures and tesla-range magnetic fields. A key ingredient for such applications is the ability to perform all-optical, coherent addressing of the electronic spin of near-surface SiV$^-$ centers. We

Nilkantha Das, Sutapa Dey

In this note, some properties of finitely generated two-periodic modules over commutative Noetherian local rings have been studied. We show that under certain assumptions on a pair of modules $\left(M,N \right)$ with $M$ two-periodic, the natural map $M \otimes_R N \to Hom_R(M^*,N)$ is an isomorphism. As a consequence, we have that the Auslander's depth form

Reyhaneh Neshatavar, Mohsen Yavartanoo, Sanghyun Son, Kyoung Mu Lee

Single image super-resolution (SISR) is a challenging ill-posed problem that aims to up-sample a given low-resolution (LR) image to a high-resolution (HR) counterpart. Due to the difficulty in obtaining real LR-HR training pairs, recent approaches are trained on simulated LR images degraded by simplified down-sampling operators, e.g., bicubic. Such an approa

Salih Marangoz, Rohit Menon, Nils Dengler, Maren Bennewitz

Although inverse kinematics of serial manipulators is a well studied problem, challenges still exist in finding smooth feasible solutions that are also collision aware. Furthermore, with collaborative service robots gaining traction, different robotic systems have to work in close proximity. This means that the current inverse kinematics approaches do not ha

Yancan Mao, Jianjun Zhao, Zhonghao Yang, Shuhao Zhang

Transactional Stream Processing Engines (TSPEs) form the backbone of modern stream applications handling shared mutable states. Yet, the full potential of these systems, specifically in exploiting parallelism and implementing dynamic scheduling strategies, is largely unexplored. We present MorphStream, a TSPE designed to optimize parallelism and performance

Pinku Routaray, H C Das, Jeet Amrit Pattnaik, Bharat Kumar

A recent observational study has constrained the maximum mass of neutron stars (NSs), with particular attention to PSR J0952-0607 and the compact star remnant HESS J1731-347, especially in the low-mass regime. Building on our earlier work, which developed the NITR energy density functional (EDF) to reproduce the mass limit of PSR J0952-0607 but did not satis

Huygen J. Jobsis, Kostas Fykouras, Joost W. C. Reinders, Jacco van Katwijk

Halide double perovskite semiconductors such as Cs2AgBiBr6 are widely investigated as a more stable, less toxic alternative to lead-halide perovskites in light conversion applications including photovoltaics and photoredox catalysis. However, the relatively large and indirect bandgap of Cs2AgBiBr6 limits efficient sunlight absorption. Here, we show that cont

A. Feeney-Johansson, S. J. D. Purser, T. P. Ray, C. Carrasco-González

Using observations with e-MERLIN and the VLA, together with archival data from ALMA, we obtain high-resolution radio images of two binary YSOs: L1551 IRS 5 and L1551 NE, covering a wide range of frequencies from 5 - 336 GHz, and resolving emission from the radio jet on scales of only ~15 au. By comparing these observations to those from a previous epoch, it

Anders Gjølbye, William Lehn-Schiøler, Áshildur Jónsdóttir, Bergdís Arnardóttir

Deep learning models are complex due to their size, structure, and inherent randomness in training procedures. Additional complexity arises from the selection of datasets and inductive biases. Addressing these challenges for explainability, Kim et al. (2018) introduced Concept Activation Vectors (CAVs), which aim to understand deep models' internal states in

Tobias Wand, Martin Heßler, Oliver Kamps

The analysis of market correlations is crucial for optimal portfolio selection of correlated assets, but their memory effects have often been neglected. In this work, we analyse the mean market correlation of the S&P500 which corresponds to the main market mode in principle component analysis. We fit a generalised Langevin equation (GLE) to the data whose me

Christophe Reype, Radu S. Stoica, Didier Gemmerlé, Antonin Richard

Studying geological fluids mixing systems allows to understand interaction among water sources. The Hug model is an interaction point process model that can be used to estimate the number and the chemical composition of the water sources involved in a geological fluids mixing system from the chemical composition of samples Reype (2022); Reype et al. (2020, 2

Christopher Criscitiello, David Martínez-Rubio, Nicolas Boumal

Let $f \colon \mathcal{M} \to \mathbb{R}$ be a Lipschitz and geodesically convex function defined on a $d$-dimensional Riemannian manifold $\mathcal{M}$. Does there exist a first-order deterministic algorithm which (a) uses at most $O(\mathrm{poly}(d) \log(\epsilon^{-1}))$ subgradient queries to find a point with target accuracy $\epsilon$, and (b) requires

Kiran Manjunatha, Nicole Schaaps, Marek Behr, Felix Vogt

Persistence of the pathology of in-stent restenosis even with the advent of drug-eluting stents warrants the development of highly resolved in silico models. These computational models assist in gaining insights into the transient biochemical and cellular mechanisms involved and thereby optimize the stent implantation parameters. Within this work, an already

Olaf Borsboom, Martijn Lokker, Mauro Salazar, Theo Hofman

In general, electric motor design procedures for automotive applications go through expensive trial-and-error processes or use simplified models that linearly stretch the efficiency map. In this paper, we explore the possibility of efficiently optimizing the motor design directly, using high-fidelity simulation software and derivative-free optimization solve

Francesco Mazza, Ona Thornquist, Leonardo Castellanos, Thomas Butterworth

We present the first experimental application of coherent Raman spectroscopy (CRS) on the ro-vibrational $\nu_2$ mode spectrum of methane (CH$_4$). Ultrabroadband femtosecond/picosecond (fs/ps) CRS is performed in the molecular fingerprint region from 1100 to 2000 cm$^{-1}$, employing fs laser-induced filamentation as the supercontinuum generation mechanism

Ibrahima Hamidine, ALi Mahamane Saminou

In this paper we consider structures of complex Poisson brackets on the space of smooth functions in a $n$-dimensional complex manifold generated by the $(1,1)$-form $d=\partial+\overline{\partial}$-closed and non-degenerate (with non-holomorphic and non-antiholomorphic coefficients). In this case, we have view the compatibility between complex Poisson and R

Niufa Fang, Jinrong Hu, Leina Zhao

In this paper, we establish a class of generalized Poincar\'{e}-type inequalities for torsional rigidity on the boundary of a convex body of class $C^{2}_{+}$ in $\rnnn$ by using the concavity of related Brunn-Minkowski inequality.

Romain Vallon, Malek Abid, Fabien Anselmet

Jet fragmentation is investigated through a Direct Numerical Simulation campaign using Basilisk (Popinet & collaborators 2013). The simulations span over one order of magnitude of gaseous Weber numbers (13 to 165), i.e. over the second wind-induced and atomization regimes, and the jets develop over distances up to 28 nozzle diameters. The study focuses on th

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

The cross sections of the $e^{+}e^{-}\to\phi\eta'$ process at center-of-mass energies from 3.508 to 4.951 GeV are measured with high precision using 26.1 fb$^{-1}$ data collected with the BESIII detector operating at the BEPCII storage ring. The cross sections are of the order of a few picobarn, and decrease as the center-of-mass energy increases as $s^{-n/2

Amic Frouvelle, Cécile Taing

We study the long-time behavior of solutions to a model of sexual populations structured in phenotypes. The model features a nonlinear integral reproduction operator derived from the Fisher infinitesimal operator and a trait-dependent selection term. The reproduction operator describes here the inheritance of the mean parental traits to the offspring without

Fabrizio Bianchi, Maxence Brévard

We study the holomorphic motions of repelling periodic points in stable families of endomorphisms of $\mathbb P^k (\mathbb C)$. In particular, we establish an asymptotic equidistribution of the graphs associated to such periodic points with respect to natural measures in the space of all holomorphic motions of points in the Julia sets.

Nashra Pistawala, Ankit Kumar, Devesh Negi, Dibyata Rout

NiPS3 is a Van der Waals antiferromagnet that has been found to display spin-charge and spin-phonon coupling in its antiferromagnetically ordered state below TN = 155 K. Here, we study high-quality crystals of site-diluted Ni1-xZnxPS3 (0 < x < 0.2) using temperature-dependent specific heat and Raman spectroscopy probes. The site dilution suppresses the antif

Chuanguang Yang, Zhulin An, Libo Huang, Junyu Bi

Contrastive Language-Image Pre-training (CLIP) has become a promising language-supervised visual pre-training framework. This paper aims to distill small CLIP models supervised by a large teacher CLIP model. We propose several distillation strategies, including relation, feature, gradient and contrastive paradigms, to examine the effectiveness of CLIP-Knowle

Xiaofeng Mao, Yuefeng Chen, Yao Zhu, Da Chen

Practical object detection application can lose its effectiveness on image inputs with natural distribution shifts. This problem leads the research community to pay more attention on the robustness of detectors under Out-Of-Distribution (OOD) inputs. Existing works construct datasets to benchmark the detector's OOD robustness for a specific application scena

Hung Tran, Vuong Le, Svetha Venkatesh, Truyen Tran

Humans are highly adaptable, swiftly switching between different modes to progressively handle different tasks, situations and contexts. In Human-object interaction (HOI) activities, these modes can be attributed to two mechanisms: (1) the large-scale consistent plan for the whole activity and (2) the small-scale children interactive actions that start and e

Ruican Ma, Mariano Mendez, Federico Garcia, Na Sai

We analyze a Neutron Star Interior Composition Explorer (NICER) observation of the black hole X-ray binary MAXI J1820+070 during a transition from type-C to type-B quasi-periodic oscillations (QPOs). We find that below ~2 keV, for the type-B QPOs the rms amplitude is lower and the magnitude of the phase lags is larger than for the type-C QPOs. Above that ene

Yuanjia Liu, Taiki Inoue, Mengyue Wang, Michiharu Arifuku

Kite growth is a process that utilizes laminar gas flow in chemical vapor deposition to grow long, well-aligned carbon nanotubes (CNTs) for electronic application. This process uses metal nanoparticles (NPs) as catalytic seeds for CNT growth. However, these NPs remain as impurities in the grown CNT. In this study, nanodiamonds (NDs) with negligible catalytic

F. Kahraman Alicavus, G. C. Coban, E. Celik, D. S. Dogan

The presence of pulsating stars in eclipsing binary systems (EBs) makes these objects significant since they allow us to investigate the stellar interior structure and evolution. Different types of pulsating stars could be found in EBs such as Delta Scuti variables. Delta Scuti stars in EBs have been known for decades and the increasing number of such system

Aleksandr Lobanov, Alexander Gasnikov

This paper is devoted to solving a convex stochastic optimization problem in a overparameterization setup for the case where the original gradient computation is not available, but an objective function value can be computed. For this class of problems we provide a novel gradient-free algorithm, whose creation approach is based on applying a gradient approxi

Behzad Azmi, Andrea Petrocchi, Stefan Volkwein

In this paper the authors study a non-linear elliptic-parabolic system, which is motivated by mathematical models for lithium-ion batteries. One state satisfies a parabolic reaction diffusion equation and the other one an elliptic equation. The goal is to determine several scalar parameters in the coupled model in an optimal manner by utilizing a reliable re

Begoña Cano, María Jesús Moreta

A technique is described in this paper to avoid order reduction when integrating reaction-diffusion initial boundary value problems with explicit exponential Rosenbrock methods. The technique is valid for any Rosenbrock method, without having to impose any stiff order conditions, and for general time-dependent boundary values. An analysis on the global error

Behzad Bozorgtabar, Dwarikanath Mahapatra, Jean-Philippe Thiran

Unsupervised anomaly detection in medical images such as chest radiographs is stepping into the spotlight as it mitigates the scarcity of the labor-intensive and costly expert annotation of anomaly data. However, nearly all existing methods are formulated as a one-class classification trained only on representations from the normal class and discard a potent

Iven Guzel, Doğukan Özbayrak, Robert Calderbank, Ahmed Hareedy

Magnetic recording devices are still competitive in the storage density race thanks to new technologies such as two-dimensional magnetic recording (TDMR). Error-prone patterns where a bit is surrounded by complementary bits at the four positions with Manhattan distance $1$ on the TDMR grid are called plus isolation (PIS) patterns. Recently, we introduced opt

S. B. Borzakov

The existence of the dineutron was predicted over 70 years ago. At present, a number of experimental works confirm this assumption. By virtue of the principle of isotopic invariance, a singlet deuteron must also exist. The possibility of describing the neutron-proton interaction in the state at low energies as the excitation of a quasi-stationary level (sing

Davide Di Nucci, Alessandro Simoni, Matteo Tomei, Luca Ciuffreda

Neural Radiance Fields (NeRFs) have gained widespread recognition as a highly effective technique for representing 3D reconstructions of objects and scenes derived from sets of images. Despite their efficiency, NeRF models can pose challenges in certain scenarios such as vehicle inspection, where the lack of sufficient data or the presence of challenging ele

Wangduo Xie, Matthew B. Blaschko

CT images corrupted by metal artifacts have serious negative effects on clinical diagnosis. Considering the difficulty of collecting paired data with ground truth in clinical settings, unsupervised methods for metal artifact reduction are of high interest. However, it is difficult for previous unsupervised methods to retain structural information from CT ima

Yusuke Sakemi, Kakei Yamamoto, Takeo Hosomi, Kazuyuki Aihara

The training of multilayer spiking neural networks (SNNs) using the error backpropagation algorithm has made significant progress in recent years. Among the various training schemes, the error backpropagation method that directly uses the firing time of neurons has attracted considerable attention because it can realize ideal temporal coding. This method use

Chih-Hong Cheng, Harald Ruess, Konstantinos Theodorou

Covariate shift may impact the operational safety performance of neural networks. A re-evaluation of the safety performance, however, requires collecting new operational data and creating corresponding ground truth labels, which often is not possible during operation. We are therefore proposing to reshape the initial test set, as used for the safety performa

Cédric Escudero, Michelle S. Chong, Paolo Massioni, Eric Zamaï

Stealthy sensor injection attacks are serious threats for industrial plants as they can compromise the plant's integrity without being detected by traditional fault detectors. In this manuscript, we study the possibility of revealing the presence of such attacks by monitoring only the control input. This approach consists in computing an ellipsoidal bound of

Annanda Sousa, Karen Young, Mathieu D'aquin, Manel Zarrouk

Automatic Emotion Detection (ED) aims to build systems to identify users' emotions automatically. This field has the potential to enhance HCI, creating an individualised experience for the user. However, ED systems tend to perform poorly on people with Autism Spectrum Disorder (ASD). Hence, the need to create ED systems tailored to how people with autism exp

C Cuny, J Dedecker, A Korepanov, F Merlevède

We prove the Almost Sure Invariance Principle (ASIP) with close to optimal error rates for nonuniformly hyperbolic maps. We do not assume exponential contraction along stable leaves, therefore our result covers in particular slowly mixing invertible dynamical systems as Bunimovich flowers, billiards with flat points as in Chernov and Zhang (2005) and Wojtkow

Adrien Gauffriau, Iryna De Albuquerque Silva, Claire Pagetti

Implementing deep neural networks in safety critical systems, in particular in the aeronautical domain, will require to offer adequate specification paradigms to preserve the semantics of the trained model on the final hardware platform. We propose to extend the nnef language in order to allow traceable distribution and parallelisation optimizations of a tra

Jean-Guillaume Dumas, Bruno Grenet

This paper deals with simultaneously fast and in-place algorithms for formulae where the result has to be linearly accumulated: some of the output variables are also input variables, linked by a linear dependency. Fundamental examples include the in-place accumulated multiplication of polynomials or matrices, C+=AB. The difficulty is to combine in-place comp

Arion Pons

Tiny flying insects, such as Drosophila melanogaster, fly by flapping their wings at frequencies faster than their brains are able to process. To do so, they rely on self-oscillation: dynamic instability, leading to emergent oscillation, arising from muscle stretch-activation. Many questions concerning this vital natural instability remain open. Does flight

Akihiro Munemasa, Kaishun Wang, Yuefeng Yang, Wenying Zhu

We classify certain non-symmetric commutative association schemes. As an application, we determine all the weakly distance-regular circulants of one type of arcs by using Schur rings. We also give the classification of primitive weakly distance-regular circulants.

Siyuan Wang, Wenchuan Wu, Chenhui Lin, Binbin Chen

The development of energy conversion techniques enhances the coupling between the gas network and power system. However, challenges remain in the joint optimal dispatch of electricity-gas systems. The dynamic model of the gas network, described by partial differential equations, is complex and computationally demanding for power system operators. Furthermore

R. Izquierdo, S. Martín, J. Alonso, I. Parra

This paper presents the results of real-world testing of human-vehicle interactions with an autonomous vehicle equipped with internal and external Human Machine Interfaces (HMIs) in a crosswalk scenario. The internal and external HMIs were combined with implicit communication techniques using gentle and aggressive braking maneuvers in the crosswalk. Results

Aytül Gökçe, Burcu Gürbüz, Alan D. Rendall

The COVID-19 pandemic led to widespread interest in epidemiological models. In this context the role of vaccination in influencing the spreading of the disease is of particular interest. There has also been a lot of debate on the role of non-pharmaceutical interventions such as the disinfection of surfaces. We investigate a mathematical model for the spread

Thomas Leguay, Théo Ladune, Pierrick Philippe, Gordon Clare

We propose a neural image codec at reduced complexity which overfits the decoder parameters to each input image. While autoencoders perform up to a million multiplications per decoded pixel, the proposed approach only requires 2300 multiplications per pixel. Albeit low-complexity, the method rivals autoencoder performance and surpasses HEVC performance under

Yvan Castin, Alan Serafin, Alice Sinatra

It is generally accepted that the phonon gas of a superfluid always enters a weak coupling regime at sufficiently low temperatures, whatever the strength of the interactions between the underlying particles (constitutive of the superfluid). Thus, in this limit, we should always be able to calculate the damping rate of thermal phonons by applying Fermi's gold

Dale Miller

Gentzen designed his natural deduction proof system to ``come as close as possible to actual reasoning.'' Indeed, natural deduction proofs closely resemble the static structure of logical reasoning in mathematical arguments. However, different features of inference are compelling to capture when one wants to support the process of searching for proofs. PSF (

Pierre Bras, Gilles Pagès

We propose a new algorithm for variance reduction when estimating $f(X_T)$ where $X$ is the solution to some stochastic differential equation and $f$ is a test function. The new estimator is $(f(X^1_T) + f(X^2_T))/2$, where $X^1$ and $X^2$ have same marginal law as $X$ but are pathwise correlated so that to reduce the variance. The optimal correlation functi

Oliver Reardon-Smith, Michał Oszmaniec, Kamil Korzekwa

We present a classical algorithm for simulating universal quantum circuits composed of "free" nearest-neighbour matchgates or equivalently fermionic-linear-optical (FLO) gates, and "resourceful" non-Gaussian gates. We achieve the promotion of the efficiently simulable FLO subtheory to universal quantum computation by gadgetizing controlled phase gates with a

Alessandro Berti, Mahnaz Sadat Qafari

This technical report describes the intersection of process mining and large language models (LLMs), specifically focusing on the abstraction of traditional and object-centric process mining artifacts into textual format. We introduce and explore various prompting strategies: direct answering, where the large language model directly addresses user queries; m

Abderrahim Halimi, Jakeoung Koo, Stephen McLaughlin

Deploying 3D single-photon Lidar imaging in real world applications faces several challenges due to imaging in high noise environments and with sensors having limited resolution. This paper presents a deep learning algorithm based on unrolling a Bayesian model for the reconstruction and super-resolution of 3D single-photon Lidar. The resulting algorithm bene

Mattia Radice

We study the statistics of random functionals $\mathcal{Z}=\int_{0}^{\mathcal{T}}[x(t)]^{\gamma-2}dt$, where $x(t)$ is the trajectory of a one-dimensional Brownian motion with diffusion constant $D$ under the effect of a logarithmic potential $V(x)=V_0\ln(x)$. The trajectory starts from a point $x_0$ inside an interval entirely contained in the positive real

Adrien Bardes, Jean Ponce, Yann LeCun

Self-supervised learning of visual representations has been focusing on learning content features, which do not capture object motion or location, and focus on identifying and differentiating objects in images and videos. On the other hand, optical flow estimation is a task that does not involve understanding the content of the images on which it is estimate

G. H. Hovhannisyan, T. M. Bakhshiyan, G. V. Martirosyan, R. K. Dallakyan

We measure cross sections of proton-induced reactions on tin up to energies of 18 MeV using the stacked-foil activation technique, and report first experimental values for 114Sn(p,{\alpha})111In, {^{120}}Sn(p,{\alpha})117gIn, and 114Sn(p,x)113Sn reactions. Measured cross sections have been compared to existing experimental values and numerical calculations b

Sebastian Stock, Regine von Klitzing, Amin Rahimzadeh

In this study, we investigate dynamic light scattering (DLS) from both randomly diffusing silica particles and acousto-responsive microgels in aqueous dispersions under ultrasonic vibration. Employing high-frequency ultrasound (US) with low amplitude ensures that the polymers remain intact without damage. We derive theoretical expressions for the homodyne au

Géraldine Bouveret, Jean-François Chassagneux, Smail Ibbou, Antoine Jacquier

We study how the climate transition through a low-carbon economy, implemented by carbon pricing, propagates in a credit portfolio and precisely describe how carbon price dynamics affects credit risk measures such as probability of default, expected and unexpected losses. We adapt a stochastic multisectoral model to take into account the greenhouse gases (GHG

Qian Feng, Feng Xiao, Xiaoyu Wang

Dissipative estimator (observer) design for continuous time-delay systems poses a significant challenge when an unlimited number of pointwise and general distributed delays (DDs) are concerned. We propose an effective solution to this semi-open problem using the Krasovski\u{\i} functional (KF) framework in conjunction with a quadratic supply rate function, w

Pintu Debnath

Using the methods of topological dynamics, H. Furstenberg introduced the notion of a central set and proved the famous Central Sets Theorem. D. De, N. Hindman, and D. Strauss introduced $C$-set, satisfying the strong central set theorem. Using the algebraic structure of the Stone-\v{C}ech compactification of a discrete semigroup, N. Hindman and D. Strauss pr

Dipankar Jana, Piotr Kapuscinski, Amit Pawbake, Anastasios Papavasileiou

Magnon gap excitations selectively coupled to phonon modes have been studied in FePSe$_3$ layered antiferromagnet with magneto-Raman scattering experiments performed at different temperatures. The bare magnon excitation in this material has been found to be split (by $\approx~1.2$ cm$^{-1}$) into two components each being selectively coupled to one of the tw

Riccardo Fantoni

We perform Monte Carlo simulation of the thermodynamic and structural properties of Hard-, Square-Well, and Square-Shoulder Disks in narrow channels. For the thermodynamics we study the internal energy per particle and the longitudinal and transverse compressibility factor. For the structure we study the Transverse Density and Density of Pairs Profiles, the

Aharon Blank, Alexander Sherman, Boaz Koren, Oleg Zgadzai

The maser, a microwave (MW) analog of the laser, is a well-established method for generating and amplifying coherent MW irradiation with ultra-low noise. This is accomplished by creating a state of population inversion between two energy levels separated by MW frequency. Thermodynamically, such a state corresponds to a small but negative temperature. The rev

Ahmed Keddi, Aicha Nemsi, Abdelfeteh Fareh

In this paper we consider a one dimensional elastic system with double porosity structure and with frictional damping in both porous equations. We introduce two stability numbers $\chi_{0}$ and $\chi_{1}$ and prove that the solution of the system decays exponentially provided that $\chi_{0}=0$ and $\chi_{1}\neq0.$ Otherwise, we prove the lack of exponential

Hooman Moradpour, Shahram Jalalzadeh, Hamid Tebyanian

This study delves into the validity of quantum mechanical operators in the context of quantum gravity, recognizing the potential need for their generalization. A primary objective is to investigate the repercussions of these generalizations on the inherent non-locality within quantum mechanics, as exemplified by Bell's inequality. Additionally, the study scr

Akansha A

Graph Neural Networks (GNNs) have achieved notable success in learning from graph-structured data, owing to their ability to capture intricate dependencies and relationships between nodes. They excel in various applications, including semi-supervised node classification, link prediction, and graph generation. However, it is important to acknowledge that the

Jonah Pears, Laura Bocchi, Andy King

Mixed-choice has long been barred from models of asynchronous communication since it compromises key properties of communicating finite-state machines. Session types inherit this restriction, which precludes them from fully modelling timeouts -- a key programming feature to handle failures. To address this deficiency, we present (binary) TimeOut Asynchronous

Hu-Sheng Li, He Huang, Wei Yang, Cheng-Ran Du

Machine learning methods have been widely used in the investigations of the complex plasmas. In this paper, we demonstrate that the unsupervised convolutional neural network can be applied to obtain the melting line in the two-dimensional complex plasmas based on the Langevin dynamics simulation results. The training samples do not need to be labeled. The re

A. Fatima, M. Sajjad Athar, S. K. Singh

We have studied neutral and charged current (anti)neutrino induced $\eta$ production off the free nucleon target at MicroBooNE energies, in the light of recent results reported by the MicroBooNE collaboration for the total $\eta$ production cross section. This study has been made using a theoretical model in which the weak hadronic current receives contribut

Hiromu Yakura, Masataka Goto

Recent text-to-audio generation techniques have the potential to allow novice users to freely generate music audio. Even if they do not have musical knowledge, such as about chord progressions and instruments, users can try various text prompts to generate audio. However, compared to the image domain, gaining a clear understanding of the space of possible mu

Sebastiaan A. Terwijn

We discuss the complexity of completions of partial combinatory algebras, in particular of Kleene's first model. Various completions of this model exist in the literature, but all of them have high complexity. We show that although there do not exist computable completions, there exists completions of low Turing degree. We use this construction to relate com

Yusuf Yüksel

We study the equilibrium and dynamic phase transition properties of two-dimensional Ising model on a decorated triangular lattice under the influence of a time-dependent magnetic field composed of a periodic square wave part plus a time independent bias term. Using Monte Carlo simulations with standard Metropolis algorithm, we determine the equilibrium criti

Alejandro Ramírez-Arroyo, Antonio Alex-Amor, Rubén Medina, Pablo Padilla

In this paper, we present an analytical framework for the joint characterization of the 3D direction of arrival (DoA), i.e., azimuth and elevation components, and time of arrival (ToA) in multipath environments. The analytical framework is based on the use of nearly frequency-invariant beamformers (FIB) formed by toric arrays. The frequency response of the t

Fan Jiang, Mingchen Li, Jiajun Dong, Yuanxi Yu

Designing protein mutants of both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can suggest protein mutants of improved stability and activity without any prior experimental mutagenesis data of the specified protein. Leveraging temperature-aware language modeling,

Reymond Akpanya, Tom Goertzen

Frucht showed that, for any finite group $G$, there exists a cubic graph such that its automorphism group is isomorphic to $G$. For groups generated by two elements we simplify his construction to a graph with fewer nodes. In the general case, we address an oversight in Frucht's construction. We prove the existence of cycle double covers of the resulting gra

Udvas Acharjee, M S Srinath

We formulate the Root Extraction problem in finite Abelian $p$-groups and then extend it to generic finite Abelian groups. We provide algorithms to solve them. We also give the bounds on the number of group operations required for these algorithms. We observe that once a basis is computed and the discrete logarithm relative to the basis is solved, root extra

Naman Maheshwari, Nicholas Malaya, Scott Moe, Jaydeep P. Kulkarni

For Deep Neural Networks (DNNs) to become useful in safety-critical applications, such as self-driving cars and disease diagnosis, they must be stable to perturbations in input and model parameters. Characterizing the sensitivity of a DNN to perturbations is necessary to determine minimal bit-width precision that may be used to safely represent the network.

Ekin Erdem Aygül, Melih Can Topal, Ufuk Korkmaz, Deniz Türkpençe

Significant progress in the construction of physical hardware for quantum computers has necessitated the development of new algorithms or protocols for the application of real-world problems on quantum computers. One of these problems is the power flow problem, which helps us understand the generation, distribution, and consumption of electricity in a system

Branislav Boričić, Mirjana Ilić, Jelena Stanojević

In this paper we consider systems which consist of binary components with known reliabilities. We discuss their algebraic properties and define the corresponding algebraic structure, which we call the reliability algebra. We prove that the reliability algebra is a Boolean algebra. The reliability algebra seems an appropriate context for defining fuzziness me

Hendrik Ranocha, Jan Giesselmann

A posteriori error estimates based on residuals can be used for reliable error control of numerical methods. Here, we consider them in the context of ordinary differential equations and Runge-Kutta methods. In particular, we take the approach of Dedner & Giesselmann (2016) and investigate it when used to select the time step size. We focus on step size contr

Takato Yasuno

Over the past decade, previous balanced datasets have been used to advance deep learning algorithms for industrial applications. In urban infrastructures and living environments, damage data mining cannot avoid imbalanced data issues because of rare unseen events and the high-quality status of improved operations. For visual inspection, the deteriorated clas

Marco Bianchi, Kimberly Hsieh, Esben Juel Porat, Florian Dirnberger

Ultrathin CrSBr flakes are exfoliated \emph{in situ} on Au(111) and Ag(111) and their electronic structure is studied by angle-resolved photoemission spectroscopy. The thin flakes' electronic properties are drastically different from those of the bulk material and also substrate-dependent. For both substrates, a strong charge transfer to the flakes is observ

Keno Moenck, Arne Wendt, Philipp Prünte, Julian Koch

Deploying deep learning-based applications in specialized domains like the aircraft production industry typically suffers from the training data availability problem. Only a few datasets represent non-everyday objects, situations, and tasks. Recent advantages in research around Vision Foundation Models (VFM) opened a new area of tasks and models with high ge

Piotr Lebiedowicz, Otto Nachtmann, Antoni Szczurek

We discuss the reactions $\pi p \to \pi p$ and $\pi p \to \pi p \gamma$ from a general quantum field theory (QFT) point of view, describing these reactions in QCD and lowest relevant order of electromagnetism. We consider the pion-proton elastic scattering both off shell and on shell. The on-shell amplitudes for $\pi^{\pm} p \to \pi^{\pm} p$ scattering are d

Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang

In dynamic Magnetic Resonance Imaging (MRI), k-space is typically undersampled due to limited scan time, resulting in aliasing artifacts in the image domain. Hence, dynamic MR reconstruction requires not only modeling spatial frequency components in the x and y directions of k-space but also considering temporal redundancy. Most previous works rely on image-

Henning Krause

The finitistic dimension of a triangulated category is introduced. For the category of perfect complexes over a ring it is shown that this dimension is finite if and only if the small finitistic dimension of the ring is finite.

Donato Bini, Andrea Geralico, Piero Rettegno

We compute the leading order contribution to radiative losses in the case of spinning binaries with aligned spins due to their spin-orbit interaction. The orbital average along hyperboliclike orbits is taken through an appropriate spin-orbit modification to the quasi-Keplerian parametrization for nonspinning bodies, which maintains the same functional form,

Bakhtawar Shaukat, Muhammad Ishaq, Ahtsham ul Haq, Zahid Iqbal

We obtain the exact values for depth and projective dimension and lower bounds for Stanley depth of the quotient rings of the edge ideals associated with all cubic circulant graphs.

Simon Brun, Thomas Willwacher

We compute numerically the homology of several graph complexes in low loop orders, extending previous results.

Carlos Mario Braga Ortuño, Blanca Martinez Donoso, Belén Muñiz Villanueva

This paper elucidates the importance of governing an artificial intelligence model post-deployment and overseeing potential fluctuations in the distribution of present data in contrast to the training data. The concepts of data drift and concept drift are explicated, along with their respective foundational distributions. Furthermore, a range of metrics is i

Md Fahim Sikder, Resmi Ramachandranpillai, Fredrik Heintz

The generation of high-quality, long-sequenced time-series data is essential due to its wide range of applications. In the past, standalone Recurrent and Convolutional Neural Network-based Generative Adversarial Networks (GAN) were used to synthesize time-series data. However, they are inadequate for generating long sequences of time-series data due to limit

Marco Matone

There are two main problems in finding the higher genus superstring measure. The first one is that for $g\geq 5$ the super moduli space is not projected. Furthermore, the supermeasure is regular for $g\leq 11$, a bound related to the source of singularities due to the divisor in the moduli space of Riemann surfaces with even spin structure having holomorphic

Oleksiy Kapustyan, Olha Martynyuk, Oleksandr Misiats, Oleksandr Stanzhytskyi

In this paper we consider stochastic thin-film equation with nonlinear drift terms, colored Gaussian Stratonovych noise, as well as nonlinear colored Wiener noise. By means of Trotter-Kato-type decomposition into deterministic and stochastic parts, we couple both of these dynamics via a discrete-in-time scheme, and establish its convergence to a non-negative

Shafeef Omar, Lorenzo Amatucci, Victor Barasuol, Giulio Turrisi

We present a footstep planning policy for quadrupedal locomotion that is able to directly take into consideration a-priori safety information in its decisions. At its core, a learning process analyzes terrain patches, classifying each landing location by its kinematic feasibility, shin collision, and terrain roughness. This information is then encoded into a

G. Kourmoulakis, A. Michail, I. Paradisanos, X. Marie

We perform micro-photoluminescence and Raman experiments to examine the impact of biaxial tensile strain on the optical properties of WS2 monolayers. A strong shift on the order of -130 meV per % of strain is observed in the neutral exciton emission at room temperature. Under near-resonant excitation we measure a monotonic decrease in the circular polarizati

Guangxiang Su, Zelin Yi

In this paper, we prove that the foliated Rosenberg index of a possibly noncompactly enlargeable, spin foliation is nonzero. It generalizes our previous result. The difficulty brought by the noncompactness is reflected in the infinite dimensionality of some vector bundles which, fortunately, can be reduced to finite dimensional vector bundles by the idea of

Raavi Gupta, Sameep Chattopadhyay, Pradyumna Paruchuri, Debasish Chatterjee

This article presents a novel numerically tractable technique for synthesizing Lyapunov functions for equilibria of nonlinear vector fields. In broad strokes, corresponding to an isolated equilibrium point of a given vector field, a selection is made of a compact neighborhood of the equilibrium and a dictionary of functions in which a Lyapunov function is ex

Umberto Michieli, Pablo Peso Parada, Mete Ozay

Keyword Spotting (KWS) models on embedded devices should adapt fast to new user-defined words without forgetting previous ones. Embedded devices have limited storage and computational resources, thus, they cannot save samples or update large models. We consider the setup of embedded online continual learning (EOCL), where KWS models with frozen backbone are