October 2023 arXiv papers — page 166

Qi Gao, Michihiko Sugawara, Paul D. Nation, Takao Kobayashi

Integration of quantum chemistry simulations, machine learning techniques, and optimization calculations is expected to accelerate material discovery by making large chemical spaces amenable to computational study; a challenging task for classical computers. In this work, we develop a combined quantum-classical computing scheme involving the computational-ba

Agnes M. Nakiganda, Spyros Chatzivasileiadis

The successful integration of machine learning models into decision support tools for grid operation hinges on effectively capturing the topological changes in daily operations. Frequent grid reconfigurations and N-k security analyses have to be conducted to ensure a reliable and secure power grid, leading to a vast combinatorial space of possible topologies

Christian Struckmann, Robin Corgier, Sina Loriani, Gina Kleinsteinberg

The Space Time Explorer and QUantum Equivalence principle Space Test (STE-QUEST) recently proposed, aims at performing a precision test of the weak equivalence principle (WEP), a fundamental cornerstone of General Relativity. Taking advantage of the ideal operation conditions for high-precision quantum sensing on board of a satellite, it aims to detect possi

Chandrika Sadanand, Emily Shinkle

A subcomplex $\mathcal{X}$ of a cell complex $\mathcal{C}$ is called \emph{rigid} with respect to another cell complex $\mathcal{C}'$ if every injective simplicial map $\lambda:\mathcal{X} \rightarrow \mathcal{C}'$ has a unique extension to an injective simplicial map $\phi:\mathcal{C}\rightarrow \mathcal{C}'$. We say that a cell complex exhibits \emph{finit

J. Einstein-Curtis, J. Edelen, B. Gur, M. Henderson

This work describes the LLRF and control system in use for a novel accelerator structure developed for a compact design operating in C-band developed by SLAC, with collaboration from RadiaBeam and RadiaSoft. This design is a pulsed RF/pulsed beam system that only provides minimal monitoring for control of each two-cavity pair. Available signals include only

Guian Fang, Mengsha Liu, Yi Zhong, Zhuolin Zhang

Alzheimer's disease is a progressive neurological disorder characterized by cognitive impairment and memory loss. With the increasing aging population, the incidence of AD is continuously rising, making early diagnosis and intervention an urgent need. In recent years, a considerable number of teams have applied computer-aided diagnostic techniques to early c

Liang Zhang, Mariano Méndez, Federico García, Yuexin Zhang

We present a detailed analysis of the spectral and timing characteristics of a 7-Hz type-A quasi-periodic oscillation (QPO) detected in NICER observations of the black hole X-ray binary MAXI J1348-630 during its high-soft state. The QPO is broad and weak, with an integrated fractional rms amplitude of 0.9 per cent in the 0.5-10 keV band. Thanks to the large

Henry Bradford, Christopher H. Cashen, Francesco Fournier-Facio, Nicolás Matte Bon

The conference `Geometric and Asymptotic Group Theory with Applications (GAGTA) 2023: Groups and Dynamics' took place at the Erwin Schr\"odinger Institute on July 17-21. These are the problems that were proposed during the Problem Session: Residual finiteness growth, Geometric v. random walk boundaries, Stability, Cogrowth, Embedding left orderable groups, S

Laura Batini, Aleksandr Chatrchyan, Jürgen Berges

We investigate false vacuum decay of a relativistic scalar field initialized in the metastable minimum of an asymmetric double-well potential. The transition to the true ground state is a well-defined initial-value problem in real time, which can be formulated in nonequilibrium quantum field theory on a closed time path. We employ the non-perturbative framew

Anupam Purwar, Rahul Sundar

Retrieving answers in a quick and low cost manner without hallucinations from a combination of structured and unstructured data using Language models is a major hurdle. This is what prevents employment of Language models in knowledge retrieval automation. This becomes accentuated when one wants to integrate a speech interface on top of a text based knowledge

S. Katsioli, R. Adam, P. Ade, H. Ajeddig

In the framework of the IMEGIN Large Program, we used the NIKA2 camera on the IRAM 30-m telescope to observe the edge-on galaxy NGC 891 at 1.15 mm and 2 mm and at a FWHM of 11.1" and 17.6", respectively. Multiwavelength data enriched with the new NIKA2 observations fitted by the HerBIE SED code (coupled with the THEMIS dust model) were used to constrain the

Jean-Francois Bony, Laurent Michel

The low-lying eigenvalues of the generator of a Langevin process are known to satisfy the Eyring-Kramers law in the low temperature regime under suitable assumptions. These eigenvalues are generically real. We construct generators whose spectral gap is given by non-real eigenvalues or by a real eigenvalue having a Jordan block.

Boaz Rafaely, Dima Khaykin

Spherical loudspeaker arrays have been recently studied for directional sound radiation, where the compact arrangement of the loudspeaker units around a sphere facilitated the control of sound radiation in three-dimensional space. Directivity of sound radiation, or beamforming, was achieved by driving each loudspeaker unit independently, where the design of

Jesus Cañas, Névine Rochat, Adeline Grenier, Audrey Jannaud

We study the origin of bimodal emission in AlGaN/AlN QD superlattices displaying high internal quantum efficiency (around 50%) in the 230-300 nm spectral range. The secondary emission at longer wavelengths is linked to the presence of cone-like defects starting at the first AlN buffer/superlattice interface and propagating vertically. These defects are assoc

Changhun Lee, Chiehyeon Lim

We study the theoretical aspects of Reinforced Language Models (RLMs) from a bi-objective optimization perspective. Specifically, we consider the RLMs as a Pareto optimization problem that maximizes the two conflicting objectives, i.e., reward objective and likelihood objectives, simultaneously. Our main contribution consists of three parts. First, we establ

E. S. Redchenko, M. Zens, M. Zemlicka, M. Peruzzo

Recent advancements in superconducting circuits have enabled the experimental study of collective behavior of precisely controlled intermediate-scale ensembles of qubits. In this work, we demonstrate an atomic frequency comb formed by individual artificial atoms strongly coupled to a single resonator mode. We observe periodic microwave pulses that originate

D. Varga, B. Gábor, B. Sárközi, K. V. Adwaith

We show that an optimized loading of a cold ensemble of rubidium-87 atoms from a magnetic trap into an optical dipole trap sustained by a single, far-red-detuned mode of a high-Q optical cavity can be efficient despite the large volume mismatch of the traps. The magnetically trapped atoms are magnetically transported to the vicinity of the cavity mode and re

Ronaldo Rodrigues Pela, Cecilia Vona, Sven Lubeck, Ben Alex

Two-dimensional (2D) materials combine many fascinating properties that make them more interesting than their three-dimensional counterparts for a variety of applications. For example, 2D materials exhibit stronger electron-phonon and electron-hole interactions, and their energy gaps and effective carrier masses can be easily tuned. Surprisingly, published b

Yujian Betterest Li, Kai Wu

Track one of CTI competition is on click-through rate (CTR) prediction. The dataset contains millions of records and each field-wise feature in a record consists of hashed integers for privacy. For this task, the keys of network-based methods might be type-wise feature extraction and information fusion across different fields. Multi-layer perceptrons (MLPs)

Stephen Choi, William Gazeley, Siu Ho Wong, Tingting Li

This paper introduces the Conversational Factor Information Retrieval Method (ConFIRM), a novel approach to fine-tuning large language models (LLMs) for domain-specific retrieval tasks. ConFIRM leverages the Five-Factor Model of personality to generate synthetic datasets that accurately reflect target population characteristics, addressing data scarcity in s

Ángel Casanova Bienzobas, Alfonso Sánchez-Macián

Threat hunting is a proactive methodology for exploring, detecting and mitigating cyberattacks within complex environments. As opposed to conventional detection systems, threat hunting strategies assume adversaries have infiltrated the system; as a result they proactively search out any unusual patterns or activities which might indicate intrusion attempts.

Alexander Brauckmann, Elizabeth Polgreen, Tobias Grosser, Michael F. P. O'Boyle

MLIR is an emerging compiler infrastructure for modern hardware, but existing programs cannot take advantage of MLIR's high-performance compilation if they are described in lower-level general purpose languages. Consequently, to avoid programs needing to be rewritten manually, this has led to efforts to automatically raise lower-level to higher-level dialect

Andronikos Paliathanasis

We consider the symmetric teleparallel $f\left( Q\right) $-gravity in Friedmann--Lema\^{\i}tre--Robertson--Walker cosmology with nonzero spatial curvature. For a nonlinear $f\left( Q\right) $ model there exist always the limit of General\ Relativity with or without the cosmological constant term. The de Sitter solution is always provided by the theory and fo

Luyuan Wang, Yiqian Wu, Yongliang Yang, Chen Liu

Despite rapid advances in computer graphics, creating high-quality photo-realistic virtual portraits is prohibitively expensive. Furthermore, the well-know ''uncanny valley'' effect in rendered portraits has a significant impact on the user experience, especially when the depiction closely resembles a human likeness, where any minor artifacts can evoke feeli

Eleanor Harris

This thesis explores the thermodynamics of the cosmological horizon, aiming to make progress towards a better understanding of the microscopic nature of its entropy. We utilise the constrained nature of low-dimensional gravity to do so and investigate timelike boundaries in these theories, with an emphasis on the stretched horizon holographic picture. Given

Daniel Weber, Fabian Thomas, Lukas Gerlach, Ruiyi Zhang

Since the initial discovery of Meltdown and Spectre in 2017, different variants of these attacks have been discovered. One often overlooked variant is Meltdown 3a, also known as Meltdown-CPL-REG. Even though Meltdown-CPL-REG was initially discovered in 2018, the available information regarding the vulnerability is still sparse. In this paper, we analyze Melt

Boaz Rafaely

The zones of quiet in pure-tone diffuse sound fields have been studied extensively in the past, both theoretically and experimentally, with the well known result of the 10\,dB attenuation extending to about a tenth of a wavelength. Recent results on the spatial-temporal correlation of broadband diffuse sound fields are used in this study to develop a theoret

Franka Bause, Samir Moustafa, Johannes Langguth, Wilfried N. Gansterer

Message passing neural networks iteratively generate node embeddings by aggregating information from neighboring nodes. With increasing depth, information from more distant nodes is included. However, node embeddings may be unable to represent the growing node neighborhoods accurately and the influence of distant nodes may vanish, a problem referred to as ov

Xinpeng Liu, Yong-Lu Li, Ailing Zeng, Zizheng Zhou

Motion understanding aims to establish a reliable mapping between motion and action semantics, while it is a challenging many-to-many problem. An abstract action semantic (i.e., walk forwards) could be conveyed by perceptually diverse motions (walking with arms up or swinging). In contrast, a motion could carry different semantics w.r.t. its context and inte

David Ellerman

The Born Rule plays a critical role in quantum mechanics (QM) since it supplies the link between the mathematical formalism and experimental results in terms of probabilities. The Born Rule does not occur in ordinary probability theory. Where then does it come from? This has been a topic of considerable controversy in the literature. We take the approach of

Henriette Padberg, Amir Regev, Giuseppe Piccolboni, Alessandro Bricalli

Processing-in-memory (PIM) is attractive to overcome the limitations of modern computing systems. Numerous PIM systems exist, varying by the technologies and logic techniques used. Successful operation of specific logic functions is crucial for effective processing-in-memory. Memristive non-stateful logic techniques are compatible with CMOS logic and can be

Glejdis Shkëmbi, Johanna P. Müller, Zhe Li, Katharina Breininger

Breast cancer is a major concern for women's health globally, with axillary lymph node (ALN) metastasis identification being critical for prognosis evaluation and treatment guidance. This paper presents a deep learning (DL) classification pipeline for quantifying clinical information from digital core-needle biopsy (CNB) images, with one step less than exist

Raffaello Foldes, Enrico Camporeale, Raffaele Marino

We present a novel machine learning approach to reduce the dimensionality of state variables in stratified turbulent flows governed by the Navier-Stokes equations in the Boussinesq approximation. The aim of the new method is to perform an accurate reconstruction of the temperature and the three-dimensional velocity of geophysical turbulent flows developing n

Chen Chen, Manuel Herrera, Ge Zheng, Liqiao Xia

Serverless edge computing adopts an event-based paradigm that provides back-end services on an as-used basis, resulting in efficient resource utilization. To improve the end-to-end latency and revenue, service providers need to optimize the number and placement of serverless containers while considering the system cost incurred by the provisioning. The parti

Chuan Zheng, Pavel Fedorets, Ralf Engels, Ilhan Engin

The preservation of nuclear spin alignment in plasmas is a prerequisite for important applications, such as energy production through polarized fusion or the acceleration of polarized particle beams. Although this conservation property has been the basis of numerous theoretical papers, it has never been experimentally confirmed. Here, we report on first expe

Daniel Weber, Fabian Thomas, Lukas Gerlach, Ruiyi Zhang

The transient-execution attack Meltdown leaks sensitive information by transiently accessing inaccessible data during out-of-order execution. Although Meltdown is fixed in hardware for recent CPU generations, most currently-deployed CPUs have to rely on software mitigations, such as KPTI. Still, Meltdown is considered non-exploitable on current systems. In t

Gabriel R. Barrenechea, Ernesto Castillo, Douglas R. Q. Pacheco

In this work we study different Implicit-Explicit (IMEX) schemes for incompressible flow problems with variable viscosity. Unlike most previous work on IMEX schemes, which focuses on the convective part, we here focus on treating parts of the diffusive term explicitly to reduce the coupling between the velocity components. We present different, both monolith

Sanket Kalwar, Mihir Ungarala, Shruti Jain, Aaron Monis

Semantic segmentation in adverse weather scenarios is a critical task for autonomous driving systems. While foundation models have shown promise, the need for specialized adaptors becomes evident for handling more challenging scenarios. We introduce DiffPrompter, a novel differentiable visual and latent prompting mechanism aimed at expanding the learning cap

Qingguo Liu, Pan Gao, Kang Han, Ningzhong Liu

Compared to CNN-based methods, Transformer-based methods achieve impressive image restoration outcomes due to their abilities to model remote dependencies. However, how to apply Transformer-based methods to the field of blind super-resolution (SR) and further make an SR network adaptive to degradation information is still an open problem. In this paper, we p

Niccolò Cavagnero, Luca Robbiano, Francesca Pistilli, Barbara Caputo

Neural Networks design is a complex and often daunting task, particularly for resource-constrained scenarios typical of mobile-sized models. Neural Architecture Search is a promising approach to automate this process, but existing competitive methods require large training time and computational resources to generate accurate models. To overcome these limits

Udo Schlegel, Daniel A. Keim

Given the increasing amount and general complexity of time series data in domains such as finance, weather forecasting, and healthcare, there is a growing need for state-of-the-art performance models that can provide interpretable insights into underlying patterns and relationships. Attribution techniques enable the extraction of explanations from time serie

Hiromasa Suzuki, Takaaki Tanaka, Tsuyoshi Inoue, Hiroyuki Uchida

Kinematics of shocks, ejecta knots, and the compact remnant of a supernova remnant gives an insight into the nature of the progenitor and surrounding environment. We report on a proper motion measurement of X-ray knots and rims of the magnetar-hosting supernova remnant RCW 103. Chandra data obtained in three epochs, 1999, 2010, and 2016 are used. We find a g

Zachary Feinstein, Niklas Hey, Birgit Rudloff

In Feinstein and Rudloff (2023), it was shown that the set of Nash equilibria for any non-cooperative $N$ player game coincides with the set of Pareto optimal points of a certain vector optimization problem with non-convex ordering cone. To avoid dealing with a non-convex ordering cone, an equivalent characterization of the set of Nash equilibria as the inte

Joseph A. Dessi, Evgenios T. A. Kakariadis

We parametrise the gauge-invariant ideals of the Toeplitz-Nica-Pimsner algebra of a strong compactly aligned product system over $\mathbb{Z}_+^d$ by using $2^d$-tuples of ideals of the coefficient algebra that are invariant, partially ordered, and maximal. We give an algebraic characterisation of maximality that allows the iteration of a $2^d$-tuple to the m

Ioanna Stamou, Sebastien Clesse

We investigate a mechanism of primordial black hole (PBH) formation that avoids any dependence on specific inflationary features or exotic physics. In this scenario, the required large curvature fluctuations leading to PBH formation are generated after inflation by the quantum fluctuations of a light stochastic spectator field during inflation, when this fie

Stefano Savazzi, Federica Fieramosca, Sanaz Kianoush, Vittorio Rampa

Electromagnetic (EM) body models predict the impact of human presence and motions on the Radio-Frequency (RF) stray radiation received by wireless devices nearby. These wireless devices may be co-located members of a Wireless Local Area Network (WLAN) or even cellular devices connected with a Wide Area Network (WAN). Despite their accuracy, EM models are tim

Marc Eisoldt, Alexander Mock, Mario Porrmann, Thomas Wiemann

Monte Carlo Localization is a widely used approach in the field of mobile robotics. While this problem has been well studied in the 2D case, global localization in 3D maps with six degrees of freedom has so far been too computationally demanding. Hence, no mobile robot system has yet been presented in literature that is able to solve it in real-time. The com

Heehyeon Kim, Jinhyeok Choi, Joyce Jiyoung Whang

Fraud detection aims to discover fraudsters deceiving other users by, for example, leaving fake reviews or making abnormal transactions. Graph-based fraud detection methods consider this task as a classification problem with two classes: frauds or normal. We address this problem using Graph Neural Networks (GNNs) by proposing a dynamic relation-attentive agg

Robert Fleischer, Eleftheria Malami, Anders Rehult, K. Keri Vos

In the pursuit of physics beyond the Standard Model, a promising path is the study of B-meson decays caused by the transition $b \to s\ell^+\ell^-$. A key observable in such decays is the ratio $R_K$, which measures electron--muon universality in $B \to K \mu^+\mu^-/e^+e^-$. At first sight, the recent LHCb measurement of $R_K \sim 1$ may seem to largely cons

Clemens Schlegel, Dirk Alexander Molitor, Christian Kubik, Daniel Michael Martin

The extend of tool wear significantly affects blanking processes and has a decisive impact on product quality and productivity. For this reason, numerous scientists have addressed their research to wear monitoring systems in order to identify or even predict critical wear at an early stage. Existing approaches are mainly based on indirect monitoring using ti

Boaz Rafaely

Spherical microphone arrays have been recently studied for spatial sound recording, speech communication, and sound field analysis for room acoustics and noise control. Complementary theoretical studies presented progress in spatial sampling and beamforming methods. This paper reviews recent results in spatial sampling that facilitate a wide range of spheric

Nicholas M. Wilkinson

Within minutes of birth a newborn gnu or giraffe works to stand and walk, asserting postural balance and organised animate behaviour in an apparently goal-directed manner. In contrast, robots learning to stand and walk from scratch begin with random flailing, the behaviour cohering over time as the robot internalises some reward or value signal. How does the

J. Allam, A. Matzkin

Wigner-friend scenarios -- in which external agents describe a closed laboratory containing a friend making a measurement -- highlight the difficulties inherent to quantum theory when accounting for measurements. In non-relativistic scenarios, the difficulty is to accommodate unitary evolution for a closed system with a definite outcome obtained by the frien

Aleksei Malyshev, Juan Miguel Arrazola, A. I. Lvovsky

Neural quantum states have established themselves as a powerful and versatile family of ansatzes for variational Monte Carlo simulations of quantum many-body systems. Of particular prominence are autoregressive neural quantum states (ANQS), which enjoy the expressibility of deep neural networks, and are equipped with a procedure for fast and unbiased samplin

Giuseppe Alfonzetti, Ruggero Bellio, Yunxiao Chen, Irini Moustaki

A composite likelihood is an inference function derived by multiplying a set of likelihood components. This approach provides a flexible framework for drawing inference when the likelihood function of a statistical model is computationally intractable. While composite likelihood has computational advantages, it can still be demanding when dealing with numero

Alexei Entin, Sean Landsberg

Cilleruelo conjectured that for an irreducible polynomial $f \in \mathbb{Z}[X]$ of degree $d \geq 2$ one has $$\log\left[\mathrm{lcm}(f(1),f(2),\ldots f(N))\right]\sim(d-1)N\log N$$ as $N \to \infty$. He proved it in the case $d=2$ but it remains open for every polynomial with $d>2$. We investigate the function field analogue of the problem by considering po

Radosław Adamczak, Dominik Kutek

Building on Talagrand's proof of the Hoffmann-J{\o}rgensen inequality for $L_p$ spaces and its version for the exponential Orlicz spaces we provide a full characterization of Orlicz functions $\Psi$ for which an analogous inequality holds in the Orlicz space $L_\Psi(F)$, where $F$ is an arbitrary Banach space. As an application we present a characterization

Shiquan Yi, Yang Lyu, Lin Hua, Quan Pan

Simultaneous Localization and Mapping (SLAM) plays an important role in robot autonomy. Reliability and efficiency are the two most valued features for applying SLAM in robot applications. In this paper, we consider achieving a reliable LiDAR-based SLAM function in computation-limited platforms, such as quadrotor UAVs based on graph-based point cloud associa

Manisha, Parveen, Jitender Kumar

The power graph $\mathcal{P}(G)$ is the simple undirected graph with group elements as a vertex set and two elements are adjacent if one of them is a power of the other. The order supergraph $\mathcal{S}(G)$ of the power graph $\mathcal{P}(G)$ is the simple undirected graph with vertex set $G$ in which two vertices $x$ and $y$ are adjacent if $o(x)\vert o(y)

Rikkert Frederix, Paolo Torrielli

We introduce a new technique, that we dub Born spreading, aimed at reducing the number of negative-weight $\mathbb S$ events in the MC@NLO matching of NLO calculations with parton-shower simulations. We show that such a technique, based on a re-distribution of Born matrix elements in the radiative phase space, achieves a sizeable reduction of negative-weight

Zitao Song, Wendi Ren, Shuang Li

Excitatory point processes (i.e., event flows) occurring over dynamic graphs (i.e., evolving topologies) provide a fine-grained model to capture how discrete events may spread over time and space. How to effectively steer the event flows by modifying the dynamic graph structures presents an interesting problem, motivated by curbing the spread of infectious d

Konstantinos Kanellopoulos, Hong Chul Nam, F. Nisa Bostanci, Rahul Bera

Address translation is a performance bottleneck in data-intensive workloads due to large datasets and irregular access patterns that lead to frequent high-latency page table walks (PTWs). PTWs can be reduced by using (i) large hardware TLBs or (ii) large software-managed TLBs. Unfortunately, both solutions have significant drawbacks: increased access latency

Davide Astesiano, Donato Bini, Andrea Geralico, Matteo Luca Ruggiero

We investigate the geometrical properties, spectral classification, geodesics, and causal structure of the Bonnor's spacetime [Journal of Physics A Math. Gen., \textbf{10}, 1673 (1977)], i.e., a stationary axisymmetric solution with a rotating dust as a source. This spacetime has a directional singularity at the origin of the coordinates (related to the dive

Max McGinley

We address how one can empirically infer properties of quantum states generated by dynamics involving measurements. Our focus is on many-body settings where the number of measurements is extensive, making brute-force approaches based on postselection intractable due to their exponential sample complexity. We introduce a general-purpose scheme that can be use

Udaya Varadarajan, Sneha Bharti

We have so many languages to communicate with others as humans. There are approximately 7000 languages in the world, and many are becoming extinct for a variety of reasons. In order to preserve and prevent the extinction of these languages, we need to preserve them. One way of preservation is to have a preservation metadata for languages. Metadata is data ab

Valeriy G. Bardakov, Tatyana A. Kozlovskaya, Komal Negi, Madeti Prabhakar

In this paper we study some subgroups and their decompositions in semi-direct product of the twisted virtual braid group $TVB_n$. In particular, the twisted virtual pure braid group $TVP_n$ is the kernel of an epimorphism of $TVB_n$ onto the symmetric group $S_n$. We find the set of generators and defining relations for $TVP_n$ and show that $TVB_n = TVP_n \

František Bartoš, Alexandra Sarafoglou, Henrik R. Godmann, Amir Sahrani

Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. We collected $350{,}757$ coin flips to test the counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it te

Yusheng Huang, Zhouhan Lin

Document-level relation extraction (DocRE) is a task that focuses on identifying relations between entities within a document. However, existing DocRE models often overlook the correlation between relations and lack a quantitative analysis of relation correlations. To address this limitation and effectively capture relation correlations in DocRE, we propose

Hye Bin Yoo, Hyun Min Han, Sung Soo Hwang, Il Yong Chun

Neural radiance field (NeRF) is an emerging view synthesis method that samples points in a three-dimensional (3D) space and estimates their existence and color probabilities. The disadvantage of NeRF is that it requires a long training time since it samples many 3D points. In addition, if one samples points from occluded regions or in the space where an obje

Punit Dubey, Ajay Kumar

The nuclear scientific community views $^{232}$Th as an option for fuel in the future nuclear energy program. Numerous experimental studies have been conducted to determine the cross-section; however, very few have been performed to calculate the total neutron multiplicity above 10 MeV energy. In this work, we have compared the experimental data of average n

Jai-chan Hwang, Hyerim Noh

Graviton-photon conversions in a given external electric or magnetic field, known as the Gertsenshtein mechanism, are usually treated using the four-potential for photons. In terms of the electric and magnetic (EM) fields, however, proper identification of the fields in curved spacetime is important. By misidentifying the fields in Minkowski form, as is ofte

Ilinka Dimitrova, Vítor H. Fernandes, Jörg Koppitz, Teresa M. Quinteiro

In this paper we consider endomorphisms of an undirected cycle graph from Semigroup Theory perspective. Our main aim is to present a process to determine sets of generators with minimal cardinality for the monoids $wEnd(C_n)$ and $End(C_n)$ of all weak endomorphisms and all endomorphisms of an undirected cycle graph $C_n$ with $n$ vertices. We also describe

Yinda Chen, Wei Huang, Shenglong Zhou, Qi Chen

The performance of existing supervised neuron segmentation methods is highly dependent on the number of accurate annotations, especially when applied to large scale electron microscopy (EM) data. By extracting semantic information from unlabeled data, self-supervised methods can improve the performance of downstream tasks, among which the mask image model (M

Anton Losev, Alexandr Filyaev, Vladimir Zavodilenko, Igor Pavlov

A 2D model of an InGaAs/InAlAs single photon avalanche photodiode has been developed. The influence of the active area structure in the multiplication region on the diode's operating parameters has been studied. It was found that changing the diameter of the structure's active region leads to a change in the dark current in the linear part of the current-vol

Christian Bayer, Simon Breneis

We provide an efficient and accurate simulation scheme for the rough Heston model in the standard ($H>0$) as well as the hyper-rough regime ($H > -1/2$). The scheme is based on low-dimensional Markovian approximations of the rough Heston process derived in [Bayer and Breneis, arXiv:2309.07023], and provides weak approximation to the rough Heston process. Num

Biao Wu, Qiang Huang, Anthony K. H. Tung

Safeguarding the Intellectual Property (IP) of data has become critically important as machine learning applications continue to proliferate, and their success heavily relies on the quality of training data. While various mechanisms exist to secure data during storage, transmission, and consumption, fewer studies have been developed to detect whether they ar

Makoto Arimoto, Katsuaki Asano, Koji S. Kawabata, Kenji Toma

Gamma-ray bursts (GRBs) are the most electromagnetically luminous cosmic explosions. They are powered by collimated streams of plasma (jets) ejected by a newborn stellar-mass black hole or neutron star at relativistic velocities (near the speed of light). Their short-lived (typically tens of seconds) prompt $\gamma$-ray emission from within the ejecta is fol

Maciej Przybylek, Piotr Beldowski

Chitosan and chitin are promising biopolymers used in many areas including biomedical applications, such as tissue engineering and viscosupplementation. Chitosan shares similar properties with hyaluronan, a natural component of synovial fluid, making it a good candidate for joint disease treatment. The structural and energetic consequences of intermolecular

Nisha Chahal, Suneel Dutt, Arvind Kumar

This paper investigates the impact of strangeness chemical potential and finite volume on QCD critical end point by employing a (2+1) flavored Polyakov quark meson model. Within the mean-field approximation, the model has been extended to study the effect of vector interactions on the thermodynamics of isospin-asymmetric quark matter. Susceptibilities of con

Alireza Zolanvari, Ashish Cherukuri

This paper considers a risk-constrained motion planning problem and aims to find the solution combining the concepts of iterative model predictive control (MPC) and data-driven distributionally robust (DR) risk-constrained optimization. In the iterative MPC, at each iteration, safe states visited and stored in the previous iterations are imposed as terminal

Daniela Thyssens, Tim Dernedde, Jonas K. Falkner, Lars Schmidt-Thieme

Neural Combinatorial Optimization has been researched actively in the last eight years. Even though many of the proposed Machine Learning based approaches are compared on the same datasets, the evaluation protocol exhibits essential flaws and the selection of baselines often neglects State-of-the-Art Operations Research approaches. To improve on both of thes

Fabian Thiery, Nikolaus A. Adams, Stefan Adami

We present a Weakly Compressible SPH (WCSPH) formulation with a temporally variable speed of sound. The benefits of a time-varying sound speed formulation and the weaknesses of a constant sound speed formulation are worked out. It is shown how a variable sound speed can improve the performance, accuracy, and applicability of the WCSPH method. In our novel Un

Manon Macary, Marie Tahon, Yannick Estève, Daniel Luzzati

The goal of our research is to automatically retrieve the satisfaction and the frustration in real-life call-center conversations. This study focuses an industrial application in which the customer satisfaction is continuously tracked down to improve customer services. To compensate the lack of large annotated emotional databases, we explore the use of pre-t

Sivaranjani A, Radha S

Paley graphs are Cayley graphs which are circulant and strongly regular. Paley-type graph of order a product of two distinct Pythagorean primes was introduced by Dr Angsuman Das. In this paper, we extend the study of Paley-type graphs to the order a product of n distinct Pythagorean primes. We have determined its adjacency spectra and the exact number of the

Snehit Panghal, Biswarup Mukhopadhyaya

We study the decay of three neutral Higgs bosons into {\gamma}{\gamma} and Z{\gamma} in the four major types of two Higgs doublet models with CP conserved. Particular focus is made on the possibility of the width of the latter decay dominating over the former. For the 125-GeV scalar, such a possibility is mostly excluded when one imposes all theoretical and

Ben Amies-King, Karolina P. Schatz, Haofan Duan, Ayan Biswas

The future quantum internet will leverage existing communication infrastructures, including deployed optical fibre networks, to enable novel applications that outperform current information technology. In this scenario, we perform a feasibility study of quantum communications over an industrial 224 km submarine optical fibre link deployed between Southport i

Song Zhang, Qingzhong Wang, Jiang Bian, Haoyi Xiong

While models derived from Vision Transformers (ViTs) have been phonemically surging, pre-trained models cannot seamlessly adapt to arbitrary resolution images without altering the architecture and configuration, such as sampling the positional encoding, limiting their flexibility for various vision tasks. For instance, the Segment Anything Model (SAM) based

S. Zamora, A. I. Díaz

Cross-correlation techniques have been used since 1974 for measuring velocity shifts and velocity dispersions from stellar and nebular spectra and, since 1979, the analysis based on the Fourier Method has been applied. However, we are currently obtaining data with spectral resolutions higher than those for which this technique was developed, hence some revis

Ansari Abdullah, Ayan Mahalanobis

The elliptic curve discrete logarithm problem is of fundamental importance in public-key cryptography. It is in use for a long time. Moreover, it is an interesting challenge in computational mathematics. Its solution is supposed to provide interesting research directions. In this paper, we explore ways to solve the elliptic curve discrete logarithm problem.

Ilya L. Shapiro

The conformal version of the antisymmetric second-order tensor field in four spacetime dimensions does not have gauge invariance extensively discussed in the literature for more than half a century. Our first observation is that, when coupled to fermions, only the conformal version provides renormalizability of the theory at the one-loop level. General consi

Peter Austin, Daniele Dell'Erba

An improved exponential time algorithm for Energy Games and Mean Payoff Games has been recently proposed in ICALP 19. The new algorithm prevents some of the repetitive operations performed by the classic value iteration algorithm of Brim et al., leading to an approach with time complexity $O(\min(mnW,mn2^{n/2}\log W))$. Unfortunately, the pseudo-code of the

T. Sahin, M. Marismak, N. Cinar, S. Bilir

We propose a line list that may be useful for the abundance analysis of G-type stars in the wavelength range 4080 -- 6780 A. It is expected that the line list will be useful for surveys/libraries with overlapping spectral regions (e.g. ELODIE/SOPHIE libraries, UVES-580 setting of Gaia-ESO), and in particular for the analysis of F- and G-type stars in general

Steven Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok

Nearly all real world tasks are inherently partially observable, necessitating the use of memory in Reinforcement Learning (RL). Most model-free approaches summarize the trajectory into a latent Markov state using memory models borrowed from Supervised Learning (SL), even though RL tends to exhibit different training and efficiency characteristics. Addressin

Anne-Sophie Bonnet-Ben Dhia, Luiz M. Faria, Carlos Pérez-Arancibia

This paper presents a novel boundary integral equation (BIE) formulation for the two-dimensional time-harmonic water-waves problem. It utilizes a complex-scaled Laplace's free-space Green's function, resulting in a BIE posed on the infinite boundaries of the domain. The perfectly matched layer (PML) coordinate stretching that is used to render propagating wa

Maria Kulikova, Gennady Kulikov

This paper addresses the problem of designing the {\it continuous-discrete} unscented Kalman filter (UKF) implementation methods. More precisely, the aim is to propose the MATLAB-based UKF algorithms for {\it accurate} and {\it robust} state estimation of stochastic dynamic systems. The accuracy of the {\it continuous-discrete} nonlinear filters heavily depe

Maria Kulikova, Gennady Kulikov

This paper explores a time-varying version of weak-form market efficiency that is a key component of the so-called Adaptive Market Hypothesis (AMH). One of the most common methodologies used for modeling and estimating a degree of market efficiency lies in an analysis of the serial autocorrelation in observed return series. Under the AMH, a time-varying mark

Jiawang Cui, Tianyou Wang, Zhizhao Che

Superhydrophobic surfaces can exhibit icephobicity in many ways due to their large contact angles and small rolling angles. The melting process of frozen droplets on superhydrophobic surfaces is still unclear, hindering the understanding of surface icephobicity. In this experimental study of the melting process of frozen sessile droplets on superhydrophobic

E. Ya. Paryev

We study the near-threshold $\Upsilon(1S)$ meson photoproduction from protons and nuclei by considering incoherent direct non-resonant (${\gamma}p \to {\Upsilon(1S)}p$, ${\gamma}n \to {\Upsilon(1S)}n$) and two-step resonant (${\gamma}p \to P^+_{bi} \to {\Upsilon(1S)}p$, ${\gamma}n \to P^0_{bi} \to {\Upsilon(1S)}n$, $i=1$, 2, 3; $P^{+,0}_{b1}=P^{+,0}_{b}(1108

Han Huang, Yan Huang, Liang Wang

Visible-Infrared person re-identification (VI-ReID) in real-world scenarios poses a significant challenge due to the high cost of cross-modality data annotation. Different sensing cameras, such as RGB/IR cameras for good/poor lighting conditions, make it costly and error-prone to identify the same person across modalities. To overcome this, we explore the us

A. Cargioli, M. Lednev, L. Lavista, A. Camposeo

Optical control is achieved on the excited state energy transfer between spatially separated donor and acceptor molecules, both coupled to the same optical mode of a cavity. The energy transfer occurs through the formed hybrid polaritons and can be switched on and off by means of ultraviolet and visible light. The control mechanism relies on a photochromic c