August 2024 arXiv papers — page 7

Jared DeLeo

A shared neighborhood structure (SNS) in a graph is a subgraph induced by the intersection of the open neighbor sets of two adjacent vertices. If a SNS is the same for all adjacent vertices in an edge-regular graph, call the SNS a uniform shared neighborhood structure (USNS). USNS-forbidden graphs (graphs which cannot be a USNS of an edge-regular graph) and

Charles Pillet, Ilshat Sagitov, Grégoire Domer, Pascal Giard

The recently proposed Successive-Cancellation List Flip (SCLF) decoding algorithm for polar codes improves the error-correcting performance of state-of-the-art SC List (SCL) decoding. However, it comes at the cost of a higher complexity. In this paper, we propose the Partitioned SCLF decoding algorithm, an algorithm that divides a word in partitions and appl

Nuno Sousa e Silva

This article provides a critical overview of the recently approved Artificial Intelligence Act. It starts by presenting the main structure, objectives, and approach of Regulation (EU) 2024/1689. A definition of key concepts follows, and then the material and territorial scope, as well as the timing of application, are analyzed. Although the Regulation does n

Xiaoyu Lin, Xinkai Yu, Ankit Aich, Salvatore Giorgi

Large Language Models (LLMs), which simulate human users, are frequently employed to evaluate chatbots in applications such as tutoring and customer service. Effective evaluation necessitates a high degree of human-like diversity within these simulations. In this paper, we demonstrate that conversations generated by GPT-4o mini, when used as simulated human

Yaxin Mo, Luca Magri

Data from fluid flow measurements are typically sparse, noisy, and heterogeneous, often from mixed pressure and velocity measurements, resulting in incomplete datasets. In this paper, we develop a physics-constrained convolutional neural network, which is a deterministic tool, to reconstruct the full flow field from incomplete data. We explore three loss fun

Andrei G. Lebed

Some time ago, Kobayashi et al. experimentally studied the so-called Lee-Naughton-Lebed's (LNL) angular effect in strong electric fields [K. Kobayashi, M. Saito, E. Omichi, and T. Osada, Phys. Rev. Lett. \textbf{96}, 126601 (2006)]. They found that strong electric fields split the LNL conductivity maxima in $α$-(ET)$_2$-based organic conductor and hypoth

Sachithra Atapattu, Oscar De Silva, Thumeera R Wanasinghe, George K I Mann

This study presents a machine learning-aided approach to accurately estimate the region of attraction (ROA) of a multi-rotor unmanned aerial vehicle (UAV) controlled using a linear quadratic regulator (LQR) controller. Conventional ROA estimation approaches rely on a nominal dynamic model for ROA calculation, leading to inaccurate estimation due to unknown d

Srija Mukhopadhyay, Abhishek Rajgaria, Prerana Khatiwada, Vivek Gupta

Vision-language models (VLMs) excel at tasks requiring joint understanding of visual and linguistic information. A particularly promising yet under-explored application for these models lies in answering questions based on various kinds of maps. This study investigates the efficacy of VLMs in answering questions based on choropleth maps, which are widely use

Robert Brandenberger, Julia Pasiecznik

We suggest a dynamical mechanism which explains why in the supersymmetric IKKT matrix model the $SO(9)$ symmetry of the Lagrangian is spontaneously broken to $SO(3) \times SO(6)$, allowing only three large classical spatial dimensions to emerge. The argument relies on the identification of D1-strings as stable excitations of the matrices about the cosmologic

Yuanze Ding, Javier A. García, Timothy R. Kallman, Claudio Mendoza

Luminous accretion disks around black holes are expected to have densities of $\sim 10^{15-22}\,$cm$^{-3}$, which are high enough such that plasma physics effects become important. Many of these effects have been traditionally neglected in the calculation of atomic parameters, and therefore from photoionization models, and ultimately also from X-ray reflecti

Will Orr, Kate Crawford

The increasing demand for high-quality datasets in machine learning has raised concerns about the ethical and responsible creation of these datasets. Dataset creators play a crucial role in developing responsible practices, yet their perspectives and expertise have not yet been highlighted in the current literature. In this paper, we bridge this gap by prese

Soumyadeep Halder, Hari Sadhan Ghosh, Arpana Saboo, Andy M. Martin

The formation of quantized vortices in a superfluid above a certain critical trap rotation frequency serves as a hallmark signature of superfluidity. Based on the beyond mean field framework, crucial for the formation of exotic supersolid and droplet states, we investigate dynamic protocols for vortex nucleation in the superfluid and supersolid states of a d

K. L. Chubb, D. Samra, Ch. Helling, L. Carone

We simulate the geometric albedo spectra of hot Jupiter exoplanets HD 209458 b and WASP-43 b, based on global climate model (GCMs) post-processed with kinetic cloud models. We predict WASP-43 b to be cloudy throughout its dayside, while HD 209458 b has a clear upper atmosphere around the hot sub-solar point, largely due to the inclusion of strong optical abs

Mahsa Amiri, Zahra Zanjani Foumani, Penghui Cao, Lorenzo Valdevit

Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving resources. Here, we propose a methodology embracing the synergy between high-throughput (HT) experimentation and hierarchical machine learning (ML) to unveil the complex relationship

Harsha Gurram, Jason R. Shuster, Li-Jen Chen, Hiroshi Hasegawa

The magnetic cloud (MC) of the Coronal Mass Ejection on April 24, 2023, contains sub-Alfvénic solar wind, transforming Earth's magnetosphere from conventional bow-shock magnetotail configuration to Alfvén wings. Utilizing measurements from the Magnetosphere Multiscale (MMS) mission, we present for the first time electron distribution signatures as the sp

Sibo Cheng, Jinyang Min, Che Liu, Rossella Arcucci

Data assimilation techniques are often confronted with challenges handling complex high dimensional physical systems, because high precision simulation in complex high dimensional physical systems is computationally expensive and the exact observation functions that can be applied in these systems are difficult to obtain. It prompts growing interest in integ

Ya-Ting Yang, Haozhe Lei, Quanyan Zhu

Leveraging recent advances in wireless communication, IoT, and AI, intelligent transportation systems (ITS) played an important role in reducing traffic congestion and enhancing user experience. Within ITS, navigational recommendation systems (NRS) are essential for helping users simplify route choices in urban environments. However, NRS are vulnerable to in

Oscar Lopez-Pamies, John E. Dolbow, Gilles A. Francfort, Christopher J. Larsen

Notwithstanding the evidence against them, classical variational phase-field models continue to be used and pursued in an attempt to describe fracture nucleation in elastic brittle materials. In this context, the main objective of this paper is to provide a comprehensive review of the existing evidence against such a class of models as descriptors of fractur

Zhiying Yu, Shalev Ben-David

We study the quantum query algorithms for simplex finding, a generalization of triangle finding to hypergraphs. This problem satisfies a rank-reduction property: a quantum query algorithm for finding simplices in rank-$r$ hypergraphs can be turned into a faster algorithm for finding simplices in rank-$(r-1)$ hypergraphs. We then show that every nested Johnso

Spencer Whitehead, Jacob Phillips, Sean Hendryx

Multimodal language models can exhibit hallucinations in their outputs, which limits their reliability. The ability to automatically detect these errors is important for mitigating them, but has been less explored and existing efforts do not localize hallucinations, instead framing this as a classification task. In this work, we first pose multimodal halluci

Sibo Cheng, Hector Chassagnon, Matthew Kasoar, Yike Guo

Global wildfire models play a crucial role in anticipating and responding to changing wildfire regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire emissions and area burnt on a global scale. However, because of the high data dimensionality and system complexity, JULES-INFERNO's computational costs make it challenging to apply

Ya-Ting Yang, Haozhe Lei, Quanyan Zhu

In urban transportation environments, drivers often encounter various path (route) options when navigating to their destinations. This emphasizes the importance of navigational recommendation systems (NRS), which simplify decision-making and reduce travel time for users while alleviating potential congestion for broader societal benefits. However, recommendi

Agelos Georgakopoulos, John Haslegrave, Joel Larsson Danielsson

We study a higher-dimensional analogue of the {Random Travelling Salesman Problem}: let the complete $d$-dimensional simplicial complex $K_n^{d}$ on $n$ vertices be equipped with i.i.d.\ volumes on its facets, uniformly random in $[0,1]$. What is the minimum volume $M_{n,d}$ of a sub-complex homeomorphic to the $d$-dimensional sphere $\mathbb{S}^d$, containi

A. Kalani, Alireza Amani, M. A. Ramzanpour

We explore the gapped graphene structure in the two-dimensional plane in the presence of the Rosen-Morse potential and an external uniform magnetic field. In order to describe the corresponding structure, we consider the propagation of electrons in graphene as relativistic fermion quasi-particles, and analyze it by the wave functions of two-component spinors

Jaewon Min

By inventing the notion of honeycombs, A. Knutson and T. Tao proved the saturation conjecture for Littlewood-Richardson coefficients. The Newell-Littlewood numbers are a generalization of the Littlewood-Richardson coefficients. By introducing honeycombs on a Möbius strip, we prove the saturation conjecture for Newell-Littlewood numbers posed by S. Gao, G. Or

Sheng Cheng, Zbigniew A. Starosolski, Devika Subramanian

Recent advancements in deep learning for Medical Artificial Intelligence have demonstrated that models can match the diagnostic performance of clinical experts in adult chest X-ray (CXR) interpretation. However, their application in the pediatric context remains limited due to the scarcity of large annotated pediatric image datasets. Additionally, significan

Petrus H. R. dos Anjos, Fernando A. Oliveira, David L. Azevedo

We propose two new kinds of infinite resistor networks based on the Fibonacci sequence: a serial association of resistor sets connected in parallel (type 1) or a parallel association of resistor sets connected in series (type 2). We show that the sequence of the network's equivalent resistance converges uniformly in the parameter $α=\frac{r_2}{r_1} \in [

Sounak Bhowmik, Himanshu Thapliyal

The rapid increase in the volume of data increased the size and complexity of the deep learning models. These models are now more resource-intensive and time-consuming for training than ever. This paper presents a quantum transfer learning (QTL) based approach to significantly reduce the number of parameters of the classical models without compromising their

Hongyu Zhang, Erlend Heir, Asbjørn Nisi, Asgeir Tomasgard

Recent developments in decomposition methods for multi-stage stochastic programming with block separable recourse enable the solution to large-scale stochastic programs with multi-timescale uncertainty. Multi-timescale uncertainty is important in energy system planning problems. Therefore, the proposed algorithms were applied to energy system planning proble

Siyu Li, Guillaume Tresset, Roya Zandi

The packaging of genetic material within a protein shell, called the capsid, marks a pivotal step in the life cycle of numerous single-stranded RNA viruses. Understanding how hundreds, or even thousands, of proteins assemble around the genome to form highly symmetrical structures remains an unresolved puzzle. In this paper, we design novel subunits and devel

David P. Blecher, Li Gao, Bang Xu

In this work, we study three problems related to the $L_1$-influence on quantum Boolean cubes. In the first place, we obtain a dimension free bound for $L_1$-influence, which implies the quantum $L^1$-KKL Theorem result obtained by Rouze, Wirth and Zhang. Beyond that, we also obtain a high order quantum Talagrand inequality and quantum $L^1$-KKL theorem. Las

Lina Johnsen Kamra, Liang Fu

Superconductors can form ideal diodes carrying nondissipative supercurrents in the forward direction and dissipative currents in the backward direction. The Josephson diode has proven to be a promising design where the junction between the two superconductors comprises the weakest link and thus provides the dominant mechanism. We here propose a Josephson dio

Yifei Simon Shao, Tianyu Li, Shafagh Keyvanian, Pratik Chaudhari

Constraint-aware estimation of human intent is essential for robots to physically collaborate and interact with humans. Further, to achieve fluid collaboration in dynamic tasks intent estimation should be achieved in real-time. In this paper, we present a framework that combines online estimation and control to facilitate robots in interpreting human intenti

Tongyue Sun, Jiayi Xiao

Event Argument Extraction (EAE) is pivotal for extracting structured information from unstructured text, yet it remains challenging due to the complexity of real-world document-level EAE. We propose a novel Definition-augmented Heuristic-driven Prompting (DHP) method to enhance the performance of Large Language Models (LLMs) in document-level EAE. Our method

Andrei G. Lebed

In framework of some extension of the quasi-classical Boltzmann kinetic equation, we show that a moderately strong electric field splits the so-called Lee-Naughton-Lebed's magnetoconductivity maxima in a layered quasi-one-dimensional conductor, if we use some reasonable approximation to the equation. By means of the above mentioned approximation, we obta

Linda Hirsch, Florian Müller, Mari Kruse, Andreas Butz

Augmented Reality (AR) is evolving to become the next frontier in social media, merging physical and virtual reality into a living metaverse, a Social MediARverse. With this transition, we must understand how different contexts (public, semi-public, and private) affect user engagement with AR content. We address this gap in current research by conducting an

Lenard Neander, Cedric Hannemann, Roland R. Netz, Anil Kumar Sahoo

Interactions of polyelectrolytes (PEs) with proteins play a crucial role in numerous biological processes, such as the internalization of virus particles into host cells. Although docking, machine learning methods, and molecular dynamics (MD) simulations are utilized to estimate binding poses and binding free energies of small-molecule drugs to proteins, qua

Mazal Bethany, Emet Bethany, Brandon Wherry, Cho-Yu Chiang

Event detection and text reasoning have become critical applications across various domains. While LLMs have recently demonstrated impressive progress in reasoning abilities, they often struggle with event detection, particularly due to the absence of training methods that consider causal relationships between event triggers and types. To address this challe

Carolyn M V Pethrick, Siva Nadarajah

A fully-discrete, nonlinearly-stable flux reconstruction (FD-NSFR) scheme is developed, which ensures robustness through entropy stability in both space and time for high-order flux reconstruction schemes. We extend the entropy-stable flux reconstruction semidiscretization of Cicchino et al. [1,2,3] with the relaxation Runge Kutta method to construct the FD-

Milinda Fernando, Daniil Bochkov, James Almgren-Bell, Todd Oliver

We present a numerical method for the velocity-space, spatially homogeneous, collisional Boltzmann equation for electron transport in low-temperature plasma (LTP) conditions. Modeling LTP plasmas is useful in many applications, including advanced manufacturing, material processing, semiconductor processing, and hypersonics, to name a few. Most state-of-the-a

Pat Pataranutaporn, Chayapatr Archiwaranguprok, Phoomparin Mano, Piyaporn Bhongse-tong

This paper introduces Text2Tradition, a system designed to bridge the epistemological gap between modern language processing and traditional dance knowledge by translating user-generated prompts into Thai classical dance sequences. Our approach focuses on six traditional choreographic elements from No. 60 in Mae Bot Yai, a revered Thai dance repertoire, whic

Antonio Laverghetta, Simone Luchini, Averie Linell, Roni Reiter-Palmon

Increasingly, large language models (LLMs) are being used to automate workplace processes requiring a high degree of creativity. While much prior work has examined the creativity of LLMs, there has been little research on whether they can generate valid creativity assessments for humans despite the increasingly central role of creativity in modern economies.

Shuai Liu, Bo-Han Wu, Jeffrey Huang, Zheshen Zhang

Bound states in the continuum (BIC) holds significant promise in manipulating electromagnetic fields and reducing losses in optical structures, leading to advancements in both fundamental research and practical applications. Despite their observation in various optical systems, the behavior of BIC in whispering-gallery-modes (WGMs) optical microcavities, ess

Ahmar Khaliq, Felix Wittwer, Niklas Pyrlik, Giovanni Fevola

4H Silicon Carbide (4H-SiC) combines many attractive properties such as a high carrier mobility, a wide bandgap, and a high thermal conductivity, making it an ideal candidate for high-power electronic devices. However, a primary challenge in utilizing 4H-SiC is the presence of defects in epitaxial layers, which can significantly degrade device performance. I

Nafis Tanveer Islam, Mazal Bethany, Dylan Manuel, Murtuza Jadliwala

Software security remains a critical concern, particularly as junior developers, often lacking comprehensive knowledge of security practices, contribute to codebases. While there are tools to help developers proactively write secure code, their actual effectiveness in helping developers fix their vulnerable code remains largely unmeasured. Moreover, these ap

Adrian A. Budini, Ruynet L. de Matos Filho, Marcelo F. Santos

The distinguishability between two quantum states can be defined in terms of their trace distance. The operational meaning of this definition involves a maximization over measurement projectors. Here we introduce an alternative definition of distinguishability which, instead of projectors, is based on maximization over normalized states (density matrices). I

Thakshila Thilakanayake, Oscar De Silva, Thumeera R. Wanasinghe, George K. Mann

This paper presents a generative adversarial network (GAN) based approach for radar image enhancement. Although radar sensors remain robust for operations under adverse weather conditions, their application in autonomous vehicles (AVs) is commonly limited by the low-resolution data they produce. The primary goal of this study is to enhance the radar images t

Kartik Samanta, Ding-Fu Shao, Evgeny Y. Tsymbal

Altermagnetic (AM) materials have recently attracted significant interest due to the non-relativistic momentum-dependent spin splitting of their electronic band structure which may be useful for antiferromagnetic (AFM) spintronics. So far, however, most research studies have been focused on AM metals which can be utilized in spintronic devices, such as AFM t

Sol Alonso, Matias Vera-Rueda, Georgina Coldwell, Fernanda Duplancic

Aims: To unveil the influence of galaxy-galaxy interactions on material transport driven by galactic bars towards the central regions of active galactic nuclei (AGN) galaxies and assess the efficiency of the combined mechanisms of interactions and bars in fueling massive black holes, we examine barred active galaxies in paired systems. Methods: Our study tar

Krishnendu Basak, Chiranjib Chaudhuri, M Suraj, Moiz Ahmed

This study investigates the trophic cascades and habitat suitability in Udanti Sitnadi Tiger Reserve (USTR), highlighting the roles of apex predators, subordinate predators, and prey species in maintaining ecosystem balance. Using the Trophic Species Distribution Model (SDM), we explored prey-predator interactions and habitat suitability, revealing that tige

Paul N. Patrone, Lili Wang, Sheng Lin-Gibson, Anthony J. Kearsley

Harmonizing serology measurements is critical for identifying reference materials that permit standardization and comparison of results across different diagnostic platforms. However, the theoretical foundations of such tasks have yet to be fully explored in the context of antibody thermodynamics and uncertainty quantification (UQ). This has restricted the u

Munazza K. Alam, Emily Rickman, Kielan Hoch, Paul Mollière

We propose a comprehensive survey of giant planets ranging from close-in highly irradiated hot Jupiters to young, wide-orbit directly imaged planets. The combination of two established techniques for probing planetary atmospheric compositions (time-series transit observations and high-contrast spectroscopy) will provide an unprecedented window into gaseous p

Naina Kushwaha, Olivia Armitage, Brendan Edwards, Liam Trzaska

Chromium ditelluride, CrTe$_2$, is an attractive candidate van der Waals material for hosting 2D magnetism. However, how the room-temperature ferromagnetism of the bulk evolves as the sample is thinned to the single-layer limit has proved controversial. This, in part, reflects its metastable nature, vs. a series of more stable self-intercalation compounds wi

A. Frazzitta, M. Yadav, J. Mann, A. R. Rossi

A fundamental comparison between undulator and ion channel radiation is presented. Conventional theory for both devices fails to describe high $k$ and $K/γ$ regimes accurately, providing an underestimation of particle trajectory amplitude and period. This may lead to incorrect estimation of radiation emission in many setups of practical interest, such as the

Chiranjib Chaudhuri, Krishnendu Basak, M Suraj, Moiz Ahmed

This study uses Joint Species Distribution Models (JSDMs) and Deep Neural Networks (DNNs) to explore how wild carnivores and free-ranging dogs interact in the Udanti-Sitanadi Tiger Reserve (USTR) in Central India. The research focuses on key species like the Striped Hyena, Grey Wolf, Golden Jackal, and Indian Fox, revealing significant overlaps in habitat wi

Jianxin Sun, David Lenz, Hongfeng Yu, Tom Peterka

Functional approximation as a high-order continuous representation provides a more accurate value and gradient query compared to the traditional discrete volume representation. Volume visualization directly rendered from functional approximation generates high-quality rendering results without high-order artifacts caused by trilinear interpolations. However,

Namit Mahajan, Dayanand Mishra

The non-local effects originating from the charm quark loops at dilepton invariant masses smaller than the charmonium threshold in $B\to K \ell\ell$ are evaluated with light meson distribution amplitudes. The revised estimates with B-meson distribution amplitude within a Light Cone Sum Rule approach yielded results about three orders smaller than the origina

Hanjun Yang, Sagarmoy Mandal, Bowen Li, Tushar Kanti Ghosh

Hybrid organic-inorganic semiconductors with strong electron-phonon interactions provide a programmable platform for developing a variety of electronic, optoelectronic, and quantum materials by controlling these interactions. However, in current hybrid semiconductors, such as halide perovskites, anharmonic vibrations with rapid dephasing hinder the ability t

Farid Aliniaeifard, Stephanie van Willigenburg

We answer a question of Bergeron, Hohlweg, Rosas, and Zabrocki from 2006 to give a combinatorial description for the coproduct of the x-basis in the Hopf algebra of symmetric functions in noncommuting variables, NCSym, which arises in the theory of Grothendieck bialgebras. We achieve this using the theory of Hopf monoids and the Fock functor. We also determi

Euclid Collaboration, L. Bisigello, M. Massimo, C. Tortora

Euclid will cover over 14000 $deg^{2}$ with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution and AGN. In this work we identify the best colour selection criteria for AGN, based

Michele Fumagalli

The circumgalactic medium (CGM) is a vital element in galaxies, as it mediates the baryon cycle essential for regulating galaxy activity. It is also highly complex due to the intricate distributions of temperature, density, metallicity, and ionization that make the CGM a multiphase medium. Therefore, learning about the CGM requires combining various observat

David Wakeham, Maria Schuld

How can we take inspiration from a typical quantum algorithm to design heuristics for machine learning? A common blueprint, used from Deutsch-Josza to Shor's algorithm, is to place labeled information in superposition via an oracle, interfere in Fourier space, and measure. In this paper, we want to understand how this interference strategy can be used fo

Yuh Tsunetoe, Tomohisa Kawashima, Ken Ohsuga, Shin Mineshige

Optically thick non-thermal synchrotron sources notably produce linear polarization vectors being parallel to projected magnetic field lines on the observer's screen, although they are perpendicular in well-known optically thin cases. To elucidate the complex relationship between the vectors and fields and to investigate the energy and spatial distributi

Alejo N. Rossia, Eleni Vryonidou

CP-violation (CPV) is a rare phenomenon in the Standard Model whilst there is compelling indirect evidence for additional CPV sources in the Universe. The search for CPV effects at the LHC is thus one of the best-motivated precision tests of the Standard Model (SM) and an excellent probe of New Physics. NLO QCD corrections can affect the predictions for thos

Ben Cassese, Justin Vega, Tiger Lu, Malena Rice

While astronomers often assume that exoplanets are perfect spheres when analyzing observations, the subset of these distant worlds that are subject to strong tidal forces and/or rapid rotations are expected to be distinctly ellipsoidal or even triaxial. Since a planet's response to these forces is determined in part by its interior structure, measurement

Felix Wittwer, Peter Modregger

High-resolution x-ray microscopy requires a high photon flux to measure the signal from weakly scattering samples. This exposes samples to high radiation doses, potentially damaging or destroying them through radiation damage. In this work, we propose the use of annular optics in scanning microscopy as an alternative to full-aperture optics. Annular optics a

Daniel Carne, Joseph Peoples, Ziqi Guo, Dudong Feng

FOS, which means light in Greek, is an open-source program for Fast Optical Spectrum calculations of nanoparticle media. This program takes the material properties and a description of the system as input, and outputs the spectral response including the reflectance, absorptance, and transmittance. Previous open-source codes often include only one portion of

Antoine Neuraz, Ghislain Vaillant, Camila Arias, Olivier Birot

Phenotyping consists in applying algorithms to identify individuals associated with a specific, potentially complex, trait or condition, typically out of a collection of Electronic Health Records (EHRs). Because a lot of the clinical information of EHRs are lying in texts, phenotyping from text takes an important role in studies that rely on the secondary us

Yuhan Zheng, Jessie A Elliott, John V Reynolds, Sheraz R Markar

Esophageal cancer is a major cause of cancer-related mortality internationally, with high recurrence rates and poor survival even among patients treated with curative-intent surgery. Investigating relevant prognostic factors and predicting prognosis can enhance post-operative clinical decision-making and potentially improve patients' outcomes. In this wo

Will Cavendish, Siddhant Das, Markus Nöth, Ali Ayatollah Rafsanjani

We note that the empirical predictions of the "Quantum Clock Proposal" [L. Maccone and K. Sacha, Phys. Rev. Lett. 124, 110402 (2020)] are paradoxical when viewed as a solution to the quantum arrival-time problem.

Jiasheng Shi, Fu Lin, Weixiong Rao

Complex mechanic systems simulation is important in many real-world applications. The de-facto numeric solver using Finite Element Method (FEM) suffers from computationally intensive overhead. Though with many progress on the reduction of computational time and acceptable accuracy, the recent CNN or GNN-based simulation models still struggle to effectively r

Jihyun Mun, Sunhee Kim, Minhwa Chung

Autism Spectrum Disorder (ASD) is a lifelong condition that significantly influencing an individual's communication abilities and their social interactions. Early diagnosis and intervention are critical due to the profound impact of ASD's characteristic behaviors on foundational developmental stages. However, limitations of standardized diagnostic to

Peter Modregger, Ahmar Khaliq, Felix Wittwer

While a few methods for the determination of depth-resolved strain distributions each with inherent limitations are available, tomographic reconstruction has been applied to this problem in only a limited sense. One of the challenges was the potential impact of geometric parallax, which constitutes a non-negligible lateral offset of diffraction information a

Roberto S. Costas-Santos, Abdelhamid Rehouma

We derive a useful result about the zeros of the $k$-polar polynomials on the unit circle; in particular we obtain a ring shaped region containing all the zeros of these polynomials. Some examples are presented.

Ahmed M Salih

Data pre-processing is a significant step in machine learning to improve the performance of the model and decreases the running time. This might include dealing with missing values, outliers detection and removing, data augmentation, dimensionality reduction, data normalization and handling the impact of confounding variables. Although it is found the steps

Quentin Gueuning, Eloy de Lera Acedo, Anthony Keith Brown, Christophe Craeye

We present a numerical method for the analysis of mutual coupling effects in large, dense and irregular arrays with identical antennas. Building on the Method of Moments (MoM), our technique employs a Macro Basis Function (MBF) approach for rapid direct inversion of the MoM impedance matrix. To expedite the reduced matrix filling, we propose an extension of

Indranil Chowdhury, Espen R. Jakobsen, Miłosz Krupski

There are few results on mean field game (MFG) systems where the PDEs are either fully nonlinear or have degenerate diffusions. This paper introduces a problem that combines both difficulties. We prove existence and uniqueness for a strongly degenerate, fully nonlinear MFG system by using the well-posedness theory for fully nonlinear MFGs established in our

Grigor Kirakosyan, Davit Karamyan

Speech applications dealing with conversations require not only recognizing the spoken words but also determining who spoke when. The task of assigning words to speakers is typically addressed by merging the outputs of two separate systems, namely, an automatic speech recognition (ASR) system and a speaker diarization (SD) system. In practical settings, spea

K. Durga Prasad, Chandan Kumar, Sanjeev K. Mishra, P. Kalyana S. Reddy

Chandra Surface Thermophysical Experiment (ChaSTE) is one of the payloads flown onboard the Chandrayaan-3 lander. The objective of the experiment is in-situ investigation of thermal behaviour of outermost 100 mm layer of the lunar surface by deploying a thermal probe. The probe consists of 10 temperature sensors (Platinum RTDs) mounted at different locations

Siling Feng, Zhisheng Qi, Cong Lin

Temporal knowledge graph (TKG) reasoning predicts future events based on historical data, but it's challenging due to the complex semantic and hierarchical information involved. Existing Euclidean models excel at capturing semantics but struggle with hierarchy. Conversely, hyperbolic models manage hierarchical features well but fail to represent complex

Ghid Karam, Maïlys Chanial, Maxime Chaumont, Martin Hendel

Climate change will result in more frequent, more intense and longer-lasting heat waves by 2050. As part of its Climate Plan and its resilience strategy, the City of Paris is deploying, through its Oasis program, a network of urban cool islands to mitigate the urban heat island phenomena: schoolyards are renovated in order to reduce the heat stress of users.

Shuai Peng, Di Fu, Liangcai Gao, Xiuqin Zhong

The rapid development of large language models (LLMs) has spurred extensive research into their domain-specific capabilities, particularly mathematical reasoning. However, most open-source LLMs focus solely on mathematical reasoning, neglecting the integration with visual injection, despite the fact that many mathematical tasks rely on visual inputs such as

Asilata Bapat, Hoel Queffelec

We discuss the extension of the faithfulness question for the Burau representation of braid groups to the case of Artin--Tits groups. We prove that the Burau representation is not faithful in affine type $\tilde{A_3}$, and not faithful over several finite rings in type $D_4$, using an algorithmic approach based on categorical methods that generalize Bigelow&

Oscar Brown, Zhengjie Wang, Andrea Do, Nikhil Mathew

The acceleration of Large Language Models (LLMs) with speculative decoding provides a significant runtime improvement without any loss of accuracy. Currently, EAGLE-2 is the state-of-the-art speculative decoding method, improving on EAGLE with a dynamic draft tree. We introduce Dynamic Depth Decoding (DDD), which optimises EAGLE-2's tree drafting method

Kate Qi Zhou, Yan Qin, Chau Yuen

Data-driven methods have gained extensive attention in estimating the state of health (SOH) of lithium-ion batteries. Accurate SOH estimation requires degradation-relevant features and alignment of statistical distributions between training and testing datasets. However, current research often overlooks these needs and relies on arbitrary voltage segment sel

Haofeng Liu, Emad Alsusa, Arafat Al-Dweik

This paper investigates the bit error rate (BER) and outage probability performance of integrated sensing and communication (ISaC) in uplink non-orthogonal multiple access (NOMA) based Internet of Things (IoT) systems. Specifically, we consider an ISaC system where the radar signal is designed to be orthogonal to the communication signal over two symbol peri

Yu Jia, Zhewen Mo, Jia-Yue Zhang

The exclusive production of $J/ψ$ through Higgs boson radiative decay may serve a clean channel to extracting the charm quark Yukawa coupling. We calculate the two-loop QCD corrections to $H\rightarrow J/ψ(Υ)+γ$ using an optimized nonrelativistic QCD (NRQCD) approach. We compute the ${\cal O}(α_s^2)$ correction in the direct channel, where Higgs directly cou

Kohei Kobayashi

The measurement-based feedback (MBF) control offers several powerful means for preparing the desired target quantum state. Therefore, it is important to investigate fundamental properties of MBF. In particular, how the entropy of the controlled system under the MBF behaves is of great interest. In this study, we examine this problem by deriving a sufficient

Yuhan Liu, Jayadev Acharya

We study quantum state testing where the goal is to test whether $ρ=ρ_0\in\mathbb{C}^{d\times d}$ or $\|ρ-ρ_0\|_1>\varepsilon$, given $n$ copies of $ρ$ and a known state description $ρ_0$. In practice, not all measurements can be easily applied, even using unentangled measurements where each copy is measured separately. We develop an information-theoretic fr

Hira Waseem, Abdul Hafeez

The decays governed by the flavor-changing-neutral-current transitions (FCNC), such as $b\to s\ell^{+}\ell^{-}$, provide an important tool to test the physics in and beyond the Standard Model (SM). This work focuses on investigating the FCNC process $B_{c}\to D_{s}^{*} \left(\to D_{s}π\right)\ell^{+}\ell^{-}(\ell=e,μ,τ)$. Being an exclusive process, the init

Trevor N. Wolf, Brandon A. Jones

The resurgence of lunar operations requires advancements in cislunar navigation and Space Situational Awareness (SSA). Challenges associated to these tasks have created an interest in autonomous planning, navigation, and tracking technologies that operate with little ground-based intervention. This research introduces a trajectory planning tool for a low-thr

Shiran Aziz, Yossi Adi, Shmuel Peleg

With the popularity of cellular phones, events are often recorded by multiple devices from different locations and shared on social media. Several different recordings could be found for many events. Such recordings are usually noisy, where noise for each device is local and unrelated to others. This case of multiple microphones at unknown locations, capturi

Mohan Shi, Zengrui Jin, Yaoxun Xu, Yong Xu

Recognizing overlapping speech from multiple speakers in conversational scenarios is one of the most challenging problem for automatic speech recognition (ASR). Serialized output training (SOT) is a classic method to address multi-talker ASR, with the idea of concatenating transcriptions from multiple speakers according to the emission times of their speech

Manuel Indaco, Daniel Gass, William James Fawcett, Richard Galvez

Understanding space weather is vital for the protection of our terrestrial and space infrastructure. In order to predict space weather accurately, large amounts of data are required, particularly in the extreme ultraviolet (EUV) spectrum. An exquisite source of information for such data is provided by the Solar Dynamic Observatory (SDO), which has been gathe

Mark Benjamin, Gianluca Iaccarino

Data from direct numerical simulations of turbulent flows are commonly used to train neural network-based models as subgrid closures for large-eddy simulations; however, models with low a priori accuracy have been observed to fortuitously provide better a posteriori results than models with high a priori accuracy. This anomaly can be traced to a dataset shif

Haggai Bonneau, Yael Avni, David Andelman, Henri Orland

The response of ionic solutions to time-varying electric fields, quantified by a frequency-dependent conductivity, is essential in many electrochemical applications. Yet, it constitutes a challenging problem due to the combined effect of Coulombic interactions, hydrodynamics, and thermal fluctuations. Here, we study the frequency-dependent conductivity of io

Yiran Chen, Anyi Rao, Xuekun Jiang, Shishi Xiao

With advancements in video generative AI models (e.g., SORA), creators are increasingly using these techniques to enhance video previsualization. However, they face challenges with incomplete and mismatched AI workflows. Existing methods mainly rely on text descriptions and struggle with camera placement, a key component of previsualization. To address these

Emily Koivu, John Kushan, Makana Silva, Gabriel Vasquez

Primordial black holes (PBHs) are theorized objects that may make up some - or all - of the dark matter in the universe. At the lowest allowed masses, Hawking radiation (in the form of photons or electrons and positrons) is the primary tool to search for PBHs. This paper is part of an ongoing series in which we aim to calculate the $O(α)$ corrections to Hawk

Li Zhang, Basu Jindal, Ahmed Alaa, Robert Weinreb

Semantic segmentation of medical images is pivotal in applications like disease diagnosis and treatment planning. While deep learning has excelled in automating this task, a major hurdle is the need for numerous annotated segmentation masks, which are resource-intensive to produce due to the required expertise and time. This scenario often leads to ultra low

Sonia Sarkar, Namita Agrawal, Dasika Shishir, Kasturi Saha

Quantum sensors based on Nitrogen Vacancy (NV) centers in diamond are highly capable of sensing multiple physical quantities. In this study, we use amplitude-modulated lock-in detection of optically detected magnetic resonance of NV nanodiamonds (NVND) to investigate the link between temperature (T) and the zero-field splitting parameter (D) and also the rel