October 2023 arXiv papers — page 117

Matijn François, Alba Grassi

It is well established that the spectral analysis of canonically quantized four-dimensional Seiberg-Witten curves can be systematically studied via the Nekrasov-Shatashvili functions. In this paper, we explore another aspect of the relation between $\mathcal{N}=2$ supersymmetric gauge theories in four dimensions and operator theory. Specifically, we study an

Mireille Boutin, Gregor Kemper

We provide a new algebraic solution procedure for the global positioning problem in $n$ dimensions using $m$ satellites. We also give a geometric characterization of the situations in which the problem does not have a unique solution. This characterization shows that such cases can happen in any dimension and with any number of satellites, leading to counter

Andrea Borio, Carlo Lovadina, Francesca Marcon, Michele Visinoni

We initiate the design and the analysis of stabilization-free Virtual Element Methods for the laplacian problem written in mixed form. A Virtual Element version of the lowest order Raviart-Thomas Finite Element is considered. To reduce the computational costs, a suitable projection on the gradients of harmonic polynomials is employed. A complete theoretical

Saleh Ashkboos, Ilia Markov, Elias Frantar, Tingxuan Zhong

Large Language Models (LLMs) from the GPT family have become extremely popular, leading to a race towards reducing their inference costs to allow for efficient local computation. Yet, the vast majority of existing work focuses on weight-only quantization, which can reduce runtime costs in the memory-bound one-token-at-a-time generative setting, but does not

Ilyoun Na, James G. McHugh, Sinéad M. Griffin, Luca Chirolli

Chiral Majorana one-dimensional modes have been proposed as they key component for topological quantum computing. In this study, we explore their potential realization as hinge modes in higher-order topological superconductors. To create such phases, we engineer a sign-changing, time-reversal symmetry-breaking mass term through an ensemble of magnetic impuri

Xuanyu Chen, Jin Zhu, Junxian Zhu, Xueqin Wang

The reconstruction of interaction networks between random events is a critical problem arising from statistical physics and politics, sociology, biology, psychology, and beyond. The Ising model lays the foundation for this reconstruction process, but finding the underlying Ising model from the least amount of observed samples in a computationally efficient m

Urs Zaberer, Sebastian Padó, Gabriella Lapesa

The identification and classification of political claims is an important step in the analysis of political newspaper reports; however, resources for this task are few and far between. This paper explores different strategies for the cross-lingual projection of political claims analysis. We conduct experiments on a German dataset, DebateNet2.0, covering the

Prosper Ngabonziza, Anand Sharma, Anna Scheid, Sethulakshmi Sajeev

For epitaxial Sr$_3$Ru$_2$O$_7$ films grown by pulsed laser deposition, we report a combined structural and magnetotransport study of thin films and Hall bar devices patterned side-by-side on the same film. Structural properties of these films are investigated using X-ray diffraction and high-resolution transmission electron microscopy, and confirm that thes

Dominik Klein, Théo Uscidda, Fabian Theis, Marco Cuturi

Single-cell genomics has significantly advanced our understanding of cellular behavior, catalyzing innovations in treatments and precision medicine. However, single-cell sequencing technologies are inherently destructive and can only measure a limited array of data modalities simultaneously. This limitation underscores the need for new methods capable of rea

Jakub Rosiński, Michał Gawełczyk, Karol Tarnowski, Paweł Karwat

Chiral coupling, which allows directional interactions between quantum dots (QDs) and photonic crystal waveguide modes, holds promise for enhancing the functionality of quantum photonic integrated circuits. Elliptical polarizations of QD transitions offer a considerable enhancement in directionality. However, in epitaxial QD fabrication, the lack of precise

Jeya Balaji Balasubramanian, Parichoy Pal Choudhury, Srijon Mukhopadhyay, Thomas Ahearn

Objective: Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, such as the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face serious limitations in portability and privacy due to their need for circulating user data in remote servers

Marco Gallo

Goal of this paper is to study the asymptotic behaviour of the solutions of the following doubly nonlocal equation $$(-\Delta)^s u + \mu u = (I_{\alpha}*F(u))f(u) \quad \hbox{on $\mathbb{R}^N$}$$ where $s \in (0,1)$, $N\geq 2$, $\alpha \in (0,N)$, $\mu>0$, $I_{\alpha}$ denotes the Riesz potential and $F(t) = \int_0^t f(\tau) d \tau$ is a general nonlinearity

Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You

Classical wisdom in machine learning holds that the generalization error can be decomposed into bias and variance, and these two terms exhibit a \emph{trade-off}. However, in this paper, we show that for an ensemble of deep learning based classification models, bias and variance are \emph{aligned} at a sample level, where squared bias is approximately \emph{

S. Wallner

While the spectrum of non-strange light mesons is well known, many predicted strange mesons have not yet been observed, and many potentially observed states require further confirmation. Using the $K^-$ component of the hadron beam at the M2 beamline at CERN, we study the strange-meson spectrum with the COMPASS experiment. The flagship channel is the $K^-\pi

S. Borrelli, T. C. H. de Raadt, P. H. A. Mutsaers, K. A. H. van Leeuwen

We present a novel method to measure the arrival time statistics of continuous electron beams with sub-ps resolution, based on the combination of an RF deflection cavity and fast single electron imaging. We observe Poissonian statistics within time bins from 100~ns to 2~ns and increasingly pronounced sub-Poissonian statistics as the time bin decreases from 2

Anton Baryshnikov, Max Ryabinin

Text-to-image synthesis has recently attracted widespread attention due to rapidly improving quality and numerous practical applications. However, the language understanding capabilities of text-to-image models are still poorly understood, which makes it difficult to reason about prompt formulations that a given model would understand well. In this work, we

D. Dosenovic, K. Sharma, S. Dechamps, J. -L. Rouviere

There has been extensive activity exploring the doping of semiconducting two-dimensional (2D) transition metal dichalcogenides in order to tune their electronic and magnetic properties. The outcome of doping depends on various factors, including the intrinsic properties of the host material, the nature of the dopants used, their spatial distribution as well

Francesco Iachello, Rodrigo G. Cortiñas, Francisco Pérez-Bernal, Lea F. Santos

We study the symmetries of the static effective Hamiltonian of a driven superconducting nonlinear oscillator, the so-called squeeze-driven Kerr Hamiltonian, and discover a remarkable quasi-spin symmetry $su(2)$ at integer values of the ratio $\eta=\Delta /K$ of the detuning parameter $\Delta $ to the Kerr coefficient $K$. We investigate the stability of this

Karan A. Shah, Matthew J. Ringuette

The unsteady lift of a high-angle-of-attack, flat-plate wing encountering finite-length obstacles is studied using towing-tank force measurements. The wing translates from rest and interacts with a rectangular channel, ceiling, or ground obstacle. Variations with angle of attack, obstacle length, mid-chord height to the obstacle, and starting distance betwee

Pirouz Nourian, Shervin Azadi, Roy Uijtendaal, Nan Bai

This chapter presents methodological reflections on the necessity and utility of artificial intelligence in generative design. Specifically, the chapter discusses how generative design processes can be augmented by AI to deliver in terms of a few outcomes of interest or performance indicators while dealing with hundreds or thousands of small decisions. The c

Nitinder Mohan, Andrew Ferguson, Hendrik Cech, Prakita Rayyan Renatin

In recent years, Low-Earth Orbit (LEO) mega-constellations have emerged as a promising network technology and have ushered in a new era for democratizing Internet access. The Starlink network from SpaceX stands out as the only consumer-facing LEO network with over 2M+ customers and more than 4000 operational satellites. In this paper, we conduct the first-of

Yiquan Wu, Siying Zhou, Yifei Liu, Weiming Lu

Legal Judgment Prediction (LJP) has become an increasingly crucial task in Legal AI, i.e., predicting the judgment of the case in terms of case fact description. Precedents are the previous legal cases with similar facts, which are the basis for the judgment of the subsequent case in national legal systems. Thus, it is worthwhile to explore the utilization o

Alexander V. Oleynichenko, Yuriy V. Lomachuk, Daniil A. Maltsev, Nikolai S. Mosyagin

A method to simulate local properties and processes in crystals with impurities via constructing cluster models within the frame of the compound-tunable embedding potential (CTEP) and highly-accurate {\it ab initio} relativistic molecular-type electronic structure calculations is developed and applied to the Ce and Th-doped yttrium orthophosphate crystals, Y

Shuo Sun, Sebastien Haneuse, Alexander W. Levis, Catherine Lee

Causal weighted quantile treatment effects (WQTE) are a useful complement to standard causal contrasts that focus on the mean when interest lies at the tails of the counterfactual distribution. To-date, however, methods for estimation and inference regarding causal WQTEs have assumed complete data on all relevant factors. In most practical settings, however,

Saumajit Saha, Albert Nanda

Bangla is the 7th most widely spoken language globally, with a staggering 234 million native speakers primarily hailing from India and Bangladesh. This morphologically rich language boasts a rich literary tradition, encompassing diverse dialects and language-specific challenges. Despite its linguistic richness and history, Bangla remains categorized as a low

Cecilia Delgado Solorzano, Carlos Toxtli Hernandez

Large Language Models (LLMs), like ChatGPT, are fundamentally tools trained on vast data, reflecting diverse societal impressions. This paper aims to investigate LLMs' self-perceived bias concerning indigeneity when simulating scenarios of indigenous people performing various roles. Through generating and analyzing multiple scenarios, this work offers a uniq

Pauline Mouches, Thibaut Dejean, Julien Jung, Romain Bouet

Magnetoencephalography (MEG) recordings of patients with epilepsy exhibit spikes, a typical biomarker of the pathology. Detecting those spikes allows accurate localization of brain regions triggering seizures. Spike detection is often performed manually. However, it is a burdensome and error prone task due to the complexity of MEG data. To address this probl

Li Feng, Ryan Yen, Yuzhe You, Mingming Fan

Natural language (NL) programming has become more approachable due to the powerful code-generation capability of large language models (LLMs). This shift to using NL to program enhances collaborative programming by reducing communication barriers and context-switching among programmers from varying backgrounds. However, programmers may face challenges during

Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi

Click-through rate (CTR) prediction has become increasingly indispensable for various Internet applications. Traditional CTR models convert the multi-field categorical data into ID features via one-hot encoding, and extract the collaborative signals among features. Such a paradigm suffers from the problem of semantic information loss. Another line of researc

Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun

Recently, there has been an emergence of employing LLM-powered agents as believable human proxies, based on their remarkable decision-making capability. However, existing studies mainly focus on simulating human dialogue. Human non-verbal behaviors, such as item clicking in recommender systems, although implicitly exhibiting user preferences and could enhanc

Emirhan Gürpınar

This paper is on developing some computer-assisted proof methods involving non-classical inequalities for Shannon entropy. Two areas of the applications of information inequalities are studied: Secret sharing schemes and hat guessing games. In the former a random secret value is transformed into shares distributed among several participants in such a way tha

Antonio Mandarino, Giovanni Scala

The theorem developed by John Bell constituted the starting point of a revolution that translated a philosophical question about the nature of reality into the broad and intense field of research of the quantum information technologies. We focus on a system of two qubits prepared in a random, mixed state, and we study the typical behavior of their nonlocalit

Michele Graffeo, Paolo Lella, Sergej Monavari, Andrea T. Ricolfi

Let $C$ be a smooth curve. In this paper we investigate the geometric properties of the double nested Hilbert scheme of points on $C$, a moduli space introduced by the third author in the context of BPS invariants of local curves and sheaf counting on Calabi-Yau 3-folds. We prove this moduli space is connected, reduced and of pure dimension; we list its comp

Aishwarya Gupta, Rahul S. Bhogale, Priyanka Thota, Prathushkumar Dathuri

Finding suitable health insurance coverage can be challenging for individuals and small enterprises in the USA. The Health Insurance Exchange Public Use Files (Exchange PUFs) dataset provided by CMS offers valuable information on health and dental policies [1]. In this paper, we leverage machine learning algorithms to predict if a health insurance plan cover

Tom Theuns, TK Chan

We present an analytical model for cosmological Lyman-limit systems (LLSs) that successfully reproduces the observed evolution of the mean free path (L) of ionizing photons. The evolution of the co-moving mean free path is predominantly a consequence of the changing meta galactic photo-ionization rate and the increase with cosmic time of the minimum mass bel

Joshua E. Ducey, Lauren Engelthaler, Jacob Gathje, Brant Jones

For integers $0 \leq \ell \leq k_{r} \leq k_{c} \leq n$, we give a description for the Smith group of the incidence matrix with rows (columns) indexed by the size $k_r$ ($k_c$, respectively) subsets of an $n$-element set, where incidence means intersection in a set of size $\ell$. This generalizes work of Wilson and Bier from the 1990s which dealt only with

N. C. Martinez, S. Paron

The star forming processes strongly influence the ISM chemistry. Nowadays, there are available many high-quality databases at millimeter wavelengths. Using them, it is possible to carry out studies that review and deepen previous results. If these studies involve large samples of sources, it is preferred to use direct tools to study the molecular gas. With t

Jixiang Fu, Xin Xu, Dekai Zhang

We prove the long time existence and uniqueness of solution to a parabolic quaternionic Monge-Amp\`{e}re type equation on a compact hyperK\"{a}hler manifold. We also show that after normalization, the solution converges smoothly to the unique solution of the Monge-Amp\`{e}re equation for $(n-1)$-quaternionic psh functions.

Tom Nonnenmacher, Jenny Nelson, Benedict Winchester

The rising energy prices in Europe and the urgent need to address global warming have sparked a significant increase in the installation of domestic photovoltaic systems to harness solar energy. However, since solar energy is available only during daytime hours and its availability varies daily, effectively shifting energy use becomes crucial. Whilst batteri

Cheng-Gang Qin, Jun Ke, Qin Li, Ya-Fen Chen

Lorentz symmetry (LS), one of the most fundamental physical symmetries, has been extensively studied in the context of quantum gravity and unification theories. Many of these theories predict a LS violation, which could arise from the discreteness of spacetime, or extra dimensions. Standard-model extension (SME) is an effective field theory to describe Loren

Eun Cheol Choi, Emilio Ferrara

In today's digital era, the rapid spread of misinformation poses threats to public well-being and societal trust. As online misinformation proliferates, manual verification by fact checkers becomes increasingly challenging. We introduce FACT-GPT (Fact-checking Augmentation with Claim matching Task-oriented Generative Pre-trained Transformer), a framework des

Minn Sein, Fu Shunkai

Structure learning is essential for Bayesian networks (BNs) as it uncovers causal relationships, and enables knowledge discovery, predictions, inferences, and decision-making under uncertainty. Two novel algorithms, FSBN and SSBN, based on the PC algorithm, employ local search strategy and conditional independence tests to learn the causal network structure

Xuewei Li, Yaqiao Zhu, Jie Gao, Xi Wei

Segmentation of nodules in thyroid ultrasound imaging plays a crucial role in the detection and treatment of thyroid cancer. However, owing to the diversity of scanner vendors and imaging protocols in different hospitals, the automatic segmentation model, which has already demonstrated expert-level accuracy in the field of medical image segmentation, finds i

Niels van der Weide, Nima Rasekh, Benedikt Ahrens, Paige Randall North

Category theory is a branch of mathematics that provides a formal framework for understanding the relationship between mathematical structures. To this end, a category not only incorporates the data of the desired objects, but also "morphisms", which capture how different objects interact with each other. Category theory has found many applications in mathem

Yixin Wan, George Pu, Jiao Sun, Aparna Garimella

Large Language Models (LLMs) have recently emerged as an effective tool to assist individuals in writing various types of content, including professional documents such as recommendation letters. Though bringing convenience, this application also introduces unprecedented fairness concerns. Model-generated reference letters might be directly used by users in

Joseph Balsells, Martin Bojowald

Investigation into the applicability of the equivalence principle in quantum mechanics has taken many forms, with varying conclusions. Here, a dynamical semi-classical description of a wave packet in terms of its center of mass and higher quantum fluctuations is applied to the case of a quantum particle in gravitational free fall. The analysis provides an in

Jason Hausenloy, Andrea Miotti, Claire Dennis

This paper proposes a Multinational Artificial General Intelligence Consortium (MAGIC) to mitigate existential risks from advanced artificial intelligence (AI). MAGIC would be the only institution in the world permitted to develop advanced AI, enforced through a global moratorium by its signatory members on all other advanced AI development. MAGIC would be e

Shiwani Singh

Using the porous structures made up of homogeneously arranged solid obstacles, we examine the effects of rarefaction on the hydraulic tortuosity in the slip and early transition flow regimes via extended lattice Boltzmann method. We observed that modification in either the obstacle's arrangement or the porosity led to a power-law relation between the porosit

E Landi, F Schironi

Ancient astronomers faced the problem of dealing with arcs and angles in their observations and predictions without the help of modern trigonometry. The usual method to deal with such problems was the Menelaus Theorem, explicitly discussed and extensively used by Ptolemy. It is generally assumed that Hipparchus, who in his Exegesis explicitly states that he

Richard D. Wilkinson, Christopher W. Lanyon

In the context of computer models, calibration is the process of estimating unknown simulator parameters from observational data. Calibration is variously referred to as model fitting, parameter estimation/inference, an inverse problem, and model tuning. The need for calibration occurs in most areas of science and engineering, and has been used to estimate h

Ye Zhu, Yu Wu, Duo Xu, Zhiwei Deng

In this work, we investigate the domain generalization capabilities of diffusion models in the context of synthesizing images that are distinct from the training data. Instead of fine-tuning, we tackle this challenge from a sampling-based perspective using frozen, pre-trained diffusion models. Specifically, we demonstrate that arbitrary out-of-domain (OOD) i

Randall D. Kamien, Yuriy Nastishin, Brigitte Pansu

Focal conic domains, are defects characteristic of layered liquid crystal phases. Their association can built flowers where petals are the ellipses of the Dupin cyclides involved in these defect. We report here the observation of focal conic flowers in cholesteric droplets sessile on a glass surface and surrounded by glycerol. The observation of the droplets

J. F. Wang, G. Qin

The transport of energetic charged particles through magnetized plasmas is ubiquitous in interplanetary space and astrophysics, and the important physical quantities are the along-field and cross-field spatial diffusion coefficients of energetic charged particles. In this paper, the influence of solar wind on particle transport is investigated. Using the foc

Mirko Bunse, Alejandro Moreo, Fabrizio Sebastiani, Martin Senz

Quantification, i.e., the task of training predictors of the class prevalence values in sets of unlabeled data items, has received increased attention in recent years. However, most quantification research has concentrated on developing algorithms for binary and multiclass problems in which the classes are not ordered. Here, we study the ordinal case, i.e.,

Rainer Löwen

We describe the development of the mathematics of Helmut R. Salzmann (3. 11. 1930 -- 8. 3. 2022) and the main difficulties he was facing, documenting his lifelong productivity and his far reaching influence. We include a comprehensive bibliography of his work.

Peter M. Higgins

We devise a scheme for producing, in the least possible time, $n$ identical objects with $p$ agents that work at differing speeds. This involves halting the process in order to transfer production across agent types. For the case of two types of agent, we construct a scheme based on the Euclidean algorithm that seeks to minimise the number of pauses in produ

Michael D. Brown, Bastian S. Generowicz, Stephanie Dijkhuizen, Sebastiaan K. E. Koekkoek

Four-dimensional ultrasound imaging of complex biological systems such as the brain is technically challenging because of the spatiotemporal sampling requirements. We present computational ultrasound imaging (cUSi), a new imaging method that uses complex ultrasound fields that can be generated with simple hardware and a physical wave prediction model to alle

Jens Niklas Eberhardt, Catharina Stroppel

In this first of a series of articles on standard extension algebras we study standard perverse sheaves on varieties with $\mathbb{G}_m$-actions. Based on Braden's hyperbolic localisation, we describe their extension algebra geometrically via a convolution structure on the intersections of attracting with repelling cells. We introduce a multiplicative struct

Kevin Weinberger, Simon Tewes, Aydin Sezgin

The integration of Reconfigurable Intelligent Surfaces (RIS) holds substantial promise for revolutionizing 6G wireless networks, offering unprecedented capabilities for real-time control over communication environments. However, determining optimal RIS configurations remains a pivotal challenge, necessitating the development of accurate analytical models. Wh

Katsuhiko Kuribayashi

The F\'elix-Tanr\'e rational model for the polyhedral product of a fibre inclusion is considered. In particular, we investigate the rational model for the polyhedral product of a pair of Lie groups corresponding to arbitrary simplicial complex and the rational homotopy group of the polyhedral product. Furthermore, it is proved that for a partial quotient $N$

Martin Averseng, Xavier Claeys, Ralf Hiptmair

We present a preconditioning method for the linear systems arising from the boundary element discretization of the Laplace hypersingular equation on a $2$-dimensional triangulated surface $\Gamma$ in $\mathbb{R}^3$. We allow $\Gamma$ to belong to a large class of geometries that we call polygonal multiscreens, which can be non-manifold. After introducing a n

Zhicheng Guo, Cheng Ding, Duc H. Do, Amit Shah

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. It is associated with an increased risk of stroke, heart failure, and other cardiovascular complications, but can be clinically silent. Passive AF monitoring with wearables may help reduce adverse clinical outcomes related to AF. Detecting AF in noisy wearable data poses a significant ch

Yang Liu, Deyu Bo, Chuan Shi

The increasing amount of graph data places requirements on the efficient training of graph neural networks (GNNs). The emerging graph distillation (GD) tackles this challenge by distilling a small synthetic graph to replace the real large graph, ensuring GNNs trained on real and synthetic graphs exhibit comparable performance. However, existing methods rely

Prathamesh Sathe, Alexander Schmitz, Satoshi Funabashi, Tito Pradhono Tomo

Skill transfer from humans to robots is challenging. Presently, many researchers focus on capturing only position or joint angle data from humans to teach the robots. Even though this approach has yielded impressive results for grasping applications, reconstructing motion for object handling or fine manipulation from a human hand to a robot hand has been spa

Emma Tolley, Simon Frasch, Etienne Orliac, Shreyam Krishna

The Bluebild algorithm is a new technique for image synthesis in radio astronomy which decomposes the sky into distinct energy levels using functional principal component analysis. These levels can be linearly combined to construct a least-squares estimate of the radio sky, i.e. minimizing the residuals between measured and predicted visibilities. This appro

Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov

This paper presents PaLI-3, a smaller, faster, and stronger vision language model (VLM) that compares favorably to similar models that are 10x larger. As part of arriving at this strong performance, we compare Vision Transformer (ViT) models pretrained using classification objectives to contrastively (SigLIP) pretrained ones. We find that, while slightly und

Zongxia Liang, Xiaodong Luo, Fengyi Yuan

We study a time-inconsistent singular control problem originating from irreversible reinsurance decisions with non-exponential discount. A novel definition of equilibrium for time-inconsistent singular control problems is introduced. For the problem with non-exponential discount, both sufficient and necessary conditions are derived, providing a thorough math

Nobuyuki Okuma

A general free bosonic system with a pairing term is described by a bosonic Bogoliubov-de Gennes (BdG) Hamiltonian. The representation is given by a pseudo-Hermitian matrix, which is crucially different from the Hermitian representation of a fermionic BdG Hamiltonian. In fermionic BdG systems, a topological invariant of the whole particle (hole) bands can be

Holger Heidrich, Jannik Irmai, Bjoern Andres

We introduce a lower bounding technique for the min max correlation clustering problem and, based on this technique, a combinatorial 4-approximation algorithm for complete graphs. This improves upon the previous best known approximation guarantees of 5, using a linear program formulation (Kalhan et al., 2019), and 40, for a combinatorial algorithm (Davies et

Vivek K. Adajania, Siqi Zhou, Arun Kumar Singh, Angela P. Schoellig

Quadrotor motion planning in complex environments leverage the concept of safe flight corridor (SFC) to facilitate static obstacle avoidance. Typically, SFCs are constructed through convex decomposition of the environment's free space into cuboids, convex polyhedra, or spheres. However, when dealing with a quadrotor swarm, such SFCs can be overly conservativ

Julien Demange-Chryst, François Bachoc, Jérôme Morio, Timothé Krauth

Probability density function estimation with weighted samples is the main foundation of all adaptive importance sampling algorithms. Classically, a target distribution is approximated either by a non-parametric model or within a parametric family. However, these models suffer from the curse of dimensionality or from their lack of flexibility. In this contrib

Andres Gomez Ramirez, Loui Al Sardy, Francis Gomez Ramirez

Blockchain security is becoming increasingly relevant in today's cyberspace as it extends its influence in many industries. This paper focuses on protecting the lowest level layer in the blockchain, particularly the P2P network that allows the nodes to communicate and share information. The P2P network layer may be vulnerable to several families of attacks,

Mohammad Khairul Bashar, Zongli Lin, Nikhil Shukla

The rich non-linear dynamics of the coupled oscillators (under second harmonic injection) can be leveraged to solve computationally hard problems in combinatorial optimization such as finding the ground state of the Ising Hamiltonian. While prior work on the stability of the so-called Oscillator Ising Machines (OIMs) has used the linearization method, in thi

Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji

Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have attracted increasing concerns. Existing graph condensation methods primarily focus on optimizing the feature matrices of condensed graphs while overlooking the impact of the structure information from the original graphs. To investig

Lars Pause, Lukas Sturm, Marcel Mittenbühler, Stephan Amann

We report on the realization of a large-scale quantum-processing architecture surpassing the tier of 1000 atomic qubits. By tiling multiple microlens-generated tweezer arrays, each operated by an independent laser source, we can eliminate laser-power limitations in the number of allocatable qubits. Already with two separate arrays, we implement combined 2D c

Hemian Yi, Lun-Hui Hu, Yi-Fan Zhao, Ling-Jie Zhou

Over the last decade, the possibility of realizing topological superconductivity (TSC) has generated much excitement, mainly due to the potential use of its excitations (Majorana zero modes) in a fault-tolerant topological quantum computer 1,2. TSC can be created in electronic systems where the topological and superconducting orders coexist3, motivating the

Ryan Requist

Perturbation theory with respect to the kinetic energy of the heavy component of a two-component quantum system is introduced. An effective Hamiltonian that is accurate to second order in the inverse heavy mass is derived. It contains a new form of kinetic energy operator with a Hermitian mass tensor and a complex-valued vector potential. All of the potentia

Lorenzo Graziotto, Francesco Macheda, Thibault Sohier, Matteo Calandra

We theoretically investigate the double-resonance Raman spectrum of monolayer graphene down to infrared laser excitation energies. By using first-principles density functional theory calculations, we improve upon previous theoretical predictions based on conical models or tight-binding approximations, and rigorously justify the evaluation of the electron-pho

Matthew Teasdale, Dimitris Stamatellos

Most stars are in multiple systems, with the majority of those being binaries. A large number of planets have been confirmed in binary stars and therefore it is important to understand their formation and dynamical evolution. We perform simulations to investigate the migration of wide-orbit giant planets (semi-major axis 100 AU) in massive circumbinary discs

Valerie Domcke, Yohei Ema, Stefan Sandner

Axion inflation, i.e. an axion-like inflaton coupled to an Abelian gauge field through a Chern-Simons interaction, comes with a rich and testable phenomenology. This is particularly true in the strong backreaction regime, where the gauge field production heavily impacts the axion dynamics. Lattice simulations have recently demonstrated the importance of acco

Qing Yin, Jong-Hyeon Jeong, Xu Qin, Shyamal D Peddada

Often linear regression is used to perform mediation analysis. However, in many instances, the underlying relationships may not be linear, as in the case of placental-fetal hormones and fetal development. Although, the exact functional form of the relationship may be unknown, one may hypothesize the general shape of the relationship. For these reasons, we de

Erkko Lehtonen, Tamás Waldhauser

We characterise the bracketing identities satisfied by linear quasigroups with the help of certain equivalence relations on binary trees that are based on the left and right depths of the leaves modulo some integers. The numbers of equivalence classes of $n$-leaf binary trees are variants of the Catalan numbers, and they form the associative spectrum (a kind

Mingjia Shi, Yuhao Zhou, Kai Wang, Huaizheng Zhang

Classical federated learning (FL) enables training machine learning models without sharing data for privacy preservation, but heterogeneous data characteristic degrades the performance of the localized model. Personalized FL (PFL) addresses this by synthesizing personalized models from a global model via training on local data. Such a global model may overlo

Ángela Capel, Massimo Moscolari, Stefan Teufel, Tom Wessel

We show that whenever the Gibbs state of a quantum spin system satisfies decay of correlations, then it is stable, in the sense that local perturbations affect the Gibbs state only locally, and it satisfies local indistinguishability, i.e. it exhibits local insensitivity to system size. These implications hold in any dimension, require only locality of the H

Jim Gatheral, Radoš Radoičić

Previously, in [GR19], we derived a rational approximation of the solution of the rough Heston fractional ODE in the special case \lambda = 0, which corresponds to a pure power-law kernel. In this paper we extend this solution to the general case of the Mittag-Leffler kernel with \lambda \geq 0. We provide numerical evidence of the convergence of the solutio

Andrea Borio, Martina Busetto, Francesca Marcon

We numerically investigate the possibility of defining stabilization-free Virtual Element (VEM) discretizations of advection-diffusion problems in the advection-dominated regime. To this end, we consider a SUPG stabilized formulation of the scheme. Numerical tests comparing the proposed method with standard VEM show that the lack of an additional arbitrary s

Alemayehu Adugna Arara, Kristian Debrabant, Anne Kværnø

In this paper a set of previous general results for the development of B--series for a broad class of stochastic differential equations has been collected. The applicability of these results is demonstrated by the derivation of B--series for non-autonomous semi-linear SDEs and exponential Runge-Kutta methods applied to this class of SDEs, which is a signific

Giampiero Bardella, Simone Franchini, Liming Pan, Riccardo Balzan

Brain-computer interfaces surged extraordinary developments in recent years, and a significant discrepancy now exists between the abundance of available data and the limited headway made in achieving a unified theoretical framework. This discrepancy becomes particularly pronounced when examining the collective neural activity at the micro- and meso-scale, wh

Mahbubul Islam, Hossain Md. Mubashshir Jamil, Samiul Ahsan Pranto, Rupak Kumar Das

The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the suitable device for the suitable usage. So far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying stren

Alessandro Tontini, Sonia Mazzucchi, Roberto Passerone, Nicolò Broseghini

We present a new method to acquire the 3D information from a SPAD-based direct-Time-of-Flight (d-ToF) imaging system which does not require the construction of a histogram of timestamps and can withstand high flux operation regime. The proposed acquisition scheme emulates the behavior of a SPAD detector with no distortion due to dead time, and extracts the T

Kingsley J. A. Cox, Paul R. Adams

Culture involves the origination and transmission of ideas, but the conditions in which culture can emerge and evolve are unclear. We constructed and studied a highly simplified neural-network model of these processes. In this model ideas originate by individual learning from the environment and are transmitted by communication between individuals. Individua

Yun-Tong Yang, Fu-Zhou Chen, Chen Cheng, Hong-Gang Luo

The frustrated spin-$1/2$ $J_1-J_2$ Heisenberg model on the square lattice has been extensively studied since 1988 because of its close relationship to the high-temperature superconductivity in cuprates and more importantly involved novel phase of matter in its own right, namely, quantum spin liquid (QSL), one of hot topics in condensed matter physics in rec

Fabio Maccheroni, Massimo Marinacci, Ruodu Wang, Qinyu Wu

We provide a new foundation of risk aversion by showing that this attitude is fully captured by the propensity to seize insurance opportunities. Our foundation, which applies to all probabilistically sophisticated preferences, well accords with the commonly held prudential interpretation of risk aversion that dates back to the seminal works of Arrow (1963) a

Pablo Díez-Valle, Diego Porras, Juan José García-Ripoll

The Quantum Approximate Optimization Algorithm (QAOA) is an algorithm originally proposed to find approximate solutions to Combinatorial Optimization problems on quantum computers. However, the algorithm has also attracted interest for sampling purposes since it was theoretically demonstrated under reasonable complexity assumptions that one layer of the algo

Israel Luis, Maarten Afschrift, Friedl De Groote, Elena M. Gutierrez-Farewik

Prior studies have produced models to predict metabolic rates based on experimental observations of isolated muscle contraction from various species. Such models can provide reliable predictions of metabolic rates in humans if muscle properties and control are accurately modeled. This study aimed to examine how muscle-tendon model calibration and metabolic e

Sebastian Dill, Maurice Rohr

In this proof of concept, we use Computer Vision (CV) methods to extract pose information out of exercise videos. We then employ a modified version of Dynamic Time Warping (DTW) to calculate the deviation from a gold standard execution of the exercise. Specifically, we calculate the distance between each body part individually to get a more precise measure f

Irene Ayuso Ventura, Quentin Berger

We consider the Ising model on a supercritical Galton-Watson tree $\mathbf{T}_n$ of depth $n$ with a sparse random external field, given by a collection of i.i.d. Bernouilli random variables with vanishing parameter $p_n$. This may me viewed as a toy model for the Ising model on a configuration model with a few interfering external vertices carrying a plus s

Fanqi Wan, Xinting Huang, Tao Yang, Xiaojun Quan

Instruction-tuning can be substantially optimized through enhanced diversity, resulting in models capable of handling a broader spectrum of tasks. However, existing data employed for such tuning often exhibit an inadequate coverage of individual domains, limiting the scope for nuanced comprehension and interactions within these areas. To address this deficie

Florian Führer, Andrea Gruber, Holger Diedam, Andreas H. Göller

An important aspect in the development of small molecules as drugs or agro-chemicals is their systemic availability after intravenous and oral administration. The prediction of the systemic availability from the chemical structure of a potential candidate is highly desirable, as it allows to focus the drug or agrochemical development on compounds with a favo

Seth P. Benson, Iain J. Cruickshank

Media bias has been extensively studied by both social and computational sciences. However, current work still has a large reliance on human input and subjective assessment to label biases. This is especially true for cable news research. To address these issues, we develop an unsupervised machine learning method to characterize the bias of cable news progra