Tootfinder

Universal framework with exponential speedup for the quantum simulation of quantum field theories including QCD
Jad C. Halimeh, Masanori Hanada, Shunji Matsuura
https://arxiv.org/abs/2506.18966

Universal framework with exponential speedup for the quantum simulation of quantum field theories including QCD
We present a quantum simulation framework universally applicable to a wide class of quantum systems, including quantum field theories such as quantum chromodynamics (QCD). Specifically, we generalize an efficient quantum simulation protocol developed for bosonic theories in [Halimeh et al., arXiv:2411.13161] which, when applied to Yang-Mills theory, demonstrated an exponential resource advantage with respect to the truncation level of the bosonic modes, to systems with both bosons and fermions …

Multivariate Discrete Generalized Pareto Distributions: Theory, Simulation, and Applications to Dry spells
Samira Aka, Marie Kratz, Philippe Naveau
https://arxiv.org/abs/2506.19361

Multivariate Discrete Generalized Pareto Distributions: Theory, Simulation, and Applications to Dry spells
This article extends the multivariate extreme value theory (MEVT) to discrete settings, focusing on the generalized Pareto distribution (GPD) as a foundational tool. The purpose of the study is to enhance the understanding of extreme discrete count data representation, particularly for discrete exceedances over thresholds, defining and using multivariate discrete Pareto distributions (MDGPD). Through theoretical results and illustrative examples, we outline the construction and properties of MD…

Coherent and Noncoherent Detection in Dense Arrays: Can We Ignore Mutual Coupling?
Aniol Mart\'i, Luca Sanguinetti, Jaume Riba, Meritxell Lamarca
https://arxiv.org/abs/2506.19470

Coherent and Noncoherent Detection in Dense Arrays: Can We Ignore Mutual Coupling?
This paper investigates the impact of mutual coupling on MIMO systems with densely deployed antennas. Leveraging multiport communication theory, we analyze both coherent and noncoherent detection approaches in a single-user uplink scenario where the receiver ignores mutual coupling effects. Simulation results indicate that while coherent detection is generally more accurate, it is highly sensitive to mismatches in the coupling model, leading to severe performance degradation when antennas are c…

Learning Heat Transport Kernels Using a Nonlocal Heat Transport Theory-Informed Neural Network
Mufei Luo, Charles Heaton, Yizhen Wang, Daniel Plummer, Mila Fitzgerald, Francesco Miniati, Sam M. Vinko, Gianluca Gregori
https://arxiv.org/abs/2506.16619

Learning Heat Transport Kernels Using a Nonlocal Heat Transport Theory-Informed Neural Network
We present a data-driven framework for the modeling of nonlocal heat transport in plasmas using a nonlocal theory informed neural network trained on kinetic Particle-in-Cell simulations that span both local and nonlocal regimes. The model learns spatiotemporal heat flux kernels directly from simulation data, capturing dynamic transport behaviors beyond the reach of classical formulations. Unlike time-independent kernel models such as Luciani Mora Virmont and Schurtz Nicolaï Busquet models, our…

A simulation of the plasmonic absorption of the silica glasses with copper selenide nanoparticles
Valerij Gurin
https://arxiv.org/abs/2506.16373 https://…

A simulation of the plasmonic absorption of the silica glasses with copper selenide nanoparticles
The plasmonic optical absorption of the silica glasses containing copper selenide nanoparticles is simulated on the basis of Drude theory. The plasmonic resonance absorption is studied in dependence on plasmonic frequency, damping factor and the matrix dielectric function. The charge carrier concentration in the nanoparticles is evaluated through the plasmonic frequency for the spectra of closest correspondence to experimental. The plasmon resonance position and the width of maxima are varied t…

AviationLLM: An LLM-based Knowledge System for Aviation Training
Jia'ang Wan, Feng Shen, Fujuan Li, Yanjin Sun, Yan Li, Shiwen Zhang
https://arxiv.org/abs/2506.14336

AviationLLM: An LLM-based Knowledge System for Aviation Training
Aviation training is a core link in ensuring flight safety, improving industry efficiency and promoting sustainable development. It not only involves flight simulation but also requires the learning of a great deal of professional aviation theory knowledge. In the existing training system, the knowledge is mainly imparted by the the instructors. However, the number of instructors is limited and the professional answers obtained from the Internet are not accurate enough, resulting in low trainin…

A Random Matrix Theory of Pauli Tomography
Nathan Keenan, John Goold, Alex Nico-Katz
https://arxiv.org/abs/2506.12010 https://arxiv.o…

A Random Matrix Theory of Pauli Tomography
Quantum state tomography (QST), the process of reconstructing some unknown quantum state $\hatρ$ from repeated measurements on copies of said state, is a foundationally important task in the context of quantum computation and simulation. For this reason, a detailed characterization of the error $Δ\hatρ= \hatρ-\hatρ^\prime$ in a QST reconstruction $\hatρ^\prime$ is of clear importance to quantum theory and experiment. In this work, we develop a fully random matrix theory (RMT) treatment of…

Plasma refilling of the lunar wake: plasma-vacuum interactions, electrostatic shocks, and electromagnetic instabilities
Xin An, Vassilis Angelopoulos, Terry Z Liu, Anton Artemyev, Andrew R. Poppe, Donglai Ma
https://arxiv.org/abs/2505.12497

Plasma refilling of the lunar wake: plasma-vacuum interactions, electrostatic shocks, and electromagnetic instabilities
A plasma void forms downstream of the Moon when the solar wind impacts the lunar surface. This void gradually refills as the solar wind passes by, forming the lunar wake. We investigate this refilling process using a fully kinetic particle-in-cell (PIC) simulation. The early stage of refilling follows plasma-vacuum interaction theory, characterized by exponential decay of plasma density into the wake, along with ion acceleration and cooling in the expansion direction. Our PIC simulation confirm…

Nanodroplets Condensation on Solid Surfaces
Matteo Teodori, Dario Abbondanza, Mirko Gallo, Carlo Massimo Casciola
https://arxiv.org/abs/2506.12565 https://…

Nanodroplets Condensation on Solid Surfaces
This paper deals with the condensation of liquid droplets on hydrophobic and hydrophilic surfaces. A stochastic mesoscale model based on the theory of fluctuating hydrodynamics and the thermodynamics of a diffuse interface approach shows how direct simulation of the vapour-liquid transition from the nucleation process to droplet hydrodynamics can be achieved. Such simulations explain the role of wettability in filmwise and dropwise condensation regimes and the main limitations of classical nucl…

Theory and simulation of elastoinertial rectification of oscillatory flows in two-dimensional deformable rectangular channels
Uday M. Rade, Shrihari D. Pande, Ivan C. Christov
https://arxiv.org/abs/2505.22799

Theory and simulation of elastoinertial rectification of oscillatory flows in two-dimensional deformable rectangular channels
A slender two-dimensional (2D) channel bounded by a rigid bottom surface and a slender elastic layer above deforms when a fluid flows through it. Hydrodynamic forces cause deformation at the fluid-solid interface, which in turn changes the cross-sectional area of the fluidic channel. The nonlinear coupling between flow and deformation, along with the attendant asymmetry in geometry caused by flow-induced deformation, produces a streaming effect (a non-zero cycle-average despite time-periodic fo…

This https://arxiv.org/abs/2501.00286 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hep…

Monte Carlo Simulation of the $SU(2)/\mathbb{Z}_2$ Yang--Mills Theory
We carry out a hybrid Monte Carlo (HMC) simulation of the $SU(2)/\mathbb{Z}_2$ Yang--Mills theory in which the $\mathbb{Z}_N$ 2-form flat gauge field (the 't~Hooft flux) is explicitly treated as one of the dynamical variables. We observe that our HMC algorithm in the $SU(2)/\mathbb{Z}_2$ theory drastically reduces autocorrelation lengths of the topological charge and of a physical quantity which couples to slow modes in the conventional HMC simulation of the $SU(2)$ theory. Provided that suffic…

This https://arxiv.org/abs/2409.16704 has been replaced.
initial toot: https://mastoxiv.page/@a…

Challenges in the Theory and Atomistic Simulation of Metal Electrodeposition
Electrodeposition is a fundamental process in electrochemistry, and has applications in numerous industries, such as corrosion protection, decorative finishing, energy storage, catalysis, and electronics. While there is a long history of using electrodeposition, its application for controlled nanostructure growth is limited. The establishment of an atomic-scale understanding of the electrodeposition process and dynamics is crucial to enable the controlled fabrication of metal nanoparticles and …

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems
Christoph Brunken, Olivier Peltre, Heloise Chomet, Lucien Walewski, Manus McAuliffe, Valentin Heyraud, Solal Attias, Martin Maarand, Yessine Khanfir, Edan Toledo, Fabio Falcioni, Marie Bluntzer, Silvia Acosta-Guti\'errez, Jules Tilly

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems
Machine Learning Interatomic Potentials (MLIP) are a novel in silico approach for molecular property prediction, creating an alternative to disrupt the accuracy/speed trade-off of empirical force fields and density functional theory (DFT). In this white paper, we present our MLIP library which was created with two core aims: (1) provide to industry experts without machine learning background a user-friendly and computationally efficient set of tools to experiment with MLIP models, (2) provide m…

This https://arxiv.org/abs/2501.15011 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Image formation theory of optical coherence tomography with optical aberrations and its application for computational aberration correction
The computational correction of defocus and aberrations in optical coherence tomography (OCT) is a promising approach to achieve high-resolution imaging with deep imaging depth without hardware costs. However, the techniques are not well understood due to the lack of an accurate theoretical model and investigation tools. The image formation theory of optical coherence tomography (OCT) with optical aberrations is formulated. Based on the theory, a numerical simulation method is developed and com…

Non-Abelian dynamics on a cube: improving quantum compilation through qudit-based simulations
Jacky Jiang, Natalie Klco, Olivia Di Matteo
https://arxiv.org/abs/2506.10945

Non-Abelian dynamics on a cube: improving quantum compilation through qudit-based simulations
Recent developments in mapping lattice gauge theories relevant to the Standard Model onto digital quantum computers identify scalable paths with well-defined quantum compilation challenges toward the continuum. As an entry point to these challenges, we address the simulation of SU(2) lattice gauge theory. Using qudit registers to encode the digitized gauge field, we provide quantum resource estimates, in terms of elementary qudit gates, for arbitrarily high local gauge field truncations. We the…

This https://arxiv.org/abs/2501.16162 has been replaced.
initial toot: https://mastoxiv.page/@a…

Quantum Transport with Spin Orbit Coupling: New Developments in TranSIESTA
We present the implementation of spinor quantum transport within the non-equilibrium Green's function (NEGF) code TranSIESTA based on Density Functional Theory (DFT). First-principles methods play an essential role in molecular and material modelling, and the DFT+NEGF approach has become a widely-used tool for quantum transport simulation. Exisiting (open source) DFT-based quantum transport codes either model non-equilibrium/finite-bias cases in an approximate way or rely on the collinear spin …

This https://arxiv.org/abs/2505.21185 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPF_…

Constructive community race: full-density spiking neural network model drives neuromorphic computing
The local circuitry of the mammalian brain is a focus of the search for generic computational principles because it is largely conserved across species and modalities. In 2014 a model was proposed representing all neurons and synapses of the stereotypical cortical microcircuit below $1\,\text{mm}^2$ of brain surface. The model reproduces fundamental features of brain activity but its impact remained limited because of its computational demands. For theory and simulation, however, the model was …

Effects of high-frequency and balanced motions on Lagrangian pair dispersion at the ocean surface
Michael Maalouly, Apolline Dekens, Guillaume Lapeyre, Aur\'elien Luigi Serge Ponte, Stefano Berti
https://arxiv.org/abs/2506.01002

Effects of high-frequency and balanced motions on Lagrangian pair dispersion at the ocean surface
We investigate the properties of relative dispersion of Lagrangian particles in a global-ocean simulation resolving both inertia-gravity waves (IGW) and meso and submesoscale (M/SM) turbulence. More specifically, we test if the dispersion laws depend on the shape of the Eulerian kinetic energy spectrum, as predicted from quasi-geostrophic turbulence theory. To this end, we focus on two areas, in the Kuroshio Extension and in the Gulf Stream, for which the relative importance of IGW compared to …

This https://arxiv.org/abs/2404.18323 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hep…

Flow-based Nonperturbative Simulation of First-order Phase Transitions
We present a flow-based method for simulating and calculating nucleation rates of first-order phase transitions in scalar field theory on a lattice. Motivated by recent advancements in machine learning tools, particularly normalizing flows for lattice field theory, we propose the ``partitioning flow-based Markov chain Monte Carlo (PFMCMC) sampling" method to address two challenges encountered in normalizing flow applications for lattice field theory: the ``mode-collapse" and ``rare-event sampli…

Constructive community race: full-density spiking neural network model drives neuromorphic computing
Johanna Senk, Anno Kurth, Steve Furber, Tobias Gemmeke, Bruno Golosio, Arne Heittmann, James C. Knight, Eric M\"uller, Tobias Noll, Thomas Nowotny, Gorka Peraza Coppola, Luca Peres, Oliver Rhodes, Andrew Rowley, Johannes Schemmel, Tim Stadtmann, Tom Tetzlaff, Gianmarco Tiddia, Sacha J. van Albada, Jos\'e Villamar, Markus Diesmann

Constructive community race: full-density spiking neural network model drives neuromorphic computing
The local circuitry of the mammalian brain is a focus of the search for generic computational principles because it is largely conserved across species and modalities. In 2014 a model was proposed representing all neurons and synapses of the stereotypical cortical microcircuit below $1\,\text{mm}^2$ of brain surface. The model reproduces fundamental features of brain activity but its impact remained limited because of its computational demands. For theory and simulation, however, the model was …