Tootfinder

Barren-plateau free variational quantum simulation of Z2 lattice gauge theories
Fariha Azad, Matteo Inajetovic, Stefan K\"uhn, Anna Pappa
https://arxiv.org/abs/2507.19203 h…

Barren-plateau free variational quantum simulation of Z2 lattice gauge theories
In this work, we design a variational quantum eigensolver (VQE) suitable for investigating ground states and static string breaking in a $\mathbb{Z}_2$ lattice gauge theory (LGT). We consider a two-leg ladder lattice coupled to Kogut-Susskind staggered fermions and verify the results of the VQE simulations using tensor network methods. We find that for varying Hamiltonian parameter regimes and in the presence of external charges, the VQE is able to arrive at the gauge-invariant ground state wit…

Beyond Demographics: Enhancing Cultural Value Survey Simulation with Multi-Stage Personality-Driven Cognitive Reasoning
Haijiang Liu, Qiyuan Li, Chao Gao, Yong Cao, Xiangyu Xu, Xun Wu, Daniel Hershcovich, Jinguang Gu
https://arxiv.org/abs/2508.17855

Beyond Demographics: Enhancing Cultural Value Survey Simulation with Multi-Stage Personality-Driven Cognitive Reasoning
Introducing MARK, the Multi-stAge Reasoning frameworK for cultural value survey response simulation, designed to enhance the accuracy, steerability, and interpretability of large language models in this task. The system is inspired by the type dynamics theory in the MBTI psychological framework for personality research. It effectively predicts and utilizes human demographic information for simulation: life-situational stress analysis, group-level personality prediction, and self-weighted cognit…

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…

Radio signatures of AGN-wind-driven shocks in elliptical galaxies: From simulations to observations
Haojie Xia, Feng Yuan, Zhiyuan Li, Bocheng Zhu
https://arxiv.org/abs/2507.19716

Radio signatures of AGN-wind-driven shocks in elliptical galaxies: From simulations to observations
We investigate the synchrotron emission signatures of shocks driven by active galactic nucleus (AGN) wind in elliptical galaxies based on our two-dimensional axisymmetric hydrodynamic $\textit{MACER}$ numerical simulations. Using these simulation data, we calculate the synchrotron radiation produced by nonthermal electrons accelerated at shocks, adopting reasonable assumptions for the magnetic field and relativistic electron distribution (derived from diffusive shock acceleration theory), and p…

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…

Structural DID with ML: Theory, Simulation, and a Roadmap for Applied Research
Yile Yu, Anzhi Xu, Yi Wang
https://arxiv.org/abs/2507.15899 https://

Structural DID with ML: Theory, Simulation, and a Roadmap for Applied Research
Causal inference in observational panel data has become a central concern in economics,policy analysis,and the broader social sciences.To address the core contradiction where traditional difference-in-differences (DID) struggles with high-dimensional confounding variables in observational panel data,while machine learning (ML) lacks causal structure interpretability,this paper proposes an innovative framework called S-DIDML that integrates structural identification with high-dimensional estimat…

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 …

Replaced article(s) found for hep-lat. https://arxiv.org/list/hep-lat/new
[1/1]:
- Efficient Truncations of SU($N_c$) Lattice Gauge Theory for Quantum Simulation
Anthony N. Ciavarella, I. M. Burbano, Christian W. Bauer

Characterizing p-Simulation Between Theories
Hunter Monroe
https://arxiv.org/abs/2507.13576 https://arxiv.org/pdf/2507.13576

Characterizing p-Simulation Between Theories
This paper characterizes when one axiomatic theory, as a proof system for tautologies, $p$-simulates another, by showing: (i)~if c.e. theory $\mathcal{S}$ efficiently interprets $\mathcal{S}{+}ϕ$, then $\mathcal{S}$ $p$-simulates $\mathcal{S}{+}ϕ$ (Jeřábek in Pudlák17 proved simulation), since the interpretation maps an $\mathcal{S}{+}ϕ$-proof whose lines are all theorems into an $\mathcal{S}$-proof; (ii)~$\mathcal{S}$ proves ``$\mathcal{S}$ efficiently interprets $\mathcal{S}{+}ϕ$'' iff…

Coupling all-electron full-potential density functional theory with grid-based continuum embeddings
Jakob Filser, Edan Bainglass, Karsten Reuter, Oliviero Andreussi
https://arxiv.org/abs/2507.17672

Coupling all-electron full-potential density functional theory with grid-based continuum embeddings
Recent advances in continuum embedding models have enabled the incorporation of solvent and electrolyte effects into density functional theory (DFT) simulations of material surfaces, significantly benefiting electrochemistry, catalysis, and other applications. To extend the simulation of diverse systems and properties, the implementation of continuum embedding models into the Environ library adopts a modular programming paradigm, offering a flexible interface for communication with various DFT …

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…

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…

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…

A Theory-driven and AI-enhanced Simulation Platform for Cultivating Nutrition Literacy
Shan Li, Guozhu Ding
https://arxiv.org/abs/2507.02138 https://

A Theory-driven and AI-enhanced Simulation Platform for Cultivating Nutrition Literacy
This study introduces and evaluates Healthy Choice, an innovative theory-driven and AI-enhanced simulation platform designed to cultivate nutrition literacy through interactive scenario-based learning experiences. We collected feedback from 114 university students with diverse backgrounds who completed simulated product selection scenarios. Quantitative ratings of usefulness and ease of use demonstrated high user satisfaction.

From Individual Learning to Market Equilibrium: Correcting Structural and Parametric Biases in RL Simulations of Economic Models
Zeqiang Zhang, Ruxin Chen
https://arxiv.org/abs/2507.18229

From Individual Learning to Market Equilibrium: Correcting Structural and Parametric Biases in RL Simulations of Economic Models
The application of Reinforcement Learning (RL) to economic modeling reveals a fundamental conflict between the assumptions of equilibrium theory and the emergent behavior of learning agents. While canonical economic models assume atomistic agents act as `takers' of aggregate market conditions, a naive single-agent RL simulation incentivizes the agent to become a `manipulator' of its environment. This paper first demonstrates this discrepancy within a search-and-matching model with concave produ…

Bridging Molecular Simulation and Process Modeling for Predictive Multicomponent Adsorption
Sunghyun Yoon, Jui Tu, Li-Chiang Lin, Yongchul G. Chung
https://arxiv.org/abs/2508.12200

Bridging Molecular Simulation and Process Modeling for Predictive Multicomponent Adsorption
Accurate and efficient prediction of multicomponent adsorption equilibria across pressures, temperatures, and compositions remain a central challenge for designing energy-efficient adsorption-based separation processes. Traditional approaches, including model fitting and ideal adsorbed solution theory (IAST), often fail to balance accuracy, computational efficiency, and transferability under process-relevant conditions. Here, we introduce a material-to-process modeling framework that integrates…

Simulating the interplay of dipolar and quadrupolar interactions in NMR by spin dynamic mean-field theory
Timo Gr\"a{\ss}er, G\"otz S. Uhrig
https://arxiv.org/abs/2507.17720

Simulating the interplay of dipolar and quadrupolar interactions in NMR by spin dynamic mean-field theory
The simulation of nuclear magnetic resonance (NMR) experiments is a notoriously difficult task, if many spins participate in the dynamics. The recently established dynamic mean-field theory for high-temperature spin systems (spinDMFT) represents an efficient yet accurate method to deal with this scenario. SpinDMFT reduces a complex lattice system to a time-dependent single-site problem, which can be solved numerically with small computational effort. Since the approach retains local quantum deg…

Observable Optimization for Precision Theory: Machine Learning Energy Correlators
Arindam Bhattacharya, Katherine Fraser, Matthew D. Schwartz
https://arxiv.org/abs/2508.10988 ht…

Observable Optimization for Precision Theory: Machine Learning Energy Correlators
The practice of collider physics typically involves the marginalization of multi-dimensional collider data to uni-dimensional observables relevant for some physics task. In any cases, such as classification or anomaly detection, the observable can be arbitrarily complicated, such as the output of a neural network. However, for precision measurements, the observable must correspond to something computable systematically beyond the level of current simulation tools. In this work, we demonstrate 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…

System Synchronization Based on Complex Frequency
Yusen Wei, Lan Tang
https://arxiv.org/abs/2508.11381 https://arxiv.org/pdf/2508.11381

System Synchronization Based on Complex Frequency
In response to the inertia decline caused by high penetration of renewable generation, traditional synchronization criteria that rely solely on frequency consistency are increasingly inadequate for characterizing the coupled behavior of frequency and voltage dynamics during power-system transients. This paper focuses on the theory of complex-frequency synchronization and develops a theory-simulation analysis framework that offers a new perspective for steady-state and transient analysis of low-…

Simulation-based validation of Bayes factor computation
Martin Modr\'ak, Sebastian Stroppel, Paul-Christian B\"urkner
https://arxiv.org/abs/2508.11814 https://

Simulation-based validation of Bayes factor computation
We propose and evaluate two methods that validate the computation of Bayes factors: one based on an improved variant of simulation-based calibration checking (SBC) and one based on calibration metrics for binary predictions. We show that in theory, binary prediction calibration is equivalent to a special case of SBC, but with finite resources, binary prediction calibration is typically more sensitive. With well-designed test quantities, SBC can however detect all possible problems in computatio…

Constraining Dynamical Dark Energy from Galaxy Clustering with Simulation-Based Priors
Shu-Fan Chen, Mikhail M. Ivanov
https://arxiv.org/abs/2507.00118 htt…

Constraining Dynamical Dark Energy from Galaxy Clustering with Simulation-Based Priors
The effective-field theory based full-shape analysis with simulation-based priors (EFT-SBP) is the novel analysis of galaxy clustering data that allows one to combine merits of perturbation theory and simulation-based modeling in a unified framework. In this paper we use EFT-SBP with the galaxy clustering power spectrum and bispectrum data from BOSS in order to test the recent preference for dynamical dark energy reported by the DESI collaboration. While dynamical dark energy is preferred by th…

Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice
Gehao Zhang, Eugene Bagdasarian, Juan Zhai, Shiqing Ma
https://arxiv.org/abs/2507.05512

Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice
Distinguishing AI-generated code from human-written code is becoming crucial for tasks such as authorship attribution, content tracking, and misuse detection. Based on this, N-gram-based watermarking schemes have emerged as prominent, which inject secret watermarks to be detected during the generation. However, their robustness in code content remains insufficiently evaluated. Most claims rely solely on defenses against simple code transformations or code optimizations as a simulation of atta…

An Adversarial Quantum Key Distribution Project
Brian R. La Cour, Noah A. Davis
https://arxiv.org/abs/2507.13389 https://arxiv.org/pdf/2507.13389

An Adversarial Quantum Key Distribution Project
Quantum key distribution (QKD) is a popular introduction to quantum technologies used in education and public outreach, as very little background in quantum theory is needed and the practical applications are easily understood. There is considerably less exposure to the many real-world considerations of practical QKD, as access to the necessary hardware is quite limited. Here we describe a simple, simulation-based QKD project that can be implemented with only a minimal background in quantum con…

Application of resource theory based on free Clifford kT computation to early fault-tolerant quantum computing
Yuya O. Nakagawa, Yasunori Lee
https://arxiv.org/abs/2508.14546 ht…

Application of resource theory based on free Clifford+kT computation to early fault-tolerant quantum computing
Recent advances in quantum hardware are bringing fault-tolerant quantum computing (FTQC) closer to reality. In the early stage of FTQC, however, the numbers of available logical qubits and high-fidelity $T$ gates remain limited, making it crucial to optimize the quantum resource usage. In this work, we aim to study the simulation cost of general quantum states under the constraint that only $k$ $T$ gates can be used, alongside an unlimited number of Clifford gates. Inspired by the notion of rob…

Thermodynamically consistent modelling and simulation of the moving contact line problem in non-isothermal compressible two-phase flows
Junkai Wang, Qiaolin He
https://arxiv.org/abs/2508.05711

Thermodynamically consistent modelling and simulation of the moving contact line problem in non-isothermal compressible two-phase flows
According to the dynamic van der Waals theory, we propose a thermodynamically consistent model for non-isothermal compressible two-phase flows with contact line motion. In this model, fluid temperature is treated as a primary variable, characterized by the proposed temperature equation instead of being obtained from intermediate variables such as total energy density, internal energy density and entropy density. The hydrodynamic boundary conditions, which represent a generalization of the gener…

Time-resolved solvation of alkali ions in superfluid helium nanodroplets: Theoretical simulation of a pump-probe study
Ernesto Garc\'ia-Alfonso, Manuel Barranco, Mart\'i Pi, Nadine Halberstadt
https://arxiv.org/abs/2507.14674

Time-resolved solvation of alkali ions in superfluid helium nanodroplets: Theoretical simulation of a pump-probe study
The solvation process of an alkali ion (Na$^+$, K$^+$, Rb$^+$, Cs$^+$) inside a superfluid $^4$He$_{2000}$ nanodroplet is investigated theoretically using liquid $^4$He time-dependent density functional theory at zero temperature. We simulate both steps of the pump-probe experiment conducted on Na$^+$ [Albrechtsen et al., Nature 623, 319 (2023)], where the alkali atom residing at the droplet surface is ionized by the pump pulse and its solvation is probed by ionizing a central xenon atom and de…

Theory uncertainties in predictions of strong-field QED
T. G. Blackburn
https://arxiv.org/abs/2508.03975 https://arxiv.org/pdf/2508.03975

Theory uncertainties in predictions of strong-field QED
Experiments using high-power lasers and relativistic electron beams will soon be capable of precision testing of the theory of strong-field quantum electrodynamics. The comparison between experiment and theory always occurs via numerical simulations, but the lack of quantitative uncertainty bounds for the latter means that the origin of any discrepancies cannot be identified conclusively. Here I present a simulation framework that can place meaningful bounds on the theory uncertainties inherent…

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…

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…

Real-time scattering and freeze-out dynamics in Rydberg-atom lattice gauge theory
De-Sheng Xiang, Peng Zhou, Chang Liu, Hao-Xiang Liu, Yao-Wen Zhang, Dong Yuan, Kuan Zhang, Biao Xu, Marcello Dalmonte, Dong-Ling Deng, Lin Li
https://arxiv.org/abs/2508.06639

Real-time scattering and freeze-out dynamics in Rydberg-atom lattice gauge theory
Understanding the non-equilibrium dynamics of gauge theories remains a fundamental challenge in high-energy physics. Indeed, most large scale experiments on gauge theories intrinsically rely on very far-from equilibrium dynamics, from heavy-ion to lepton and hadron collisions, which is in general extremely challenging to treat ab initio. Quantum simulation holds intriguing potential in tackling this problem and pioneering experiments have observed different characteristic features of gauge theo…

Agent-based modeling and the sociology of money: some suggestions for refining monetary theory using social simulation
Eduardo Coltre Ferraciolli, Tanya V. Ara\'ujo
https://arxiv.org/abs/2506.22318

Agent-based modeling and the sociology of money: some suggestions for refining monetary theory using social simulation
The institution of money can be seen as a foundational social mechanism, enabling communities to quantify collectively regulate economic processes. Money can be said, indeed, to constitute the micro-macro link in economics. This paper reviews influential views on the nature of money in economics and sociology, contrasting them to the relatively limited findings of recent agent-based models of "the emergence of money". Noting ample room for novel combinations of sociological and formal methods t…

Simulation of extreme functionals in meteoceanic data: Application to surge evolution over tidal cycles
Nathan Gorse (INSA Toulouse, IMT), Olivier Roustant (INSA Toulouse, IMT), J\'er\'emy Rohmer (BRGM), D\'eborah Idier (BRGM)
https://arxiv.org/abs/2508.13687

Simulation of extreme functionals in meteoceanic data: Application to surge evolution over tidal cycles
We investigate the influence of time-varying meteoceanic conditions on coastal flooding under the prism of rare events. Focusing on conditions observed over half tidal cycles, we observe that such data fall within the framework of functional extreme value theory, but violate standard assumptions due to temporal dependence and short-tailed behavior.a To address this, we propose a two-stage methodology. First, we introduce an autoregressive model to eliminate temporal dependence between cycles. S…

Replaced article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[2/2]:
- Quantum correlations in a gravitational collapse simulation with SpheriCo.jl
Benjamin Berczi, Magdalena Eriksson, Thanasis Giannakopoulos, Paul M. Saffin

Minimal sofic shift on a group that is not finitely-generated
Ville Salo
https://arxiv.org/abs/2507.06599 https://arxiv.org/pdf/2507.…

Minimal sofic shift on a group that is not finitely-generated
We prove that there exists a group which is not finitely generated, but admits a minimal sofic shift. This answers a question of Doucha, Melleray and Tsankov. The group is of the form $(F_4 \times F_2) \rtimes F_{\infty}$. The construction itself is based on simulation theory and properties of Thompson's~$V$.

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 …

Aubry-Andr\'e Transition for an Active Undulator
Christopher J. Pierce, Tianyu Wang, Dmitri Kalinin, Andrew Zangwill, Daniel I. Goldman
https://arxiv.org/abs/2507.03715

Aubry-André Transition for an Active Undulator
The transport of deformable self-propelling objects like bacteria, worms, snakes, and robots through heterogeneous environments is poorly understood. In this paper, we use experiment, simulation, and theory to study a snake-like robot as it undulates without sensory feedback through a narrow channel containing a linear array of boulder-like hemispherical obstacles. The profile of the boulder landscape approximates a one-dimensional bichromatic potential introduced by Aubry and André (AA) to st…

Structure of the $\Omega^{-}(2012)$ with Hamiltonian Effective Field Theory
Fang-Chao Han, Zhan-Wei Liu, Derek B. Leinweber, Anthony W. Thomas
https://arxiv.org/abs/2507.06682

Structure of the $Ω^{-}(2012)$ with Hamiltonian Effective Field Theory
We investigate the internal structure of the $Ω(2012)^-$ by analyzing lattice QCD simulation and experimental data within Hamiltonian effective field theory, considering both $J^P = 1/2^-$ and $3/2^-$ assignments. The couplings to the dominant decay channel $Ξ\bar{K}$ and the near-threshold channel $Ξ(1530) \bar{K}$ are determined through the quark-pair-creation model. By studying the lattice QCD spectra in these two spin-parity scenarios, we extract the masses and widths of the resonances. …

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…

Covariate adjustment for linear models in estimating treatment effects in randomised clinical trials. Some useful theory to guide simulation
Stephen Senn, Franz K\"onig, Martin Posch
https://arxiv.org/abs/2508.05459

Covariate adjustment for linear models in estimating treatment effects in randomised clinical trials. Some useful theory to guide simulation
Building on key papers that were published in special issues of Biometrics in 1957 and 1982 we propose and develop a three-aspect system for evaluating the effect of fitting covariates in the analysis of designed experiments, in particular randomised clinical trials. The three aspects are: first the effect on residual mean square error, second the effect on the variance inflation factor (VIF) and third the effect on second order precision. We concentrate, in particular, on the VIF and highlight…

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/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…

Learning the bulk and interfacial physics of liquid-liquid phase separation
Silas Robitschko, Florian Samm\"uller, Matthias Schmidt, Robert Evans
https://arxiv.org/abs/2507.08395

Learning the bulk and interfacial physics of liquid-liquid phase separation
We use simulation-based supervised machine learning and classical density functional theory to investigate bulk and interfacial phenomena associated with phase coexistence in binary mixtures. For a prototypical symmetrical Lennard-Jones mixture our trained neural density functional yields accurate liquid-liquid and liquid-vapour binodals together with predictions for the variation of the associated interfacial tensions across the entire fluid phase diagram. From the latter we determine the cont…

The Effect of Sporadic Dormancy on Adaptation under Natural Selection: A Formal Theory
Sasanka Sekhar Chanda
https://arxiv.org/abs/2506.22758 https://

The Effect of Sporadic Dormancy on Adaptation under Natural Selection: A Formal Theory
Researchers puzzle over questions as to how rare species survive extinction, and why a significant proportion of microbial taxa are dormant. Computational simulation modeling by a genetic algorithm provides some answers. First, a weak/rare/lowly-adapted species can obtain significantly higher fitness by resorting to sporadic dormancy; thereby the probability of extinction is reduced. Second, the extent of fitness-gain is greater when a higher fraction of the population is dormant; thus, the pro…

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 …

Robust Inference with High-Dimensional Instruments
Qu Feng, Sombut Jaidee, Wenjie Wang
https://arxiv.org/abs/2506.23834 https://arxiv…

Robust Inference with High-Dimensional Instruments
We propose a weak-identification-robust test for linear instrumental variable (IV) regressions with high-dimensional instruments, whose number is allowed to exceed the sample size. In addition, our test is robust to general error dependence, such as network dependence and spatial dependence. The test statistic takes a self-normalized form and the asymptotic validity of the test is established by using random matrix theory. Simulation studies are conducted to assess the numerical performance of …

Rapid cosmological inference with the two-loop matter power spectrum
Thomas Bakx, Henrique Rubira, Nora Elisa Chisari, Zvonimir Vlah
https://arxiv.org/abs/2508.00611 https://

Rapid cosmological inference with the two-loop matter power spectrum
We compute the two-loop effective field theory (EFT) power spectrum of dark matter density fluctuations in $Λ$CDM using the recently proposed COBRA method (Bakx. et al, 2025). With COBRA, we are able to evaluate the two-loop matter power spectrum in $\sim 1$ millisecond at $ \sim 0.1 \%$ precision on one CPU for arbitrary redshifts and on scales where perturbation theory applies. As an application, we use the nonlinear matter power spectrum from the Dark Sky simulation to assess the performanc…

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 …

Simulation of the total energy of a triatomic silicon cluster in the first order of perturbation theory
V. P. Koshcheev, Yu. N. Shtanov
https://arxiv.org/abs/2507.00053

Simulation of the total energy of a triatomic silicon cluster in the first order of perturbation theory
As part of a new approach to calculating the total energy of a diatomic molecule (cluster), it is shown that in the first order of perturbation theory, the total energy of a triatomic cluster is equal to the sum of the total energies of the diatomic clusters (molecules). If all three aluminum atoms are in the ground state of Al(2p), then the quantum of energy of collective electron oscillations (plasmon energy) in each of the diatomic clusters (molecules) is eV (electron volts).

Prepare-and-measure and entanglement simulation beyond qubits
Mani Zartab, Giulio Gasbarri, Gael Sent\'is, Ramon Mu\~noz-Tapia
https://arxiv.org/abs/2508.02377 https://

Prepare-and-measure and entanglement simulation beyond qubits
For two non-communicating parties, quantum theory can give rise to probability distributions of outcomes that cannot be reproduced by any local classical model without communication. However, in the case of two-dimensional systems ($d=2$), it is known that allowing a finite amount of classical communication to shared classical resources makes it possible to simulate these quantum correlations. Whether such a simulation remains possible in higher dimensions is still an open question. In this wor…

Replaced article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[3/3]:
- Efficient Truncations of SU($N_c$) Lattice Gauge Theory for Quantum Simulation
Anthony N. Ciavarella, I. M. Burbano, Christian W. Bauer

Simulating Mass-Dependent Decoherence in Quantum Computers: Baseline Signatures for Testing Gravity-Induced Collapse
Viswak R Balaji, Samuel Punch
https://arxiv.org/abs/2508.10590

Simulating Mass-Dependent Decoherence in Quantum Computers: Baseline Signatures for Testing Gravity-Induced Collapse
We present a quantum computing simulation study of mass-dependent decoherence models inspired by Penrose's gravity-induced collapse hypothesis. According to objective reduction (OR) theory, quantum superpositions become unstable when the gravitational self-energy difference between branches exceeds a certain threshold, leading to a collapse time $τ\approx \hbar / E_G$. In this work, we implement a mass-dependent dephasing noise channel, $p(m) = 1 - e^{-k m^α}$, within the Qiskit AerSimulator,…

Hybrid renormalization for distribution amplitude of a light baryon in large momentum effective theory
Haoyang Bai, Jun Hua, Xiangdong Ji, Xiangyu Jiang, Jian Liang, Andreas Schafer, Wei Wang, Yibo Yang, Jianhui Zhang, JiaLu Zhang, Muhua Zhang, Qian Zhang
https://arxiv.org/abs/2508.08971

Hybrid renormalization for distribution amplitude of a light baryon in large momentum effective theory
Lightcone distribution amplitudes for a light baryon can be extracted through the simulation of the quasi-distribution amplitudes (quasi-DAs) on the lattice. We implement the hybrid renormalization for the quasi DAs of light baryons. Lattice simulations are performed using $N_f = 2+1$ stout-smeared clover fermions and a tree-level Symanzik-improved gauge action, with three lattice spacings of ${0.105, 0.077, 0.052}$ fm. By analyzing zero-momentum matrix elements for different lattice spacings, …

Hydrodynamics of a three-dimensional mesoscale odd fluid
Yuxing Jiao, Mingcheng Yang
https://arxiv.org/abs/2508.04420 https://arxiv.org/pdf/2508.04420

Hydrodynamics of a three-dimensional mesoscale odd fluid
Odd fluids are a class of fluids characterized by non-zero antisymmetric transport coefficient tensors induced by broken time-reversal symmetry. In our previous work, a mesoscale simulation model for two-dimensional isotropic odd fluids was developed. Here, we extend the model to the three-dimensional case that corresponds to an anisotropic odd fluid with cylindrical symmetry. Using kinetic theory, we analytically derive the viscosity tensor and Navier-Stokes equation for the three-dimensional …

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 …

Kinetic Fragmentation of the QCD Axion on the Lattice
Matteo Fasiello, Joanes Lizarraga, Alexandros Papageorgiou, Ander Urio
https://arxiv.org/abs/2507.01822

Kinetic Fragmentation of the QCD Axion on the Lattice
Kinetic misalignment, one of the most compelling scenarios for the non-thermal generation of axion dark matter, is generally accompanied by axion fragmentation, a process in which the energy of the axion condensate is transferred to its perturbations. The dynamics of fragmentation, at least in the context of dark matter production, have so far been studied semi-analytically using perturbation theory. In this work, we present the first classical lattice simulation of kinetic axion fragmentation …

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…

Polarized-boson pairs at NLO in the SMEFT
Ulrich Haisch, Jakob Linder, Giovanni Pelliccioli, Emanuele Re, Giulia Zanderighi
https://arxiv.org/abs/2507.21768 https://

Polarized-boson pairs at NLO in the SMEFT
We present a computation of diboson production in the $W^\pm Z$ channel at the Large Hadron Collider (LHC), incorporating leptonic decays of the gauge bosons and considering intermediate gauge bosons with definite polarization states. The analysis includes contributions from the Standard Model effective field theory (SMEFT) and is carried out at next-to-leading order accuracy in QCD, matched to a parton-shower simulation. Our implementation allows for the selection of specific helicity configur…

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…

Operational interpretation of the Stabilizer Entropy
Lennart Bittel, Lorenzo Leone
https://arxiv.org/abs/2507.22883 https://arxiv.org/pdf/2507.22883…

Operational interpretation of the Stabilizer Entropy
Magic-state resource theory is a fundamental framework with far-reaching applications in quantum error correction and the classical simulation of quantum systems. Recent advances have significantly deepened our understanding of magic as a resource across diverse domains, including many-body physics, nuclear and particle physics, and quantum chemistry. Central to this progress is the stabilizer Rényi entropy, a computable and experimentally accessible magic monotone. Despite its widespread adop…

Configurable photonic simulator for quantum field dynamics
Mauro D'Achille, Martin G\"arttner, Tobias Haas
https://arxiv.org/abs/2506.23838 https:…

Configurable photonic simulator for quantum field dynamics
Quantum field simulators provide unique opportunities for investigating the dynamics of quantum fields through tabletop experiments. A primary drawback of standard encoding schemes is their rigidity: altering the theory, its coupling geometry, metric structure, or simulation time typically requires redesigning the experimental setup, which imposes strong constraints on the types of dynamics and theories that can be simulated. Here, we introduce the Optical Time Algorithm (OTA) as a unifying fra…