arXiv subjects

Michael S. Murillo

Publications and source records attributed to Michael S. Murillo.

18 recordsLinked to original sources

arXiv2026

Improved Kelbg Potentials for $Z>1$ and Application to Carbon Plasmas

In this work, we present a general form for the electron-ion diffractive potential derived from the quantum pair density matrix and fit to the improved Kelbg potential for atomic numbers up to $Z = 54$. We apply classical molecular dynamics using the improved Kelbg potential for carbon with various forms of the Pauli potential to compute internal energies and pressures for hot, dense plasma conditions. Our results are compared to an equation of state model based on path integral Monte Carlo and density functional theory simulations to examine the extent to which the improved Kelbg potential reproduces the internal energy and pressure of carbon plasmas. The regions of validity for carbon agree generally with those derived previously for hydrogen once pressure ionization effects are incorporated. Based on our carbon results and previously published hydrogen studies, we discuss the general applicability and limitations of these potentials for equation of state studies in warm dense matter and high energy density plasmas.

physics.plasm-ph↗

arXiv2026

Mermin's dielectric function and the f-sum rule

Mermin's dielectric function [N.D. Mermin, Phys. Rev. B 1, 2362 (1970)] is widely assumed to satisfy the f-sum rule because he constrains his ansatz with the continuity equation. However, we identify a moment-closure problem in Mermin's use of the continuity equation. Further, we show that the Mermin's model can be derived without invoking continuity. We describe how other approaches such as the ``completed Mermin'' model of Chuna and Murillo [Phys. Rev. E 111, 035206 (2025)] remedy this closure issue. We then inspect the f-sum rule for both the original and completed Mermin models and find for the Mermin ansatz that collision frequencies scaling as $ω$ must violate the f-sum rule, whereas constant, real, positive collision frequencies will satisfy it, with the caveat that, in practice, convergence with respect to the upper integration limit $ω_{\max}$ is sufficiently slow that finite-domain numerical evaluations exhibit apparent violations, regardless of wavenumber $q$. We also find that collision frequencies with constant imaginary components cause f-sum rule violations. We conclude that if Mermin's model is fit to data via optimizing its collision frequency, then the f-sum rule is not inherently satisfied; constraints, though broad, are needed in order to assume the f-sum rule is satisfied. Further, if the f-sum rule is theoretically satisfied, but violations still appear, then these deviations ought to be included in the error estimates.

cond-mat.stat-mech↗

arXiv2026

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the warm dense matter physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations \& experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments and contemporary challenges that are faced by theoretical methods, and experimental techniques needed to create and diagnose warm dense matter. A large part of this roadmap is dedicated to specific warm dense matter systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

physics.plasm-ph↗

arXiv2026

Generalized Langevin Models of Linear Agent-Based Systems: Strategic Influence Through Environmental Coupling

Agent-based models typically treat systems in isolation, discarding environmental coupling as either computationally prohibitive or dynamically irrelevant. We demonstrate that this neglect misses essential physics: environmental degrees of freedom create memory effects that fundamentally alter system dynamics. By systematically transforming linear update rules into exact generalized Langevin equations, we show that unobserved environmental agents manifest as memory kernels whose timescales and coupling strengths are determined by the environmental interaction spectrum. Network topology shapes this memory structure in distinct ways: small-world rewiring drives dynamics toward a single dominant relaxation mode, while fragmented environments sustain multiple persistent modes corresponding to isolated subpopulations. We apply this framework to covert influence operations where adversaries manipulate target populations exclusively via environmental intermediaries. The steady-state response admits a random-walk interpretation through hitting probabilities, revealing how zealot opinions diffuse through the environment to shift system agent opinions toward the zealot mean - even when zealots never directly contact targets.

physics.soc-ph↗

arXiv2025

Quantum Kinetic Modeling of KEEN waves in a Warm-Dense Regime

We report a fully kinetic, quantum study of Kinetic Electrostatic Electron Nonlinear (KEEN) waves, showing that quantum diffraction systematically erodes the classical trapping mechanism, narrow harmonic locking to the fundamental, and hasten post-drive decay. Electrons are evolved with a second-order Strang-split 1D1V Wigner-Poisson solver that couples conservative semi-Lagrangian WENO advection to an analytic Fourier space update for the non-local Wigner term, while ions remain classical. Short, frequency-tuned ponderomotive pulses drive KEEN formation in a uniform Maxwellian plasma; as the dimensionless quantum parameter H rises from the classical limit to values relevant to warm-dense matter, doped semiconductors, and 2D electron systems, the drive threshold increases, higher harmonics are damped, trapped electron vortices diffuse, and the subplasma electrostatic energy relaxes to a lower stationary level, as confirmed by continuous wavelet analysis. These microscopic changes carry macroscopic weight. Ignition-scale capsules now compress matter to regimes where the electron de Broglie wavelength rivals the Debye length, making classical kinetic descriptions insufficient. By extending KEEN physics into this quantum domain, our results offer a potential diagnostic of nonequilibrium electron dynamics for next-generation inertial-confinement designs and high-energy-density platforms, indicating that predictive fusion modeling may benefit from the integration of kinetic fidelity with quantum effects.

physics.plasm-ph↗

arXiv2025

Quantum Ornstein-Zernike Theory for Two-Temperature Two-Component Plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. High-fidelity modeling of these systems can be achieved with density functional theory molecular dynamics in the two-temperature, adiabatic electron limit. Motivated by this, we construct a statistical mechanics framework for the multi-temperature system that is theoretically consistent with the ab initio calculation. We proceed to derive multi-temperature quantum Ornstein-Zernike equations for the first time. We then construct a two-temperature two-component plasma model using the average atom and compute the radial distribution function, viscosity, ion thermal conductivity, and ion self-diffusion. We verify that we recover the ionic structure and self-diffusion of density functional molecular dynamics simulations.

physics.plasm-ph↗

arXiv2025

Tensor Networks for Liquids in Heterogeneous Systems

Many-body correlations in strongly coupled liquids and plasmas are critical for many applications in nanofluids, biology, and fusion-related plasma physics, but their description in fully heterogeneous environments remains challenging due to the high-dimensional equations involved. Recently, tensor network decompositions have emerged as powerful tools for tackling such equations by reducing memory usage and computational complexity. In this paper, we solve for equilibrium density and density-density correlation functions of liquids in confined heterogeneous environments using tensor network methods. We demonstrate that these functions admit high compression when their lengthscale dependence is encoded via quantized tensor trains or when their spatial-coordinate dependence is represented in standard tensor-train format, but not with respect to their dependence on distinct particle coordinates.

physics.comp-ph↗

arXiv2025

Adaptive Equilibration of Molecular Dynamics Simulations

We present a systematic framework for shortening and automating molecular dynamics equilibration through improved position initialization methods and uncertainty quantification analysis, using the Yukawa one-component plasma as an exemplar system. Our comprehensive evaluation of seven initialization approaches (uniform random, uniform random with rejection, Halton and Sobol sequences, perfect and perturbed lattices, and a Monte Carlo pair distribution method) demonstrates that initialization significantly impacts equilibration efficiency, with microfield distribution analysis providing diagnostic insights into thermal behaviors. Our results establish that initialization method selection is relatively inconsequential at low coupling strengths, while physics-informed methods demonstrate superior performance at high coupling strengths, reducing equilibration time. We establish direct relationships between temperature stability and uncertainties in transport properties (diffusion coefficient and viscosity), comparing thermostating protocols including ON-OFF versus OFF-ON duty cycles, Berendsen versus Langevin thermostats, and thermostat coupling strengths. Our findings demonstrate that weaker thermostat coupling generally requires fewer equilibration cycles, and OFF-ON thermostating sequences outperform ON-OFF approaches for most initialization methods. The methodology implements temperature forecasting as a quantitative metric for system thermalization, enabling users to determine equilibration adequacy based on specified uncertainty tolerances in desired output properties, thus transforming equilibration from a heuristic process to a rigorously quantifiable procedure with clear termination criteria.

physics.comp-ph↗

arXiv2023

Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education

In the rapidly evolving landscape of education, digital technologies have repeatedly disrupted traditional pedagogical methods. This paper explores the latest of these disruptions: the potential integration of large language models (LLMs) and chatbots into graduate engineering education. We begin by tracing historical and technological disruptions to provide context and then introduce key terms such as machine learning and deep learning and the underlying mechanisms of recent advancements, namely attention/transformer models and graphics processing units. The heart of our investigation lies in the application of an LLM-based chatbot in a graduate fluid mechanics course. We developed a question bank from the course material and assessed the chatbot's ability to provide accurate, insightful responses. The results are encouraging, demonstrating not only the bot's ability to effectively answer complex questions but also the potential advantages of chatbot usage in the classroom, such as the promotion of self-paced learning, the provision of instantaneous feedback, and the reduction of instructors' workload. The study also examines the transformative effect of intelligent prompting on enhancing the chatbot's performance. Furthermore, we demonstrate how powerful plugins like Wolfram Alpha for mathematical problem-solving and code interpretation can significantly extend the chatbot's capabilities, transforming it into a comprehensive educational tool. While acknowledging the challenges and ethical implications surrounding the use of such AI models in education, we advocate for a balanced approach. The use of LLMs and chatbots in graduate education can be greatly beneficial but requires ongoing evaluation and adaptation to ensure ethical and efficient use.

cs.CY↗

arXiv2022

Yukawa Friedel-Tail pair potentials for warm dense matter applications

Accurate equations of state (EOS) and plasma transport properties are essential for numerical simulations of warm dense matter encountered in many high-energy-density situations. Molecular dynamics (MD) is a simulation method that generates EOS and transport data using an externally provided potential to dynamically evolve the particles without further reference to the electrons. To minimize computational cost, pair potentials needed in MD may be obtained from the neutral-pseudoatom (NPA) approach, a form of single-ion density functional theory (DFT), where many-ion effects are included via ion-ion correlation functionals. Standard $N$-ion DFT-MD provides pair potentials via the force matching technique but at much greater computational cost. Here we propose a simple analytic model for pair potentials with physically meaningful parameters based on a Yukawa form with a thermally damped Friedel tail (YFT) applicable to systems containing free electrons. The YFT model accurately fits NPA pair potentials or the non-parametric force-matched potentials from $N$-ion DFT-MD, showing excellent agreement for a wide range of conditions. The YFT form provides accurate extrapolations of the NPA or force-matched potentials for small and large particle separations within a physical model. Our method can be adopted to treat plasma mixtures, allowing for large-scale simulations of multi-species warm dense matter.

cond-mat.stat-mech↗

arXiv2022

Microscopic theory for the pair correlation function of liquidlike colloidal suspensions under shear flow

We present a theoretical framework to investigate the microscopic structure of concentrated hard-sphere colloidal suspensions under strong shear flows by fully taking into account the boundary-layer structure of convective diffusion. We solve the pair Smoluchowski equation with shear separately in the compressing and extensional sectors of the solid angle, by means of matched asymptotics. A proper, albeit approximate, treatment of the hydrodynamic interactions in the different sectors allows us to construct a potential of mean force containing the effect of the flow field on pair correlations. We insert the obtained pair potential in the Percus-Yevick relation and use the latter as a closure to solve the Ornstein-Zernike integral equation. For a wide range of either the packing fraction $η$ and the Péclet ($\textrm{Pe}$) number, we compute the pair correlation function and extract scaling laws for its value at contact. For all the considered value of $\textrm{Pe},$ we observe a very good agreement between theoretical findings and numerical results from literature, up to rather large values of $η.$ The theory predicts a consistent enhancement of the structure factor $ S(k)$ at $k \to 0,$ upon increasing the $\textrm{Pe}$ number. We argue this behaviour may signal the onset of a phase transition from the isotropic phase to a non-uniform one, induced by the external shear flow.

cond-mat.soft↗

arXiv2021

Sarkas: A Fast Pure-Python Molecular Dynamics Suite for Plasma Physics

We present an open-source, performant, pure-python molecular dynamics (MD) suite for non-ideal plasmas. The code, Sarkas, aims to accelerate the research process by providing an MD code but also pre- and post-processing tools. Sarkas offers the ease of use of Python while employing the Numba library to obtain execution speeds comparable to that of compiled languages. The available tools in Sarkas include graphical displays of the equilibration process through a Jupyter interface and the ability to compute quantities such as, radial distribution functions, autocorrelation functions and Green-Kubo relations. Many force laws used to simulate plasmas are included in Sarkas, namely, pure Coulomb, Yukawa, and Molière pair-potentials. Sarkas also contains quantum statistical potentials and fast Ewald methods are included where necessary. An object-oriented approach allows for easy modification of Sarkas, such as adding new time integrators, boundary conditions and force laws.

physics.plasm-ph↗

arXiv2020

Efficacy of the Radial Pair Potential Approximation for Molecular Dynamics Simulations of Dense Plasmas

Macroscopic simulations of dense plasmas rely on detailed microscopic information that can be computationally expensive and is difficult to verify experimentally. In this work, we delineate the accuracy boundary between microscale simulation methods by comparing Kohn-Sham density functional theory molecular dynamics (KS-MD) and radial pair potential molecular dynamics (RPP- MD) for a range of elements, temperature, and density. By extracting the optimal RPP from KS-MD data using force-matching, we constrain its functional form and dismiss classes of potentials that assume a constant power law for small interparticle distances. Our results show excellent agreement between RPP-MD and KS-MD for multiple metrics of accuracy at temperatures of only a few electron volts. The use of RPPs offers orders of magnitude decrease in computational cost and indicates that three-body potentials are not required beyond temperatures of a few eV. Due to its efficiency, the validated RPP-MD provides an avenue for reducing errors due to finite-size effects that can be on the order of $\sim20\%$.

physics.plasm-ph↗

arXiv2020

Data-driven prediction of the equivalent sand-grain height in rough-wall turbulent flows

This paper investigates a long-standing question about the effect of surface roughness on turbulent flow: what is the equivalent roughness sand-grain height for a given roughness topography? Deep Neural Network (DNN) and Gaussian Process Regression (GPR) machine learning approaches are used to develop a high-fidelity prediction approach of the Nikuradse equivalent sand-grain height $k_s$ for turbulent flows over a wide variety of different rough surfaces. To this end, 45 surface geometries were generated and the flow over them simulated at $\hbox{Re}_τ=1000$ using direct numerical simulations. These surface geometries differed significantly in moments of surface height fluctuations, effective slope, average inclination, porosity and degree of randomness. Thirty of these surfaces were considered fully-rough and they were supplemented with experimental data for fully-rough flows over 15 more surfaces available from previous studies. The DNN and GPR methods predicted $k_s$ with an average error of less than 10% and a maximum error of less than 30%, which appears to be significantly more accurate than existing prediction formulas. They also identified the surface porosity and the effective slope of roughness in the spanwise direction as important factors in drag prediction.

physics.flu-dyn↗

arXiv2019

Ion friction at small values of the Coulomb logarithm

Transport properties of high-energy-density plasmas are influenced by the ion collision rate. Traditionally, this rate involves the Coulomb logarithm, $\lnΛ$. Typical values of $\lnΛ$ are $\approx 10~\mbox{to}~20$ in kinetic theories where transport properties are dominated by weak-scattering events caused by long-range forces. The validity of these theories breaks down for strongly-coupled plasmas, when $\lnΛ$ is of order one. We present measurements and simulations of collision data in strongly-coupled plasmas when $\lnΛ$ is small. Experiments are carried out in the first dual-species ultracold neutral plasma (UNP), using Ca$^+$ and Yb$^+$ ions. We find strong collisional coupling between the different ion species in the bulk of the plasma. We simulate the plasma using a two-species fluid code that includes Coulomb logarithms derived from either a screened Coulomb potential or a the potential of mean force. We find generally good agreement between the experimental measurements and the simulations. With some improvements, the mixed Ca$^+$ and Yb$^+$ dual-species UNP will be a promising platform for testing theoretical expressions for $\lnΛ$ and collision cross-sections from kinetic theories through measurements of energy relaxation, stopping power, two-stream instabilities, and the evolution of sculpted distribution functions in an idealized environment in which the initial temperatures, densities, and charge states are accurately known.

physics.plasm-ph↗

arXiv2009

Wave spectra of 2D dusty plasma solids and liquids

Brownian dynamics simulations were carried out to study wave spectra of two-dimensional dusty plasma liquids and solids for a wide range of wavelengths. The existence of a longitudinal dust thermal mode was confirmed in simulations, and a cutoff wavenumber in the transverse mode was measured. Dispersion relations, resulting from simulations, were compared with those from analytical theories, such as the random-phase approximation (RPA), quasi-localized charged approximation (QLCA), and harmonic approximation (HA). An overall good agreement between the QLCA and simulations was found for wide ranges of states and wavelengths after taking into account the direct thermal effect in the QLCA, while for the RPA and HA good agreement with simulations were found in the high and low temperature limits, respectively.

physics.plasm-ph↗

arXiv2007

Temperature Relaxation in Hot Dense Hydrogen

Temperature equilibration of hydrogen is studied for conditions relevant to inertial confinement fusion. New molecular-dynamics simulations and results from quantum many-body theory are compared with Landau-Spitzer (LS) predictions for temperatures T from 50 eV to 5000 eV, and densities with Wigner-Seitz radii r_s = 1.0 and 0.5. The relaxation is slower than the LS result, even for temperatures in the keV range, but converges to agreement in the high-T limit.

cond-mat.str-el↗

arXiv2007

Pair-distribution functions of two-temperature two-mass systems: Comparison of MD, HNC, CHNC, QMC and Kohn-Sham calculations for dense hydrogen

Two-temperature, two-mass quasi-equilibrium plasmas may occur in electron-ion plasmas,nuclear-matter, as well as in electron-hole condensed-matter systems. Dense two-temperature hydrogen plasmas straddle the difficult partially - degenerate regime of electron densities and temperatures which are important in astrophysics, in inertial-confinement fusion research, and other areas of warm dense matter physics. Results from Kohn-Sham calculations and QMC are used to benchmark the procedures used in classical molecular-dynamics simulations, HNC and CHNC methods to derive electron-electron and electron-proton pair - distribution functions. Then, nonequilibrium molecular dynamics for two -temperature, two-mass plasmas are used to obtain the pair distribution. Using these results, the correct HNC and CHNC procedures for the evaluation of pair-distribution functions in two-temperature two-mass two-component charged fluids are established. Results for a mass ratio of 1:5, typical of electron-hole fluids, as well as for compressed hydrogen are presented. PACS Numbers: 52.25.Kn, 52.25Gj, 71.10.-w, 52.27.Gr, 26.30.+k

cond-mat.stat-mech↗