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At least 127 records · Page 7

Model atmospheres, predicted spectra, and colors

Theoretical models of stellar atmospheres and the process of forming a spectrum are reviewed with particular reference to the spectra of B stars. In the case of classical models the stellar atmosphere is though to consist of plane parallel layers of gas in which radiative and hydrostatic equilibrium exists. No radiative energy is lost or gained in the model atmosphere, but the detailed shape of the spectrum is changed as a result of the interactions with the ionized gas. Predicted line spectra using statistical equilibrium local thermodynamic equilibrium (LTE), and non-LTE physics are compared and the determination of abundances is discussed. The limitations of classical modeling are examined. Models developed to demonstrate what motions in the upper atmosphere will do to the spectrum and to explore the effects of using geometries different from plane parallel layer are reviewed. In particular the problem of radiative transfer is addressed.

Source record↗

Thermodynamically informed priors for uncertainty propagation in first-principles statistical mechanics

Here, this work demonstrates how first-principles statistical mechanics approaches within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of 0 K ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the fcc zirconium nitride system, including confidence intervals on order-disorder transition temperatures.

Bayesian methods↗

Observation of Energy Fluctuation

The fluctuation of energy is discussed in all thermodynamics textbooks because of the crucial role it plays in bringing to light the statistical uncertainties of all thermodynamic quantities.

fluctuation-dissipation theorem magnetic salt ther↗

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. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗

Quantum Jarzynski Equality in Open Quantum Systems from the One-Time Measurement Scheme

In open quantum systems, a clear distinction between work and heat is often challenging, and extending the quantum Jarzynski equality to systems evolving under general quantum channels beyond unitality remains an open problem in quantum thermodynamics. In this Letter, we introduce well-defined notions of guessed quantum heat and guessed quantum work, by exploiting the one-time measurement scheme, which only requires an initial energy measurement on the system alone. We derive a modified quantum Jarzynski equality and the principle of maximum work with respect to the guessed quantum work, which requires the knowledge of the system only. We further show the significance of guessed quantum heat and work by linking them to the problem of quantum hypothesis testing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The 2006 Cape Canaveral Air Force Station Range Reference Atmosphere Model Validation Study and Sensitivity Analysis to the National Aeronautics and Space Administration's Space Shuttle

NASA's Space Shuttle utilizes atmospheric thermodynamic properties to evaluate structural dynamics and vehicle flight performance impacts by the atmosphere during ascent. Statistical characteristics of atmospheric thermodynamic properties at Kennedy Space Center (KSC) used in Space. Shuttle Vehicle assessments are contained in the Cape Canaveral Air Force Station (CCAFS) Range Reference Atmosphere (RRA) Database. Database contains tabulations for monthly and annual means (mu), standard deviations (sigma) and skewness of wind and thermodynamic variables. Wind, Thermodynamic, Humidity and Hydrostatic parameters 1 km resolution interval from 0-30 km 2 km resolution interval 30-70 km Multiple revisions of the CCAFS RRA database have been developed since initial RRA published in 1963. 1971, 1983, 2006 Space Shuttle program utilized 1983 version for use in deriving "hot" and "cold" atmospheres, atmospheric density dispersions for use in vehicle certification analyses and selection of atmospheric thermodynamic profiles for use in vehicle ascent design and certification analyses. During STS-114 launch preparations in July 2005 atmospheric density observations between 50-80 kft exceeded density limits used for aerodynamic ascent heating constraints in vehicle certification analyses. Mission specific analyses were conducted and concluded that the density bias resulted in small changes to heating rates and integrated heat loading on the vehicle. In 2001, the Air Force Combat Climatology Center began developing an updated RRA for CCAFS.

Decker, Ryan↗

Framework for phase transitions between the Maxwell and Gibbs constructions

By taking the nucleon-to-quark phase transition within a neutron star as an example, we present a thermodynamically consistent method to calculate the equation of state of ambient matter so that transitions that are intermediate to those of the familiar Maxwell and Gibbs constructions can be described. This method does not address the poorly known surface tension between the two phases microscopically (as, for example, in the calculation of the core pasta phases via the Wigner-Seitz approximation) but instead combines the local and global charge neutrality conditions characteristic of the Maxwell and Gibbs constructions, respectively. Overall charge neutrality is achieved by dividing the leptons to those that obey local charge neutrality (Maxwell) and those that maintain global charge neutrality (Gibbs). The equation of state is obtained by using equilibrium constraints derived from minimizing the total energy density. The results of this minimization are then used to calculate neutron star mass-radius curves, tidal deformabilities, equilibrium and adiabatic sound speeds, and nonradial g-mode oscillation frequencies for several intermediate constructions. Various quantities of interest transform smoothly from their Gibbs structures to those of Maxwell as the local-to-total electron ratio η, introduced to mimic the hadron-to-quark interface tension from 0 (Gibbs) to ∞ (Maxwell), is raised from 0 to 1. As a result, a notable exception is the g-mode frequency for the specific case of η = 1 for which a gap appears between the quark and hadronic branches.

79 ASTRONOMY AND ASTROPHYSICS↗

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗

Prediction of the Al-rich part of the Al-Cu phase diagram using cluster expansion and statistical mechanics

In this work, the thermodynamic properties of α-Al and other phases (GP zones, θ'', θ' and θ) in the Al-rich part of the Al-Cu system have been obtained by means of the cluster expansion formalism in combination with statistical mechanics. This information was used to build the Al-rich part of the Al-Cu phase-diagram taking into account vibrational entropic contributions for θ', as those of the other phases were negligible. The simulation predictions of the phase boundaries between α-Al and either θ'', θ' or θ phases as a function of temperature are in good agreement with experimental data and extend the phase boundaries to a wider temperature range. The DFT calculations reveal the presence of a number of metastable Guinier-Preston-zone type configurations that may coexist with α-Al and θ'' at low temperatures. They also demonstrate that θ' is the stable phase below 550K but it is replaced by θ above this temperature due to the vibrational entropic contribution to the Gibbs energy of θ'. This work shows how the combination of cluster expansion and statistical mechanics can be used to expand our knowledge of the phase diagram of metallic alloys and to provide Gibbs free energies of different phases that can be used as input in mesoscale simulations of precipitation.

36 MATERIALS SCIENCE↗

Spatially-resolved soot evolution and statistics in high-pressure diesel spray flames using two-color pyrometry

Previous studies of diesel spray flames have focused on details of the sooting behavior mainly during the quasi-steady period, but few have considered the spatially-resolved transient evolution in combination with injection-to-injection variations. In this study, a 500-injection data set is utilized to investigate the temporal evolution of a spray flame during auto-ignition, the premixed burn phase, and the quasi-steady period. Spatially-resolved OH* chemiluminescence data provide ignition delay times and reaction zone locations. Two-color pyrom-etry with a vastly improved optical system is used to quantify spatially-resolved soot evolution and its statistical variations. The ambient thermodynamic con-ditions are slightly below those in modern diesel engines, resulting in longer lift-off lengths and lower overall soot production. Spatially, soot formation in the lift-off region is small, but appreciable soot forms in the jet core and jet head regions, while it oxidizes gradually on the jet periphery. Total soot mass profiles indicate that regions with larger local soot mass take longer to form, but are the first to oxidize. Probability distributions of soot mass in localized regions indicate that a few injections with high soot mass bias the average soot mass data towards higher values. Altogether, results show good agreement with previous studies employing different diagnostic techniques while providing statistical details of transient and localized soot behavior in high pressure diesel spray flames in support of the related modeling efforts.

09 BIOMASS FUELS↗

Emergent microrobotic oscillators via asymmetry-induced order

Abstract Spontaneous oscillations on the order of several hertz are the drivers of many crucial processes in nature. From bacterial swimming to mammal gaits, converting static energy inputs into slowly oscillating power is key to the autonomy of organisms across scales. However, the fabrication of slow micrometre-scale oscillators remains a major roadblock towards fully-autonomous microrobots. Here, we study a low-frequency oscillator that emerges from a collective of active microparticles at the air-liquid interface of a hydrogen peroxide drop. Their interactions transduce ambient chemical energy into periodic mechanical motion and on-board electrical currents. Surprisingly, these oscillations persist at larger ensemble sizes only when a particle with modified reactivity is added to intentionally break permutation symmetry. We explain such emergent order through the discovery of a thermodynamic mechanism for asymmetry-induced order. The on-board power harvested from the stabilised oscillations enables the use of electronic components, which we demonstrate by cyclically and synchronously driving a microrobotic arm. This work highlights a new strategy for achieving low-frequency oscillations at the microscale, paving the way for future microrobotic autonomy.

42 ENGINEERING↗

When do short-range atomistic machine-learning models fall short?

In this work, we explore the role of long-range interactions in atomistic machine-learning models by analyzing the effects on fitting accuracy, isolated cluster properties, and bulk thermodynamic properties. Such models have become increasingly popular in molecular simulations given their ability to learn highly complex and multi-dimensional interactions within a local environment; however, many of them fundamentally lack a description of explicit long-range interactions. In order to provide a well-defined benchmark system with precisely known pairwise interactions, we chose as the reference model a flexible version of the Extended Simple Point Charge (SPC/E) water model. Our analysis shows that while local representations are sufficient for predictions of the condensed liquid phase, the short-range nature of machine-learning models falls short in representing cluster and vapor phase properties. These findings provide an improved understanding of the role of long-range interactions in machine learning models and the regimes where they are necessary.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Model Intercomparison Study of Aerosol‐Cloud‐Turbulence Interactions in a Cloud Chamber: 1. Model Results

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties.

54 ENVIRONMENTAL SCIENCES↗

Quantum wake dynamics in Heisenberg antiferromagnetic chains

Traditional spectroscopy, by its very nature, characterizes physical system properties in the momentum and frequency domains. However, the most interesting and potentially practically useful quantum many-body effects emerge from local, short-time correlations. Here, using inelastic neutron scattering and methods of integrability, we experimentally observe and theoretically describe a local, coherent, long-lived, quasiperiodically oscillating magnetic state emerging out of the distillation of propagating excitations following a local quantum quench in a Heisenberg antiferromagnetic chain. This “quantum wake” displays similarities to Floquet states, discrete time crystals and nonlinear Luttinger liquids. We also show how this technique reveals the non-commutativity of spin operators, and is thus a model-agnostic measure of a magnetic system’s “quantumness.”

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Kagome qubit ice

Abstract Topological phases of spin liquids with constrained disorder can host a kinetics of fractionalized excitations. However, spin-liquid phases with distinct kinetic regimes have proven difficult to observe experimentally. Here we present a realization of kagome spin ice in the superconducting qubits of a quantum annealer, and use it to demonstrate a field-induced kinetic crossover between spin-liquid phases. Employing fine control over local magnetic fields, we show evidence of both the Ice-I phase and an unconventional field-induced Ice-II phase. In the latter, a charge-ordered yet spin-disordered topological phase, the kinetics proceeds via pair creation and annihilation of strongly correlated, charge conserving, fractionalized excitations. As these kinetic regimes have resisted characterization in other artificial spin ice realizations, our results demonstrate the utility of quantum-driven kinetics in advancing the study of topological phases of spin liquids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Learning protocols for the fast and efficient control of active matter

Exact analytic calculation shows that optimal control protocols for passive molecular systems often involve rapid variations and discontinuities. However, similar analytic baselines are not generally available for active-matter systems, because it is more difficult to treat active systems exactly. Here we use machine learning to derive efficient control protocols for active-matter systems, and find that they are characterized by sharp features similar to those seen in passive systems. We show that it is possible to learn protocols that effect fast and efficient state-to-state transformations in simulation models of active particles by encoding the protocol in the form of a neural network. We use evolutionary methods to identify protocols that take active particles from one steady state to another, as quickly as possible or with as little energy expended as possible. Our results show that protocols identified by a flexible neural-network ansatz, which allows the optimization of multiple control parameters and the emergence of sharp features, are more efficient than protocols derived recently by constrained analytical methods. Our learning scheme is straightforward to use in experiment, suggesting a way of designing protocols for the efficient manipulation of active matter in the laboratory.

74 ATOMIC AND MOLECULAR PHYSICS↗

Extended harmonic mapping connects the equations in classical, statistical, fluid, quantum physics and general relativity

Abstract One potential pathway to find an ultimate rule governing our universe is to hunt for a connection among the fundamental equations in physics. Recently, Ren et al. reported that the harmonic maps with potential introduced by Duan, named extended harmonic mapping (EHM), connect the equations of general relativity, chaos and quantum mechanics via a universal geodesic equation. The equation, expressed as Euler–Lagrange equations on the Riemannian manifold, was obtained from the principle of least action. Here, we further demonstrate that more than ten fundamental equations, including that of classical mechanics, fluid physics, statistical physics, astrophysics, quantum physics and general relativity, can be connected by the same universal geodesic equation. The connection sketches a family tree of the physics equations, and their intrinsic connections reflect an alternative ultimate rule of our universe, i.e. , the principle of least action on a Finsler manifold.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗