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Results for “Maximum Entropy Model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Maximally entangled state and Bell’s inequality in qubits

A maximally entangled state is a quantum state which has maximum von Neumann entropy for each bipartition. Through proposing a new method to classify quantum states by using concurrences of pure states of a region, one can apply Bell’s inequality to study intensity of quantum entanglement of maximally entangled states. We use a class of seven-qubit quantum states to demonstrate the method, in which we express all coefficients of the quantum states in terms of concurrences of pure states of a region. When a critical point of an upper bound of Bell’s inequality occurs in our quantum states, one of the quantum state is a ground state of the toric code model on a disk manifold. Our result also implies that the maximally entangled states do not suggest local maximum quantum entanglement in our quantum states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Miscibility gap and phonon thermodynamics of Fe-Au alloys studied by inelastic neutron scattering and nuclear-resonant inelastic x-ray scattering

Recent measurements of the phonon spectra of several Au-rich alloys of face-centered-cubic Fe-Au using inelastic neutron scattering and nuclear-resonant inelastic x-ray scattering are summarized. The Wills-Harrison model, accounting for charge transfer upon alloying, is used to explain the observed negative excess vibrational entropy of mixing, which increases the miscibility gap temperature in the system by an estimated maximum of 550 K and we adjudicate to a charge transfer from the Fe to the Au atoms that results in an increase in the electron density in the free-electron-like states and in stronger sd-hybridization. When Au is the solvent, this softens the Fe–Fe bonds but stiffens the Au–Au and Au–Fe bonds which results in a net stiffening relative to the elemental components.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Designing Free Energy Surfaces That Match Experimental Data with Metadynamics

Creating models that are consistent with experimental data is essential in molecular modeling. This is often done by iteratively tuning the molecular force field of a simulation to match experimental data. An alternative method is to bias a simulation, leading to a hybrid model composed of the original force field and biasing terms. Previously we introduced such a method called experiment directed simulation (EDS). EDS minimally biases simulations to match average values. We also introduce a new method called experiment directed metadynamics (EDM) that creates minimal biases for matching entire free energy surfaces such as radial distribution functions and phi/psi angle free energies. It is also possible with EDM to create a tunable mixture of the experimental data and free energy of the unbiased ensemble with explicit ratios. EDM can be proven to be convergent, and we also present proof, via a maximum entropy argument, that the final bias is minimal and unique. Examples of its use are given in the construction of ensembles that follow a desired free energy. Finally, the example systems studied include a Lennard-Jones fluid made to match a radial distribution function, an atomistic model augmented with bioinformatics data, and a three-component electrolyte solution where ab initio simulation data is used to improve a classical empirical model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Photon entanglement entropy as a probe of many-body correlations and fluctuations

Recent theories and experiments have explored the use of entangled photons as a spectroscopic probe of physical systems. In this work, we describe here a theoretical description for entropy production in the scattering of an entangled biphoton Fock state within an optical cavity. We develop this using perturbation theory by expanding the biphoton scattering matrix in terms of single-photon terms in which we introduce the photon-photon interaction via a complex coupling constant, ξ. We show that the von Neumann entropy provides a concise measure of this interaction. We then develop a microscopic model and show that in the limit of fast fluctuations, the entanglement entropy vanishes, whereas in the limit of slow fluctuations, the entanglement entropy depends on the magnitude of the fluctuations and reaches a maximum. In conclusion, our result suggests that experiments measuring biphoton entanglement give microscopic information pertaining to exciton-exciton correlations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Ion Transport in Concentrated Crosslinked Solid Polymer Electrolytes

Crosslinking polymers is a common approach to create mechanically stable solid materials such as polymer electrolytes for lithium batteries. In conventional liquid electrolytes, the solvent molecules move freely to accommodate the field-induced motion of ions. However, in crosslinked polymer electrolytes, the rearrangement of polymer segments is constrained by the deformation limits of the network. Herein, we develop a new transport model that accounts for both the formation of concentration gradients and the elasticity of the electrolyte. The elasticity is incorporated by adding an additional term related to the entropy of crosslinked strands to the electrochemical potential of the salt. The resulting Crosslink Model contains two adjustable parameters: $\mathcal{N}$, the average number of monomers in a strand, and λ crit , the maximum strain the network can sustain. These solid-like constraints produce singularities in the governing transport equations, fundamentally altering the concentration profiles. Plateaus in salt concentrations emerge near the electrodes, and network elasticity introduces a strain overpotential. When compared to a Baseline Model ($\mathcal{N}$ → ∞, equivalent to concentrated solution theory), which predicts steepest gradients near the electrodes, both models yield similar current–voltage relationships. Model predictions are compared to electrochemical data for a poly(ethylene oxide)-based crosslinked polymer electrolyte.

Patel, Vivaan [University of California, Berkeley,↗
DOE OSTI2017

SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (∼> 10{sup 5}) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that are motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |ℓ|<90{sup o} and | b |<20{sup o}, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Effect of total and pair configurational entropy in determining dynamics of supercooled liquids over a range of densities

In this paper, we present a study of supercooled liquids interacting with the Lennard Jones potential and the corresponding purely repulsive (Weeks-Chandler-Andersen) potential, over a range of densities and temperatures, in order to understand the origin of their different dynamics in spite of their structures being similar. Using the configurational entropy as the thermodynamic marker via the Adam Gibbs relation, we show that the difference in the dynamics of these two systems at low temperatures can be explained from thermodynamics. At higher densities both the thermodynamical and dynamical difference between these model systems decrease, which is quantitatively demonstrated in this paper by calculating different parameters. The study also reveals the origin of the difference in pair entropy despite the similarity in the structure. Although the maximum difference in structure is obtained in the partial radial distribution function of the B type of particles, the rdf of AA pairs and AB pairs gives rise to the differences in the entropy and dynamics. This work supports the observation made in an earlier study [A. Banerjee et al., Phys. Rev. Lett. 113, 225701 (2014)] and shows that they are generic in nature, independent of density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

THE GALACTIC {sup 26}AL EMISSION MAP AS REVEALED BY INTEGRAL SPI

Diffuse emission is often challenging since it is undetectable by most instruments, which are generally dedicated to point-source studies. The {sup 26}Al emission is a good illustration: the only available {sup 26}Al map to date has been released, more than 15 yr ago, thanks to the COMPTEL instrument. However, at the present time, the SPI spectrometer aboard the International Gamma-Ray Astrophysics Laboratory mission offers a unique opportunity to enrich this first result. In this paper, 2 × 10{sup 8} s of data accumulated between 2003 and 2013 are used to perform a dedicated analysis, aiming to deeply investigate the spatial morphology of the {sup 26}Al emission. The data are first compared with several sky maps based on observations at various wavelengths to model the {sup 26}Al distribution throughout the Galaxy. For most of the distribution models, the inner Galaxy flux is compatible with a value of 3.3 × 10{sup −4} photons cm{sup −2} s{sup −1}, while the preferred template maps correspond to young stellar components such as core-collapse supernovae (SNe), Wolf–Rayet stars, and massive AGB stars. To get more details about this emission, an image reconstruction is performed using an algorithm based on the maximum-entropy method. In addition to the inner Galaxy emission, several excesses suggest that some sites of emission are linked to the spiral arm structure. Lastly, an estimation of the {sup 60}Fe line flux, assuming a spatial distribution similar to {sup 26}Al line emission, results in a {sup 60}Fe-to-{sup 26}Al ratio around 0.14, which agrees with the most recent studies and with the SN explosion model predictions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Off-policy deep reinforcement learning with automatic entropy adjustment for adaptive online grid emergency control

Electric overloading conditions and contingencies put modern power systems at risk of voltage collapse and blackouts. Load shedding is crucial to maintain voltage stability for grid emergency control. However, the rule- or model-based schemes rely on accurate dynamic system models and face considerable challenges in adapting to various operating conditions and uncertain event occurrences. Here, to address these issues, this paper proposes a novel deep reinforcement learning (DRL)-based voltage stability control algorithm with automatic entropy adjustment (AEA) for grid emergency control. Various dynamic network components for complex system operations are modeled to construct the DRL environment. An off-policy soft actor-critic architecture is developed to maximize the expected reward and policy entropy simultaneously. The AEA mechanism is proposed to facilitate the policy maximum entropy procedure, and the proposed method can automatically provide effective discrete and continuous actions against various fault scenarios. Our approach accomplishes high sampling efficiency, scalability, and auto-adaptivity of the control policies under high uncertainties. Comparative studies with the existing DRL-based control methods in IEEE benchmarks indicate salient performance improvement of the proposed method for dynamic system emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗
DOE OSTI2020

Discerning the thermodynamic feasibility of the spontaneous coexistence of multiple functional vegetation groups

Can the Second Law of Thermodynamics explain why ecosystems naturally organize into a complex structure composed of multiple vegetation species and functional groups? Ecosystem structure, which refers to the number and type of plant functional groups, is the result of self-organization, or the spontaneous emergence of order from random fluctuations. By considering ecosystems as open thermodynamic systems, we model and study these fluctuations of throughput signatures on short timescales to determine the drivers and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of energy and entropy to calculate an ecosystem’s estimated work and understand the thermodynamic behavior of the system. We use a multi-layer canopy-root-soil model to calculate the energy and entropy fluxes of different scenarios for field sites across various climates. At each site, scenarios comprised of native individual plant functional groups and a coexisting multi-group composition scenario including all functional groups observed at the site are compared. Ecosystem-scale calculations demonstrate that entropy fluxes and work efficiency—the work performed for the amount of radiation entering the ecosystem—are greatest in the multi-group scenario when its leaf area is significantly larger than each of its individual functional groups. Thus, we conclude that ecosystems self-organize towards the vegetation structure with the greatest outgoing entropy flux and work efficiency, resulting in the coexistence of multiple functional groups and performing the maximum amount of work within the constraints of locally available energy, water, and nutrients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Possible dynamical explanations for Paltridge's principle of maximum entropy production

Throughout the history of non-equilibrium thermodynamics a number of theories have been proposed in which complex, far from equilibrium flow systems are hypothesised to reach a steady state that maximises some quantity. Perhaps the most celebrated is Paltridge's principle of maximum entropy production for the horizontal heat flux in Earth's atmosphere, for which there is some empirical support. There have been a number of attempts to derive such a principle from maximum entropy considerations. However, we currently lack a more mechanistic explanation of how any particular system might self-organise into a state that maximises some quantity. This is in contrast to equilibrium thermodynamics, in which models such as the Ising model have been a great help in understanding the relationship between the predictions of MaxEnt and the dynamics of physical systems. In this paper we show that, unlike in the equilibrium case, Paltridge-type maximisation in non-equilibrium systems cannot be achieved by a simple dynamical feedback mechanism. Nevertheless, we propose several possible mechanisms by which maximisation could occur. Showing that these occur in any real system is a task for future work. The possibilities presented here may not be the only ones. We hope that by presenting them we can provoke further discussion about the possible dynamical mechanisms behind extremum principles for non-equilibrium systems, and their relationship to predictions obtained through MaxEnt.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Structural Heterogeneity in Medium-Entropy AgMnSbPbTe 4 for Glassy Thermal Transport and High Thermoelectric Performance

Medium-entropy semiconductors represent a unique category of entropy-engineered materials. They possess a considerable level of randomness in atomic mixing, although this is not sufficient to conclusively achieve single-phase structure stabilization, in contrast to high-entropy materials. This introduces strong competition between the formation of different phases, which can potentially lead to structural heterogeneity. Here, in this work, we uncover endotaxial nanoprecipitates in the microscopically identified homogeneous medium-entropy semiconductor AgMnSbPbTe 4 . These nanoprecipitates initially crystallize in a cubic phase $(Fm\bar{3}m)$ within kinetically stabilized AgMnSbPbTe 4 , subsequently evolving into a thermodynamically stable monoclinic phase $(P2_1/c)$ during thermal annealing while maintaining an endotaxial relationship with the matrix lattice. This nanophase segregation and the resultant lattice mismatch at interfaces introduce strain fluctuations up to 5% at intervals of 20 nm across the entire microstructure. Within the matrix phase, atomic displacement of up to 23 pm was observed. This structural heterogeneity results in glass-like thermal transport behavior, achieving an ultralow lattice thermal conductivity κ L = 0.312 Wm –1 K –1 at 800 K, which is in accordance with the amorphous limit predicted by the Cahill model. The synergy of band convergence effect and well-maintained carrier mobility leads to a maximum ZT of 1.72 at 800 K and an average ZT avg of 1.02 over the temperature range of 300–825 K. This study highlights that the underexplored structural heterogeneity in medium-entropy semiconductors can potentially yield beneficial phenomena, such as the phonon-glass electron-crystal transport behavior in this case, which holds promise for advancing thermoelectric applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Stochastic reconstructions of spectral functions: Application to lattice QCD

Here, we present a detailed study of the applications of two stochastic approaches, stochastic optimization method (SOM) and stochastic analytical inference (SAI), to extract spectral functions from Euclidean correlation functions. SOM has the advantage that it does not require prior information. On the other hand, SAI is a more generalized method based on Bayesian inference. Under mean field approximation SAI reduces to the often-used maximum entropy method (MEM), and for a specific choice of the prior SAI becomes equivalent to SOM. To test the applicability of these two stochastic methods to lattice QCD, Firstly, we apply these methods to various reasonably chosen model correlation functions, and present detailed comparisons of the reconstructed spectral functions obtained from SOM, SAI and MEM. Next, we present similar studies for charmonia correlation functions obtained from lattice QCD computations using clover-improved Wilson fermions on large, fine, isotropic lattices at 0:75 and 1:5 T c , T c being the deconfinement transition temperature of a pure gluon plasma. We find that SAI and SOM give consistent results to MEM at these two temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Oscillating magnetocaloric effect of a multilayer graphene

The oscillating magnetocaloric effect of a multilayer graphene in Bernal and rhombohedral stacking is investigated to extend the previous knowledge of the effect on a single layer graphene. We started from results of a tight-binding model and obtained analytical expressions for the thermodynamic potential and for the entropy change. The last exhibits the same dependence on field and temperature observed for other diamagnetic systems; it oscillates with the inverse magnetic field and presents a maximum value at a given temperature. The amplitude of the oscillating entropy change decreases with the number of layers and the stacking sequence rules the magnetocaloric properties of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Crossover from first-order to second-order phase transitions and magnetocaloric effect in La{sub 0.7}Ca{sub 0.3}Mn{sub 0.91}Ni{sub 0.09}O{sub 3}

We have prepared La{sub 0.7}Ca{sub 0.3}Mn{sub 0.91}Ni{sub 0.09}O{sub 3} and then studied its critical behavior and magnetocaloric effect. Analyzing temperature and field dependences of magnetization around the ferromagnetic-paramagnetic transition reveals the sample undergoing the second-order magnetic phase transition with the critical parameters T{sub C} ≈ 199.4 K, β = 0.171 ± 0.006, and γ = 0.976 ± 0.012. A considerable difference of these critical exponents compared with those expected for the standard models is due to the sample exhibiting the crossover property (tricriticality); its exponent values are more close to those expected for the tricritical mean-field theory with β = 0.25 and γ = 1. Under the field 40 kOe, the maximum magnetic entropy change (−ΔS{sub max}) around T{sub C} is about 7.1 J·kg{sup −1}·K{sup −1}, corresponding to a refrigerant capacity RC ≈ 170 J/kg. Particularly, its magnetic-field dependence obeys a power law |ΔS{sub max}| ∝ H{sup n}, where n = 0.55 is quite far from the value calculated from the relation n = 1 + (β − 1)/(β + γ)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Walking on the dark side: Anthropogenic factors limit suitable habitat for gray wolf ( Canis lupus ) in a large natural area covering Belarus and Ukraine

Due to successful conservation initiatives and legislations, the grey wolf (Canis lupus) is recolonising its historic range in Europe. However, wolves have never been extirpated across large areas in Eastern Europe but are often constrained to remote and inaccessible places due to centuries of persecution. This study aimed to identify the potentially suitable wolf habitats in Polesia, a massive cross-border lowland region extending over southern Belarus and northern Ukraine, which are often neglected in large carnivore studies at the continental scale. We hypothesized that anthropogenic rather than environmental factors govern wolf habitat suitability. We used a dataset of 4191 GPS locations obtained from radio-collared wolves (n = 26) and confirmed observations (n = 231) during 2014–2021 and applied maximum entropy method to estimate relative habitat suitability for wolves in Polesia. Artificial light at night (ALAN), proportion of cropland and tree cover were the most important factors affecting wolf habitat suitability. Road densities contributed poorly to predicting habitat suitability for wolves. Our models predicted a quarter of Polesia as suitable habitat and revealed priority areas connecting the important source populations in the Chornobyl Exclusion Zone in the east and the Bialowieza Forest in the west and thus essential for long-term wolf conservation. Our results provide the bases for effective, long-term wolf monitoring and management programs in both Belarus and Ukraine. However, national and transboundary wolf management in Polesia has been extremely challenging since 2022 due to the ongoing war and subsequent habitat degradation in this part of Europe.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Analytic closures for M1 neutrino transport

Carefully accounting for neutrino transport is an essential component of many astrophysical studies. Solving the full transport equation is too expensive for most realistic applications, especially those involving multiple spatial dimensions. For such cases, resorting to approximations is often the only viable option for obtaining solutions. One such approximation, which recently became popular, is the M1 method. It utilizes the system of the lowest two moments of the transport equation and closes the system with an ad hoc closure relation. The accuracy of the M1 solution depends on the quality of the closure. Several closures have been proposed in the literature and have been used in various studies. We carry out an extensive study of these closures by comparing the results of M1 calculations with precise Monte Carlo calculations of the radiation field around spherically symmetric protoneutron star models. We find that no closure performs consistently better or worse than others in all cases. The level of accuracy that a given closure yields depends on the matter configuration, neutrino type and neutrino energy. As a result, given this limitation, the maximum entropy closure by Minerbo on average yields relatively accurate results in the broadest set of cases considered in this work.

79 ASTRONOMY AND ASTROPHYSICS↗