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Results for “Reversible computation”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A new method to compute periodic orbits in general symplectic maps

The search of high-order periodic orbits has been typically restricted to problems with symmetries that help to reduce the dimension of the search space. Well-known examples include reversible maps with symmetry lines. The present work proposes a new method to compute high-order periodic orbits in twist maps without the use of symmetries. The method is a combination of the parameterization method in Fourier space and a Newton–Gauss multiple shooting scheme. The parameterization method has been successfully used in the past to compute quasi-periodic invariant circles. However, this is the first time that this method is used in the context of periodic orbits. Numerical examples are presented showing the accuracy and efficiency of the proposed method. Furthermore, the method is also applied to verify the renormalization prediction of the residues’ convergence at criticality (extensively studied in reversible maps) in the relatively unexplored case of maps without symmetries.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Interpreting the Operando X-ray Absorption Near-Edge Structure of Supported Cu and CuPd Clusters in Conditions of Oxidative Dehydrogenation of Propane: Dynamic Changes in Composition and Size

Supported subnano-cluster catalysts are highly dynamic, developing true active sites only under the pressures and temperatures of reaction conditions. Operando X-ray absorption near-edge structure (XANES) spectroscopy can track changes in the oxidation state and the local environment of cluster atoms, providing insight into the development of these active sites. While bulk metal, oxide, and hydroxide standards are often used for fitting experimental XANES spectra to obtain average oxidation states, we recently showed that computed cluster standards of relevant compositions are a more suitable basis, producing more accurate fits. Here, we theoretically interpret the operando XANES of supported Cu 3 Pd and Cu 4 clusters during temperature-programmed reaction (TPRx) of oxidative dehydrogenation of propane. We use an expanded basis set including both globally optimized computed clusters and bulk standards. Not only can we track reversible composition/oxidation state change with temperature, but also the irreversible growth of the bulk fraction upon heating, which we attribute to cluster sintering. This has important implications for the mechanism of the catalyzed reaction and the nature of the available active sites. Here, we propose that operando XANES provides most significant insight into the nature of supported cluster catalysts in reaction conditions when interpreted using mixed computed cluster and bulk standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Reversible Control of Interfacial Magnetism through Ionic-Liquid-Assisted Polarization Switching

The ability to control magnetism of materials via electric field enables a myriad of technological innovations in information storage, sensing, and computing. In this paper, we use ionic-liquid-assisted ferroelectric switching to demonstrate reversible modulation of interfacial magnetism in a multiferroic heterostructure composed of ferromagnetic (FM) La 0.8 Sr 0.2 MnO 3 and ferroelectric (FE) PbZr 0.2 Ti 0.8 O 3 . It is shown that ionic liquids can be used to persistently and reversibly switch a large area of a FE film. Finally, this is a prerequisite for polarized neutron reflectometry (PNR) studies that are conducted to directly probe magnetoelectric coupling of the FE polarization to the interfacial magnetization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Up‐And‐Coming Advances in Optical and Microwave Nonreciprocity: From Classical to Quantum Realm

Reciprocity is a fundamental physical principle that roots in the time‐reversal symmetry of physical laws. It allows making predictions on any arbitrary complex system's response and operation and hence simplifies the analysis. However, there are many practical situations in which it is advantageous to break reciprocity, e.g., isolators preventing wave scattering back to lasers and generators, full‐duplex systems for multiplexing transmission and receiving in the same channel, nonreciprocal cavity excitation, and protection of fragile states of superconductor quantum computers from thermal noise. The most widespread approach to time‐reversal symmetry breaking and nonreciprocity based on magnetic field biasing suffers from bulkiness, cost ineffectiveness, and loss, motivating researchers and engineers to search for more practical approaches. Herein, the up‐and‐coming advances in optical nonreciprocity, including new materials (Weyl semimetals, topological insulators, metasurfaces), active structures, time‐modulation, parity‐time (PT)‐symmetry breaking, nonlinearity combined with a structural asymmetry, quantum nonlinearity, unidirectional gain and loss, chiral quantum states and valley polarization are overviewed. A general description of nonreciprocal systems is provided and the pros and cons of the mentioned approaches to nonreciprocity are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Time reversal symmetry of generalized quantum measurements with past and future boundary conditions

Here we expand the time reversal symmetry arguments of quantum mechanics, originally proposed by Wigner in the context of unitary dynamics, to contain situations including generalized measurements for monitored quantum systems. We propose a scheme to derive the time-reversed measurement operators by considering the Schrödinger picture dynamics of a qubit coupled to a measuring device, and show that the time-reversed measurement operators form a Positive Operator Valued Measure (POVM) set. We present three particular examples to illustrate time reversal of measurement operators: (1) the Gaussian spin measurement, (2) a dichotomous POVM for spin, and (3) the measurement of qubit fluorescence. We then propose a general rule to unravel any rank two qubit measurement, and show that the backward dynamics obeys the retrodicted equations of the forward dynamics starting from the time reversed final state. We demonstrate the time reversal invariance of dynamical equations using the example of qubit fluorescence. We also generalize the discussion of a statistical arrow of time for continuous quantum measurements introduced by Dressel et al. (Phys Rev Lett 119:220507, 2017): we show that the backward probabilities can be computed from a process similar to retrodiction from the time-reversed final state, and extend the definition of an arrow of time to ensembles prepared with pre- and post-selections, where we obtain a non-vanishing arrow of time in general. We discuss sufficient conditions for when time’s arrow vanishes and show our method also captures the contributions to time’s arrow due to natural physical processes like relaxation of an atom to its ground state. As a special case, we recover the time reversibility of the weak value as its complex conjugate using our method, and discuss how our conclusions differ from the time-symmetry argument of Aharonov–Bergmann–Lebowitz rule.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Optimization of Forward Wave Modeling on Contemporary HPC Architectures

Reverse Time Migration (RTM) is one of the main approaches in the seismic processing industry for imaging the subsurface structure of the Earth. While RTM provides qualitative advantages over its predecessors, it has a high computational cost warranting implementation on HPC architectures. We focus on three progressively more complex kernels extracted from RTM: for isotropic (ISO), vertical transverse isotropic (VTI) and tilted transverse isotropic (TTI) media. In this work, we examine performance optimization of forward wave modeling, which describes the computational kernels used in RTM, on emerging multi- and manycore processors and introduce a novel common subexpression elimination optimization for TTI kernels. We compare attained performance and energy efficiency in both the single-node and distributed memory environments in order to satisfy industry’s demands for fidelity, performance, and energy efficiency. Moreover, we discuss the interplay between architecture (chip and system) and optimizations (both on-node computation) highlighting the importance of NUMA-aware approaches to MPI communication. Ultimately, our results show we can improve CPU energy efficiency by more than 10× on Magny Cours nodes while acceleration via multiple GPUs can surpass the energy-efficient Intel Sandy Bridge by as much as 3.6×.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Defying Thermodynamics: Stabilization of Alane Within Covalent Triazine Frameworks for Reversible Hydrogen Storage

The highly unfavorable thermodynamics of direct aluminum hydrogenation can be overcome by stabilizing alane within a nanoporous bipyridine-functionalized covalent triazine framework (AlH 3 @CTF-bipyridine). This material and the counterpart AlH 3 @CTF-biphenyl rapidly desorb H 2 between 95 and 154°C, with desorption complete at 250°C. Sieverts measurements, 27 Al MAS NMR and 27 Al{ 1 H} REDOR experiments, and computational spectroscopy reveal that AlH 3 @CTF-bipyridine dehydrogenation is reversible at 60°C under 700 bar hydrogen, >10 times lower pressure than that required to hydrogenate bulk aluminum. DFT calculations and EPR measurements support an unconventional mechanism whereby strong AlH 3 binding to bipyridine results in single-electron transfer to form AlH 2 (AlH 3 ) n clusters. Here the resulting size-dependent charge redistribution alters the dehydrogenation/rehydrogenation thermochemistry, suggesting a novel strategy to enable reversibility in high-capacity metal hydrides.

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

Statistics of time delay and scattering correlation functions in chaotic systems. I. Random matrix theory

We consider the statistics of time delay in a chaotic cavity having M open channels, in the absence of time-reversal invariance. In the random matrix theory approach, we compute the average value of polynomial functions of the time delay matrix Q = − iħS{sup †}dS/dE, where S is the scattering matrix. Our results do not assume M to be large. In a companion paper, we develop a semiclassical approximation to S-matrix correlation functions, from which the statistics of Q can also be derived. Together, these papers contribute to establishing the conjectured equivalence between the random matrix and the semiclassical approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Simulating energetic particle losses in JET plasmas with a reverse integration biasing scheme

We report that an integrated energetic particle transport model has been constructed in JET plasmas constrained by experimental fast ion loss measurements. The model incorporates a synthetic fast ion loss detector identical to JET’s thin-foil Faraday cup fast ion loss detector array. The loss model combines analyses from the TRANSP and ORBIT-kick codes with enhanced features for producing the synthetic diagnostic. Extensions to the ORBIT code framework allow a full-orbit representation within the vacuum region that can map particles directly to an installed detector geometry. Since synthetic fast ion loss detectors are plagued by weak loss statistics, a novel reverse integration biasing scheme has been implemented to boost computational efficiency. The model is validated against experimental loss measurements induced by long-lived kink modes and is found to be in good agreement. This confirms the development of a fully integrated transport/loss model which can be quantitatively verified against experiment allowing for future validation and predictive studies. The model is particularly useful for more complicated plasma scenarios that involve multiple fast ion species such as JET’s 2021 DT-campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Current profile redistribution driven by neutral beam injection in a reversed-field pinch

Neutral beam injection in reversed-field pinch (RFP) plasmas on the Madison Symmetric Torus [Dexter et al., Fusion Sci. Technol. 19, 131 (1991)] drives current redistribution with increased on-axis current density but negligible net current drive. Internal fluctuations correlated with tearing modes are observed on multiple diagnostics; the behavior of tearing mode correlated structures is consistent with flattening of the safety factor profile. The first application of a parametrized model for island flattening to temperature fluctuations in an RFP allows inferrence of rational surface locations for multiple tearing modes. The m = 1, n = 6 mode is observed to shift inward by 1.1 ± 0.6 cm with neutral beam injection. Tearing mode rational surface measurements provide a strong constraint for equilibrium reconstruction, with an estimated reduction of q{sub 0} by 5% and an increase in on-axis current density of 8% ± 5%. The inferred on-axis current drive is consistent with estimates of fast ion density using TRANSP [Goldston et al., J. Comput. Phys. 43, 61 (1981)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for. Computational modeling can aim to fulfill this expectation, thanks to the sustained growth of computing power and the collective engagement of the scientific community in developing more efficient and accurate workflows for predicting materials' performances. We discuss the impact that reproducibility and automation of the modeling protocols have on the field of gas adsorption in nanoporous crystals. We envision a platform that combines these tools and enables effective matching between promising materials and industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding

Direct oral anticoagulants (DOACs) targeting activated factor Xa (FXa) are used to prevent or treat thromboembolic disorders. DOACs reversibly bind to FXa and inhibit its enzymatic activity. However, DOAC treatment carries the risk of anticoagulant-associated bleeding. Currently, only one specific agent, andexanet alfa, is approved to reverse the anticoagulant effects of FXa-targeting DOACs (FXaDOACs) and control life-threatening bleeding. However, because of its mechanism of action, andexanet alfa requires a cumbersome dosing schedule, and its use is associated with the risk of thrombosis. Here, we present the computational design, engineering, and evaluation of FXa-variants that exhibit anticoagulation reversal activity in the presence of FXaDOACs. Our designs demonstrate low DOAC binding affinity, retain FXa-enzymatic activity and reduce the DOAC-associated bleeding by restoring hemostasis in mice treated with apixaban. Importantly, the FXaDOACs reversal agents we designed, unlike andexanet alfa, do not inhibit TFPI, and consequently, may have a safer thrombogenic profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The lightcone bootstrap and the spectrum of the 3d Ising CFT

In this paper. we compute numerically the dimensions and OPE coefficients of several operators in the 3d Ising CFT, and then try to reverse-engineer the solution to crossing symmetry analytically. Our key tool is a set of new techniques for computing infinite sums of SL(2,R) conformal blocks. Using these techniques, we solve the lightcone bootstrap to all orders in an asymptotic expansion in large spin, and suggest a strategy for going beyond the large spin limit. We carry out the first steps of this strategy for the 3d Ising CFT, deriving analytic approximations for the dimensions and OPE coefficients of several infinite families of operators in terms of the initial data $\{\Delta_\sigma,\Delta_\epsilon,f_{\sigma\sigma\epsilon},f_{\epsilon\epsilon\epsilon},c_T\}$. The analytic results agree with numerics to high precision for about 100 low-twist operators (correctly accounting for O(1) mixing effects between large-spin families). Plugging these results back into the crossing equations, we obtain approximate analytic constraints on the initial data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

An autoencoder compression approach for accelerating large-scale inverse problems

Abstract Partial differential equation (PDE)-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes required to accurately compute the PDE solution introduce an enormous number of parameters and require large-scale computing resources such as more processors and more memory to solve such systems in a reasonable time. For inverse problems constrained by time-dependent PDEs, the adjoint method often employed to compute gradients and higher order derivatives efficiently requires solving a time-reversed, so-called adjoint PDE that depends on the forward PDE solution at each timestep. This necessitates the storage of a high-dimensional forward solution vector at every timestep. Such a procedure quickly exhausts the available memory resources. Several approaches that trade additional computation for reduced memory footprint have been proposed to mitigate the memory bottleneck, including checkpointing and compression strategies. In this work, we propose a close-to-ideal scalable compression approach using autoencoders to eliminate the need for checkpointing and substantial memory storage, thereby reducing the time-to-solution and memory requirements. We compare our approach with checkpointing and an off-the-shelf compression approach on an earth-scale ill-posed seismic inverse problem. The results verify the expected close-to-ideal speedup for the gradient and Hessian-vector product using the proposed autoencoder compression approach. To highlight the usefulness of the proposed approach, we combine the autoencoder compression with the data-informed active subspace (DIAS) prior showing how the DIAS method can be affordably extended to large-scale problems without the need for checkpointing and large memory.

Mathematics↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Defying Thermodynamics: Stabilization of Alane Within Covalent Triazine Frameworks for Reversible Hydrogen Storage

Metastable metal hydrides such as AlH 3 have many attractive features as hydrogen storage media, but generally require complex reaction schemes for regeneration following H 2 release. Here in this paper, we demonstrate that the highly unfavorable thermodynamics of direct aluminum hydrogenation can be overcome by stabilizing alane within a nanoporous bipyridine-functionalized Covalent Triazine Framework (AlH 3 @CTF-bipyridine). This material and the counterpart AlH 3 @CTF-biphenyl rapidly desorb H 2 between 95 and 154 °C, with desorption complete at 250 °C. Sieverts measurements, 27 Al MAS NMR and 27 Al{ 1 H} REDOR experiments, and computational spectroscopy reveal that AlH 3 @CTF-bipyridine dehydrogenation is reversible at 60 °C under 700 bar hydrogen, >10 times lower pressure than that required to hydrogenate bulk aluminum. DFT calculations and EPR measurements support an unconventional mechanism whereby strong AlH 3 binding to bipyridine results in single-electron transfer to form AlH 2 (AlH 3 ) n clusters. The resulting size-dependent charge redistribution alters the dehydrogenation/rehydrogenation thermochemistry, suggesting a novel strategy to enable reversibility in high-capacity metal hydrides.

Coordination Chemistry↗