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At least 631 records · Page 35

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NASA NTRSDate not supplied

Quantifying Emergent Fluid Dynamics Using Reynolds-Interpolated Fluid Reduced-order Models

Fluid reduced-order models (ROMs) which capture the flow physics within the problem's physical domain are usually constrained in accuracy to only the parameter points, e.g. Reynolds and Mach numbers, at which reference data was provided. Interpolation-focused quantity-of-interest ROMs are often structured differently and fail to provide flow volume data with the same quality - if at all. In this paper, techniques which reside at the intersection of these two ROM schools - flow physics ROMs which can be interpolated within a parameter space of interest - are explored. Using a combination of existing and novel techniques, emergent physics are identified using a fluid ROM at parameter points which are not provided in the ROM's training data.

uncertainty quantification↗

NASA NTRSDate not supplied

Quantifying Emergent Fluid Dynamics Using Reynolds-Interpolated Fluid Reduced-order Models

uncertainty quantification↗

DOE OSTI2022

Detailing cloud property feedbacks with a regime-based decomposition

Here, we report diagnosing the root causes of cloud feedback in climate models and reasons for inter-model disagreement is a necessary first step in understanding their wide variation in climate sensitivities. Here we bring together two analysis techniques that illuminate complementary aspects of cloud feedback. The first quantifies feedbacks from changes in cloud amount, altitude, and optical depth, while the second separates feedbacks due to cloud property changes within specific cloud regimes from those due to regime occurrence frequency changes. We find that in the global mean, shortwave cloud feedback averaged across ten models comes solely from a positive within-regime cloud amount feedback countered slightly by a negative within-regime optical depth feedback. These within-regime feedbacks are highly uniform: In nearly all regimes, locations, and models, cloud amount decreases and cloud albedo increases with warming. In contrast, global-mean across-regime components vary widely across models but are very small on average. This component, however, is dominant in setting the geographic structure of the shortwave cloud feedback: Thicker, more extensive cloud types increase at the expense of thinner, less extensive cloud types in the extratropics, and vice versa at low latitudes. The prominent negative extratropical optical depth feedback has contributions from both within- and across-regime components, suggesting that thermodynamic processes affecting cloud properties as well as dynamical processes that favor thicker cloud regimes are important. The feedback breakdown presented herein may provide additional targets for observational constraints by isolating cloud property feedbacks within specific regimes without the obfuscating effects of changing dynamics that may differ across timescales.

58 GEOSCIENCES↗

DOE OSTI2021

Perennial grass bioenergy cropping systems: Impacts on soil fauna and implications for soil carbon accrual

ABSTRACT Perennial grass energy crop production is necessary for the successful and sustainable expansion of bioenergy in North America. Numerous environmental advantages are associated with perennial grass cropping systems, including their potential to promote soil carbon accrual. Despite growing research interest in the abiotic and biotic factors driving soil carbon cycling within perennial grass cropping systems, soil fauna remain a critical yet largely unexplored component of these ecosystems. By regulating microbial activity and organic matter decomposition dynamics, soil fauna influence soil carbon stability with potentially significant implications for soil carbon accrual. We begin by reviewing the diverse, predominantly indirect effects of soil fauna on soil carbon dynamics in the context of perennial grass cropping systems. Since the impacts of perennial grass energy crop production on soil fauna will mediate their potential contributions to soil carbon accrual, we then discuss how perennial grass energy crop traits, diversity, and management influence soil fauna community structure and activity. We assert that continued research into the interactions of soil fauna, microbes, and organic matter will be important for advancing our understanding of soil carbon dynamics in perennial grass cropping systems. Furthermore, explicit consideration of soil faunal effects on soil carbon can improve our ability to predict changes in soil carbon following perennial grass cropping system establishment. We conclude by addressing the major knowledge gaps that should be prioritized to better understand and model the complex connections between perennial grass bioenergy systems, soil fauna, and carbon accrual.

sustainability↗

DOE OSTI2018

Sensitivity of Surface Temperature to Oceanic Forcing via q -Flux Green’s Function Experiments. Part II: Feedback Decomposition and Polar Amplification

A large set of Green’s function-type experiments is performed with q-flux forcings mimicking the effects of the ocean heat uptake (OHU) to examine the global surface air temperature (SAT) sensitivities to the location of the forcing. The result of the experiments confirms the earlier notion derived from experiments with different model complexities that the global mean SAT is far more sensitive to the oceanic forcing from high latitudes than the tropics. Remarkably, no matter in which latitude the q-flux forcings are placed, the SAT response is always characterized by a feature of polar amplification, implicating that it is intrinsic to our climate system. Considerable zonal asymmetry is also present in the efficacy of the tropical OHU, with the tropical eastern Pacific being much more efficient than the Indian Ocean and tropical Atlantic in driving global SAT warming by exciting the leading neutral mode of the SAT that projects strongly onto global mean warming. Using a radiative kernel, feedback analysis is also conducted to unravel the underlying processes responsible for the spatial heterogeneity in the global OHU efficacy, the polar amplification structures, and the tropical altruism of sharing the warmth with remote latitudes. Warming “altruism” for a q flux at a given latitude is also investigated in terms of the ratio of the induced remote latitudes versus the directly forced local warming. It is found that the tropics are much more altruistic than higher latitudes because of the high-energy transport efficiency of the Hadley circulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

A novel partitioning method for block-structured adaptive meshes

We propose a novel partitioning method for block-structured adaptive meshes utilizing the meshless Lagrangian particle concept. With the observation that an optimum partitioning has high analogy to the relaxation of a multi-phase fluid to steady state, physically motivated model equations are developed to characterize the background mesh topology and are solved by multi-phase smoothed-particle hydrodynamics. In contrast to well established partitioning approaches, all optimization objectives are implicitly incorporated and achieved during the particle relaxation to stationary state. Distinct partitioning sub-domains are represented by colored particles and separated by a sharp interface with a surface tension model. In order to obtain the particle relaxation, special viscous and skin friction models, coupled with a tailored time integration algorithm are proposed. Numerical experiments show that the present method has several important properties: generation of approximately equal-sized partitions without dependence on the mesh-element type, optimized interface communication between distinct partitioning sub-domains, continuous domain decomposition which is physically localized and implicitly incremental. Therefore it is particularly suitable for load-balancing of high-performance CFD simulations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1999

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗

NASA NTRS1994

A simple hyperbolic model for communication in parallel processing environments

We introduce a model for communication costs in parallel processing environments called the 'hyperbolic model,' which generalizes two-parameter dedicated-link models in an analytically simple way. Dedicated interprocessor links parameterized by a latency and a transfer rate that are independent of load are assumed by many existing communication models; such models are unrealistic for workstation networks. The communication system is modeled as a directed communication graph in which terminal nodes represent the application processes that initiate the sending and receiving of the information and in which internal nodes, called communication blocks (CBs), reflect the layered structure of the underlying communication architecture. The direction of graph edges specifies the flow of the information carried through messages. Each CB is characterized by a two-parameter hyperbolic function of the message size that represents the service time needed for processing the message. The parameters are evaluated in the limits of very large and very small messages. Rules are given for reducing a communication graph consisting of many to an equivalent two-parameter form, while maintaining an approximation for the service time that is exact in both large and small limits. The model is validated on a dedicated Ethernet network of workstations by experiments with communication subprograms arising in scientific applications, for which a tight fit of the model predictions with actual measurements of the communication and synchronization time between end processes is demonstrated. The model is then used to evaluate the performance of two simple parallel scientific applications from partial differential equations: domain decomposition and time-parallel multigrid. In an appropriate limit, we also show the compatibility of the hyperbolic model with the recently proposed LogP model.

Stoica, Ion↗

DOE OSTI2018

Harmonic decomposition of three-particle azimuthal correlations at energies available at the BNL Relativistic Heavy Ion Collider

Here, we present measurements of three-particle correlations for various harmonics in Au+Au collisions at energies ranging from √ s NN=7.7 to 200 GeV using the STAR detector. The quantity < cos(mΦ 1 +nΦ 2 –(m+n)Φ 3 ) >, with Φ being the azimuthal angles of the particles is evaluated as a function of √ s NN, collision centrality, transverse momentum, p T , pseudorapidity difference, Δη, and harmonics (m and n). These data provide detailed information on global event properties such as the three-dimensional structure of the initial overlap region, the expansion dynamics of the matter produced in the collisions, and the transport properties of the medium. A strong dependence on Δη is observed for most harmonic combinations, which is consistent with breaking of longitudinal boost invariance. An interesting energy dependence is observed when one of the harmonics m,n, or m+n is equal to two, for which the correlators are dominated by the two-particle correlations relative to the second-harmonic event plane. These measurements can be used to constrain models of heavy-ion collisions over a wide range of temperature and baryon chemical potential.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Enthalpies of formation of polyhalite: A mineral relevant to salt repository

Polyhalite is an important coexisting mineral with halite in salt repositories for nuclear waste disposal, such as Waste Isolation Pilot Plant (WIPP) in Carlsbad, New Mexico. The thermal stability of this mineral is a key knowledge in evaluating the integrity of a salt repository in the long term, as water may release due to thermal decomposition of polyhalite. Previous studies on structural evolution of polyhalite at elevated temperatures laid the basis for detailed calorimetric measurements. Using high-temperature oxide-melt drop-solution calorimetry at 975 K with sodium molybdate as the solvent, we have determined the standard enthalpies of formation from constituent sulfates (ΔH° f,sul ), oxides (ΔH° f,ox ) and elements (ΔH° f,ele ) of a polyhalite sample with the composition of K 2 Ca 2 Mg(SO 4 ) 4 ·1.95H 2 O from the Salado formation at the WIPP site. The obtained results are: ΔH° f,sul = -152.5 ± 5.3 kJ/mol, ΔH° f,ox = -1926.1 ± 10.5 kJ/mol, and ΔH° f,ele = -6301.2 ± 9.9 kJ/mol. Furthermore, based on the estimated formation entropies of polyhalite, its standard Gibbs free energy of formation has been derived to be in the range of -5715.3 ± 9.9 kJ/mol to -5739.3 ± 9.9 kJ/mol. In conclusion, these determined thermodynamic properties provide fundamental parameters for modeling the stability behavior of polyhalite in salt repositories.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Microstructural pattern formation during liquid metal dealloying: Phase-field simulations and theoretical analyses

In recent years, liquid metal dealloying has emerged as a promising material processing method to generate micro- and nanoscale bicontinuous or porous structures. Most previous studies focused on the experimental characterization of the dealloying process and on the properties of the dealloyed materials, leaving the theoretical study incomplete to fully understand the fundamental mechanisms of the liquid metal dealloying process. In this paper, we use theoretical models and phase-field simulations to clarify the kinetics and pattern formation during liquid metal dealloying. Our investigation starts from a theoretical analysis of the 1D dissolution of a binary precursor alloy, which reveals that the 1D dissolution process involves two regimes. In the first regime, due to the low solubility of one of the elements in the melt, it accumulates at the solid-liquid interface, which reduces the dissolution kinetics. In the second regime, the interface kinetics reaches a stationary regime where both elements of the precursor alloy dissolve into the melt. Previous works revealed that in the early dealloying stage, the dealloying front is destabilized by an interfacial spinodal decomposition, which triggers the formation of interconnected ligaments. Here we extend this line of work by proposing a linear stability analysis able to predict the initial length scale of the ligaments formed in the initial stage of the dealloying. Combining this analysis with the 1D dissolution model proposed here enables us to better understand the initial conditions (composition of the precursor alloy and the melt) leading to a planar dissolution without interface destabilization. Finally, we report a strong influence of solid-state diffusion on dealloying. Although the solid-state diffusivity is four to five orders of magnitude smaller than in the liquid phase, it is found to affect both dissolution kinetics and ligament morphologies.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Conceptual design of extended magnetic probe set to improve 3D field detection in NSTX-U

Adding toroidal arrays of magnetic probes at the top and bottom of NSTX-U would improve both the detection of the multimodal plasma response to applied magnetic perturbations and the identification of the poloidal structure of unstable plasma modes, as well as contribute to the validation of MHD models, improve the understanding of the plasma response to external fields, and improve the error field correction. In this paper, the linear MHD code MARS-F/K has been used to identify poloidal locations that would improve the capability to measure stationary or near-stationary 3D fields that may result from the plasma response to external sources of non-axisymmetric fields. The study highlighted 6 poloidal positions where new arrays of both poloidal and radial magnetic field sensors would improve the poloidal resolution. Here, the proposed set of new arrays combined with the present ones is shown to be capable of measuring the poloidal structure of perturbations with n ≤ 6 and of detecting the multimodal plasma response. Assessment of the trade-off in the poloidal length of the probes leads to an ideal length between 10 cm and 30 cm. A method to configure the probes of a toroidal array based on the singular value decomposition condition number is proposed, and an ideal solution and a low-cost one are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications

In this work we introduce a novel two-level overlapping additive Schwarz preconditioner for accelerating the training of scientific machine learning applications. The design of the proposed preconditioner is motivated by the nonlinear two-level overlapping additive Schwarz preconditioner. The neural network parameters are decomposed into groups (subdomains) with overlapping regions. In addition, the network’s feed-forward structure is indirectly imposed through a novel subdomain-wise synchronization strategy and a coarse-level training step. Through a series of numerical experiments, which consider physicsinformed neural networks and operator learning approaches, we demonstrate that the proposed two-level preconditioner significantly speeds up the convergence of the standard (LBFGS) optimizer while also yielding more accurate machine learning models. Moreover, the devised preconditioner is designed to take advantage of model-parallel computations, which can further reduce the training time.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Electrochemical reactivity and passivation of organic electrolytes at spinel MgCrMnO 4 cathode interfaces for rechargeable high voltage magnesium-ion batteries

Magnesium transition metal oxides such as MgCr 2−x Mn x O 4 are promising high-voltage and high-capacity cathode materials for rechargeable magnesium batteries (RMBs). Understanding and improving the chemical and electrochemical stability of the cathode–electrolyte interface (CEI) has been the primary technical emphasis to enable this category of cathode materials, which has been significantly underexplored. Herein, in this study, we focus on investigating the fundamental mechanism of parasitic reactions at the charged surface of the high-voltage MgCrMnO 4 model cathode with different organic electrolytes. The aim is to reveal the underlying effect of anions and solvents responsible for the passivation behavior of the cathode by using three exemplary anions: [(CF 3 SO 2 ) 2 N] − (TFSI − ), Al[OC(CF 3 ) 3 ] 4 − (TPFA − ), and [CB 11 H 12 ] − (MC) and three solvents: diglyme (G2), triglyme (G3), and 3-methoxypropylamine (MPA). High precision leakage current measurements during potentiostatic hold reveal that the electrolyte solvent chemistry has a more profound impact than anion's on the passivation of the MgCrMnO 4 cathode surface during deintercalation of Mg 2+ . X-ray photoelectron spectroscopy exhibits the differences in CEI composition. Amine solvents like MPA show poor passivation due to a higher degree of solvent decomposition, while the thin and anion-derived CEI in glyme-based electrolytes is directly linked with the better passivation behavior on the cathode. Furthermore, we leverage the knowledge from these findings to modify the electrolyte structure by adding a solvent additive, with the goal of reducing the parasitic reaction.

25 ENERGY STORAGE↗

DOE OSTI2018

Kinematic Flexibility Analysis: Hydrogen Bonding Patterns Impart a Spatial Hierarchy of Protein Motion

Elastic network models (ENMs) and constraint-based, topological rigidity analysis are two distinct, coarse-grained approaches to study conformational flexibility of macromolecules. In the two decades since their introduction, both have contributed significantly to insights into protein molecular mechanisms and function. However, despite a shared purpose of these approaches, the topological nature of rigidity analysis, and thereby the absence of motion modes, has impeded a direct comparison. We present an alternative, kinematic approach to rigidity analysis, which circumvents these drawbacks. We introduce a novel protein hydrogen bond network spectral decomposition, which provides an orthonormal basis for collective motions modulated by noncovalent interactions, analogous to the eigenspectrum of normal modes. The zero modes decompose proteins into rigid clusters identical to those from topological rigidity, while nonzero modes rank protein motions by their hydrogen bond collective energy penalty. Our kinematic flexibility analysis bridges topological rigidity theory and ENM, enabling a detailed analysis of motion modes obtained from both approaches. Analysis of a large, structurally diverse data set revealed that collectivity of protein motions, reported by the Shannon entropy, is significantly reduced for rigidity theory compared to normal mode approaches. Strikingly, kinematic flexibility analysis suggests that the hydrogen bonding network encodes a protein-fold specific, spatial hierarchy of motions, which goes nearly undetected in ENM. This hierarchy reveals distinct motion regimes that rationalize experimental and simulated protein stiffness variations. Kinematic motion modes highly correlate with reported crystallographic B factors and molecular dynamics simulations of adenylate kinase. A formal expression for changes in free energy derived from the spectral decomposition indicates that motions across nearly 40% of modes obey enthalpy–entropy compensation. Taken together, our results suggest that hydrogen bond networks have evolved to modulate protein structure and dynamics, which can be efficiently probed by kinematic flexibility analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Isotopic Tracers for CO 2 Produced During A Planetary Impact Into Limestone Target Rocks

Terrestrial meteorite impacts have been directly linked with multiple mass extinction events throughout Earth’s history. Among these impacts, those that land in sedimentary target rocks are thought to generate large quantities of CO 2 via decarbonation. This injection of CO 2 into the atmosphere has the potential to alter the climate and threaten terrestrial habitability. The magnitude of this change depends upon the net amount of CO 2 released, which is controlled by how much CO 2 is produced by the impact, how much CO 2 is removed by back-reactions after the impact, and other post-impact CO 2 sinks. To interrogate the behavior of CO 2 release into the impact atmosphere, we present carbon (δ 13 C), oxygen (δ 18 O), and clumped (Δ 47 ) isotope results from carbonate clasts preserved within the impact breccia of the Steen River Impact Structure (SRIS) in Alberta, Canada. These clasts exhibit a ~65‰ range in δ 13 C and a ~5‰ variation in δ 18 O. However, while δ 13 C and δ 18 O are positively correlated, Δ 47 unexpectedly has a negative relationship with δ 13 C and δ 18 O. Based on prior assumptions, there would either be (1) no relationship with carbonate Δ 47 and the bulk ratios because Δ 47 would be reset at extreme impact temperatures, or (2) Δ 47 would have a positive correlation with the bulk ratios, reflecting gradual Δ 47 ‘resetting.’ To reconcile the SRIS result with these expectations, we conducted a series of in vacuo heating experiments at temperatures above calcite decomposition. As predicted by Rayleigh fractionation, these heating experiments generated depletions in δ 13 C and δ 18 O that increased with reaction time. Mimicking the SRIS results, these experiments also produced concomitant increases in Δ 47 . Using an adaptation of a mechanistic model for decomposition fractionation (Hayles & Killingsworth, 2022) we hypothesize that these exotic isotope trends are caused by Rayleigh fractionation and a Δ 47 kinetic isotope effect that results from the disproportionation of O to CaO and CO 2 during thermal decomposition. This high Δ 47 CO 2 subsequently exchanges with the residual CaCO 3 . This work highlights a potential pathway for identifying and quantifying CO 2 generation by impacts and builds on the relatively limited literature characterizing the behavior of carbonate clumped isotopes at very high geologic temperatures.

Multi-isotope systems↗

DOE OSTI2018

Simulations of relativistic quantum plasmas using real-time lattice scalar QED

Real-time lattice quantum electrodynamics (QED) provides a unique tool for simulating plasmas in the strong-field regime, where collective plasma scales are not well separated from relativistic-quantum scales. As a toy model, we study scalar QED, which describes self-consistent interactions between charged bosons and electromagnetic fields. To solve this model on a computer, we first discretize the scalar-QED action on a lattice, in a way that respects geometric structures of exterior calculus and U(1)-gauge symmetry. The lattice scalar QED can then be solved, in the classical-statistics regime, by advancing an ensemble of statistically equivalent initial conditions in time, using classical field equations obtained by extremizing the discrete action. To demonstrate the capability of our numerical scheme, we apply it to two example problems. The first example is the propagation of linear waves, where we recover analytic wave dispersion relations using numerical spectrum. The second example is an intense laser interacting with a one-dimensional plasma slab, where we demonstrate natural transition from wakefield acceleration to pair production when the wave amplitude exceeds the Schwinger threshold. Our real-time lattice scheme is fully explicit and respects local conservation laws, making it reliable for long-time dynamics. The algorithm is readily parallelized using domain decomposition, and the ensemble may also be computed using quantum parallelism in the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗