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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Effects of Manufacturing Techniques on Neutron-Irradiated C26M Mechanical Properties

Nuclear energy provides 13% of the total energy produced globally. To further improve the safety and reliability of nuclear reactors material challenges need to be successfully resolved. C26M/FeCrAl alloy systems can improve the safety and reliability of current Generation III reactors due to the potential benefits of a stable passivation layer from the Al, which can protect against corrosion, and promising mechanical performance at boiling- and light-water reactor temperatures. However, information is limited on how manufacturing techniques affect the mechanical performance of C26M in neutron-irradiated environments. In this research, C26M specimens were manufactured using three techniques and then irradiated at the Advanced Test Reactor at Idaho National Laboratory. This research aims to bridge this gap by investigating how the manufacturing techniques affects the mechanical performance of irradiated C26M at Generation III reactor relevant temperatures.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Macroalgal Cultivation Modeling System (MACMODS): Evaluating the Role of Physical-Biological Coupling on Nutrients and Farm Yield

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera , predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Using Machine Learning for Quantum Annealing Accuracy Prediction

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or quadratic unconstrained binary optimization (QUBO) form. Although such solutions are typically of very high quality, problem instances are usually not solved to optimality due to imperfections of the current generations quantum annealers. In this contribution, we aim to understand some of the factors contributing to the hardness of a problem instance, and to use machine learning models to predict the accuracy of the D-Wave 2000Q annealer for solving specific problems. We focus on the maximum clique problem, a classic NP-hard problem with important applications in network analysis, bioinformatics, and computational chemistry. By training a machine learning classification model on basic problem characteristics such as the number of edges in the graph, or annealing parameters, such as the D-Wave’s chain strength, we are able to rank certain features in the order of their contribution to the solution hardness, and present a simple decision tree which allows to predict whether a problem will be solvable to optimality with the D-Wave 2000Q. We extend these results by training a machine learning regression model that predicts the clique size found by D-Wave.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Fueling the Future: The Emergence of Self-Powered Enzymatic Biofuel Cell Biosensors

Self-powered biosensors are innovative devices that can detect and analyze biological or chemical substances without the need for an external power source. These biosensors can convert energy from the surrounding environment or the analyte itself into electrical signals for sensing and data transmission. The self-powered nature of these biosensors offers several advantages, such as portability, autonomy, and reduced waste generation from disposable batteries. They find applications in various fields, including healthcare, environmental monitoring, food safety, and wearable devices. While self-powered biosensors are a promising technology, there are still challenges to address, such as improving energy efficiency, sensitivity, and stability to make them more practical and widely adopted. This review article focuses on exploring the evolving trends in self-powered biosensor design, outlining potential advantages and limitations. With a focal point on enzymatic biofuel cell power generation, this article describes various sensing mechanisms that employ the analyte as substrate or fuel for the biocatalyst’s ability to generate current. Technical aspects of biofuel cells are also examined. Research and development in the field of self-powered biosensors is ongoing, and this review describes promising areas for further exploration within the field, identifying underexplored areas that could benefit from further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Classification of Photovoltaic Failures with Hidden Markov Modeling, an Unsupervised Statistical Approach

Failure detection methods are of significant interest for photovoltaic (PV) site operators to help reduce gaps between expected and observed energy generation. Current approaches for field-based fault detection, however, rely on multiple data inputs and can suffer from interpretability issues. In contrast, this work offers an unsupervised statistical approach that leverages hidden Markov models (HMM) to identify failures occurring at PV sites. Using performance index data from 104 sites across the United States, individual PV-HMM models are trained and evaluated for failure detection and transition probabilities. This analysis indicates that the trained PV-HMM models have the highest probability of remaining in their current state (87.1% to 93.5%), whereas the transition probability from normal to failure (6.5%) is lower than the transition from failure to normal (12.9%) states. A comparison of these patterns using both threshold levels and operations and maintenance (O&M) tickets indicate high precision rates of PV-HMMs (median = 82.4%) across all of the sites. Although additional work is needed to assess sensitivities, the PV-HMM methodology demonstrates significant potential for real-time failure detection as well as extensions into predictive maintenance capabilities for PV.

classification↗
DOE OSTI2018

A Review on Low-Grade Thermal Energy Harvesting: Materials, Methods and Devices

Combined rejected and naturally available heat constitute an enormous energy resource that remains mostly untapped. Thermal energy harvesting can provide a cost-effective and reliable way to convert available heat into mechanical motion or electricity. This extensive review analyzes the literature covering broad topical areas under solid-state low temperature thermal energy harvesting. These topics include thermoelectricity, pyroelectricity, thermomagneticity, and thermoelasticity. For each topical area, a detailed discussion is provided comprising of basic physics, working principle, performance characteristics, state-of-the-art materials, and current generation devices. Technical advancements reported in the literature are utilized to analyze the performance, identify the challenges, and provide guidance for material and mechanism selection. The review provides a detailed analysis of advantages and disadvantages of each energy harvesting mechanism, which will provide guidance towards designing a hybrid thermal energy harvester that can overcome various limitations of the individual mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2020

One Planet or Two Planets? The Ultra-sensitive Extreme-magnification Microlensing Event KMT-2019-BLG-1953

We present the analysis of a very high-magnification (A ∼ 900) microlensing event KMT-2019-BLG-1953. A single-lens single-source (1L1S) model appears to approximately delineate the observed light curve, but the residuals from the model exhibit small but obvious deviations in the peak region. A binary-lens (2L1S) model with a mass ratio of q ∼ 2 × 10{sup −3} improves the fits by Δχ {sup 2} = 181.8, indicating that the lens possesses a planetary companion. From additional modeling by introducing an extra planetary lens component (3L1S model) and an extra source companion (2L2S model), it is found that the residuals from the 2L1S model further diminish, but claiming these interpretations is difficult due to the weak signals with Δχ {sup 2} = 16.0 and 13.5 for the 3L1S and 2L2L models, respectively. From a Bayesian analysis, we estimate that the host of the planets has a mass of M{sub host}=0.31{sub −0.17}{sup +0.37} M{sub ⊙} and that the planetary system is located at a distance of D{sub L}=7.04{sub −1.33}{sup +1.10} kpc toward the Galactic center. The mass of the securely detected planet is M{sub p}=0.64{sub −0.35}{sup +0.76} M{sub J}. The signal of the potential second planet could have been confirmed if the peak of the light curve had been more densely observed by follow-up observations, and thus the event illustrates the need for intensive follow-up observations for very high-magnification events even in the current generation of high-cadence surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Exoplanet Sciences with Nulling Interferometers and a Single-mode Fiber-fed Spectrograph

Understanding the atmospheres of exoplanets is a milestone to decipher their formation history and potential habitability. High-contrast imaging and spectroscopy of exoplanets is the major pathway toward the goal. Direct imaging of an exoplanet requires high spatial resolution. Interferometry has proven to be an effective way of improving spatial resolution. However, means of combining interferometry, high-contrast imaging, and high-resolution spectroscopy have been rarely explored. To fill in the gap, we present the dual-aperture fiber nuller (FN) for current-generation 8–10 m telescopes, which provides the necessary spatial and spectral resolution to (1) conduct follow-up spectroscopy of known exoplanets and (2) detect planets in debris-disk systems. The concept of feeding an FN to a high-resolution spectrograph can also be used for future space and ground-based missions. We present a case study of using the dual-aperture FN to search for biosignatures in rocky planets around M stars for a future space interferometry mission. Moreover, we discuss how an FN can be equipped on future extremely large telescopes by using the Giant Magellan Telescope as an example.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the Short-scale Spatial Variability of Electron Inflows in Electron-only Magnetic Reconnection in the Turbulent Magnetosheath Observed by MMS

We investigate the detailed properties of electron inflow in an electron-only reconnection event observed by the four Magnetospheric Multiscale (MMS) spacecraft in the Earth's turbulent magnetosheath downstream of the quasi-parallel bow shock. The lack of ion coupling was attributed to the small-scale sizes of the current sheets, and the observed bidirectional super-Alfvénic electron jets indicate that the MMS spacecraft crossed the reconnecting current sheet on both sides of an active X-line. Remarkably, the MMS spacecraft observed the presence of large asymmetries in the two electron inflows, with the inflows (normal to the current sheet) on the two sides of the reconnecting current layer differing by as much as a factor of four. Furthermore, even though the four MMS spacecraft were separated by less than seven electron skin depths, the degree of inflow asymmetry was significantly different at the different spacecraft. The asymmetry in the inflow speeds was larger with increasing distances downstream from the reconnection site, and the asymmetry was opposite on the two sides of the X-line. We compare the MMS observations with a 2D kinetic particle-in-cell (PIC) simulation and find that the asymmetry in the inflow speeds stems from in-plane currents generated via the combination of reconnection-mediated inflows and parallel flows along the magnetic separatrices in the presence of a large guide field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tearing-mediated Alfvénic Turbulence in a Relativistic Plasma

In astrophysical relativistic plasmas, Alfvénic turbulence exists across a wide range of scales. Similar to a nonrelativistic case, this turbulence can be influenced by the tearing instability. We argue that in an ultrarelativistic pair plasma the tearing effects become significant at the critical scale given by ${a}_{t}\sim {d}_{\mathrm{rel}}{\left({L}_{\perp }/{d}_{\mathrm{rel}}\right)}^{n/(4+5n)}$, where L ⊥ represents the outer scale of the turbulence and d rel the relativistic electron inertial scale. Here n = 1 corresponds to the Harris magnetic configurations, while n = 2 applies to localized (non-Harris) magnetic profiles of turbulence-generated current sheets. Below the critical scale, the energy spectrum of magnetic fluctuations steepens to W(k)dk ∝ k -(7n+2)/3n dk. However, this happens only when $\tilde{\sigma }\ll {\left({L}_{\perp }/{d}_{\mathrm{rel}}\right)}^{(2+4n)/(4+5n)}$, where $\tilde{\sigma }$ is the magnetization parameter based on the magnetic fluctuations. If the opposite inequality holds, the Alfvénic cascade is instead affected by charge starvation at scales below ${a}_{\mathrm{ch}}\sim {d}_{\mathrm{rel}}{\left({d}_{\mathrm{rel}}/{L}_{\perp }\right)}^{1/3}{\tilde{\sigma }}^{2/3}$, and the energy spectrum becomes steeper than W(k)dk ∝ k -3 dk. When d rel is replaced by its nonrelativistic equivalent, our results agree with the nonrelativistic analysis of N. F. Loureiro & S. Boldyrev (2018). In the Harris case n = 1, they agree with the recent relativistic studies by I. Demidov & Y. Lyubarsky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

GROWTH on S190426c: Real-time Search for a Counterpart to the Probable Neutron Star–Black Hole Merger using an Automated Difference Imaging Pipeline for DECam

The discovery of a transient kilonova following the gravitational-wave (GW) event GW170817 highlighted the critical need for coordinated rapid and wide-field observations, inference, and follow-up across the electromagnetic spectrum. In the southern hemisphere, the Dark Energy Camera (DECam) on the Blanco 4 m telescope is well suited to this task, as it is able to cover wide fields quickly while still achieving the depths required to find kilonovae like the one accompanying GW170817 to ~500 Mpc, the binary neutron star (NS) horizon distance for current generation of LIGO/Virgo collaboration (LVC) interferometers. Here, as part of the multi-facility follow-up by the Global Relay of Observatories Watching Transients Happen collaboration, we describe the observations and automated data movement, data reduction, candidate discovery, and vetting pipeline of our target-of-opportunity DECam observations of S190426c, the first possible NS-black hole merger detected in GWs. Starting 7.5 hr after S190426c, over 11.28 hr of observations, we imaged an area of 525 deg 2 ( r band) and 437 deg 2 ( z band); this was 16.3% of the total original localization probability, and nearly all of the probability visible from the southern hemisphere. The machine-learning-based pipeline was optimized for fast turnaround, delivering transients for human vetting within 17 minutes, on average, of shutter closure. We reported nine promising counterpart candidates 2.5 hr before the end of our observations. One hour after our data-taking ended (roughly 20 hr after the announcement of S190426c), LVC released a refined skymap that reduced the probability coverage of our observations to 8.0%, demonstrating a critical need for localization updates on shorter (~hour) timescales. Our observations yielded no detection of a bona fide counterpart to m z = 21.7 and m r = 22.2 at the 5σ level of significance, consistent with the refined LVC positioning. Here, we view these observations and rapid inferencing as an important real-world test for this novel end-to-end wide-field pipeline.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. For this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A parallel workflow implementation for PEST version 13.6 in high-performance computing for WRF-Hydro version 5.0: a case study over the midwestern United States

The Weather Research and Forecasting Hydrological (WRF-Hydro) system is a state-of-the-art numerical model that models the entire hydrological cycle based on physical principles. As with other hydrological models, WRF-Hydro parameterizes many physical processes. Hence, WRF-Hydro needs to be calibrated to optimize its output with respect to observations for the application region. When applied to a relatively large domain, both WRF-Hydro simulations and calibrations require intensive computing resources and are best performed on multimode, multicore high-performance computing (HPC) systems. Typically, each physics-based model requires a calibration process that works specifically with that model and is not transferrable to a different process or model. The parameter estimation tool (PEST) is a flexible and generic calibration tool that can be used in principle to calibrate any of these models. In its existing configuration, however, PEST is not designed to work on the current generation of massively parallel HPC clusters. To address this issue, we ported the parallel PEST to HPCs and adapted it to work with WRF-Hydro. The porting involved writing scripts to modify the workflow for different workload managers and job schedulers, as well as to connect the parallel PEST to WRF-Hydro. To test the operational feasibility and the computational benefits of this first-of-its-kind HPC-enabled parallel PEST, we developed a case study using a flood in the midwestern United States in 2013. Results on a problem involving the calibration of 22 parameters show that on the same computing resources used for parallel WRF-Hydro, the HPC-enabled parallel PEST can speed up the calibration process by a factor of up to 15 compared with commonly used PEST in sequential mode. The speedup factor is expected to be greater with a larger calibration problem (e.g., more parameters to be calibrated or a larger size of study area).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Interaction of radio frequency waves with cylindrical density filaments -- scattering and radiation pressure

The propagation of radio-frequency (RF) waves in tokamaks can be affected by filamentary structures, or blobs, that are present in the edge plasma and the scrape-off layer. The difference in the permittivity between the surrounding plasma and interior of a filament leads to reflection, refraction and diffraction of the waves. This, in turn, can affect the power flow into the core of the plasma and reduce the efficiency of heating and/or current generation. The scattering of RF waves, lower hybrid, helicon and ion cyclotron waves, by a single cylindrical filament, embedded in a background plasma, is studied using a full-wave analytical theory developed previously (Ram & Hizanidis, Phys. Plasmas, vol. 23, 2016, 022504). The theory assumes that the plasma in and around a filament is homogeneous and cold. A detailed scattering analysis reveals a variety of common features that exist among the three distinctly different RF waves. These common attributes can be inferred intuitively based on an examination of the cold plasma dispersion relation. The physical intuition is a useful step to understanding experimental observations on scattering, as well as results from simulations that include general forms of edge plasma turbulence. While a filament can affect the propagation of RF waves, the radiation force exerted by the waves can influence the filament. The force on a filament is determined using the Maxwell stress tensor. In 1905, Poynting was the first to evaluate and measure the radiation force on an interface separating two different dielectric media (Poynting, London Edinburgh Dublin Philos. Mag. J. Sci., vol. 9, 1905, pp. 393–406). For ordinary light propagating in vacuum and incident on a glass surface, Poynting noted that the surface is ‘pulled’ towards the vacuum. In a magnetized cold plasma, there are two independent wave modes. Even if only one of these modes is excited by an RF antenna, a filament will couple power to the other mode: a consequence of electromagnetic boundary conditions. This facet of scattering has consequences on the radiation force that go beyond Poynting's seminal contribution. The direction of the force depends on the polarization of the incident wave and on the mode structure of the waves inside and in the vicinity of a filament. It can either pull the filament toward the RF source or push it away. For slow lower hybrid waves, filaments with densities greater than the ambient density are pulled in, while filaments with lower densities are pushed out, thereby enhancing the density in front of the antenna. In the case of fast helicon and ion cyclotron waves, the direction of the force depends on the plasma and wave parameters; in particular, on the ambient density. The radiation force, in all three frequency ranges, is large enough to affect the motion of a filament and could be measured experimentally. This also suggests the possibility of modifying the edge turbulence using RF waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Diffraction of radio frequency waves by spatially modulated interfaces in the plasma edge in tokamaks

The use of radio frequency (RF) waves in fusion plasmas for heating, for non-inductive current generation, for profile control, and for diagnostics has been well established. The RF waves, excited by antenna structures placed near the wall of a fusion device, have to propagate through density fluctuations in the plasma edge. These fluctuations can modify the properties of the RF waves that propagate towards the core of the plasma. A full-wave electromagnetic computational code ScaRF based on the finite diifference frequency domain (FDFD) method has been developed to study the effect of density turbulence on RF waves. The anisotropic plasma permittivity used in the scattering studies is that for a magnetized, cold plasma. The code is used to study the propagation of an RF plane wave through a modulated, spatially periodic density interface. Such an interface could arise in the edge region due to magnetohydrodynamic instability or drift waves. The frequency of the plane wave is taken to be in the range of the electron cyclotron frequency. The scattering analysis is applicable to ITER-like plasmas, as well as to plasmas in medium sized tokamaks such as TCV, ASDEX-U, and DIII-D. The effect of diifferent density contrasts across the interface and of diifferent spatial modulations are discussed. While ScaRF is used to study a periodic density fluctuation, the code is general enough to include diifferent varieties of density fluctuations in the edge region -- such as blobs and filaments, and spatially random fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

An Experimental Platform for Pulsed-Power Driven Magnetic Reconnection

We describe a versatile pulsed-power driven platform for magnetic reconnection experiments, based on exploding wire arrays driven in parallel [Suttle, L. G. et al. PRL, 116, 225001]. This platform produces inherently magnetised plasma flows for the duration of the generator current pulse (250 ns), resulting in a long-lasting reconnection layer. The layer exists for long enough to allow evolution of complex processes such as plasmoid formation and movement to be diagnosed by a suite of high spatial and temporal resolution laser-based diagnostics. We can access a wide range of magnetic reconnection regimes by changing the wire material or moving the electrodes inside the wire arrays. We present results with aluminium and carbon wires, in which the parameters of the inflows and the layer which forms are significantly different. By moving the electrodes inside the wire arrays, we change how strongly the inflows are driven. This enables us to study both symmetric reconnection in a range of different regimes, and asymmetric reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Reflection and transmission of electromagnetic pulses at a planar dielectric interface -- theory and quantum lattice simulations

There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is described by Maxwell equations with an appropriate description of the plasma as a dielectric medium. Before advancing to the tensor dielectric of a magnetized plasma, this paper considers electromagnetic wave propagation in a one-dimensional inhomogeneous scalar dielectric. The classic theory of scattering of plane electromagnetic waves at a planar interface, separating two different dielectric media, leads to Fresnel equations for reflection and transmission coefficients. In contrast to plane waves, this paper is on the reflection and transmission of a spatially confined electromagnetic pulse. Following an analytical formulation for the scattering of a Gaussian pulse, it is deduced that the maximum transmission coefficient for a pulse is $\sqrt{n_2/n_1}$ times that for a plane wave; the incident and transmitted pulses propagating in dielectric media with refractive indices $n_1$ and $n_2$, respectively. The analytical theory is complemented by numerical simulations using a quantum lattice algorithm for Maxwell equations. The algorithm, based on the Riemann-Silberstein-Weber representation of the electromagnetic fields and expressed in term of qubits, is an interleaved sequence of entangling operators at each lattice site and unitary streaming operators which transmit information from one site to an adjacent lattice site. Besides substantiating results from the theory for Gaussian pulses, numerical simulations show their validity for non-Gaussian pulses. Apart from their time-asymptotic forms, the simulations display an interplay between the incident, reflected, and transmitted pulses in the vicinity of the transition region between two dielectric media.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗