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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Comparative study of adaptive variational quantum eigensolvers for multi-orbital impurity models

Hybrid quantum-classical embedding methods for correlated materials simulations provide a path towards potential quantum advantage. However, the required quantum resources arising from the multi-band nature of d and f electron materials remain largely unexplored. Here we compare the performance of different variational quantum eigensolvers in ground state preparation for interacting multi-orbital embedding impurity models, which is the computationally most demanding step in quantum embedding theories. Focusing on adaptive algorithms and models with 8 spin-orbitals, we show that state preparation with fidelities better than 99.9% can be achieved using about 2 14 shots per measurement circuit. When including gate noise, we observe that parameter optimizations can still be performed if the two-qubit gate error lies below 10 -3 , which is slightly smaller than current hardware levels. Finally, we measure the ground state energy on IBM and Quantinuum hardware using a converged adaptive ansatz and obtain a relative error of 0.7%.

42 ENGINEERING↗

DOE OSTI2019

Memristor design rules for dynamic learning and edge processing applications

The ability to dynamically learn and adapt to changes in the environment is one of the hallmarks of biological systems. In this work, we identify the subset of the design space of memristive materials that is optimal for dynamic learning applications. Using an architecture inspired on the learning center of the insect brain, we implement a model system consisting of a discrete implementation of spiking neurons where dynamic learning takes place on a set of plastic synapses formed by memristor pairs in a crossbar array. Using two separate benchmarks, one comprising the dynamic learning of the Modified National Institute of Standards and Technology dataset and another one targeting one shot learning, we have identified the key properties that memristive materials should have to be optimal dynamic learners. The results obtained show that a fine degree of control of the memristor internal state is key to achieve high classification accuracy during dynamic learning but that within this optimal region learning is extremely robust both to device variability and to errors in the writing of the internal state, in all cases allowing for 2 sigma variations greater than 40% without significant loss of accuracy, hence overcoming two of the perceived limitations of memristors. By additionally requiring that learning takes place concurrently to information processing, we are able to derive a set constraints to the memristor dynamics.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Deep learning based x-ray spectrometer for high repetition rate characterization of betatron radiation

Betatron radiation produced from a laser-wakefield accelerator is a broadband, hard x-ray (>1 keV) source that has been used in a variety of applications in medicine, engineering, and fundamental science. Further development and optimization of stable, high repetition rate (HRR) (>1 Hz) betatron sources will provide a means to extend their application base to include single-shot dynamical measurements of ultrafast processes or dense materials. Recent advances in laser technology used in such experiments have enabled increases in shot-rate and system stability, providing improved statistical analysis and detailed parameter scans. However, unique challenges exist at high repetition rate, where data throughput and source optimization are now limited by diagnostic acquisition rates and analysis. Here, we present the development of a machine-learning algorithm for the real-time analysis of betatron radiation. We report on the fielding of this deep learning algorithm for online source characterization at the Institut National de la Recherche Scientifique's Advanced Laser Light Source. By fine-tuning an algorithm originally trained on a fully synthetic dataset using a subset of experimental data, the algorithm can predict the betatron critical energy with a percent error of 7.2 % with a reconstruction time of 1.5 ms, providing a valuable tool for real-time, multi-objective optimization at HRR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Gas Gun Model and Comparison to Experimental Performance of Pipe Guns Operating with Light Propellant Gases and Large Cryogenic Pellets

Injection of multiple large (~10 to 30 mm diameter) shattered pellets into ITER plasmas is presently part of the scheme planned to mitigate the deleterious effects of disruptions on the vessel components. To help in the design and optimize performance of the pellet injectors for this application, a model referred to as “the gas gun simulator” has been developed and benchmarked against experimental data. The computer code simulator is a Java program that models the gas-dynamics characteristics of a single-stage gas gun. Following a stepwise approach, the code utilizes a variety of input parameters to incrementally simulate and analyze the dynamics of the gun as the projectile is launched down the barrel. Using input data, the model can calculate gun performance based on physical characteristics, such as propellant-gas and fast-valve properties, barrel geometry, and pellet mass. Although the model is fundamentally generic, the present version is configured to accommodate cryogenic pellets composed of H2, D2, Ne, Ar, and mixtures of them and light propellant gases (H2, D2, and He). The pellets are solidified in situ in pipe guns that consist of stainless steel tubes and fast-acting valves that provide the propellant gas for pellet acceleration (to speeds ~200 to 700 m/s). The pellet speed is the key parameter in determining the response time of a shattered pellet system to a plasma disruption event. The calculated speeds from the code simulations of experiments were typically in excellent agreement with the measured values. With the gas gun simulator validated for many test shots and over a wide range of physical and operating parameters, it is a valuable tool for optimization of the injector design, including the fast valve design (orifice size and volume) for any operating pressure (~40 bar expected for the ITER application) and barrel length for any pellet size (mass, diameter, and length). Key design parameters and proposed values for the pellet injectors for the ITER disruption mitigation systems are discussed.

Combs, Stephen Kirk↗

DOE OSTI2015

High-resolution single-shot spectral monitoring of hard x-ray free-electron laser radiation

We have developed an on-line spectrometer for hard x-ray free-electron laser (XFEL) radiation based on a nanostructured diamond diffraction grating and a bent crystal analyzer. Our method provides high spectral resolution, interferes negligibly with the XFEL beam, and can withstand the intense hard x-ray pulses at high repetition rates of >100 Hz. The spectrometer is capable of providing shot-to-shot spectral information for the normalization of data obtained in scientific experiments and optimization of the accelerator operation parameters. We have demonstrated these capabilities of the setup at the Linac Coherent Light Source, in self-amplified spontaneous emission mode at full energy of >1 mJ with a 120 Hz repetition rate, obtaining a resolving power of Ε/δΕ > 3 × 10 4 . In conclusion, the device was also used to monitor the effects of pulse duration down to 8 fs by analysis of the spectral spike width.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Optimization of Graded Bed Reactors for Syngas to Olefin (STO) Processes

Reactor designs with mixed catalysts play an important role to transform a multiple reactor system to single-shot reactors. In addition to savings in capital and ease of implementation, single-shot reactors are useful to break equilibrium limitations, therefore increasing the yield and selectivity of desired product. However, the nonlinear, highly exothermic and poorly conditioned nature of mixed-catalyst systems makes it difficult for commercial process simulation and optimization tools to optimize these systems. Here, this study describes the zone and partial moving finite element approaches and their applications to o-xylene oxidation and syngas to olefin (STO) processes. 35% and 5% increases are achieved in the product yield for o-xylene oxidation and STO problems, respectively. Shown with these two examples, this tool is very promising in process intensification for other reactive systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Startup regime of high-efficiency tapering-enhanced FEL oscillator

In this paper, we present a design of a high-efficiency high-gain free-electron laser oscillator based on the use of a strongly tapered undulator for extracting energy from high-brightness electron beams. We provide an analytical model of the setup followed by numerical simulations for lasing at the wavelength of 13.5 nm. We discuss the optimization of the system in steady state and the conditions necessary for the pass-per-pass buildup of the power from shot noise level. We propose the use of fast phase shifters as a way to accelerate the buildup. Finally, we present time-dependent simulations of the oscillator and discuss the role of spectral filtering. The optimized working point yields a total energy conversion efficiency from the electron beam to output radiation above 1% at the wavelength of 13.5 nm.

Beam dynamics↗

DOE OSTI2023

Machine learning-based surrogate models and transfer learning for derivative free optimization of HT-PEM fuel cells

Widespread adoption of high-temperature polymer electrolyte membrane electrochemical systems, such as fuel cells (HT-PEMFCs), requires models and computational tools for accurate optimization and guiding new materials for enhancing performance and durability. In this contribution, knowledge-based modelling and data-driven modelling are combined using Few-Shot Learning and implementing an Automated Machine Learning framework for the generation of Machine Learning-based surrogate models. Applicability of the resulting model for derivative-free optimization is demonstrated. Additionally, a way of considering extrapolation in the optimization task is presented. Results show that although extrapolation is needed to achieve better solutions during optimization, it can be monitored and managed. As a result, tuning the electrode ionomer binder's properties, such as ionic conductivity, in the fuel cell represents a promising pathway for improving HT-PEMFC performance.

08 HYDROGEN↗

DOE OSTI2026

Combined tracer analysis for DESI 2024 BAO

This paper demonstrates how the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) and future baryon acoustic oscillations (BAO) analyses can optimally combine overlapping tracers (galaxies of distinct types) in the same redshift range. We make a unified catalog of Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) in the redshift range 0.8 < z < 1.1 and investigate the impact on the BAO constraints. DESI DR1 contains ∼ 30% of the final DESI LRG sample and less than 25% of the final ELG sample, and the combination of LRGs and ELGs increases the number density and reduces the shot noise. We developed a pipeline to merge the overlapping tracers using galaxy bias as an approximately optimal weight and tested the pipeline on a suite of Abacus simulations, calibrated on the final version of the DESI Early Data Release. When applying our pipeline to the DESI DR1 catalog, we find an improvement in the BAO constraints of 11% for α iso and ∼ 7.0% for α AP consistent with our findings in mock catalogs. Our analysis was integrated into the DESI DR1 BAO analysis to produce theLRG+ELG result in the 0.8 < z < 1.1 redshift bin, which provided the most precise BAO measurement from DESI DR1 with a 0.86% constraint on the BAO distance scale and a 9.1σ detection of the isotropic BAO feature.

baryon acoustic oscillations↗

DOE OSTI2026

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗

DOE OSTI2022

Optimism is not a strategy: A white paper on how to give IFE a fighting chance to be real

With NIF shot N210808, we now have an existence proof of ignition (i.e. Lawson-like criteria exceeded and capsule gain well exceeding unity) in the laboratory and it has generated renewed interest in IFE. However, it is important to recognize that ignition on the NIF has been much more difficult than what was originally envisioned. Moreover, the design for the target that actually obtained burning plasma (Kritcher, Young, Robey, et al., Nature Phys. 2022; Zylstra, Hurricane, Callahan, et al., Nature, 601, 542, 2022) and ignition conditions is much different than the high gain design originally planned in the National Ignition Campaign (NIC; e.g. Lindl, Phys. Plasmas, 2, 3933, 1995; Lindl, Amendt, Berger, et al., Phys. Plasmas, 11, 339, 2004). In order to avoid squandering time and resources, the IFE community must learn the lessons of what happened on the NIF over the past decade.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Interaction of the high energy deuterons with the graphite target in the plasma focus devices based on Lee model

Numerical experiments are systematically carried out using the Lee model code extended to compute the ion beams on various plasma focus devices operated with Deuterium gas. The deuteron beam properties of the plasma focus are studied for low and high energy plasma focus device. The energy spectral distribution for deuteron ions ejected from the pinch plasma is calculated and the ion numbers with energy around 1 MeV is then determined. The deuteron–graphite target interaction is studied for different conditions. The yield of the reaction {sup 12}C(d,n){sup 13}N and the induced radioactivity for one and multi shots plasma focus devices in the graphite solid target is investigated. Our results present the optimized high energy repetitive plasma focus devices as an alternative to accelerators for the production of {sup 13}N short lived radioisotopes. However, technical challenges await solutions on two fronts: (a) operation of plasma focus machines at high rep rates for a sufficient period of time (b) design of durable targets that can take the thermal load.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

The design of the optical Thomson scattering diagnostic for the National Ignition Facility [The preliminary design of the optical Thomson scattering diagnostic for the National Ignition Facility]

Here, the National Ignition Facility (NIF) is a 192 laser beam facility designed to support the Stockpile Stewardship, High Energy Density and Inertial Confinement Fusion (ICF) programs. We report on the design of an Optical Thomson Scattering (OTS) diagnostic that has the potential to transform the community’s understanding of NIF hohlraum physics by providing first principle, local, time-resolved measurements of under-dense plasma conditions. The system design allows operation with different probe laser wavelengths by manual selection of the appropriate beam splitter and gratings before the shot. A deep-UV probe beam (λ 0 -210 nm) will be used to optimize the scattered signal for plasma densities of 5 × 10 20 electrons/cm 3 while a 3ω probe will be used for experiments investigating lower density plasmas of 1 × 10 19 electrons/cm 3 . We report the phase I design of a two phase design strategy. Phase I includes the OTS telescope, spectrometer, and streak camera; these will be used to assess the background levels at NIF. Phase II will include the design and installation of a probe laser.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2014

TH-A-9A-06: Inverse Planning of Gamma Knife Radiosurgery Using Natural Physical Models

Purpose: Treatment-planning systems rely on computer intensive optimization algorithms in order to provide radiation dose localization. We are investigating a new optimization paradigm based on natural physical modeling and simulations, which tend to evolve in time and find the minimum energy state. In our research, we aim to match physical models with radiation therapy inverse planning problems, where the minimum energy state coincides with the optimal solution. As a prototype study, we have modeled the inverse planning of Gamma Knife radiosurgery using the dynamic interactions between charged particles and demonstrate the potential of the paradigm. Methods: For inverse planning of Gamma Knife radiosurgery: (1) positive charges are uniformly placed on the surface of tumors and critical structures. (2) The Gamma Knife dose kernels of 4mm, 8mm and 16mm radii are modeled as geometric objects with variable charges. (3) The number of shots per each kernel radii is obtained by solving a constrained integer-linear problem. (4) The shots are placed into the tumor volume and move under electrostatic forces. The simulation is performed until internal forces are zero or maximum iterations are reached. (5) Finally, non-negative least squares (NNLS) is used to calculate the beam-on times for each shot. Results: A 3D C-shaped tumor surrounding a spherical critical structure was used for testing the new optimization paradigm. These tests showed that charges spread out evenly covering the tumor while keeping distance from the critical structure, resulting in a high quality plan. Conclusion: We have developed a new paradigm for dose optimization based on the simulation of physical models. As prototype studies, we applied electrostatic models to Gamma Knife radiosurgery and demonstrated the potential of the new paradigm. Further research and fine-tuning of the model are underway. NSF CBET-0853157.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Approaching hydro-equivalent ignition in laser direct-drive via target design optimization using novel statistical modeling

Laser direct-drive offers significant advantages in terms of target simplicity, improved energy coupling, and large fuel masses over indirect drive. However, performance degradations from hydrodynamic and laser-plasma instabilities seeded and driven by the direct illumination pose limitations on the parameter space available for achieving ignition. In this paper, new design improvements are identified to forge a path forward for a hydro-equivalent ignition demonstration. The first is related to a new formulation of the statistical model (SM) used to accurately predict target performance directly from input parameters such as laser pulse shape and target specifications. This new SM formulation provides direct guidance on target dimensions and laser beam-to-target radius to achieve the highest fusion yield on the OMEGA laser. The second improvement comes from cooling the deuterium–tritium (DT) ice layer below the triple point right before shot time leading to lower DT vapor densities and higher convergence. Guided by these design improvements, a Bayesian optimization algorithm was used to design an implosion that is predicted to closely approach a Lawson triple product that hydrodynamically scales to ignition if equivalent laser–target coupling is achieved at laser energies typical of the National Ignition Facility.

Deuterium↗

DOE OSTI2016

Gas Gun Model and Comparison to Experimental Performance of Pipe Guns Operating with Light Propellant Gases and Large Cryogenic Pellets

Combs, S. K.↗

DOE OSTI2024

Efficient prediction of attosecond two-colour pulses from an X-ray free-electron laser with machine learning

Abstract X-ray free-electron lasers are sources of coherent, high-intensity X-rays with numerous applications in ultra-fast measurements and dynamic structural imaging. Due to the stochastic nature of the self-amplified spontaneous emission process and the difficulty in controlling injection of electrons, output pulses exhibit significant noise and limited temporal coherence. Standard measurement techniques used for characterizing two-coloured X-ray pulses are challenging, as they are either invasive or diagnostically expensive. In this work, we employ machine learning methods such as neural networks and decision trees to predict the central photon energies of pairs of attosecond fundamental and second harmonic pulses using parameters that are easily recorded at the high-repetition rate of a single shot. Using real experimental data, we apply a detailed feature analysis on the input parameters while optimizing the training time of the machine learning methods. Our predictive models are able to make predictions of central photon energy for one of the pulses without measuring the other pulse, thereby leveraging the use of the spectrometer without having to extend its detection window. We anticipate applications in X-ray spectroscopy using XFELs, such as in time-resolved X-ray absorption and photoemission spectroscopy, where improved measurement of input spectra will lead to better experimental outcomes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗