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Results for “differentiable simulation”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Differentiable Simulation of a Liquid Argon Time Projection Chamber

Liquid argon time projection chambers (LArTPCs) are widely used in particle detection for their tracking and calorimetric capabilities. The particle physics community actively builds and improves high-quality simulators for such detectors in order to develop physics analyses in a realistic setting. The ability of these simulators to mimic real, measured data is limited by the modeling of the physical detectors used for data collection. This modeling can be improved by performing dedicated calibration measurements. Conventional approaches calibrate individual detector parameters or processes one at a time. However, the impact of detector processes is entangled, making this a poor description of the underlying physics. We introduce a differentiable simulator that enables a gradient-based optimization, allowing for the first time a simultaneous calibration of all detector parameters. We describe the procedure of making a differentiable simulator, highlighting the challenges of retaining the physics quality of the standard, non-differentiable version while providing meaningful gradient information. We further discuss the advantages and drawbacks of using our differentiable simulator for calibration. Finally, we provide a starting point for extensions to our approach, including applications of the differentiable simulator to physics analysis pipelines.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A differentiable simulation package for performing inference of synchrotron-radiation-based diagnostics

The direction of particle accelerator development is ever-increasing beam quality, currents and repetition rates. This poses a challenge to traditional diagnostics that directly intercept the beam due to the mutual destruction of both the beam and the diagnostic. An alternative approach is to infer beam parameters non-invasively from the synchrotron radiation emitted in bending magnets. However, inferring the beam distribution from a measured radiation pattern is a complex and computationally expensive task. To address this challenge we present SYRIPY ( SYnchrotron Radiation In PYthon ), a software package intended as a tool for performing inference of synchrotron-radiation-based diagnostics. SYRIPY has been developed using PyTorch , which makes it both differentiable and able to leverage the high performance of GPUs, two vital characteristics for performing statistical inference. The package consists of three modules: a particle tracker, Lienard–Wiechert solver and Fourier optics propagator, allowing start-to-end simulation of synchrotron radiation detection to be carried out. SYRIPY has been benchmarked against SRW , the prevalent numerical package in the field, showing good agreement and up to a 50× speed improvement. Finally, we have demonstrated how SYRIPY can be used to perform Bayesian inference of beam parameters using stochastic variational inference.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Measurement of the liquid argon scintillation pulse shape using differentiable simulation in the coherent CAPTAIN-Mills experiment

The coherent CAPTAIN-Mills (CCM) experiment is a liquid argon (LAr) light collection detector searching for MeV-scale neutrino and beyond Standard Model physics signatures. Two hundred eight-inch photomultiplier tubes instrument the seven-ton fiducial volume with 50% photocathode coverage to detect light produced by charged particles. CCM’s light-based approach reduces requirements of LAr purity, compared to other detection technologies, such that sub-MeV particles can be reliably detected without additional LAr filtration and with 𝒪⁡(1) parts per million of common contaminants. We present a measurement of LAr light production and propagation parameters, with uncertainties, obtained from a sample of MeV-scale electromagnetic events. The optimization of this high-dimensional parameter space was facilitated by a differentiable optical photon Monte Carlo simulation and detailed photomultiplier tube response characterization. This result accurately predicts the timing and spatial distribution of light due to scintillation and Cherenkov emission in the detector. This is the first description of photon propagation in LAr to include several effects, including anomalous dispersion of the index of refraction near the ultraviolet resonance, Mie scattering from impurities, and Cherenkov light production.

Cherenkov detectors↗
DOE OSTI2023

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations

Characterizing the phase space distribution of particle beams in accelerators is a central part of accelerator understanding and performance optimization. However, conventional reconstruction-based techniques either use simplifying assumptions or require specialized diagnostics to infer high-dimensional (> $2D$) beam properties. In this Letter, we introduce a general-purpose algorithm that combines neural networks with differentiable particle tracking to efficiently reconstruct high-dimensional phase space distributions without using specialized beam diagnostics or beam manipulations. Furthermore, we demonstrate that our algorithm accurately reconstructs detailed 4D phase space distributions with corresponding confidence intervals in both simulation and experiment using a single focusing quadrupole and diagnostic screen. This technique allows for the measurement of multiple correlated phase spaces simultaneously, which will enable simplified 6D phase space distribution reconstructions in the future.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Four-dimensional phase-space reconstruction of flat and magnetized beams using neural networks and differentiable simulations

Beams with cross-plane coupling or extreme asymmetries between the two transverse phase spaces are often encountered in particle accelerators. Flat beams with large transverse-emittance ratios are critical for future linear colliders. Similarly, magnetized beams with significant cross-plane coupling are expected to enhance the performance of electron cooling in hadron beams. Preparing these beams requires precise control and characterization of the four-dimensional transverse phase space. In this study, we employ generative phase-space reconstruction techniques to rapidly characterize magnetized and flat-beam phase-space distributions using a conventional quadrupole-scan method. The reconstruction technique is experimentally demonstrated on an electron beam produced at the Argonne Wakefield Accelerator and successfully benchmarked against conventional diagnostics techniques. Specifically, we show that predicted beam parameters from the reconstructed phase-space distributions (e.g., as magnetization and flat-beam emittances) are in excellent agreement with those measured from the conventional diagnostic methods. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
NASA NTRS1973

Description and performance of the Langley differential maneuvering simulator

The differential maneuvering simulator for simulating two aircraft or spacecraft operating in a differential mode is described. Tests made to verify that the system could provide the required simulated aircraft motions are given. The mathematical model which converts computed aircraft motions into the required motions of the various projector gimbals is described.

Ashworth, B. R.↗
NASA NTRS1991

Differential thermal analysis of lunar soil simulant

Differential thermal analysis of a lunar soil simulant, 'Minnesota Lunar Simulant-1' (MLS-1) was performed. The MLS-1 was tested in as-received form (in glass form) and with another silica. The silica addition was seen to depress nucleation events which lead to a better glass former.

Tucker, D.↗
NASA NTRS1976

Application of a helicopter mathematical model to the Langley differential maneuvering simulator for use in a helicopter/fighter evasive maneuver study

A real time simulation study was conducted using a differential maneuvering simulator to determine and evaluate helicopter evasive maneuvers when attacked by fighter aircraft. A general helicopter mathematical model was modified to represent an H-53 helicopter. The helicopter model was compared to H-53 flight test data to determine any differences between the simulated and actual vehicles. The simulated helicopter was also subjectively validated by participating pilots. Two fighter mathematical models validated in previous studies were utilized for the attacking aircraft. The results of this simulation study have been verified in a flight test program conducted by the U. S. Air Force and were found to closely match the flight results.

Houck, J. A.↗
NASA NTRS1972

Differential maneuvering simulator data reduction and analysis software

A multielement data reduction and analysis software package has been developed for use with the Langley differential maneuvering simulator (DMS). This package, which has several independent elements, was developed to support all phases of DMS aircraft simulation studies with a variety of both graphical and tabular information. The overall software package is considered unique because of the number, diversity, and sophistication of the element programs available for use in a single study. The purpose of this paper is to discuss the overall DMS data reduction and analysis package by reviewing the development of the various elements of the software, showing typical results that can be obtained, and discussing how each element can be used.

Beasley, G. P.↗
DOE OSTI2022

Unsupervised discovery of nonlinear plasma physics using differentiable kinetic simulations

Plasma supports collective modes and particle–wave interactions that lead to complex behaviour in, for example, inertial fusion energy applications. While plasma can sometimes be modelled as a charged fluid, a kinetic description is often crucial for studying nonlinear effects in the higher-dimensional momentum–position phase space that describes the full complexity of the plasma dynamics. We create a differentiable solver for the three-dimensional partial-differential equation describing the plasma kinetics and introduce a domain-specific objective function. Using this framework, we perform gradient-based optimization of neural networks that provide forcing function parameters to the differentiable solver given a set of initial conditions. We apply this to an inertial-fusion-relevant configuration and find that the optimization process exploits a novel physical effect.

plasma nonlinear phenomena↗
NASA NTRS2012

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗
NASA NTRSDate not supplied

Beyond Low-Earth Orbit: Characterizing Immune and microRNA Differentials Following Simulated Deep Spaceflight Conditions in Mice

Spaceflight missions can cause immune system dysfunction in astronauts with little understanding of immune outcomes in deep space. This study assessed immune responses in mice following ground-based, simulated deep spaceflight conditions, compared to data from astronauts on ISS missions. For ground studies, we simulated microgravity using the hindlimb unloaded mouse model alone or in combination with acute simulated galactic cosmic rays or solar particle events irradiation. Immune profiling results revealed unique immune diversity following each experimental condition, suggesting each stressor results in distinct circulating immune responses, with clear consequences for deep spaceflight. Circulating plasma microRNA sequence analysis revealed involvement in immune system dysregulation. Furthermore, a large astronaut cohort showed elevated inflammation during LEO missions, thereby supporting our simulated ground experiments in mice. Herein, circulating immune biomarkers are defined by distinct deep space irradiation types coupled to simulated microgravity and could be targets for future space health initiatives.

deep spaceflight stressors↗
DOE OSTI2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of accelerator facilities. However, when using reverse-mode automatic differentiation, the memory usage continuously increases during the simulation, and can potentially exceed the available hardware memory - especially when costly space charge computation is included. To study the memory requirements for differentiable simulations, we have implemented space charge in Cheetah, a PyTorch-based beam tracking code that supports reverse-mode differentiation. We find that the memory usage for reverse-mode differentiation grows linearly with the number of macroparticles and cells, and that it is proportional to the number of space charge kicks involved in the simulation. This general scaling can be used to evaluate whether a given differentiable simulation is feasible given hardware memory constraints.

Dhamrait, Arjun↗
NASA NTRS1990

Development of realtime connected element interferometry at the Goldstone Deep Space Communications Complex

Connected-element interferometry (CEI) has the potential to provide high-accuracy angular spacecraft tracking on short baselines by making use of the very precise phase delay observable. Within the Goldstone Deep Space Communications Complex (DSCC), one of three tracking complexes in the NASA Deep Space Network, baselines of up to 21 km in length are available. Analysis of data from a series of short-baseline phase-delay interferometry experiments are presented to demonstrate the potential tracking accuracy on these baselines. Repeated differential observations of pairs of angularly close extragalactic radio sources were made to simulate differential spacecraft-quasar measurements. Fiber-optic data links and a correlation processor are currently being developed and installed at Goldstone for a demonstration of real-time CEI in 1990.

Edwards, C. D.↗
NASA NTRS1993

Phase transitions and 2D spherical convection in a large icy satellite

Three ice phase transitions, based on experimental and theoretical results, were incorporated into a 2D spherical convection model. These phase transitions are the exothermic Ice 1-2, the endothermic Ice 2-6, and the exothermic Ice 6-8 phase transitions. The fluid is assumed isoviscous and the anelastic liquid formulation was used. The object is an icy satellite whose physical characteristics resemble those of Ganymede or Callisto. Structural models, similar to those of Mueller and McKinnon, with different core sizes, i.e. with different degree of differentiation were studied. The shells, i.e. the mantle of the satellite, is heated both internally and from below to account for the decaying radiogenic heating and the heat flow from the solid core. The lower boundary of the mantle is rigid and isothermal, the upper boundary is isothermal. Calculations with rigid and shear stress free upper boundary are carried out in order to assess the role of the different boundary conditions. Two different Rayleigh numbers, depending on the assumed value of the viscosity, were used in the calculations and the thermal evolution of the satellite was studied. The suit of calculations presented demonstrates that phase transition cannot be ignored when the thermal evolution of a large icy satellite has to be studied. The importance of the construction of the realistic phase diagram for ice was also documented. On the other hand the degree of differentiation, simulated with the structures with different core's radius does not seem to drastically influence the overall behavior of the convective activity. Within the limits of our simulations, the post-accretional evolution seems to be independent on the degree of primordial differentiation.

Forni, O.↗