Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Development and case study of the liquid desiccant system module in sorption system simulation program (SorpSim)

Liquid desiccant systems (LDS) have recently seen an increase in research interest as they can utilize low-grade heat resources and separate the sensible and latent cooling loads by efficiently removing moisture in the air without cooling it to the dew point. Yet, simulation and analysis of LDS had remained complex and demanding due to the limited resources of LDS simulation tools. This work presents the new LDS module developed in the Sorption system Simulation program (SorpSim), which is an open-source and flexible platform for steady-state simulation and analysis of various sorption systems. First, the new LDS module containing a finite-difference model and an effectiveness-NTU model for the heat and mass transfer in LDS dehumidifier/regenerator component was introduced. Then the simulation results of the new module were verified using data from the literature. Lastly, a case study was carried out in SorpSim where an LDS cycle was built and simulated using the new module. The impacts of design and operating parameters on the simulated LDS performance were investigated. The parametric study revealed that a high source temperature improved moisture removal rate (MRR) but reduced the system coefficient of performance (COP); the COP increased monotonically with the desiccant solution recirculation ratio, while the MRR peaked at a ratio of 85%; and an internal solution heat exchanger with UA of 800 W/K was found to be sufficient for optimal performance under high recirculation ratios. The case study demonstrated the LDS module’s capability to facilitate the analysis of LDS design and operation. The LDS module can be further coupled with other component models in SorpSim to simulate and analyze various liquid-desiccant-based systems.

42 ENGINEERING↗
DOE OSTI2013

Adaptive scapula bone remodeling computational simulation: Relevance to regenerative medicine

Shoulder arthroplasty success has been attributed to many factors including, bone quality, soft tissue balancing, surgeon experience, and implant design. Improved long-term success is primarily limited by glenoid implant loosening. Prosthesis design examines materials and shape and determines whether the design should withstand a lifetime of use. Finite element (FE) analyses have been extensively used to study stresses and strains produced in implants and bone. However, these static analyses only measure a moment in time and not the adaptive response to the altered environment produced by the therapeutic intervention. Computational analyses that integrate remodeling rules predict how bone will respond over time. Recent work has shown that subject-specific two- and three dimensional adaptive bone remodeling models are feasible and valid. Feasibility and validation were achieved computationally, simulating bone remodeling using an intact human scapula, initially resetting the scapular bone material properties to be uniform, numerically simulating sequential loading, and comparing the bone remodeling simulation results to the actual scapula’s material properties. Three-dimensional scapula FE bone model was created using volumetric computed tomography images. Muscle and joint load and boundary conditions were applied based on values reported in the literature. Internal bone remodeling was based on element strain-energy density. Initially, all bone elements were assigned a homogeneous density. All loads were applied for 10 iterations. After every iteration, each bone element’s remodeling stimulus was compared to its corresponding reference stimulus and its material properties modified. The simulation achieved convergence. At the end of the simulation the predicted and actual specimen bone apparent density were plotted and compared. Location of high and low predicted bone density was comparable to the actual specimen. High predicted bone density was greater than actual specimen. Low predicted bone density was lower than actual specimen. Differences were probably due to applied muscle and joint reaction loads, boundary conditions, and values of constants used. Work is underway to study this. Nonetheless, the results demonstrate three dimensional bone remodeling simulation validity and potential. Such adaptive predictions take physiological bone remodeling simulations one step closer to reality. Computational analyses are needed that integrate biological remodeling rules and predict how bone will respond over time. We expect the combination of computational static stress analyses together with adaptive bone remodeling simulations to become effective tools for regenerative medicine research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Accelerating solidification process simulation for large-sized system of liquid metal atoms using GPU with CUDA

Molecular dynamics simulation is a powerful tool to simulate and analyze complex physical processes and phenomena at atomic characteristic for predicting the natural time-evolution of a system of atoms. Precise simulation of physical processes has strong requirements both in the simulation size and computing timescale. Therefore, finding available computing resources is crucial to accelerate computation. However, a tremendous computational resource (GPGPU) are recently being utilized for general purpose computing due to its high performance of floating-point arithmetic operation, wide memory bandwidth and enhanced programmability. As for the most time-consuming component in MD simulation calculation during the case of studying liquid metal solidification processes, this paper presents a fine-grained spatial decomposition method to accelerate the computation of update of neighbor lists and interaction force calculation by take advantage of modern graphics processors units (GPU), enlarging the scale of the simulation system to a simulation system involving 10 000 000 atoms. In addition, a number of evaluations and tests, ranging from executions on different precision enabled-CUDA versions, over various types of GPU (NVIDIA 480GTX, 580GTX and M2050) to CPU clusters with different number of CPU cores are discussed. The experimental results demonstrate that GPU-based calculations are typically 9∼11 times faster than the corresponding sequential execution and approximately 1.5∼2 times faster than 16 CPU cores clusters implementations. On the basis of the simulated results, the comparisons between the theoretical results and the experimental ones are executed, and the good agreement between the two and more complete and larger cluster structures in the actual macroscopic materials are observed. Moreover, different nucleation and evolution mechanism of nano-clusters and nano-crystals formed in the processes of metal solidification is observed with large-sized system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing

This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule provides a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are demonstrated in a physically realistic Brownian coagulation case. The computational accuracy is validated with benchmark solution of discrete-sectional method. The simulation results show that the comprehensive approach can attain very favorable improvement in cost without sacrificing computational accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial “patches” distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A fast method for optical simulation of flood maps of light-sharing detector modules

Optical simulation of the detector module level is highly desired for Position Emission Tomography (PET) system design. Commonly used simulation toolkits such as GATE are not efficient in the optical simulation of detector modules with complicated light-sharing configurations, where a vast amount of photons need to be tracked. Here, we present a fast approach based on a simplified specular reflectance model and a structured light-tracking algorithm to speed up the photon tracking in detector modules constructed with polished finish and specular reflector materials. We also simulated conventional block detector designs with different slotted light guide patterns using the new approach and compared the outcomes with those from GATE simulations. And while the two approaches generated comparable flood maps, the new approach was more than 200–600 times faster. The new approach has also been validated by constructing a prototype detector and comparing the simulated flood map with the experimental flood map. The experimental flood map has nearly uniformly distributed spots similar to those in the simulated flood map. In conclusion, the new approach provides a fast and reliable simulation tool for assisting in the development of light-sharing-based detector modules with a polished surface finish and using specular reflector materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Lowering entry barriers to developing custom simulators of distributed applications and platforms with SimGrid

Researchers in parallel and distributed computing (PDC) often resort to simulation because experiments conducted using a simulator can be for arbitrary experimental scenarios, are less resource-, labor-, and time-consuming than their real-world counterparts, and are perfectly repeatable and observable. Many frameworks have been developed to ease the development of PDC simulators, and these frameworks provide different levels of accuracy, scalability, versatility, extensibility, and usability. Further, the SimGrid framework has been used by many PDC researchers to produce a wide range of simulators for over two decades. Its popularity is due to a large emphasis placed on accuracy, scalability, and versatility, and is in spite of shortcomings in terms of extensibility and usability. Although SimGrid provides sensible simulation models for the common case, it was difficult for users to extend these models to meet domain-specific needs. Furthermore, SimGrid only provided relatively low-level simulation abstractions, making the implementation of a simulator of a complex system a labor-intensive undertaking. In this work we describe developments in the last decade that have contributed to vastly improving extensibility and usability, thus lowering or removing entry barriers for users to develop custom SimGrid simulators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Impact of detector simulation in particle physics collider experiments

Through the last three decades, precise simulation of the interactions of particles with matter and modeling of detector geometries has proven to be of critical importance to the success of the international high-energy physics experimental programs. For example, the detailed detector modeling and accurate physics of the Geant4-based simulation software of the CMS and ATLAS particle physics experiments at the European Center of Nuclear Research (CERN) Large Hadron Collider (LHC) was a determinant factor for these collaborations to deliver physics results of outstanding quality faster than any hadron collider experiment ever before. This review article highlights the impact of detector simulation on particle physics collider experiments. It presents numerous examples of the use of simulation, from detector design and optimization, through software and computing development and testing, to cases where the use of simulation samples made a difference in the accuracy of the physics results and publication turnaround, from data-taking to submission. It also presents the economic impact and cost of simulation in the CMS experiment. Future experiments will collect orders of magnitude more data, taxing heavily the performance of simulation and reconstruction software for increasingly complex detectors. Consequently, it becomes urgent to find solutions to speed up simulation software in order to cope with the increased demand in a time of flat budgets. The study ends with a short discussion on the potential solutions that are being explored, by leveraging core count growth in multicore machines, using new generation coprocessors, and re-engineering of HEP code for concurrency and parallel computing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

Atomic configurations of glassy or amorphous materials containing medium-range order (MRO) may be identified by comparing fluctuation transmission electron microscopy (FTEM) measurements to FTEM simulations obtained using model configurations. Candidate model sizes have traditionally been much thinner than the samples measured experimentally, and publicly available FTEM simulation software has until now omitted microscope parameters, dynamical scattering, and the phase of the diffracted electron wave. We introduce MS–STEM–FEM, an open-source software package for simulating FTEM experiments using established multi-slice TEM simulation techniques to emulate experiment more closely by incorporating microscope parameters and simulating electron scattering and propagation as a complex valued wave. Simulations using established models are compared with results of experimental STEM–FEM to validate the software. Several statistical measures of diffraction are implemented and their responses to model features are compared. Dynamical scattering is found to be less influential than the variety of crystallite orientations which occur in thicker models. Simulations of variable resolution microscopy confirm that cumulative intensity of the FTEM signal decreases with reduced model MRO and increased coherence volume. In conclusion, advantageous model scaling characteristics and efficient processor performance scaling are demonstrated, along with a study of convergence with respect to pertinent simulation parameters to identify accuracy requirements.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States

Abstract Regional climate simulations over the continental United States were conducted for the 2011 warm season using the Weather Research and Forecasting model at convection‐permitting resolution (4 km) with two commonly used microphysics parameterizations (Thompson and Morrison). Sensitivities of the simulated mesoscale convective system (MCS) properties and feedbacks to large‐scale environments are systematically examined against high‐resolution geostationary satellite and 3‐D mosaic radar observations. MCS precipitation including precipitation amount, diurnal cycle, and distribution of hourly precipitation intensity are reasonably captured by the two simulations despite significant differences in their simulated MCS properties. In general, the Thompson simulation produces better agreement with observations for MCS upper level cloud shield and precipitation area, convective feature horizontal and vertical extents, and partitioning between convective and stratiform precipitation. More importantly, Thompson simulates more stratiform rainfall, which agrees better with observations and results in top‐heavier heating profiles from robust MCSs compared to Morrison. A stronger dynamical feedback to the large‐scale environment is therefore seen in Thompson, wherein an enhanced mesoscale vortex behind the MCS strengthens the synoptic‐scale trough and promotes advection of cool and dry air into the rear of the MCS region. The latter prolongs the MCS lifetimes in the Thompson relative to the Morrison simulations. Hence, different treatment of cloud microphysics not only alters MCS convective‐scale dynamics but also has significant impacts on their macrophysical properties such as lifetime and precipitation. As long‐lived MCSs produced 2–3 times the amount of rainfall compared to short‐lived ones, cloud microphysics parameterizations have profound impact in simulating extreme precipitation and the hydrologic cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Simulation ensemble for a laser–driven shear experiment

We perform an ensemble of simulations of a laser-driven shear experiment [L. Welser-Sherrill et al., “Two laser-driven mix experiments to study reshock and shear,” High Energy Density Phys. J. 9(3), 496–499 (2013)] in the strong-shock high energy-density regime to better understand material mixing driven by the Kelvin–Helmholtz instability. Each simulation uses a different realization of random initial interface perturbations based on data from targets used in experiments. Validation of the simulations is based on direct comparison of simulation and radiographic data. Simulations are also compared with published direct numerical simulation and the theory of homogeneous isotropic turbulence. Despite the fact that the flow is neither homogeneous, isotropic, nor fully turbulent, there are local regions in which the flow demonstrates characteristics of homogeneous isotropic turbulence. Our analysis shows characteristics consistent with those of incompressible isotropic turbulence. Our results show that turbulent features are present both near the shock front and in a separated region in the wake of the shock. These features develop and decay at different rates. Finally, we use the ensemble of three-dimensional simulations to test the performance of two-dimensional Reynolds-averaged Navier-Stokes simulations. In this context, we also test a presumed probability density function turbulent mixing model extensively used in combustion applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Nonlinear intrinsic variables and state reconstruction in multiscale simulations

Finding informative low-dimensional descriptions of high-dimensional simulation data (like the ones arising in molecular dynamics or kinetic Monte Carlo simulations of physical and chemical processes) is crucial to understanding physical phenomena, and can also dramatically assist in accelerating the simulations themselves. In this paper, we discuss and illustrate the use of nonlinear intrinsic variables (NIV) in the mining of high-dimensional multiscale simulation data. In particular, we focus on the way NIV allows us to functionally merge different simulation ensembles, and different partial observations of these ensembles, as well as to infer variables not explicitly measured. The approach relies on certain simple features of the underlying process variability to filter out measurement noise and systematically recover a unique reference coordinate frame. We illustrate the approach through two distinct sets of atomistic simulations: a stochastic simulation of an enzyme reaction network exhibiting both fast and slow time scales, and a molecular dynamics simulation of alanine dipeptide in explicit water.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Testing the high turbulence level breakdown of low-frequency gyrokinetics against high-frequency cyclokinetic simulations

This paper presents numerical simulations of the nonlinear cyclokinetic equations in the cyclotron harmonic representation [R. E. Waltz and Zhao Deng, Phys. Plasmas 20, 012507 (2013)]. Simulations are done with a local flux-tube geometry and with the parallel motion and variation suppressed using a newly developed rCYCLO code. Cyclokinetic simulations dynamically follow the high-frequency ion gyro-phase motion which is nonlinearly coupled into the low-frequency drift-waves possibly interrupting and suppressing gyro-averaging and increasing the transport over gyrokinetic levels. By comparing the more fundamental cyclokinetic simulations with the corresponding gyrokinetic simulations, the breakdown of gyrokinetics at high turbulence levels is quantitatively tested over a range of relative ion cyclotron frequency 10 < Ω*{sup }< 100 where Ω*{sup }= 1/ρ*, and ρ* is the relative ion gyroradius. The gyrokinetic linear mode rates closely match the cyclokinetic low-frequency rates for Ω*{sup }> 5. Gyrokinetic transport recovers cyclokinetic transport at high relative ion cyclotron frequency (Ω*{sup }≥ 50) and low turbulence level as required. Cyclokinetic transport is found to be lower than gyrokinetic transport at high turbulence levels and low-Ω* values with stable ion cyclotron (IC) modes. The gyrokinetic approximation is found to break down when the density perturbations exceed 20%. For cyclokinetic simulations with sufficiently unstable IC modes and sufficiently low Ω*{sup }∼ 10, the high-frequency component of cyclokinetic transport level can exceed the gyrokinetic transport level. However, the low-frequency component of the cyclokinetic transport and turbulence level does not exceed that of gyrokinetics. At higher and more physically relevant Ω*{sup }≥ 50 values and physically realistic IC driving rates, the low-frequency component of the cyclokinetic transport and turbulence level is still smaller than that of gyrokinetics. Thus, the cyclokinetic simulations do not account for the so-called “L-mode near edge short fall” seen in some low-frequency gyrokinetic transport and turbulence simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

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

One-dimensional particle-in-cell simulations of electrostatic Bernstein waves in plasmas with kappa velocity distributions

Electrostatic Bernstein waves that propagate exactly perpendicularly to a static magnetic field in an electron-ion plasma are investigated using one-and-two-halves dimensional particle-in-cell simulations. An ion-to-electron mass ratio of m{sub i}/m{sub e} = 100 is used, allowing sufficient separation of the electron and ion time scales while still accounting for the ion dynamics without resorting to exceptionally long simulation run times. As a consequence of the mass ratio used, both the high frequency electron Bernstein wave and the lower frequency ion Bernstein wave are resolved within a single simulation run. The simulations presented here use isotropic three-dimensional kappa velocity distributions as well as the widely used Maxwellian velocity distribution, and the results from using each of these velocity distributions are analysed and compared. The behaviour of the Bernstein waves is found to be significantly dependent on the spectral index, κ, of the kappa distribution in all frequency domains of the Bernstein waves. In both the Maxwellian and kappa cases, spectral analysis of the electric field (wave) intensities, as a function of ω and k, show very good agreement between the simulation results and the linear dispersion relation for Bernstein waves. This agreement serves to validate the simulation techniques used, as well as the theory of Bernstein waves in plasmas with a kappa velocity distribution. The intensity of the field fluctuations in the simulations containing an abundance of superthermal particles, i.e., where the plasma has a kappa velocity distribution with a low kappa index, is slightly higher compared to the simulations of plasmas with higher kappa values. The plasmas with low kappa values also exhibit a broader region in frequency space of high intensity field fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Cusps in the center of galaxies: a real conflict with observations or a numerical artefact of cosmological simulations?

Galaxy observations and N-body cosmological simulations produce conflicting dark matter halo density profiles for galaxy central regions. While simulations suggest a cuspy and universal density profile (UDP) of this region, the majority of observations favor variable profiles with a core in the center. In this paper, we investigate the convergency of standard N-body simulations, especially in the cusp region, following the approach proposed by [1]. We simulate the well known Hernquist model using the SPH code Gadget-3 and consider the full array of dynamical parameters of the particles. We find that, although the cuspy profile is stable, all integrals of motion characterizing individual particles suffer strong unphysical variations along the whole halo, revealing an effective interaction between the test bodies. This result casts doubts on the reliability of the velocity distribution function obtained in the simulations. Moreover, we find unphysical Fokker-Planck streams of particles in the cusp region. The same streams should appear in cosmological N-body simulations, being strong enough to change the shape of the cusp or even to create it. Our analysis, based on the Hernquist model and the standard SPH code, strongly suggests that the UDPs generally found by the cosmological N-body simulations may be a consequence of numerical effects. A much better understanding of the N-body simulation convergency is necessary before a 'core-cusp problem' can properly be used to question the validity of the CDM model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Refining fast calorimeter simulations with a Schrödinger Bridge

Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a fraction of the generation time. Nearly all methods proposed so far learn neural networks that map a random variable with a known probability density, like a Gaussian, to realistic-looking events. In many cases, physics events are not close to Gaussian and so these neural networks have to learn a highly complex function. We study an alternative approach: Schrödinger bridge Quality Improvement via Refinement of Existing Lightweight Simulations (SQuIRELS). SQuIRELS leverages the power of diffusion-based neural networks and Schrödinger bridges to map between samples where the probability density is not known explicitly. We apply SQuIRELS to the task of refining a classical fast simulation to approximate a full classical simulation. On simulated calorimeter events, we find that SQuIRELS is able to reproduce highly non-trivial features of the full simulation with a fraction of the generation time.

Calorimeter methods↗
DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗