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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Evaluating WRF-Chem multi-scale model in simulating aerosol radiative properties over the tropics – A case study over India

We utilized WRF-Chem multi-scale model to simulate the regional distribution of aerosols, optical properties and its effect on radiation over India for a winter month. The model is evaluated using measurements obtained from upper-air soundings, AERONET sun photometers, various satellite instruments, and pyranometers operated by the Indian Meteorological Department. The simulated downward shortwave flux was overestimated when the effect of aerosols on radiation and clouds was neglected. Downward shortwave radiation from a simulation that included aerosol-radiation interaction processes was 5 to 25 Wm{sup -2} closer to the observations, while a simulation that included aerosol-cloud interaction processes were another 1 to 20 Wm{sup -2} closer to the observations. For the few observations available, the model usually underestimated particulate concentration. This is likely due to turbulent mixing, transport errors and the lack of secondary organic aerosol treatment in the model. The model efficiently captured the broad regional hotspots such as high aerosol optical depth over Indo-Gangetic basin as well as the northwestern and southern part of India. The regional distribution of aerosol optical depth compares well with AVHRR aerosol optical depth and the TOMS aerosol index. The magnitude and wavelength-dependence of simulated aerosol optical depth was also similar to the AERONET observations across India. Differences in surface shortwave radiation between simulations that included and neglected aerosol-radiation interactions were as high as -25 Wm{sup -2}, while differences in surface shortwave radiation between simulations that included and neglect aerosol-radiation-cloud interactions were as high as -30 Wm{sup -2}. The spatial variations of these differences were also compared with AVHRR observation. This study suggests that the model is able to qualitatively simulate the impact of aerosols on radiation over India; however, additional measurements of particulate mass and composition are needed to fully evaluate whether the aerosol precursor emissions are adequate when simulating radiative forcing in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗
DOE OSTI2014

Numerical Simulation of Carbon Dioxide Injection in the Western Section of the Farnsworth Unit

Numerical simulation is an invaluable analytical tool for scientists and engineers in making predictions about of the fate of carbon dioxide injected into deep geologic formations for long-term storage. Current numerical simulators for assessing storage in deep saline formations have capabilities for modeling strongly coupled processes involving multifluid flow, heat transfer, chemistry, and rock mechanics in geologic media. Except for moderate pressure conditions, numerical simulators for deep saline formations only require the tracking of two immiscible phases and a limited number of phase components, beyond those comprising the geochemical reactive system. The requirements for numerically simulating the utilization and storage of carbon dioxide in partially depleted petroleum reservoirs are more numerous than those for deep saline formations. The minimum number of immiscible phases increases to three, the number of phase components may easily increase fourfold, and the coupled processes of heat transfer, geochemistry, and geomechanics remain. Public and scientific confidence in the ability of numerical simulators used for carbon dioxide sequestration in deep saline formations has advanced via a natural progression of the simulators being proven against benchmark problems, code comparisons, laboratory-scale experiments, pilot-scale injections, and commercial-scale injections. This paper describes a new numerical simulator for the scientific investigation of carbon dioxide utilization and storage in partially depleted petroleum reservoirs, with an emphasis on its unique features for scientific investigations; and documents the numerical simulation of the utilization of carbon dioxide for enhanced oil recovery in the western section of the Farnsworth Unit and represents an early stage in the progression of numerical simulators for carbon utilization and storage in depleted oil reservoirs.

carbon sequestration↗
DOE OSTI2024

An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems

Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use. The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. Here we perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Comparison of three-dimensional morphologies of abnormally growing grains between Monte Carlo simulations and experiments of Fe-3% Si steel

Highlights: • Grains with sub-boundaries grew abnormally in the MC simulation with realistic grain boundary energy. • The experimental 3-D morphology of Goss grain was reconstructed from serially sectioned images. • 2-D sectioned microstructures of the MC simulation and experiment have highly irregular shape. • Both simulated and experimental 3-D morphologies of AGG have similar complicated shapes. - Abstract: Three-dimensional (3-D) Monte Carlo simulations of grain growth with sub-boundaries in the presence of precipitates were performed based on the distribution of realistic grain boundary energy data. The simulated grains with sub-boundaries grew abnormally. The simulated and experimental morphologies of the abnormally growing grains in Fe-3%Si steel were compared. The experimental 3-D morphology was reconstructed from serially sectioned images. Both the simulated and experimental 3-D morphologies of abnormally growing grains have highly irregular and complicated shapes whereas both the simulated and experimental 3-D morphologies of normally growing grains have relatively regular and simple shapes. Growth by wetting is responsible for the highly irregular shape of the experimental abnormally growing grains of Fe-3%Si steel as well as for the highly irregular shape of the simulated abnormally growing grains.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling of proton-induced radioactivation background in hard X-ray telescopes: Geant4-based simulation and its demonstration by Hitomi ’s measurement in a low Earth orbit

Hard X-ray astronomical observatories in orbit suffer from a significant amount of background due to radioactivation induced by cosmic-ray protons and/or geomagnetically trapped protons. Within the framework of a full Monte Carlo simulation, we present modeling of in-orbit instrumental background which is dominated by radioactivation. To reduce the computation time required by straightforward simulations of delayed emissions from activated isotopes, we insert a semi-analytical calculation that converts production probabilities of radioactive isotopes by interaction of the primary protons into decay rates at measurement time of all secondary isotopes. Therefore, our simulation method is separated into three steps: (1) simulation of isotope production, (2) semi-analytical conversion to decay rates, and (3) simulation of decays of the isotopes at measurement time. This method is verified by a simple setup that has a CdTe semiconductor detector, and shows a 100-fold improvement in efficiency over the straightforward simulation. To demonstrate its experimental performance, the simulation framework was tested against data measured with a CdTe sensor in the Hard X-ray Imager onboard the Hitomi X-ray Astronomy Satellite, which was put into a low Earth orbit with an altitude of 570 km and an inclination of 31°, and thus experienced a large amount of irradiation from geomagnetically trapped protons during its passages through the South Atlantic Anomaly. The simulation is able to treat full histories of the proton irradiation and multiple measurement windows. As a result, the simulation results agree very well with the measured data, showing that the measured background is well described by the combination of proton-induced radioactivation of the CdTe detector itself and thick Bi 4 Ge 3 O 12 scintillator shields, leakage of cosmic X-ray background and albedo gamma-ray radiation, and emissions from naturally contaminated isotopes in the detector system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A data-driven framework for error estimation and mesh-model optimization in system-level thermal-hydraulic simulation

We report over the past decades, several computer codes have been developed for simulation and analysis of thermal-hydraulics and system response in nuclear reactors under operating, abnormal transient, and accident conditions. However, simulation errors and uncertainties still inevitably exist even while these codes have been extensively assessed and used. In this work, a data-driven framework (Optimal Mesh/Model Information System, OMIS) is formulated and demonstrated to estimate simulation error and suggest optimal selection of computational mesh size (i.e., nodalization) and constitutive correlations (e.g., wall functions and turbulence models) for low-fidelity, coarse-mesh thermal-hydraulic simulation, in order to achieve accuracy comparable to that of high-fidelity simulation. Using results from high-fidelity simulations and experimental data with many fast-running low-fidelity simulations, an error database is built and used to train a machine learning model that can determine the relationship between local simulation error and local physical features. This machine learning model is then used to generate insight and help correct low-fidelity simulations for similar physical conditions. The OMIS framework is designed as a modularized six-step procedure and accomplished with state-of-the-art methods and algorithms. A mixed-convection case study was performed to illustrate the entire framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Vehicle energy consumption estimation using large scale simulations and machine learning methods

Vehicle energy consumption and powertrain operations for future vehicle powertrain technologies are predicted through full-vehicle simulations using Autonomie, a simulation tool developed at Argonne National Laboratory. Over 1 million vehicles, with different powertrain types (conventional and numerous electrified powertrains) and component technologies (advanced engines, batteries, electrical machines, light weighting) are simulated for outputs including vehicle fuel economy and cost. Despite the ability of Autonomic to predict fuel economy given various combination of vehicle inputs, the full-vehicle simulation is very time-consuming. It takes approximately 84 h to simulate for 33,060 vehicles even using distributed computing on a cluster of 128 worker nodes. Moreover, Autonomic is unable to populate a continuous output space through simulation since it only yields outputs with discrete values instead of an input-output relation. This paper proposes a novel large-scale learning and prediction process (LSLPP) via machine learning approaches to answer the need for a continuous space of vehicle fuel economy and a more efficient simulation process. By learning in a supervised fashion to discover structures in data, the machine learning approaches seek to train a model that can explain the data with which we can perform prediction over unseen data. As such, we are able to accomplish analytic continuation on the current discrete space of simulation results. In addition, we present a random sampling -based numerosity reduction algorithm incorporated in LSLPP that reduces simulation runs and improves efficiency of data procurement. We analytically derive a theoretical bound in order to guarantee the effectiveness of our algorithm. We also compare random sampling to stratified sampling and suggest sampling strategies. A user-friendly tool is developed to support the process. Our experimental results confirm that the proposed LSLPP is able to greatly accelerate prediction and analysis of vehicle fuel economy. The output of this study is used by the US government to evaluate the impact of its R&D funding on energy security and CO 2 emission as well as for the setting of Corporate Average Fuel Economy (CAFE) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

gRASPA

GPU Monte Carlo Simulation Code with a taste of RASPA We present enhancements in Monte Carlo simulation speed and functionality within an open-source code, gRASPA, which uses graphical processing units (GPUs) to achieve significant performance improvements compared to serial, CPU implementations of Monte Carlo. The code supports a wide range of Monte Carlo simulations, including canonical ensemble (NVT), grand canonical, NVT Gibbs, Widom test particle insertions, and continuous-fractional component Monte Carlo. Implementation of grand canonical transition matrix Monte Carlo (GC-TMMC) and a novel feature to allow different moves for the different components of metal-organic framework (MOF) structures exemplify the capabilities of gRASPA for precise free energy calculations and enhanced adsorption studies, respectively. The introduction of a High-Throughput Computing (HTC) mode permits many Monte Carlo simulations on a single GPU device for accelerated materials discovery. The code can incorporate machine learning (ML) potentials. The open-source nature of gRASPA promotes reproducibility and openness in science, and users may add features to the code and optimize it for their own purposes. The code is written in CUDA/C++ and SYCL/C++ to support different GPU vendors. The gRASPA code is publicly available at https://github.com/snurr-group/gRASPA.

Li, Zhao [Purdue/Northwestern/Notre Dame Universit↗
DOE OSTI2018

Sensitivities of Simulated Satellite Views of Clouds to Subgrid-Scale Overlap and Condensate Heterogeneity

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of this framework is to enable more robust evaluation of model cloud properties, so that differences between models and observations can more confidently be attributed to model errors. A critical step in this process is accounting for the difference between the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4-km global model output from the multiscale modeling framework to evaluate the sensitivity of simulated satellite retrievals to common assumptions about cloud and precipitation overlap and condensate variability used in climate models whose grid spacing is many tens to hundreds of kilometers. We find the simulated retrievals are sensitive to these assumptions. Using maximum-random overlap with homogeneous cloud and precipitation condensate leads to errors in Multiangle Imaging Spectroradiometer and International Satellite Cloud Climatology Project-simulated cloud cover and in CloudSat-simulated radar reflectivity that are significant compared to typical differences between the model simulations and observations. A more realistic treatment of unresolved clouds and precipitation is shown to substantially reduce these errors. The sensitivity to these assumptions underscores the need for the adoption of more realistic subcolumn treatments in models and the need for consistency among subcolumn assumptions between models and simulators to ensure that simulator-diagnosed errors are consistent with the model formulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Subpolar North Atlantic Water Mass Transformation and Overturning in Eddying and Non‐Eddying Simulations

Buoyancy forcing in the subpolar North Atlantic Ocean (SPNA) is an important driver of the Atlantic Meridional Overturning Circulation (AMOC). To advance understanding of the mechanisms connecting the two processes and their relative importance in sub-basins within the SPNA, we apply the Water Mass Transformation Framework to a matched-pair of forced, ocean-sea ice simulations configured at eddying and non-eddying resolution. Within the first decade of simulation, the non-eddying simulation produces a weak AMOC, ~11 Sv at 26.5 ° N, while the AMOC in the eddying simulation is more realistic and is thus analyzed for comparison. Surface water mass transformation and boundary transport are calculated in both density and temperature–salinity coordinates in three separate deep water formation regions, the Iceland Basin, the Irminger Sea and Labrador Sea, during the first decade of both simulations. We identify strong surface freshening in the Irminger and Labrador seas in the non-eddying simulation during the AMOC decline. This freshening significantly reduces the density of the surface outcrops where surface water mass formation occurs, essentially removing this contribution to deep water formation. Concurrently, boundary transports in these two regions are warmer and saltier in the non-eddying simulation compared to the eddying simulation where the density of surface water mass formation is stable. The warming and salinification of boundary transports in the non-eddying simulation is interpreted as an obstacle to deep water formation. Labrador Sea surface water mass transformation is important, despite its small contribution to buoyancy overturning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Variational fast forwarding for quantum simulation beyond the coherence time

Abstract Trotterization-based, iterative approaches to quantum simulation (QS) are restricted to simulation times less than the coherence time of the quantum computer (QC), which limits their utility in the near term. Here, we present a hybrid quantum-classical algorithm, called variational fast forwarding (VFF), for decreasing the quantum circuit depth of QSs. VFF seeks an approximate diagonalization of a short-time simulation to enable longer-time simulations using a constant number of gates. Our error analysis provides two results: (1) the simulation error of VFF scales at worst linearly in the fast-forwarded simulation time, and (2) our cost function’s operational meaning as an upper bound on average-case simulation error provides a natural termination condition for VFF. We implement VFF for the Hubbard, Ising, and Heisenberg models on a simulator. In addition, we implement VFF on Rigetti’s QC to demonstrate simulation beyond the coherence time. Finally, we show how to estimate energy eigenvalues using VFF.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Three dimensional particle-in-cell simulations of electron beams created via reflection of intense laser light from a water target

We present 3D Particle-in-Cell (PIC) modeling of an ultra-intense laser experiment by the Extreme Light group at the Air Force Research Laboratory using the Large Scale Plasma (LSP) PIC code. This is the first time PIC simulations have been performed in 3D for this experiment which involves an ultra-intense, short-pulse (30 fs) laser interacting with a water jet target at normal incidence. The laser-energy-to-ejected-electron-energy conversion efficiency observed in 2D(3v) simulations were comparable to the conversion efficiencies seen in the 3D simulations, but the angular distribution of ejected electrons in the 2D(3v) simulations displayed interesting differences with the 3D simulations' angular distribution; the observed differences between the 2D(3v) and 3D simulations were more noticeable for the simulations with higher intensity laser pulses. An analytic plane-wave model is discussed which provides some explanation for the angular distribution and energies of ejected electrons in the 2D(3v) simulations. We also performed a 3D simulation with circularly polarized light and found a significantly higher conversion efficiency and peak electron energy, which is promising for future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Mirrored continuum and molecular scale simulations of the ignition of high-pressure phases of RDX

We present a mirrored atomistic and continuum framework that is used to describe the ignition of energetic materials, and a high-pressure phase of RDX in particular. The continuum formulation uses meaningful averages of thermodynamic properties obtained from the atomistic simulation and a simplification of enormously complex reaction kinetics. In particular, components are identified based on molecular weight bin averages and our methodology assumes that both the averaged atomistic and continuum simulations are represented on the same time and length scales. The atomistic simulations of thermally initiated ignition of RDX are performed using reactive molecular dynamics (RMD). The continuum model is based on multi-component thermodynamics and uses a kinetics scheme that describes observed chemical changes of the averaged atomistic simulations. Thus the mirrored continuum simulations mimic the rapid change in pressure, temperature, and average molecular weight of species in the reactive mixture. This mirroring enables a new technique to simplify the chemistry obtained from reactive MD simulations while retaining the observed features and spatial and temporal scales from both the RMD and continuum model. The primary benefit of this approach is a potentially powerful, but familiar way to interpret the atomistic simulations and understand the chemical events and reaction rates. The approach is quite general and thus can provide a way to model chemistry based on atomistic simulations and extend the reach of those simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Kinematic evolution of simulated star-forming galaxies

Recent observations have shown that star-forming galaxies like our own Milky Way evolve kinematically into ordered thin disks over the last ∼8 billion years since z = 1.2, undergoing a process of 'disk settling'. For the first time, we study the kinematic evolution of a suite of four state of the art 'zoom in' hydrodynamic simulations of galaxy formation and evolution in a fully cosmological context and compare with these observations. Until now, robust measurements of the internal kinematics of simulated galaxies were lacking because the simulations suffered from low resolution, overproduction of stars, and overly massive bulges. The current generation of simulations has made great progress in overcoming these difficulties and is ready for a kinematic analysis. We show that simulated galaxies follow the same kinematic trends as real galaxies: they progressively decrease in disordered motions (σ{sub g}) and increase in ordered rotation (V{sub rot}) with time. The slopes of the relations between both σ{sub g} and V{sub rot} with redshift are consistent between the simulations and the observations. In addition, the morphologies of the simulated galaxies become less disturbed with time, also consistent with observations. This match between the simulated and observed trends is a significant success for the current generation of simulations, and a first step in determining the physical processes behind disk settling'.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Conservative GRMHD simulations of moderately thin, tilted accretion disks

This paper presents our latest numerical simulations of accretion disks that are misaligned with respect to the rotation axis of a Kerr black hole. In this work, we use a new, fully conservative version of the Cosmos++ general relativistic magnetohydrodynamics (GRMHD) code, coupled with an ad hoc cooling function designed to control the thickness of the disk. Together these allow us to simulate the thinnest tilted accretion disks ever using a GRMHD code. In this way, we are able to probe the regime where the dimensionless stress and scale height of the disk become comparable. We present results for both prograde and retrograde cases. The simulated prograde tilted disk shows no sign of Bardeen-Petterson alignment even in the innermost parts of the disk. The simulated retrograde tilted disk, however, does show modest alignment. The implication of these results is that the parameter space associated with Bardeen-Petterson alignment for prograde disks may be rather small, only including very thin disks. Unlike our previous work, we find no evidence for standing shocks in our simulated tilted disks. We ascribe this to the black hole spin, tilt angle, and disk scale height all being small in these simulations. We also add to the growing body of literature pointing out that the turbulence driven by the magnetorotational instability in global simulations of accretion disks is not isotropic. Finally, we provide a comparison between our moderately thin, untilted reference simulation and other numerical simulations of thin disks in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

OpenUniverse2024: a shared, simulated view of the sky for the next generation of cosmological surveys

The OpenUniverse2024 simulation suite is a cross-collaboration effort to produce matched simulated imaging for multiple surveys as they would observe a common simulated sky. Both the simulated data and associated tools used to produce it are intended to uniquely enable a wide range of studies to maximize the science potential of the next generation of cosmological surveys. We have produced simulated imaging for approximately 70 deg 2 of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Wide-Fast-Deep survey and the Nancy Grace Roman Space Telescope High-Latitude Wide-Area Survey, as well as overlapping versions of the ELAIS-S1 Deep-Drilling Field for LSST and the High-Latitude Time-Domain Survey for Roman. OpenUniverse2024 includes (i) an early version of the updated extragalactic model called Diffsky, which substantially improves the realism of optical and infrared photometry of objects, compared to previous versions of these models; (ii) updated transient models that extend through the wavelength range probed by Roman and Rubin; and (iii) improved survey, telescope, and instrument realism based on up-to-date survey plans and known properties of the instruments. It is built on a new and updated suite of simulation tools that improves the ease of consistently simulating multiple observatories viewing the same sky. The approximately 400 TB of synthetic survey imaging and simulated universe catalogs are publicly available, and we preview some scientific uses of the simulations.

large-scale structure of Universe↗
DOE OSTI2021

Toward simulating quantum field theories with controlled phonon-ion dynamics: A hybrid analog-digital approach

Quantum field theories are the cornerstones of modern physics, providing relativistic and quantum mechanical descriptions of physical systems at the most fundamental level. Simulating real-time dynamics within these theories remains elusive in classical computing. This provides a unique opportunity for quantum simulators, which hold the promise of revolutionizing our simulation capabilities. Trapped-ion systems are successful quantum-simulator platforms for quantum many-body physics and can operate in digital, or gate-based, and analog modes. Inspired by the progress in proposing and realizing quantum simulations of a number of relativistic quantum field theories using trapped-ion systems, and by the hybrid analog-digital proposals for simulating interacting boson-fermion models, we propose hybrid analog-digital quantum simulations of selected quantum field theories, taking recent developments to the next level. On one hand, the semi-digital nature of this proposal offers more flexibility in engineering generic model interactions compared with a fully-analog approach. On the other hand, encoding the bosonic fields onto the phonon degrees of freedom of the trapped-ion system allows a more efficient usage of simulator resources, and a more natural implementation of intrinsic quantum operations in such platforms. This opens up new ways for simulating complex dynamics of e.g., Abelian and non-Abelian gauge theories, by combining the benefits of digital and analog schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗