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There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.
We present new radial velocity (RV) measurements of old (horizontal branch) and intermediate-age (red clump) stellar tracers in the Carina dwarf spheroidal. They are based on more than 2200 low-resolution spectra collected with VIMOS at Very Large Telescope (VLT). The targets are faint (20 ≲ V ≲ 21.5 mag), but the accuracy at the faintest limit is ≤9 km s{sup −1}. These data were complemented with RV measurements either based on spectra collected with FORS2 and FLAMES/GIRAFFE at VLT or available in the literature. We ended up with a sample of 2748 stars and among them, 1389 are candidate Carina stars. We found that the intermediate-age stellar component shows a well-defined rotational pattern around the minor axis. The western and the eastern side of the galaxy differ by +5 and −4 km s{sup −1} when compared with the main RV peak. The old stellar component is characterized by a larger RV dispersion and does not show evidence of the RV pattern. We compared the observed RV distribution with N-body simulations for a former disky dwarf galaxy orbiting a giant Milky Way–like galaxy. We rotated the simulated galaxy by 60° with respect to the major axis, we kept the observer on the orbital plane of the dwarf and extracted a sample of stars similar to the observed one. Observed and predicted V{sub rot}/σ ratios across the central regions are in remarkable agreement. This evidence indicates that Carina was a disky dwarf galaxy that experienced several strong tidal interactions with the Milky Way. Owing to these interactions, Carina transformed from a disky to a prolate spheroid and the rotational velocity transformed into random motions.
There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.
This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads with both an AC and a DC electrical distribution topology.
Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.
The toroidal distribution of boron deposition on plasma-facing components (PFCs) in boron powder injection using an impurity power dropper (IPD) was investigated by full-torus simulation and observations in a systematic plasma density-scan experiment. The images of the ablation of dropped boron powders observed with a visible CCD camera were consistently explained by the simulations of the ablation positions of the boron powders considering the size distribution. Simulations assuming full-torus boron deposition on the PFCs did not reproduce the observed intensity profile of boron emission lines for higher plasma densities. It indicated that the density of boron deposited on PFCs installed toroidally far from the IPD was low for higher plasma densities due to the change in the ablation positions of the boron powders toward the outboard side. The experimental results verified the previous full-torus simulation of the toroidal distribution of the boron deposition in both lower and higher plasma densities.
An accurate model of the nonlinear detector response of organic scintillators to neutrons is required to correctly simulate fast neutron detection, as well as interpret measured pulse height data. Several empirical and semi-empirical models are available to fit measured scintillator light output data. In this work, EJ-309 light output data from neutrons depositing 1.15–5.15 MeV on hydrogen were analyzed using empirical models as well as semi-empirical models based on the work of Birks and Voltz. Although all tested models fit the experimental light output data well in the measured range, the models were observed to diverge in low-energy extrapolation. The models were then tested by comparing a measurement and MCNPX-PoliMi simulation of an EJ-309 detector response to fast neutrons from a 252 Cf spontaneous fission source. The agreement between the measured and simulated pulse height distributions varied significantly depending on the light output model used. The best agreement between simulated and measured neutron pulse height distributions was achieved by using the Birks model. The bin-by-bin agreement was better than 5% over the range 0.08–2.18 MeVee, and better than 10% from 2.18 to 3.13 MeVee. Furthermore, the integral count rate over the range 0.08–3.14 MeVee differed by less than 1% in absolute units.
This paper presents the modeling framework of an asynchronous, real-time co-simulation platform for modeling the interactions between microgrids and power distribution systems. Components of each microgrid are simulated on the OPAL-RT eMEGASIM platform so that electromagnetic transients of the inverter units are modeled at a time step of 100 microseconds. The 3-phase unbalanced distribution feeder that microgrids are connected to is simulated by using the OPAL-RT ePHASORSIM so that load transients, capacitor switching, and tap-changing events can be modeled. A MATLAB-based microgrid controller will interface controllable microgrid components through the Modbus communication. This co-simulation framework allows different microgrid controller logic to be developed and tested on a hardware-in-the-loop testbed considering both the inverter-level transient and the dynamic response of loads and utility equipment. Because the controller communicates with controllable devices via actual communication links, the impact of communication errors, delays, or denial-of-service can also be properly quantified.
Introduction: Crops are vulnerable to precipitation and heat extremes during late spring through summer. Methods: We analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041- 2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap. Results: Identified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type. Discussion: The information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.
Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.
To interpret the mean depth of cosmic ray air shower maximum and its dispersion, we parametrize those two observables as functions of the first two moments of the ln A distribution. We examine the goodness of this simple method through simulations of test mass distributions. The application of the parameterization to Pierre Auger Observatory data allows one to study the energy dependence of the mean ln A and of its variance under the assumption of selected hadronic interaction models. We discuss possible implications of these dependences in term of interaction models and astrophysical cosmic ray sources.
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.
In this study, atom probe tomography (APT) is used to characterize the influence of hydrogen dosing duringGaN barrier growth on the indium distribution of In x Ga 1-x N quantum wells, and correlatedmicro-photoluminescence is used to measure changes in the emission spectrum and efficiency. We found that relative to the control growth, hydrogen dosing leads to a 50% increase in emission intensity arising from discontinuous quantum wells that are narrower, of lower indium content, and with more abrupt interfaces. Additionally, simulations of carrier distributions based on APT composition profiles indicate that the greater carrier confinement leads to an increased radiative recombination rate. Furthermore, APT analysis of quantum well profiles enables refinement of x-ray diffractionanalysis for more accurate nondestructive measurements of composition.
Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by twelve global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the results suggest that most global aerosol microphysics models simulate the global variation of the particle size distribution with a good degree of skill, but some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
A theoretical study of the time-of-flight (TOF) distributions under pulsed laser evaporation in vacuum has been performed. A database of TOF distributions has been calculated by the direct simulation Monte Carlo (DSMC) method. It is shown that describing experimental TOF signals through the use of the calculated TOF database combined with a simple analysis of evaporation allows determining the irradiated surface temperature and the rate of evaporation. Analysis of experimental TOF distributions under laser ablation of niobium, copper, and graphite has been performed, with the evaluated surface temperature being well agreed with results of the thermal model calculations. General empirical dependences are proposed, which allow indentifying the regime of the laser induced thermal ablation from the TOF distributions for neutral particles without invoking the DSMC-calculated database.
This presentation touches upon the TSL community that has been growing rapidly. Additionally, this presentation mentions the more exotic materials and theories that are being implemented in TSL files. This lecture concludes on three areas of potential concern: Coherent scattering, Computational simulations, and Isotopic distribution.
We use high spatial resolution observations and numerical simulations to study the velocity distribution of solar photospheric magnetic bright points. The observations were obtained with the Rapid Oscillations in the Solar Atmosphere instrument at the Dunn Solar Telescope, while the numerical simulations were undertaken with the MURaM code for average magnetic fields of 200 G and 400 G. We implemented an automated bright point detection and tracking algorithm on the data set and studied the subsequent velocity characteristics of over 6000 structures, finding an average velocity of approximately 1 km s{sup -1}, with maximum values of 7 km s{sup -1}. Furthermore, merging magnetic bright points were found to have considerably higher velocities, and significantly longer lifetimes, than isolated structures. By implementing a new and novel technique, we were able to estimate the background magnetic flux of our observational data, which is consistent with a field strength of 400 G.
Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.