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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential R410A heat pump, and the performance was compared with two baseline VRC algorithms. The results are: (1) The proposed algorithm outperforms for the case with subcooling temperature less than 1 °C. (2) The proposed algorithm achieves a tested mean absolute percentage error (MAPE) of 4.23%, and improves the overall accuracy for cooling conditions by approximately 60%, compared with the two baseline algorithms. (3) The proposed algorithm uses two fewer features and improves the accuracy for undercharge cooling conditions by 68.0%, compared with baseline algorithm 2. These improvements enhance prediction accuracy and prevent overfitting, providing a more reliable refrigerant charge level prediction and helping improve the heat pump energy efficiency.

Liang, Chenjiyu↗
DOE OSTI2018

Dielectric-barrier-discharge plasma-assisted hydrogen diffusion flame. Part 1: Temperature, oxygen, and fuel measurements by one-dimensional fs/ps rotational CARS imaging

One-dimensional hybrid fs/ps CARS imaging provides single-laser-shot measurements of temperature, oxygen, and hydrogen in a plasma-assisted hydrogen diffusion flame. The coaxial dielectric-barrier-discharge burner collapses the Re ~50 hydrogen diffusion flame to within ~5 mm of the burner surface at an applied AC potential of 8.75 kV at 18 kHz, coinciding nicely with the full spatial extent of the 1D CARS measurements. Translating the burner through the measurement volume allowed for measurements at numerous radial locations in increments of 1 mm with a resolution of 140 µm × 30 µm × 600 µm, sufficient to resolve spatial gradients in this unsteady flame. Longer probe delays, required for improved dynamic range in regions of high temperature fluctuations, proved difficult to model as a result of a nontrivial decay in the O 2 Raman coherence arising from complexities associated with the triplet ground electronic state of the O 2 molecule. Oxygen linewidths were treated empirically using the observed O 2 coherence decay in spectra acquired from the product gases of lean, near-adiabatic H 2 /air flames stabilized on a Hencken flat-flame burner. While still leading to errors up to 10% at worst, the empirically determined Raman linewidth factors eliminated any systematic error in the O 2 /N 2 measurements with probe delay. Temperature measurements in the Hencken Burner flames proved to be insensitive to probe pulse delay, providing robust thermometry. Here, demonstration of this technique in both the canonical Hencken burner flames and a new DBD burner validates its effectiveness in producing multiple spatially resolved measurements in combustion environments. Measurements in the DBD burner revealed an unsteady, counterflow flattened flame structure near the fuel orifice which became unsteady as the reaction zone curves towards the surface for larger radial positions. Lastly, fluctuations in the fuel concentration were largest at the source, as the large, plasma-generated, unsteady external toroidal vortex that dominates the transport in this flame provides enhanced ventilation of the flame surface in close proximity to the fuel tube.

42 ENGINEERING↗
DOE OSTI2023

Open-Shell Tensor Hypercontraction

The extension of least-squares tensor hypercontracted second- and third-order Møller–Plesset perturbation theory (LS-THC-MP2 and LS-THC-MP3) to open-shell systems is an important development due to the scaling reduction afforded by THC and the ubiquity of molecular ions, radicals, and other open-shell reactive species. The complexity of wavefunction-based quantum-chemical methods such as Møller–Plesset and coupled cluster theory is reflected in the steep scaling of the computational costs with the molecular size. The least-squares tensor hypercontraction (LS-THC) method is an efficient, single-step factorization for the two-electron integral tensor but can also be used to factorize the double excitation amplitudes, leading to significant scaling reduction. Herein we extend this promising method to open-shell variants of LS-THC-MP2 and -MP3 by using diagrammatic techniques and explicit spin summation. The accuracy of the resulting methods for open-shell species is benchmarked on standard test systems such as regular alkanes as well as realistic systems involving bond breaking, radical stabilization, and other effects. We find that open-shell LS-THC-MPn methods exhibit errors highly comparable to those produced by closed-shell LS-THC-MPn and are highly insensitive to particular chemical interactions, geometries, or even moderate spin contamination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling Liquid Water by Climbing up Jacob’s Ladder in Density Functional Theory Facilitated by Using Deep Neural Network Potentials

Within the framework of Kohn–Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately normed (SCAN) functional has been extensively demonstrated in recent years. Here, we further advance the modeling of water by building a more accurate model on the fourth rung of Jacob’s ladder with the hybrid functional, SCAN0. In particular, we carry out both classical and Feynman path-integral molecular dynamics calculations of water with the SCAN0 functional and the isobaric–isothermal ensemble. To generate the equilibrated structure of water, a deep neural network potential is trained from the atomic potential energy surface based on ab initio data obtained from SCAN0 DFT calculations. For the electronic properties of water, a separate deep neural network potential is trained by using the Deep Wannier method based on the maximally localized Wannier functions of the equilibrated trajectory at the SCAN0 level. The structural, dynamic, and electric properties of water were analyzed. The hydrogen-bond structures, density, infrared spectra, diffusion coefficients, and dielectric constants of water, in the electronic ground state, are computed by using a large simulation box and long simulation time. For the properties involving electronic excitations, we apply the GW approximation within many-body perturbation theory to calculate the quasiparticle density of states and bandgap of water. Compared to the SCAN functional, mixing exact exchange mitigates the self-interaction error in the meta-generalized-gradient approximation and further softens liquid water toward the experimental direction. For most of the water properties, the SCAN0 functional shows a systematic improvement over the SCAN functional. However, some important discrepancies remain. The H-bond network predicted by the SCAN0 functional is still slightly overstructured compared to the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Topologically trivial gap-filling in superconducting Fe(Se,Te) by one-dimensional defects

Abstract Structural distortions and imperfections are a crucial aspect of materials science, on the macroscopic scale providing strength, but also enhancing corrosion and reducing electrical and thermal conductivity. At the nanometre scale, multi-atom imperfections, such as atomic chains and crystalline domain walls have conversely been proposed as a route to topological superconductivity, whose most prominent characteristic is the emergence of Majorana Fermions that can be used for error-free quantum computing. Here, we shed more light on the nature of purported domain walls in Fe(Se,Te) that may host 1D dispersing Majorana modes. We show that the displacement shift of the atomic lattice at these line-defects results from sub-surface impurities that warp the topmost layer(s). Using the electric field between the tip and sample, we manage to reposition the sub-surface impurities, directly visualizing the displacement shift and the underlying defect-free lattice. These results, combined with observations of a completely different type of 1D defect where superconductivity remains fully gapped, highlight the topologically trivial nature of 1D defects in Fe(Se,Te).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

The triply-ionized carbon forest from eBOSS: cosmological correlations with quasars in SDSS-IV DR14

Here, we present measurements of the cross-correlation of the triply-ionized carbon (CIV) forest with quasars using Sloan Digital Sky Survey Data Release 14. The study exploits a large sample of new quasars from the first two years of observations by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). The CIV forest is a weaker tracer of large-scale structure than the Lyα forest, but benefits from being accessible at redshifts z<2 where the quasar number density from eBOSS is high. Our data sample consists of 287,651 CIV forest quasars in the redshift range 1.4 CIV =0.27 –0.14 –0.26 +0.16 +0.34 and its combination with the CIV linear transmission bias parameter is b CIV (1+β CIV )=–0.0183 –0.0014 –0.0029 +0.0013 +0.0025 (1σ and 2σ statistical errors) at the mean redshift z=2.00. Splitting the sample at z=2.2 to constrain the bias evolution with redshift yields the power-law exponent γ=0.60±0.63, indicating a significantly weaker redshift-evolution than for the Lyα forest linear transmission bias. Additionally, we demonstrate that CIV absorption has the potential to be used as a probe of baryon acoustic oscillations (BAO). While the current data set is insufficient for a detection of the BAO peak feature, the final quasar samples for redshifts 1.4<z<2.2 from eBOSS and the Dark Energy Spectroscopic Instrument (DESI) are expected to provide measurements of the isotropic BAO scale to ~7% and ~3% precision, respectively, at zsime1.6.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Ring artifact and Poisson noise attenuation via volumetric multiscale nonlocal collaborative filtering of spatially correlated noise

X-ray micro-tomography systems often suffer from high levels of noise. In particular, severe ring artifacts are common in reconstructed images, caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. Furthermore, the projections commonly contain high levels of Poissonian noise arising from the photon-counting detector. This work presents a 3-D multiscale framework for streak attenuation through a purposely designed collaborative filtering of correlated noise in volumetric data. A distinct multiscale denoising step for attenuation of the Poissonian noise is further proposed. By utilizing the volumetric structure of the projection data, the proposed fully automatic procedure offers improved feature preservation compared with 2-D denoising and avoids artifacts which arise from individual filtering of sinograms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

A Moving Target Defense Control Framework for Cyber-Physical Systems

This paper considers the problem of efficiently and securely controlling cyber-physical systems that are operating in uncertain, and adversarial environments. To mitigate sensor, actuator attacks, and performance loss due to such attacks, we formulate a secure control algorithm that consists of a proactive and a reactive defense mechanism. The proactive mechanism, which is based on the principles of moving target defense, utilizes a stochastic switching structure to dynamically and continuously alter the parameters of the system, while hindering the attacker's ability to conduct successful reconnaissance to the system. The unpredictability of the current actuator and sensor is optimized using an information entropy measure, which is induced by probabilistic switching. The reactive mechanism on the other side, detects potentially attacked components, namely sensors and actuators, by leveraging online data to compute an integral Bellman error. A rigorous mathematical framework is presented to guarantee the stability of the equilibrium point of the closed-loop system, and provide a quantified bound on the performance loss when utilizing both reactive and proactive mechanisms. Simulation results show the efficacy of the proposed approaches on a benchmark aircraft model.

42 ENGINEERING↗
DOE OSTI2017

Django Remote Submission

The Django Remote Submission (DRS) is a Django (Django, n.d.) application to manage long running job submission, including starting the job, saving logs, and storing results. It is an independent project available as a standalone pypi package (PyPi, n.d.). It can be easily integrated in any Django project. The source code is freely available as a GitHub repository (django-remote-submission, n.d.). To run the jobs in background, DRS takes advantage of Celery (Celery, n.d.), a powerful asynchronous job queue used for running tasks in the background, and the Redis Server (Redis, n.d.), an in-memory data structure store. Celery uses brokers to pass messages between a Django Project and the Celery workers. Redis is the message broker of DRS. In addition DRS provides real time monitoring of the progress of Jobs and associated logs. Through the Django Channels project (Channels, n.d.), and the usage of Web Sockets, it is possible to asynchronously display the Job Status and the live Job output (standard output and standard error) on a web page.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Unveiling a Drift Resistant Cryptotope within Marburgvirus Nucleoprotein Recognized by Llama Single-Domain Antibodies

Marburg virus (MARV) is a highly lethal hemorrhagic fever virus that is increasingly re-emerging in Africa, has been imported to both Europe and the US, and is also a Tier 1 bioterror threat. As a negative sense RNA virus, MARV has error prone replication which can yield progeny capable of evading countermeasures. To evaluate this vulnerability, we sought to determine the epitopes of 4 llama single-domain antibodies (sdAbs or VHH) specific for nucleoprotein (NP), each capable of forming MARV monoclonal affinity reagent sandwich assays. Here, we show that all sdAb bound the C-terminal region of NP, which was produced recombinantly to derive X-ray crystal structures of the three best performing antibody-antigen complexes. The common epitope is a trio of alpha helices that form a novel asymmetric basin-like depression that accommodates each sdAb paratope via substantial complementarity-determining region (CDR) restructuring. Shared core contacts were complemented by unique accessory contacts on the sides and overlooks of the basin yielding very different approach routes for each sdAb to bind the antigen. The C-terminal region of MARV NP was unable to be crystallized alone and required engagement with sdAb to form crystals suggesting the antibodies acted as crystallization chaperones. While gross structural homology is apparent between the two most conserved helices of MARV and Ebolavirus, the positions and morphologies of the resulting basins were markedly different. Naturally occurring amino acid variations occurring in bat and human Marburgvirus strains all mapped to surfaces distant from the predicted sdAb contacts suggesting a vital role for the NP interface in virus replication. As an essential internal structural component potentially interfacing with a partner protein it is likely the C-terminal epitope remains hidden or “cryptic” until virion disruption occurs. Conservation of this epitope over 50 years of Marburgvirus evolution should make these sdAb useful foundations for diagnostics and therapeutics resistant to drift.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

The AWAKEN wind farm benchmark, Part 2: Modeling results

Accurately modeling wind farm performance in complex atmospheric flows remains a challenge. This paper presents the modeling results of the American WAKE experimeNt (AWAKEN) wind farm benchmark, a collaborative effort involving 16 research groups from academia and industry within the International Energy Agency Wind Technology Collaboration Programme Task 57. The study evaluates a diverse suite of simulation tools, ranging from fast-running engineering wake models to high-fidelity large-eddy simulations, against a diurnal case study observed during the AWAKEN campaign. The benchmark utilized a three-phase structure to progressively assess model performance as observational data availability increased. Initial blind predictions showed that higher-fidelity models did not uniformly outperform simpler simulation tools. A distinct spatial bias was observed where models struggled to resolve the interplay between a low-level jet, wakes, and terrain-induced flow acceleration. In subsequent phases, leveraging additional measurements for model improvement led to a reduction in mean absolute error across the model ensemble; however, this effect was most pronounced in engineering wake models, where targeted calibration reduced error by up to 40~\%. Overall, the study demonstrates that inflow characterization remains a primary prerequisite for accuracy, particularly for models relying on coarse forcing datasets. While the limited ability to resolve local terrain-flow interactions under single-day conditions represent a recognized constraint, the overall findings on wake modeling and real-world validation still provide valuable guidance for model application and for mitigating this limitation.

Bodini, Nicola↗
DOE OSTI2025

Characterization of Gas-Phase Native(-like) Proteins Using Structures for Lossless Ion Manipulations

High-resolution mobility-based ion separations in Structures for Lossless Ion Manipulations (SLIM) have been useful for ion mobility separations for a variety of molecular classes in the gas phase. Here, in this study, we present multipass SLIM separations for gas-phase proteins in their near-native state exhibiting charge-state-dependent arrival time distributions using carbonic anhydrase (29 kDa), alcohol dehydrogenase (148 kDa), and apo-transferrin (79 kDa). The experimental CCS values were obtained from calibration curves for the arrival times of Agilent Tune Mix ions. For multipass separations, the ATDs were converted to CCS values by deconvoluting the multipass arrival times into accurate single-pass values amenable to the single-pass calibration curves. Mass spectra of carbonic anhydrase (CA) showed three different charge states (z = 9+ to 11+). Their corresponding mobility peaks were baseline-separated by using 8-m single-pass separations. When compared to the corresponding drift tube ion mobility (DTIMS) measurements, the CCS values obtained from DTIMS and SLIM were in agreement within experimental error. Single-pass analysis of alcohol dehydrogenase (ADH) exhibits three predominant charge states (z = 23+ to 25+) with mobility overlap between adjacent charge states. The mobility peak resolution for ADH improved with multipass separations (up to 24-m path length). In addition, CCS distributions obtained for charge states z = 16+ to 18+ of apo-transferrin reveal a transition from a compact unimodal form (z = 18+ and 19+) to broader multimodal CCS distributions for z = 16+. For apo-transferrin, 40-m multipass separations were performed allowing for complete isolation of the selected mobility range corresponding to z = 17+, leading to selective isolation of a narrow arrival time window. The extended mobility separations provided minimal alterations to the structure of the proteins, and the experimentally derived CCS values showed minimal change as a function of the separation time or number of passes. Mobility-based ion separations for native-like proteins, using SLIM, open opportunities for native-IMS applications as well as other manipulations enabled by SLIM-like mobility-selective isolation and collection.

charge state distribution↗
DOE OSTI2025

Equation-of-motion internally contracted multireference unitary coupled-cluster theory

The accurate computation of excited states remains a challenge in electronic structure theory, especially for systems with a ground state that requires a multireference treatment. In this work, we introduce a novel equation-of-motion (EOM) extension of the internally contracted multireference unitary coupled-cluster framework (ic-MRUCC), termed EOM-ic-MRUCC. EOM-ic-MRUCC follows the transform-then-diagonalize approach, in analogy to its non-unitary counterpart. By employing a projective approach to optimize the ground state, the method retains additive separability and proper scaling with system size. We show that excitation energies are size-intensive if the EOM operator satisfies the “killer” and the projective conditions. Furthermore, we propose to represent changes in the reference state upon electron excitation via projected many-body operators that span the active orbitals and show that the EOM equations formulated in this way are invariant with respect to active orbital rotations. We test the EOM-ic-MRUCC method truncated to single and double excitations by computing the potential energy curves for several excited states of a BeH2 model system, the HF molecule, and water undergoing symmetric dissociation. Across these systems, our method delivers accurate excitation energies and potential energy curves within 5 mE h (∼0.14 eV) from full configuration interaction. Here, we find that truncating the Baker–Campbell–Hausdorff series to fourfold commutators contributes negligible errors (on the order of 10 −5 E h or less), offering a practical route to highly accurate excited-state calculations with reduced computational overhead.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

A method for the characterization of intra-pixel response of infrared sensor

Due to the response variations within a pixel, response of sensor varies with the positions of the point target. The accurate measurement of intra-pixel response of the sensor is the key to high-precision centroid estimation and radiometric calibration. In this paper, we establish an intra-pixel response model based on the pixel structure and use Gauss function to describe the beam spot profile. We further calculate the full width at half maximum (FWHM) of the Gauss function and the fill factor of the infrared sensor using the grid search algorithm. Experimental results show that the Gauss function FWHM differences among different pixels using the same radius could be less than 6%. The fill factors are not constant in different pixels because of errors in the process of manufacture and assembly, and the error between model and measured values is less than 3.6%. This work could be useful for stellar calibration and centroid estimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic–lipophilic difference equation used to predict microemulsions’ phase behavior expresses the oils’ physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. As a result, the best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R² score of 0.9

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Systematic analysis of magnetic equilibrium reconstruction with eddy currents on LTX- β

Magnetic equilibrium reconstruction in the Lithium Tokamak Experiment-Beta (LTX-β) is complicated by strong eddy currents and toroidal asymmetries arising from its segmented, close-fitting conducting shell. In the earlier experiment LTX, these three-dimensional (3D) conductor effects significantly distorted diagnostic signals and challenged conventional axisymmetric reconstruction methods. In this work, we demonstrate that accurate plasma equilibria can be recovered on LTX-β by incorporating a small number of dominant eddy current modes derived from realistic conductor models. Using the open-source $\tt{TokaMaker}$ Grad–Shafranov solver, we reconstruct equilibria across a systematically selected set of LTX-β discharges and validate them against the legacy $\tt{PSI-Tri}$ hybrid 2D-3D code. Our results show that fully 2D $\tt{TokaMaker}$ reconstructions achieve significantly improved agreement with flux loop and Mirnov probe measurements, reducing total chi-squared fitting errors, especially during startup. Finally, we develop new hybrid 2D-3D $\tt{TokaMaker}$ reconstructions by integrating the $\tt{ThinCurr}$ 3D eddy current model, which we optimize for significant further reduction of chi-squared in most scenarios. These findings underscore the importance of realistic wall-current modeling in short-pulse tokamaks, and establish a physics-based reconstruction framework that is extensible to devices with complex passive structures and 3D wall interactions.

Grad–Shafranov solver↗
DOE OSTI2024

Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds

The profile of the liquid water content (LWC) in clouds provides fundamental information for understanding the internal structure of clouds, their radiative effects, propensity to precipitate, and degree of entrainment and mixing with the surrounding environment. In principle, differential absorption techniques based on coincident dual-frequency radar reflectivity observations have the potential to provide the LWC profile. Previous differential frequency radar reflectivity (DFR) efforts were challenged by the fact that the measurable differential attenuation for small quantities of LWC is usually comparable to the system measurement error. This typically renders the retrieval impractical, as the uncertainty can become many times greater than the retrieved value itself. Theoretically, this drawback can be mitigated following two interconnected approaches: (1) increasing the frequency separation between the dual-frequency radar system to measure greater differential attenuation and (2) increasing the radar operating frequency to reduce the instrument measurement random error. Our recently developed 239 GHz radar was deployed during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) along with a variety of collocated remote sensing and in situ instruments. We have combined Ka-band (35 GHz) and G-band (239 GHz) observations to retrieve the LWC from more than 100 vertical profiles of shallow clouds with typical amounts of LWC smaller than 1 g m -3 . We theoretically and experimentally demonstrate that the Ka-band and G-band pair of frequencies offers at least a 65 % relative improvement in the LWC retrieval sensitivity compared to previous works reported in the literature using lower-frequency radars. This new technique provides a missing capability to determine the LWC in the challenging low liquid water path (LWP) range (< 200 g m -2 ) and suggests a way forward to characterize microphysical and dynamical processes more precisely in shallow clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A high-fidelity realization of the Euclid code comparison N-body simulation with Abacus

Abstract We present a high-fidelity realization of the cosmological N-body simulation from the Schneider et al. code comparison project. The simulation was performed with our AbacusN-body code, which offers high-force accuracy, high performance, and minimal particle integration errors. The simulation consists of 20483 particles in a $500\ h^{-1}\, \mathrm{Mpc}$ box for a particle mass of $1.2\times 10^9\ h^{-1}\, \mathrm{M}_\odot$ with $10\ h^{-1}\, \mathrm{kpc}$ spline softening. Abacus executed 1052 global time-steps to z = 0 in 107 h on one dual-Xeon, dual-GPU node, for a mean rate of 23 million particles per second per step. We find Abacus is in good agreement with Ramses and Pkdgrav3 and less so with Gadget3. We validate our choice of time-step by halving the step size and find sub-percent differences in the power spectrum and 2PCF at nearly all measured scales, with ${\lt }0.3{{\ \rm per\ cent}}$ errors at $k\lt 10\ \mathrm{Mpc}^{-1}\, h$. On large scales, Abacus reproduces linear theory better than 0.01 per cent. Simulation snapshots are available at http://nbody.rc.fas.harvard.edu/public/S2016.

79 ASTRONOMY AND ASTROPHYSICS↗