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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Velocity dispersion and dynamical masses for 388 galaxy clusters and groups

The second catalogue of Planck Sunyaev-Zeldovich (SZ) sources, hereafter PSZ2, represents the largest galaxy cluster sample selected by means of their SZ signature in a full-sky survey. For this work, using telescopes at the Canary Island observatories, we conducted the long-term observational program 128- MULTIPLE-16/15B (hereafter LP15), a large and complete optical follow-up campaign of all the unidentified PSZ2 sources in the northern sky, with declinations above –15° and no correspondence in the first Planck catalogue PSZ1. This paper is the third and last in the series of LP15 results, after Streblyanska et al. (2019, A&A, 628, A13) and Aguado-Barahona et al. (2019, A&A, 631, A148), and presents all the spectroscopic observations of the full program. We complement these LP15 spectroscopic results with Sloan Digital Sky Survey archival data and other observations from a previous program (ITP13-08), and present a catalogue of 388 clusters and groups of galaxies including estimates of their velocity dispersion. The majority of them (356) are optical counterparts of PSZ2 sources. A subset of 297 of those clusters are used to construct the M SZ – M dyn scaling relation based on the estimated SZ mass from Planck measurements and our dynamical mass estimates. We discuss and correct for different statistical and physical biases in the estimation of the masses, such as the Eddington bias when estimating M SZ and the aperture and the number of galaxies used to calculate M dyn . The SZ-to-dynamical mass ratio for those 297 PSZ2 clusters is (1 – B) = 0.80 ± 0.04 (stat) ± 0.05 (sys), with only marginal evidence for a possible mass dependence for this factor. Our value is consistent with previous results in the literature, but is associated with a significantly smaller uncertainty due to the use of the largest sample size for this type of study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Hamiltonian simulation in Zeno subspaces

Here, we investigate the quantum Zeno effect as a framework for designing and analyzing quantum algorithms for Hamiltonian simulation. We show that frequent projective measurements of an ancilla qubit register can be used to simulate quantum dynamics on a target qubit register with a circuit complexity similar to randomized approaches. The classical sampling overhead in the latter approaches is traded for ancilla qubit overhead in Zeno-based approaches. A second-order Zeno sequence is developed to improve scaling and implementations through unitary kicks are discussed. We derive rigorous error bounds that allow for identifying the associated circuit complexities for the first- and second-order Zeno sequences. We show that the circuits over the combined register can be identified as a subroutine commonly used in post-Trotter Hamiltonian simulation methods. We build on this observation to reveal connections between different Hamiltonian simulation algorithms.

Hamiltonian simulation↗
DOE OSTI2024

Computing equilibrium free energies through a nonequilibrium quench

Many methods to accelerate sampling of molecular configurations are based on the idea that temperature can be used to accelerate rare transitions. These methods typically compute equilibrium properties at a target temperature using reweighting or through Monte Carlo exchanges between replicas at higher temperatures. A recent paper [G. M. Rotskoff and E. Vanden-Eijnden, Phys. Rev. Lett. 122, 150602 (2019)] demonstrated that accurate equilibrium densities of states can also be computed through a nonequilibrium “quench” process, where sampling is performed at a higher temperature to encourage rapid mixing and then quenched to lower energy states with dissipative dynamics. Here, we provide an implementation of the quench dynamics in LAMMPS and evaluate a new formulation of nonequilibrium estimators for the computation of partition functions or free energy surfaces (FESs) of molecular systems. We show that the method is exact for a minimal model of N-independent harmonic springs and use these analytical results to develop heuristics for the amount of quenching required to obtain accurate sampling. We then test the quench approach on alanine dipeptide, where we show that it gives an FES that is accurate near the most stable configurations using the quench approach but disagrees with a reference umbrella sampling calculation in high FE regions. We then show that combining quenching with umbrella sampling allows the efficient calculation of the free energy in all regions. Moreover, by using this combined scheme, we obtain the FES across a range of temperatures at no additional cost, making it much more efficient than standard umbrella sampling if this information is required. Finally, we discuss how this approach can be extended to solute tempering and demonstrate that it is highly accurate for the case of solvated alanine dipeptide without any additional modifications.

Chemistry↗
DOE OSTI2023

Toward accurate measurement of electromagnetic field by retrieving and refining the center position of non-uniform diffraction disks in Lorentz 4D-STEM

Recent advancement in scanning transmission electron microscopy (STEM) allows the use of 4D-STEM, a technique that captures an electron diffraction pattern at each scan point in STEM, to measure electrostatic and magnetic potential and field in materials. However, accurate measurement, separation of the magnetic and electric signals, and removal of artifacts remain challenging, especially in the presence of complex non-uniform diffraction contrast within the disks. In this work, based on dynamic simulations of 4D-STEM patterns built upon superstructures consisting of millions of atoms to account for different sample thickness and edge geometries, we show how the shape and intensity distribution of the central disk are affected by multiple scattering. We propose a robust refinement procedure through iteration of the spin-sensitive peak position of the disk-center in the circular Hough transform filtered images from experimental Lorentz 4D-STEM dataset after minimizing the possible artifacts, such as those due to the change of thickness, dynamic scattering, and scanning process. We verify that caution must be taken as in practice the rigid-disk-shift model used to reconstruct induction maps can easily break down due to disk-protrusion when there exists a nonconstant phase gradient or thickness within the width of the probe. Through quantitative analysis and comparing experiment with calculation the effect of the non-spin-related intensity distribution inside the disk as well as that causes the disk shift due to the intensity-protrusion can be removed, and high-quality magnetic field mapping is possible.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Computing the binding affinity of a ligand buried deep inside a protein with the hybrid steered molecular dynamics

Computing the ligand-protein binding affinity (or the Gibbs free energy) with chemical accuracy has long been a challenge for which many methods/approaches have been developed and refined with various successful applications. False positives and, even more harmful, false negatives have been and still are a common occurrence in practical applications. Inevitable in all approaches are the errors in the force field parameters we obtain from quantum mechanical computation and/or empirical fittings for the intra- and inter-molecular interactions. These errors propagate to the final results of the computed binding affinities even if we were able to perfectly implement the statistical mechanics of all the processes relevant to a given problem. And they are actually amplified to various degrees even in the mature, sophisticated computational approaches. In particular, the free energy perturbation (alchemical) approaches amplify the errors in the force field parameters because they rely on extracting the small differences between similarly large numbers. In this paper, we develop a hybrid steered molecular dynamics (hSMD) approach to the difficult binding problems of a ligand buried deep inside a protein. Sampling the transition along a physical (not alchemical) dissociation path of opening up the binding cavity- -pulling out the ligand- -closing back the cavity, we can avoid the problem of error amplifications by not relying on small differences between similar numbers. We tested this new form of hSMD on retinol inside cellular retinol-binding protein 1 and three cases of a ligand (a benzylacetate, a 2-nitrothiophene, and a benzene) inside a T4 lysozyme L99A/M102Q(H) double mutant. In all cases, we obtained binding free energies in close agreement with the experimentally measured values. This indicates that the force field parameters we employed are accurate and that hSMD (a brute force, unsophisticated approach) is free from the problem of error amplification suffered by many sophisticated approaches in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Analysis of Time Dependent Data and PRA

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, 'extracting information' means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Radiation defect dynamics in solids studied by pulsed ion beams

The buildup of radiation damage is often a dynamic phenomenon proceeding via migration and interaction of point defects ballistically generated in collision cascades. In this work, we describe how the dynamic aspects of damage formation via inter-cascade defect interaction can be studied by pulsed ion beam bombardment. We illustrate the pulsed beam method by an example for Si bombarded at 100°C with 1.35 MeV Xe ions and compare with previously reported data for 0.5 MeV Xe ion irradiation. Results reveal that the time constant of defect relaxation strongly depends on both ion energy and the depth from the sample surface. This observation cannot be entirely explained as an effect of the collision cascade density on defect interaction dynamics, based on depth dependencies of cascade densities calculated with a recently developed model that accounts for the fractal nature of cascades. There results call for future systematic studies to better understand ion energy and cascade density effects on defect relaxation dynamics in Si.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Magnetic resonance force microscopy with a paramagnetic probe

Here, we consider theoretically extension of magnetic resonance force microscopy (MRFM) replacing a ferromagnetic probe on a cantilever tip (CT) with a paramagnetic one (PMRFM). The dynamics of the interaction between the paramagnetic probe and a local magnetic moment in a sample is analyzed, using a quasi-classical approach. We show that the application of a proper sequence of electromagnetic pulses provides a significant deflection of the CT from the initial equilibrium position. Periodic application of these sequences of pulses results in quasi-periodic CT deflections from the equilibrium, which can be used for detection of the magnetic moment in a sample.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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 OSTI2020

Infrasound and Gravity Waves Over the Andes Observed by a Pressure Sensor on Board a Stratospheric Balloon

The study of infrasound (acoustic) and gravity waves sources and propagation in the atmosphere of a planet gives us precious insight on atmosphere dynamics, climate, and even internal structure. The implementation of modern pressure sensors with high rate sampling on stratospheric balloons is improving their study. In our work we analyzed the data from the National Aeronautics and Space Administration Ultra Long Duration Balloon mission (16 May to 30 June 2016). Here, we focus on the balloon's transit of the Andes Mountains. We detected gravity waves that are associated to troposphere convective activity and mountain waves. An increase of the horizontal wavelengths from 50 to 70 km with increasing distance to the mountains is favoring the presence of mountain waves. We also report on the detection of infrasounds generated by the mountains in the 0.01–0.1 Hz range with a pressure amplitude increase by a factor 2 relative background signal. Besides, we characterized the decrease of microbaroms power when the balloon was flying away from the ocean coast. These observations suggest, in a way similar to microseisms for seismometers, that microbaroms are the main background noise sources recorded in the stratosphere even far from the ocean sources. Finally, we observed a broadband signal above the Andes, between 0.45 and 2 Hz, probably associated with a thunderstorm. The diversity of geophysical phenomena captured in less than a day of observation stresses the interest of high rate pressure sensors on board long-duration balloon missions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Nanoscale rheology at solid-complex fluid interfaces

Here we present an approach to measure dynamic membrane properties of phospholipid membranes close to an interface. As an example we show results of the membrane dynamics of a phospholipid membrane multilayer-stack on a solid substrate (silicon). On this sample we were able to measure local interaction and friction parameters using Grazing Incidence Neutron Spin Echo Spectroscopy (GINSES), where an evanescent neutron wave probes the fluctuations close to a rigid interface. With this method it is possible to access length scales in the nano to micrometer region as well as energies in the μeV range. Using a new neutron resonator structure we achieved the required intensity gain for this experiment. During our investigations we found an excitation mode of the phospholipid membrane that has not been reported previously and only became visible using the new methodology. We speculate that the energy transported by that undulation can also serve to distribute energy over a larger area of the membrane, stabilizing it. This new methodology has the capability to probe the viscoelastic effects of biological membranes, becoming a new tool for tribology on the nanoscale and has allowed the observation of the hitherto invisible property of phospholipid membranes using neutrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Refractive index of lithium fluoride to 900 gigapascal and implications for dynamic equation of state measurements

Lithium fluoride (LiF) is a unique crystal possessing the largest reported bandgap of any material and is predicted to remain transparent to visible light under stresses in excess of 1000 GPa. Dynamic compression experiments often utilize LiF as a window material to maintain stress on a sample while enabling direct measurements of interface velocity. However, typical velocimetry diagnostics measure changes in the optical path length; therefore, an accurate understanding of LiF’s equation of state and refractive index is needed. Here, we present a measurement of the LiF refractive index up to 900 GPa from a low-temperature ramp-compression experiment at the National Ignition Facility. To demonstrate propagation of optical uncertainty from this work to equation of state measurements, simulations in which a tin–LiF interface reaches a peak stress of 825 GPa show that the principal isentrope of tin can be determined up to 1450 GPa with a 1.2% uncertainty in density while considering uncertainties in the optical response of LiF.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Simulation of adiabatic quantum computing for molecular ground states

Quantum computation promises to provide substantial speedups in many practical applications with a particularly exciting one being the simulation of quantum many-body systems. Adiabatic state preparation (ASP) is one way that quantum computers could recreate and simulate the ground state of a physical system. In this paper, we explore a novel approach for classically simulating the time dynamics of ASP with high accuracy and with only modest computational resources via an adaptive sampling configuration interaction scheme for truncating the Hilbert space to only the most important determinants. We verify that this truncation introduces negligible error and use this new approach to simulate ASP for sets of small molecular systems and Hubbard models. Furthermore, we examine two approaches to speeding up ASP when performed on quantum hardware: (i) using the complete active space configuration interaction (CASCI) wave function instead of the Hartree–Fock initial state and (ii) a nonlinear interpolation between the initial and target Hamiltonians. We find that starting with a CASCI wave function with a limited active space yields substantial speedups for many of the systems examined, while nonlinear interpolation does not. In additional, we observe interesting trends in the minimum gap location (based on the initial state) as well as how state preparation time can depend on certain molecular properties, such as the number of valence electrons. Importantly, we find that the required state preparation times do not show an immediate exponential wall that would preclude an efficient run of ASP on actual hardware.

Kremenetski, Vladimir↗
DOE OSTI2022

Effect of proton irradiation temperature on persistent photoconductivity in zinc oxide metal-semiconductor-metal ultraviolet photodetectors

The electrical and structural characteristics of 50-nm-thick zinc oxide (ZnO) metal-semiconductor-metal ultraviolet (UV) photodetectors subjected to proton irradiation at different temperatures are reported and compared. The devices were irradiated with 200 keV protons to a fluence of 1016 cm−2. Examination of the x-ray diffraction (XRD) rocking curves indicates a preferred (100) orientation prior to irradiation, with decrease in crystal quality afterward. Additionally, peak shifts in XRD and Raman spectra of the control sample relative to well-known theoretical positions are indicative of tensile strain in the as-deposited ZnO films. Shifts toward theoretical unstrained positions are observed in the irradiated films, which indicates partial relaxation. Raman spectra also indicate increase in oxygen vacancies (VO) and zinc interstitial defects (Zni) compared to the control sample. Additionally, transient photocurrent measurements performed on each sample at different temperatures showed up to 2× increase in photocurrent decay time constants for irradiated samples vs the control. This persistent photoconductive behavior is linked to the activation of electron and hole traps near the surface, and to the desorption and reabsorption of O2 molecules on the ZnO surface under the influence of UV light. Using an Arrhenius model, trap activation energies were extracted and, by comparing with known energies from the literature, the dominant defects contributing to persistent photoconductivity for each irradiation condition were identified. The persistence of differences in photocurrent transients between different samples months after irradiation indicates that the defects introduced by the suppression of thermally activated dynamic annealing processes have a long-term deleterious effect on device performance.

Heuser, Thomas A. (ORCID:0000000225642400)↗
DOE OSTI2019

Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

Significance A major challenge in biology is characterizing the structural flexibility of intrinsically disordered proteins (IDPs). Ensemble-averaged experimental data do not provide the underlying protein structures. Here, we performed independently small-angle neutron and X-ray scattering experiments and unbiased molecular dynamics simulations to probe the solution structure of an IDP. We report that enhancing the sampling of the simulations can generate an ensemble of IDP structures in quantitative agreement with scattering and NMR, without the need for biasing the simulation or reweighting the results. The demonstration of established simulation technology that produces accurate physical models of flexible biosystems may pave the way to relating conformational flexibility to biological function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Improving Ligand Geometry in Protein Data Bank Structures Computationally

Information about the three‐dimensional structures of complex biological molecules is an indispensable research tool for many fields of study, including biology, chemistry, pharmacology, and computer science. The Protein Data Bank (PDB) is an public digital archive providing access to structures of nucleic acids, proteins, and large macromolecular machines determined experimentally by X‐ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and 3‐dimensional electron microscopy (3DEM). PDB structures undergo validation for structural plausibility upon their deposition into the PDB using the program Mogul, which cross references each deposited structure against similar data in the Cambridge Structural Database (CSD). Ligands associated with PDB structures are a common source of structural inaccuracy. In this study, a programmatic pipeline was developed to determine if ligand geometric accuracy could be improved using known computational tools. Ligands with dubious geometry were identified through a Python mining code. A sample set of the identified structures was remodeled into minimum energy conformations using the molecular dynamics program AMBER and then fit to the original experimental density maps using the molecular modeling program Coot. The refined models were compared to the original models in the PDB as well as to similar structures in the CSD using the deposition statistical validation server. Preliminary results suggest that the pipeline effectively identifies and improves ligand structures that possess inaccurate geometry. This method can be used to evaluate and improve the accuracy of specific ligands in structures both archived and pending deposition. Support or Funding Information This work was supported by an NSF REU and the RCSB PDB [NSF (DBI‐1338415), NIH, and DOE.] This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Miller, Beck↗
DOE OSTI2019

Estimates of Ta strength at ultrahigh pressures and strain rates using thin-film graded-density impactors

In this paper, we present results from an experimental technique used to estimate the strength of Ta at extreme pressures (150 GPa) and strain rates (10 7 s -1 ). A graded-density impactor (GDI) was fabricated using sputter deposition to produce an approximately 40-μm-thick film containing alternating layers of Al and Cu. The thicknesses of the respective layers are adjusted to give an effective density gradient through the film. The GDIs were launched with a 2-stage light gas gun, and shock-ramp-release velocity profiles were measured over timescales of ~10 ns. Results are presented for the direct impact of the film onto LiF windows, which allows for a dynamic characterization of the GDI, as well as from impact onto thin (~40μm) sputtered Ta samples backed by a LiF window. The measurements were coupled with mesoscale numerical simulations to infer the strength of Ta, and the results agree well with other high-pressure platforms, particularly when strain-rate, microstructural, and thermodynamic-path differences are considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Interpretable AI forecasting for numerical relativity waveforms of quasicircular, spinning, nonprecessing binary black hole mergers

We present a deep-learning artificial intelligence model (AI) that is capable of learning and forecasting the late-inspiral, merger and ringdown of numerical relativity waveforms that describe quasicircular, spinning, nonprecessing binary black hole mergers. We used the NRHybSur3dq8 surrogate model to produce train, validation and test sets of ℓ = |m| = 2 waveforms that cover the parameter space of binary black hole mergers with mass ratios q ≤ 8 and individual spins |s$^{z}_ {(1,2)}$| ≤ 0.8. These waveforms cover the time range t ∊ [-5000 M, 130 M], where t = 0M marks the merger event, defined as the maximum value of the waveform amplitude. We harnessed the ThetaGPU supercomputer at the Argonne Leadership Computing Facility to train our AI model using a training set of 1.5 million waveforms. We used 16 NVIDIA DGX A100 nodes, each consisting of 8 NVIDIA A100 Tensor Core GPUs and 2 AMD Rome CPUs, to fully train our model within 3.5 h. Our findings show that artificial intelligence can accurately forecast the dynamical evolution of numerical relativity waveforms in the time range t ∊ [-100 M, 130 M]. Sampling a test set of 190,000 waveforms, we find that the average overlap between target and predicted waveforms is ≳99% over the entire parameter space under consideration. We also combined scientific visualization and accelerated computing to identify what components of our model take in knowledge from the early and late-time waveform evolution to accurately forecast the latter part of numerical relativity waveforms. This work aims to accelerate the creation of scalable, computationally efficient and interpretable artificial intelligence models for gravitational wave astrophysics

79 ASTRONOMY AND ASTROPHYSICS↗