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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Primitive quantum gates for an S U ( 2 ) discrete subgroup: Binary tetrahedral

We construct a primitive gate set for the digital quantum simulation of the binary tetrahedral ($\mathbb{BT}$) group on two quantum architectures. This nonabelian discrete group serves as a crude approximation to $SU(2)$ lattice gauge theory while requiring five qubits or one quicosotetrit per gauge link. The necessary basic primitives are the inversion gate, the group multiplication gate, the trace gate, and the $\mathbb{BT}$ Fourier transform over $\mathbb{BT}$. We experimentally benchmark the inversion and trace gates on ibm nairobi, with estimated fidelities between $14-55\%$, depending on the input state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Primitive quantum gates for an S U ( 2 ) discrete subgroup: Binary octahedral

We construct a primitive gate set for the digital quantum simulation of the 48-element binary octahedral ( BO ) group. This non-Abelian discrete group better approximates S U ( 2 ) lattice gauge theory than previous work on the binary tetrahedral group at the cost of one additional qubit—for a total of six—per gauge link. The necessary primitives are the inversion gate, the group multiplication gate, the trace gate, and the BO Fourier transform. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Preliminary Results on Bayesian Inverse UQ for OECD/NEA WPNCS Subgroup 14 Benchmark Exercise for Error Recovery and Experimental Coverage

The Organization for Economic Cooperation and Development (OECD) Working Party on Nucelar Criticality Safety (WPNCS) has proposed a benchmark exercise representative of neutronic behavior in criticality experiments. Here, the goal is to develop confidence in data assimilation techniques used to adjust nuclear data. Participants are given synthetic experimental models with associated measured data and asked to estimate the model parameters given the model and measurements as well as provide predictions for separate application models. In this work, we performed data assimilation using Bayesian inverse Uncertainty Quantification (UQ) with machine learning surrogate models to produce posterior parameter distributions for the requested parameters and posterior predictive distributions for the requested responses. Several experimental models are shown to insufficiently inform the posterior parameter distributions for the applications involved. However, given sufficient experimental data, posterior parameter estimates yielded reduced uncertainty in the response predictions of interest while covering the experimental data.

Bayesian Inference↗
DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bias. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Reference 2 (at the end of the article).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

New Subgrouping of Multiple Stellar Populations in NGC 2808 Based on Low-resolution Spectroscopy

We performed low-resolution spectroscopy for the red giant branch stars in an intriguing globular cluster (GC) NGC 2808, which hosts subpopulations with extreme helium and light-element abundances. In order to trace N, C, and Ca abundance differences among subpopulations, we measured CN, CH, and Ca ii H&K spectral indices, respectively. We identified four subpopulations (G1, G2, G3, and G4) from CN and CH strength, with CN-weak/CH-strong G1, CN-intermediate/CH-strong G2, CN-strong/CH-intermediate G3, and CN-strong/CH-weak G4. Compared to [Na/O] from high-resolution spectroscopy, we show that CN index can more clearly separate G1 and G2. Since CN traces N abundance in a GC, it implies that G1 and G2 would show a larger difference in [N/Fe] compared to [Na/Fe], as predicted by chemical evolution models. Later generation stars G3 and G4, however, are better separated with high-resolution spectroscopy. We also found that G4 shows a stronger Ca ii H&K line strength compared to that of G1, but we suspect this to be a result of unusually strong He enhancement and/or Mg depletion in G4 of this GC. This work illustrates that combining low- and high-resolution spectroscopic studies can improve the separation of subpopulations in GCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

Comparisons of population subgroups performance on a keyboard psychomotor task

Response time and pass/fail data were obtained from 163 subjects performing a psychomotor task. The basic task comprised a random five digit number briefly displayed to the subject at the start of each trail, and the keyboard on which the subject was to enter the number as fast as he could accurately do so after the display was extinguished. Some tests were run with the addition of a secondary task which required the subject to respond to a displayed light appearing at a random time. Matched pairs of subjects were selected from the group to analyze the effects of age, sex, intelligence, prior keyboard skill, and drinking habits. There was little or no effect due to age or drinking habits. Differences in response time were: average IQ subjects faster than low IQ subjects by 0.5 to 0.6 sec; subjects with prior keyboard skill faster by 0.4 to 0.5 sec; and female subjects faster by 0.2 to 0.3 sec. These effects were generally insensitive to the presence of the secondary task.

Stapleford, R. L.↗