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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 829 records · Page 46
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DOE OSTI2020

Permutation matrix representation quantum Monte Carlo

We present a quantum Monte Carlo algorithm for the simulation of general quantum and classical many-body models within a single unifying framework. The algorithm builds on a power series expansion of the quantum partition function in its off-diagonal terms and is both parameter-free and Trotter error-free. In our approach, the quantum dimension consists of products of elements of a permutation group. As such, it allows for the study of a very wide variety of models on an equal footing. To demonstrate the utility of our technique, we use it to clarify the emergence of the sign problem in the simulations of non-stoquastic physical models. We showcase the flexibility of our algorithm and the advantages it offers over existing state-of-the-art by simulating transverse- field Ising model Hamiltonians and comparing the performance of our technique against that of the stochastic series expansion algorithm. Furthermore, we also study a transverse-field Ising model augmented with randomly chosen two-body transverse-field interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Confinement of Ti 3 C 2 T x MXene Nanosheets within a Polymer Matrix via In-situ Polymerization and Deposition on Carbon Cloth for Supercapacitors

Here, with the promising preliminary electrochemical performance, further investigation into polymer-filler interfacial regulation and confined ion transport in the CC/polymer/MXene system could provide deeper insights, paving the way for its application in flexible supercapacitors and other energy storage devices requiring highly adaptable electrodes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Advances in Cell Wall Matrix Research with a Focus on Mixed-Linkage Glucan

Mixed β(1,3;1,4)-linkage glucan (MLG) is commonly found in the monocot lineage, at particularly high levels in the Poaceae family, but also in the evolutionally distant genus, Equisetum. MLG has several properties that make it unique from other plant cell wall polysaccharides. It consists of β1,4-linked polymers of glucose interspersed with β1,3-linkages, but the presence of β1,3-linkages provides quite different physical properties compared to its closest form of the cell wall component, cellulose. The mechanisms of MLG biosynthesis have been investigated to understand whether single or multiple enzymes are required to build mixed linkages in the glucan chain. Currently, MLG synthesis by a single enzyme is supported by mutagenesis analyses of cellulose synthase-like F6, the major MLG synthase, but further investigation is needed to gather mechanistic insights. Because of transient accumulation of MLG in elongating cells and vegetative tissues, several hypotheses have been proposed to explain the role of MLG in the plant cell wall. Studies have been carried out to identify gene expression regulators during development and light cycles as well as enzymes involved in MLG organization in the cell wall. A role of MLG as a storage molecule in grains is evident, but the role of MLG in vegetative tissues is still not well understood. Characterization of a cell wall component is difficult due to the complex heterogeneity of the plant cell wall. Furthermore, as detailed in this review, recent exciting research has made significant impacts in the understanding of MLG biology in plants.

Transglucosylase/hydrolase (XTH)↗
DOE OSTI2024

On the Magnitudes of some CKM Matrix Elements

This write-up follows the presentation at the symposium, with emphasis on topics and ideas discussed there. It is purposefully informal, not a review of the field, and neither does it include a complete list of references. However, I hope that readers might find somwe comments useful or amusing, and may appreciate the challenges and reasons for excitement about recent progress and future opportunities in flavor physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Simulating lossy Gaussian boson sampling with matrix-product operators

Gaussian boson sampling, a computational model that is widely believed to admit quantum supremacy, has already been experimentally demonstrated and is claimed to surpass the classical simulation capabilities of even the most powerful supercomputers today. However, whether the current approach limited by photon loss and noise in such experiments prescribes a scalable path to quantum advantage is an open question. Here, to understand the effect of photon loss on the scalability of Gaussian boson sampling, we analytically derive the asymptotic operator entanglement entropy scaling, which relates to the simulation complexity. As a result, we observe that efficient tensor network simulations are likely possible under the N out ∝ √N scaling of the number of surviving photons N out in the number of input photons N. We numerically verify this result using a tensor network algorithm with U⁡(1) symmetry, and we overcome previous challenges due to the large local Hilbert-space dimensions in Gaussian boson sampling with hardware acceleration. Additionally, we observe that increasing the photon number through larger squeezing does not increase the entanglement entropy significantly. Finally, we numerically find the bond dimension necessary for fixed accuracy simulations, providing more direct evidence for the complexity of tensor networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗