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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dynamic, symmetry-preserving, and hardware-adaptable circuits for quantum computing many-body states and correlators of the Anderson impurity model

We present a hardware-reconfigurable ansatz on N q -qubits for the variational preparation of many-body states of the Anderson impurity model (AIM) with N imp + N bath = N q /2 sites, which conserves total charge and spin z component within each variational search subspace. The many-body ground state of the AIM is determined as the minimum over all minima of O(N$^2_ q$) distinct charge-spin sectors. Hamiltonian expectation values are shown to require ω(N q ) < N meas. $\leqslant$ O(N imp N bath ) symmetry-preserving, parallelizable measurement circuits, each amenable to postselection. To obtain the one-particle impurity Green’s function we show how initial Krylov vectors can be computed via midcircuit measurement and how Lanczos iterations can be computed using the symmetry-preserving ansatz. For a single-impurity Anderson model with a number of bath sites increasing from one to seven, we show using numerical emulation that the ease of variational ground-state preparation is suggestive of linear scaling in circuit depth and subquartic scaling in optimizer complexity. We therefore expect that, combined with time-dependent methods for Green’s function computation, our ansatz provides a useful tool to account for electronic correlations on early fault-tolerant processors. Finally, with a view towards computing real materials properties of interest like magnetic susceptibilities and electron-hole propagators, we provide a straightforward method to compute many-body, time-dependent correlation functions using a combination of time evolution, midcircuit measurement-conditioned operations, and the Hadamard test.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Higher Hall conductivity from a single wave function: Obstructions to symmetry-preserving gapped edge of (2+1)-dimensional topological order

A (2+1)D topologically ordered phase with U(1) symmetry may or may not have a symmetric gapped edge state, even if both thermal and electric Hall conductivity are vanishing. It has recently been discovered that there are “higher” versions of Hall conductivity valid for fermionic fractional quantum Hall (FQH) states that obstruct symmetry-preserving gapped edge states beyond thermal and electric Hall conductivity. In this paper, we show that one can extract higher Hall conductivity from a single wave function of an FQH state, by evaluating the expectation value of the “partial rotation” unitary, which is a combination of partial spatial rotation and a U(1) phase rotation. This result is verified numerically with the fermionic Laughlin state with 𝜈=1/3 and 1/5, as well as the non-Abelian Moore-Read state. Together with topological entanglement entropy, we prove that the expectation values of the partial rotation completely determine if a bosonic/fermionic Abelian topological order with U(1) symmetry has a symmetry-preserving gappable edge state or not. We also show that thermal and electric Hall conductivity of Abelian topological order can be extracted by partial rotations. Even in non-Abelian FQH states, partial rotation provides the Lieb-Schultz-Mattis type theorem constraining the low-energy spectrum of the bulk-boundary system. The generalization of higher Hall conductivity to the case with Lie group symmetry is also presented.

2-dimensional systems↗
DOE OSTI2023

(U)SAXS characterization of porous microstructure of chert: insights into organic matter preservation

This study characterizes the microstructure and mineralogy of 132 (ODP sample), 1000 and 1880 million-year-old chert samples. By using ultra-small-angle X-ray scattering (USAXS), wide-angle X-ray scattering and other techniques, the preservation of organic matter (OM) in these samples is studied. The scarce microstructural data reported on chert contrast with many studies addressing porosity evolution in other sedimentary rocks. The aim of this work is to solve the distribution of OM and silica in chert by characterizing samples before and after combustion to pinpoint the OM distribution inside the porous silica matrix. The samples are predominantly composed of alpha quartz and show increasing crystallite sizes up to 33 ± 5 nm (1σ standard deviation or SD). In older samples, low water abundances (~0.03%) suggest progressive dehydration. (U)SAXS data reveal a porous matrix that evolves over geological time, including, from younger to older samples, (1) a decreasing pore volume down to 1%, (2) greater pore sizes hosting OM, (3) decreasing specific surface area values from younger (9.3 ± 0.1 m 2 g -1 ) to older samples (0.63 ± 0.07 m 2 g -1 , 1σ SD) and (4) a lower background intensity correlated to decreasing hydrogen abundances. The pore-volume distributions (PVDs) show that pores ranging from 4 to 100 nm accumulate the greater volume fraction of OM. Raman data show aromatic organic clusters up to 20 nm in older samples. Raman and PVD data suggest that OM is located mostly in mesopores. Observed structural changes, silica–OM interactions and the hydro­phobicity of the OM could explain the OM preservation in chert.

(U)SAXS↗
DOE OSTI2024

In situ counter-diffusion crystallization and long-term crystal preservation in microfluidic fixed targets for serial crystallography

Compared with batch and vapor diffusion methods, counter diffusion can generate larger and higher-quality protein crystals yielding improved diffraction data and higher-resolution structures. Typically, counter-diffusion experiments are conducted in elongated chambers, such as glass capillaries, and the crystals are either directly measured in the capillary or extracted and mounted at the X-ray beamline. Despite the advantages of counter-diffusion protein crystallization, there are few fixed-target devices that utilize counter diffusion for crystallization. In this article, different designs of user-friendly counter-diffusion chambers are presented which can be used to grow large protein crystals in a 2D polymer microfluidic fixed-target chip. Methods for rapid chip fabrication using commercially available thin-film materials such as Mylar, propylene and Kapton are also detailed. Rules of thumb are provided to tune the nucleation and crystal growth to meet users' needs while minimizing sample consumption. These designs provide a reliable approach to forming large crystals and maintaining their hydration for weeks and even months. This allows ample time to grow, select and preserve the best crystal batches before X-ray beam time. Importantly, the fixed-target microfluidic chip has a low background scatter and can be directly used at beamlines without any crystal handling, enabling crystal quality to be preserved. The approach is demonstrated with serial diffraction of photoactive yellow protein, yielding 1.32 Å resolution at room temperature. Fabrication of this standard microfluidic chip with commercially available thin films greatly simplifies fabrication and provides enhanced stability under vacuum. These advances will further broaden microfluidic fixed-target utilization by crystallographers.

Liu, Zhongrui↗
DOE OSTI2024

Privacy-preserving Average Consensus Algorithm with Beaver Triple

A privacy-preserving average consensus algorithm is designed based on the Beaver triple technique against passive adversaries. The Beaver triple technique is integrated into a restructure of the discrete-time average consensus algorithm to preserve the privacy of initial values of agents in a multiagent system. The performance of the algorithm is theoretically analyzed.

Wang, Peng [Shanghai Jiao Tong University, China]↗
DOE OSTI2022

Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning

Graph convolution incorporates topological information of a graph into learning. Message passing corresponds to traversal of a local neighborhood in classical graph algorithms. We show that incorporating additional global structures, such as shortest paths, through distance preserving embedding can improve performance. Our approach, Gavotte, significantly improves the performance of a range of popular graph neu-ral networks such as GCN, GA T,Graph SAGE, and GCNII for transductive learning. Gavotte also improves the performance of graph neural networks for full-supervised tasks, albeit to a smaller degree. As high-quality embeddings are generated by Gavotte as a by-product, we leverage clustering algorithms on these embed dings to augment the training set and introduce Gavotte+. Our results of Gavotte+ on datasets with very few labels demonstrate the advantage of augmenting graph convolution with distance preserving embedding.

Cong, Guojing↗
DOE OSTI2025

Privacy-Preserving Average Consensus With Beaver Triple and Communication Obfuscation

A privacy-preserving average consensus algorithm is proposed that synergizes the Beaver triple in secret sharing theory and noise obfuscation. The algorithm safeguards the initial values of agents against passive adversaries in a multiagent system. It is proved that the proposed algorithm can concurrently ensure average consensus and privacy, while also reducing the online computation and communication overhead compared to encryption-based ones. In addition, it imposes a less stringent condition for privacy preservation compared to certain noise-obfuscation techniques.

Beaver triple↗
DOE OSTI2021

A Privacy-Preserving Distributed Control of Optimal Power Flow

Here, we consider a distributed optimal power flow formulated as an optimization problem that maximizes a nondifferentiable concave function. Solving such a problem by the existing distributed algorithms can lead to data privacy issues because the solution information exchanged within the algorithms can be utilized by an adversary to infer the data. To preserve data privacy, in this paper we propose a differentially private projected subgradient (DP-PS) algorithm that includes a solution encryption step. We show that a sequence generated by DP-PS converges in expectation, in probability, and with probability 1. Moreover, we show that the rate of convergence in expectation is affected by a target privacy level of DP-PS chosen by the user. We conduct numerical experiments that demonstrate the convergence and data privacy preservation of DP-PS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

3D-printed mirror-less helicity preserving metasurface “mirror” for THz applications

Stimulated by seminal works on generalized reflection and refraction laws, metasurfaces have evolved to a highly promising research direction, as they allow a multitude of different functionalities by optically thin wave-control elements/structures. Among them, structures functioning in the low THz regime are of extensive research interest, due to their high potential in communication and sensing applications. In this paper we propose a simple THz metasurface design that exhibits ideally perfect cross-polarized reflection for linear polarization and perfect helicity-preserving reflection with a geometric (Pancharatnam–Berry) phase for circular polarization, without the presence of any back-reflector. Numerical calculations demonstrating the structure response are justified by analytical models, which provide physical insights on this response. The designed metasurfaces are fabricated using the direct laser writing 3D-printing technology, metallized with electroless silver plating, and are characterized by THz time domain spectroscopy, with the experimental results validating the corresponding theoretical ones. Applications including beam steering and focusing, exploring the Pancharatnam–Berry phase, are also demonstrated numerically. Besides those applications, the helicity preserving mirror response of our metasurfaces can be valuable, among others, also in molecular chirality sensing applications, an issue that is also highlighted here.

3D-printed metasurfaces↗
DOE OSTI2020

AmeriFlux US-xDS NEON Disney Wilderness Preserve (DSNY)

This is the AmeriFlux version of the carbon flux data for the site US-xDS NEON Disney Wilderness Preserve (DSNY). Site Description - The 12,000-acre Disney Wilderness Preserve straddles the headwaters of the Everglades ecosystem in south-central Florida. This site is seasonally wet and flooded. The Disney site was heavily logged and used as ranchland for decades. However, vegetation and site conditions have been restored to closely represent site condition records, documented by the area’s first Spanish missionaries. The large-scale wetland and upland restoration at Disney included the removal of non-native, invasive plants and grasses and the removal of agricultural ditches. The primary management activity is controlled burns.

Network), NEON (National Ecological Observatory↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-DPW Disney Wilderness Preserve Wetland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-DPW Disney Wilderness Preserve Wetland. This is the FLUXNET version of the carbon flux data for the site US-DPW Disney Wilderness Preserve Wetland produced by applying the standard ONEFlux (1F) software. Site Description - The area was set aside for conservation as a mitigation site. It was unmanaged depression marsh

Hinkle, Charles Ross [University of Central Florid↗
DOE OSTI2021

Structure-preserving numerical discretizations for domains with boundaries

This SAND report documents Exploratory Express LDRD Project 223790, "Structure-preserving numerical discretizations for domains with boundaries", which developed a method to incorporate consistent treatment of domain boundaries and arbitrary boundary conditions in discrete exterior calculus (DEC) for arbitrary polygonal (2D) and tensor-product structure prism (3D) grids. The new DEC required the development of novel discrete exterior derivatives, boundary operators, wedge products and Hodge stars. This was accomplished through the use of boundary extension and the blending of known 2D operators on the interior with 1D operators on the boundary. The Hodge star was based on the Voronoi Hodge star, and retained the limitation of a triangular circumcentric primal or dual grid along with low-order accuracy. In addition to the new DEC, two related software packages were written: one for the study of DEC operators on arbitrary polygonal and polyhedral grids using both symbolic and numerical approaches and one for a (thermal) shallow water testbed using TRiSK-type numerics. Immediately relevant (already funded, through CANGA) followup work is the development of a high-order, geometrically flexible Hodge star and structure-preserving, high-order, oscillation-limiting transport operators (using WENO) for n-forms on arbitrary 2D and 3D grids. This will provide all of the machinery required for a high-order version of TRiSK with boundaries on arbitrary 2D and tensor-product 3D grids, which is applicable to both the atmospheric (CRM in E3SM-MMF) and oceanic (MPAS-O) components of E3SM.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Record of Treatment for Concrete Preservation Work at TA-6-0037 Concrete Bowl, TA-08 Gun Site, TA-16-0518 Stem Wall, and TA-18 Battleship Bunkers (Historic Buildings Report)

This completion report documents concrete preservation work that occurred in Fiscal Years 2019 and 2020. Work took place at four sites (Technical Areas [TAs] -06, -08, -16, and -18) that hold Manhattan Project–era significance. Seven buildings and structures were included in the project scope, with concentrated assessments and treatment plans accomplished before the start of preservation activities. The attended buildings and structures represent eligible or included Manhattan Project National Historical Park resources. The stabilization of original fabric and the retention of integrity and significance remained paramount throughout all phases of this project.

42 ENGINEERING↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Making an s1G Self-Preserving Environmental DNA (eDNA) Filter from Sustainable Materials

Environmental DNA (eDNA) sampling of aquatic environments is a powerful new tool for resource managers to use in detecting the presence of rare and endangered species. The use of eDNA for species detection is quickly becoming an industry-standard methodology in environmental science, and the technology sector is moving quickly to create purpose-built tools for eDNA sampling. Smith-Root, Inc. pioneered the new technology of self-preserving eDNA filters that automatically preserve the DNA captured on filters by desiccating the internal filter membrane. This capability saves the sampling technician significant time in the field and drastically reduces the potential for sample contamination. One main constraint of this new technology, however, is the necessity of single-use plastics for eDNA sampling. Single-use designs are employed because sampling equipment must be devoid of potential contaminating DNA, and the time required to sterilize equipment is often not cost-effective for practitioners. Thus, this technology is creating a significant new source of plastic waste—something that eDNA practitioners, and society, would like to avoid. This project explores the use of alternative bio based polymers and composites as replacements for incumbent industrial standards for eDNA filtration systems, with an emphasis on ease of processing and biodegradable options. 8 candidate materials, 3 for the top filter housing and 5 for the bottom filter housing, were investigated to replace incumbent housing materials. Of the 8 candidates, 2 materials were identified for future investigation which met performance requirements, were bio-based and could potentially offer better disposal options like soil degradation or composting, features sought by the customers of these products. The top housing candidate, material 1, has comparable performance to the incumbent material and equally manufacturable. The bottom housing candidate, material 6, improved desiccation performance by 81% after 1 hour in comparison to the incumbent material, is 100% bio-based, compostable and can be sourced domestically throughout the U.S.A.

36 MATERIALS SCIENCE↗
DOE OSTI2026

MINERvA s Open Data Product: A First for Neutrino Data Preservation

Access to information on neutrino nucleus interactions is critical to the success of all neutrino oscillation experiments. MINERvA's rich dataset covers a range of energies and nuclei unique amongst experiments, and as such is critical to the community in building the important shared knowledge needed to unravel the mysteries of the neutrino. In particular, its dataset provides the greatest statistical coverage in in the range of neutrino energies pertinent for DUNE until DUNE's near detector begins operation. Historically, such significant datasets in neutrino physics have been preserved primarily through their published results. While meaningful and useful, this limits the ability to explore the data to its fullest extent as new perspectives continue to form. MINERvA has undertaken a major effort to break this trend and preserve its data in a format to be as analyzable as possible from outside the collaboration. This has culminated in the officially-released MINERvA Open Data Product for the community to take advantage of and utilize. Maintaining direct access to the dataset in an analyzable form will allow new insights to continue to be extracted indefinitely. This talk will cover the contents of this product, the information included (and excluded), the tools provided to utilize the product effectively, the support MINERvA intends to provide in its use, and some lessons learned through the process.

Last, David [Rochester U.] (ORCID:0000000245147183↗
DOE OSTI2025

Variance Preserving Spectral Subsampling

Generating statistically faithful short-duration gamma-ray spectra from a single long measurement is essential in nuclear safeguards, supporting tasks such as algorithm development and machine-learning applications, especially when list-mode data are unavailable. Existing subsampling methods often distort the statistical characteristics of genuine short-duration measurements, leading to biased or unreliable analytical outcomes and thereby undermining downstream tasks. In this work, we compare five subsampling approaches using a benchmark set of 156 genuine replicate spectra collected with a high-purity germanium detector. We evaluate each method with respect to run-to-run variance, channel-to-channel variance, and preservation of total counts (losslessness). Across a wide range of subsampling ratios, only binomial subsampling without replacement consistently reproduces the statistical properties of genuine short-duration spectra, maintaining proper dispersion even in sparse spectral regions and perfectly preserving total counts. These results provide a mathematically principled and practically validated framework for generating synthetically shortened spectra when true short-duration measurements are unavailable.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Preservation of Mammalian Teeth and Bones Influences Identification of Terminal Pleistocene to Middle Holocene Hunter-Gatherer Subsistence at Ban Rai Rockshelter, Northwest Thailand

Ban Rai Rockshelter in northwest Thailand, dating to the Terminal Pleistocene and Middle Holocene, includes evidence for hunter-gatherer exploitation of mammals, birds, reptiles, fish, and arthropods. Abundant faunal remains, identified throughout site deposits, include macaques (Macaca sp.) and Sambar deer (Rusa unicolor), but these identifications are influenced by an assemblage largely comprised of preserved tooth elements and fragmented bone. Area 3 at Ban Rai has the largest abundance and diversity of faunal remains recovered and identified in this study. Here, we examine the zooarchaeological assemblage from Ban Rai Rockshelter, to understand long-term hunter-gatherer subsistence change, influenced by site preservation, during and after the Pleistocene–Holocene transition. Our results support the presence of the exploitation of arboreal taxa during the Early and Middle Holocene in northwest Thailand.

59 BASIC BIOLOGICAL SCIENCES↗