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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Onset of Scrambling as a Dynamical Transition in Tunable-Range Quantum Circuits

In a fast-scrambling many-body quantum system, information is spread and entanglement is built up on a time scale that grows logarithmically with the system size. This is of fundamental interest in understanding the dynamics of many-body systems, as well as in efficiently producing entangled resource states and error-correcting codes. In this work, we identify a dynamical transition marking the onset of scrambling in quantum circuits with different levels of long-range connectivity. In particular, we show that as a function of the interaction range for circuits of different structures, the tripartite mutual information exhibits a scaling collapse around a critical point between two clearly defined regimes of different dynamical behavior. We study this transition analytically in a related long-range Brownian-circuit model and show how the transition can be mapped onto the statistical mechanics of a long-range Ising model in a particular region of parameter space. This mapping predicts mean-field critical exponents v=–1/(1 + s c ), which are consistent with the critical exponents extracted from Clifford-circuit numerics. In addition to systems with conventional power-law interactions, we identify the same phenomenon in deterministic sparse circuits that can be realized in experiments with neutral-atom arrays.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Learning to Predict Arbitrary Quantum Processes

We present an efficient machine-learning (ML) algorithm for predicting any unknown quantum process ℰ over 𝑛 qubits. For a wide range of distributions 𝒟 on arbitrary 𝑛-qubit states, we show that this ML algorithm can learn to predict any local property of the output from the unknown process ℰ, with a small average error over input states drawn from 𝒟. The ML algorithm is computationally efficient even when the unknown process is a quantum circuit with exponentially many gates. Our algorithm combines efficient procedures for learning properties of an unknown state and for learning a low-degree approximation to an unknown observable. The analysis hinges on proving new norm inequalities, including a quantum analogue of the classical Bohnenblust-Hille inequality, which we derive by giving an improved algorithm for optimizing local Hamiltonians. Numerical experiments on predicting quantum dynamics with evolution time up to 10 6 and system size up to 50 qubits corroborate our proof. Overall, our results highlight the potential for ML models to predict the output of complex quantum dynamics much faster than the time needed to run the process itself.

quantum computation↗
DOE OSTI2025

Complementarity-based complementarity: The choice of mutually unbiased observables shapes quantum uncertainty relations

Quantum uncertainty relations impose fundamental limits on the joint knowledge that can be acquired from complementary observables: Perfect knowledge of a quantum state in one basis implies maximal indetermination in all other mutually unbiased bases (MUBs). Uncertainty relations derived from joint properties of the MUBs are generally assumed to be uniform, irrespective of the specific observables chosen within a set. In this work, we demonstrate instead that the uncertainty relations can depend on the choice of observables. Through both experimental observation and numerical methods, we show that selecting different sets of three MUBs in a five-dimensional quantum system results in distinct uncertainty bounds, i.e., in varying degrees of complementarity, in terms of both entropy and variance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Polynomial-Time Classical Algorithm for Noisy Quantum Circuits

We provide a polynomial-time classical algorithm for noisy quantum circuits. The algorithm computes the expectation value of any observable for any circuit, with a small average error over input states drawn from an ensemble (e.g., the computational basis). Our approach is based upon the intuition that noise exponentially damps nonlocal correlations relative to local correlations. This enables one to classically simulate a noisy quantum circuit by keeping track of only the dynamics of local quantum information. Our algorithm also enables sampling from the output distribution of a circuit in quasipolynomial time, so long as the distribution anticoncentrates. A number of implications are discussed, including a fundamental limit on the efficacy of noise mitigation strategies: For constant noise rates, any quantum circuit for which error mitigation succeeds in polynomial-time on most input states can also be classically simulated in polynomial-time on most input states. Our algorithms scale exponentially in the inverse noise rate, which is fundamental and makes them impractical for current quantum devices.

decoherence↗
DOE OSTI2026

Ultra-Wideband Communications: Interference Challenges and Solutions

The idea of ultra-wideband (UWB) communications for short ranges (up to a few tens of meters) has been around for nearly three decades. However, despite significant efforts by the industry, UWB deployment has not yet reached its predicted potential. This article, thus, seeks to rectify this situation by providing a practical examination of UWB interference conditions. Through a spectrum survey of today's wireless environments, we explore the interference that UWB devices may face from a perspective of outage probability in both high- and low-rate configurations. We find that by suppressing interference, the outage probability can be reduced by one or more orders of magnitude. In the non-line-of-sight channels, in particular, we find that both interference suppression and bandwidth expansion are required to support the minimum data rates suggested in the IEEE802.15.4 series of standards. Here, we connect these findings to a recently proposed UWB signaling method based on filter banks and show this method fulfills the above requirements for implementing effective UWB systems.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

cabbi-bio/BECT-ABM

The emergence of the cellulosic bioeconomy requires not only adequate technological, economic, and policy advances, but also effective communication and coordination among the multiple stakeholders in the bioeconomy community. Aiming to facilitate stakeholder communication and collaboration for cellulosic bioeconomy growth, an agent-based model is developed as a community communication tool in this study. The tool simulates the behaviors and interactions of key stakeholders, as well as the responses and interactions between the stakeholders and biophysical, socioeconomic, and environmental conditions. The agent behavior rules are developed and validated based on behavior and economic theories and information attained from a stakeholder focus group study and a land use survey.

Yang, Pan↗
DOE OSTI2020

Variable Precision Computing (VPC) (Final Report)

The overall goal of the Variable Precision Computing project is exploring and identifying ways to reduce internodal communication cost in production physics simulation experiments running on a distributed-memory systems by compressing data, either in a lossy or lossless way, thus resulting in a significant computational performance increase. Among the several approaches proposed, the one discussed here has been proposed, designed and implemented by me. It concerns the application of information theory-derived metrics to classical molecular dynamics and computational fluid dynamics simulation experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Fundamental aspects of Spacetime and Quantum Fields

The proposal contained two goals: firstly, placing fundamental bound on thermalization in Quantum Field Theories (QFTs) and, secondly, developing our understanding of emergent spacetime from matrices through concrete models. Since the previous reporting period, in collaboration with Sean Hartnoll we have continued our study of entanglement edge modes in matrix quantum mechanics (MQM). This has resulted in two papers. The first applies our construction for the Matrix Quantum Hall system first to fuzzy sphere states known to correspond to stringy M2-branes in MQM. Entanglement in these states using machine learning methods have also been studied by Sean Hartnoll and Xizhi Han in previous work done under this grant. Our construction builds on this work, and further demonstrates how area laws on fuzzy geometries emerge from strongly coupled systems. The second paper generalizes this construction to all noncommutative geometries with curvature much larger than the noncommutativity parameter. We demonstrate that despite UV/IR mixing effects, the structure of entanglement edge mode irreducible representations is determined by the boundary area of subsystems. On manifolds without global symmetries, we have demonstrated that nonlocal effects inherent to noncommutative geometries resum into a change of frame of the metric structure, similar to the change from string frame to Einstein frame for entanglement entropies calculated in string theory. These advancements lay the groundwork for future progress in the understanding of emergent geometry from large-N theories. Using these techniques, we are currently working on applying our methods to noncom mutative geometries whose construction is not so well understood, such as the fuzzy 5-sphere. Despite their opacity these objects are quite important, as string physics in the bulk of holographic systems bears many features of noncommutative geometry. We have also laid the groundwork of applying our methods to tensor networks, one of the most powerful models for understanding how geometry emerges from entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The Need for a System Science Approach to Global Magnetospheric Models

This perspective advocates for the need of a combined system science approach to global magnetospheric models and to spacecraft magnetospheric data to answer the question “Do simulations behave in the same manner as the magnetosphere does?” (instead of the standard validation question “How well do simulations reproduce spacecraft data?”). This approach will 1) validate global magnetospheric models statistically, without the need for a direct comparison against spacecraft data, 2) expose the deficiencies of the models, and 3) provide physics support to the system analysis performed on the magnetospheric system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Diffusion Codes: Self-Correction from Small(er)-Set Expansion with Tunable Non-locality

Optimal constructions of classical LDPC codes can be obtained by choosing the Tanner graph uniformly at random among biregular graphs. We introduce a class of codes that we call ``diffusion codes'', defined by placing each edge connecting bits and checks on some graph, and acting on that graph with a random SWAP network. By tuning the depth of the SWAP network, we can tune a tradeoff between the amount of randomness -- and hence the optimality of code parameters -- and locality with respect to the underlying graph. For diffusion codes defined on the cycle graph, if the SWAP network has depth $\sim Tn$ with $T> n^{2β}$ for arbitrary $β>0$, then we prove that almost surely the Tanner graph is a lossless ``smaller set'' vertex expander for small sets up size $δ\sim \sqrt T \sim n^β$, with bounded bit and check degree. At the same time, the geometric size of the largest stabilizer is bounded by $\sqrt T$ in graph distance. We argue, based on physical intuition, that this result should hold more generally on arbitrary graphs. By taking hypergraph products of these classical codes we obtain quantum LDPC codes defined on the torus with smaller-set boundary and co-boundary expansion and the same expansion/locality tradeoffs as for the classical codes. These codes are self-correcting and admit single-shot decoding, while having the geometric size of the stabilizer growing as an arbitrarily small power law. Our proof technique establishes mixing of a random SWAP network on small subsystems at times scaling with only the subsystem size, which may be of independent interest.

Combinatorics (math.CO)↗