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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 1,081 records · Page 60

Relevance of non-equilibrium defect generation processes to resistive switching in TiO{sub 2}

First principles calculations are employed to identify atomistic pathways for the generation of vacancy-interstitial pair defects in TiO{sub 2}. We find that the formation of both oxygen and titanium defects induces a net dipole moment indicating that their formation can be assisted by an electric field. We also show that the activation barrier to formation of an oxygen vacancy defect can be reduced by trapping of holes which may be injected by the electrode. The calculated activation energies suggest that generation of titanium defects is more favorable than generation oxygen defects although activation energies in both cases are relatively high (>3.3 eV). These results provide much needed insight into an issue that has been widely debated but for which little definitive experimental information is available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

In Situ Real-Time Radiographic Study of Thin Film Formation Inside Rotating Hollow Spheres

Hollow spheres with uniform coatings on the inner surface have applications in optical devices, time- or site controlled drug release, heat storage devices, and target fabrication for inertial confinement fusion experiments. The fabrication of uniform coatings, which is often critical for the application performance, requires precise understanding and control over the coating process and its parameters. Here, we report on in-situ real-time radiography experiments that provide critical spatio-temporal information about the distribution of fluids inside hollow spheres during uniaxial rotation. Image analysis and computer fluid dynamics simulations were used to explore the effect of liquid viscosity and rotational velocity on the film uniformity. The data were then used to demonstrate the fabrication of uniform sol-gel chemistry derived porous polymer films inside 2mm inner diameter diamond shells.

aerogel↗

Gamma-ray probes of dark matter substructure

The substructure content of dark matter halos is interesting because it can be affected by complex galaxy physics and dark matter particle physics. However, observing the small scale structure of dark matter is a challenge. The subhalo abundance (mass function, minimum mass) and morphology (density profile, subhalo shape, subsubstructure) contain information about complex astrophysics (halo formation processes) and new exotic fundamental physics (dark matter interactions). Indirect detection of dark matter annihilation radiation (DMAR) in gamma rays may be the most direct method for observing small scale structure. I outline the ways in which gamma rays may probe halo substructure. If substructure is bountiful, it may be responsible for the eventual discovery of DMAR, for instance in galaxy clusters or the diffuse gamma-ray background. Otherwise, the observation of DMAR in places without much substructure, such as the Galactic center, would lead to strict limits on the properties of small scale structure. Properties of the gamma-ray angular power spectrum will also provide information or constraints on Milky Way halo substructure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Novel In-situ Patterning Technique to Fabricate Single Quantum Dots for Quantum Photonics

Photon sources able to emit single or entangled photon pairs are key components in quantum information systems. Semiconductor quantum dots (QDs) are promising candidates due to their high efficiencies and ease of integration with other photonic or electronic components. State-of-the-art QDs, however, are limited to certain emission wavelengths and specific applications due to material choice constraints and their randomness in shape/size. This project is focused on developing a novel in-situ patterning technique to realize QDs with a broad emission range, shape/size control and the ability to emit single/entangled photons. Our approach has two key elements: (1) In-situ patterning via arsenic-induced nanovoid etching on antimonide surfaces and (2) In-filling of nanovoids to form QDs. By closely controlling the experimental conditions, it is shown that this technique can be used to realize III-V QDs in As 2 - etched nanovoids on a GaSb surface. The exposure to As 2 in terms of substrate temperature, time and flux is found to have a significant impact on the process variables such as nanovoid depth, QD dimensions etc. An in-depth analysis of the etch mechanism reveals that by controlling the As 2 exposure, uniform 3-dimensional nanostructures with varying areal densities can be obtained without an in-filling step. Preliminary optical characterization of these nanostructures shows that these QDs may be relevant for realizing emitters in the telecom wavelength range.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Interactive cryptographic proofs of quantumness using mid-circuit measurements

The ability to perform measurements in the middle of a quantum circuit is a powerful resource. It underlies a wide range of applications, from remote state preparation to quantum error correction. Here we apply mid-circuit measurements for a particular task: demonstrating quantum computational advantage. The goal of such a demonstration is for a quantum device to perform a computational task that is infeasible for a classical device with comparable resources. In contrast to existing demonstrations, the distinguishing feature of our approach is that the classical verification process is efficient, both in asymptotic complexity and in practice. Furthermore, the classical hardness of performing the task is based upon well-established cryptographic assumptions. Protocols with these features are known as cryptographic proofs of quantumness. Using a trapped-ion quantum computer, we perform mid-circuit measurements by spatially isolating portions of the ion chain via shuttling. This enables us to implement two interactive cryptographic proofs of quantumness, which when suitably scaled to larger systems, promise the efficient verification of quantum computational advantage. In conclusion, our methods can be applied to a range of interactive quantum protocols.

97 MATHEMATICS AND COMPUTING↗

Generalization in quantum machine learning from few training data

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as $\sqrt{T/N}$. When only K$\ll$T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to $\sqrt{K/N}$. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data.

97 MATHEMATICS AND COMPUTING↗

Stabilization and control of topological magnetic solitons via magnetic nanopatterning of exchange bias systems

Stabilizing and manipulating topological magnetic quasiparticles in thin films is of great interest for potential applications in data storage and information processing. Here, we present a strategy for stabilizing magnetic vortices and Bloch lines with controlled position, vorticity, and chirality in a continuous exchange bias system. By tailoring vectorially the unidirectional anisotropy of the system at the nanoscale, via thermally assisted magnetic scanning probe lithography, we show experimentally and via micromagnetic simulations the non-volatile creation of vortex-antivortex pairs. In addition, we demonstrate the deterministic stabilization of cross and circular Bloch lines within patterned Néel magnetic domain walls. This work enables the implementation of complex functionalities based on the control of tailored topological spin-textures in spintronic and magnonic nanodevices.

Magnetic ordering↗

Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning

Using electron beam manipulation, we enable deterministic motion of individual Si atoms in graphene along predefined trajectories. Structural evolution during the dopant motion was explored, providing information on changes of the Si atom neighborhood during atomic motion and providing statistical information of possible defect configurations. The combination of a Gaussian mixture model and principal component analysis applied to the deep learning-processed experimental data allowed disentangling of the atomic distortions for two different graphene sublattices. This approach demonstrates the potential of e-beam manipulation to create defect libraries of multiple realizations of the same defect and explore the potential of symmetry breaking physics. The rapid image analytics enabled via a deep learning network further empowers instrumentation for e-beam controlled atom-by-atom fabrication. Here, the analysis described in the paper can be reproduced via an interactive Jupyter notebook at https://git.io/JJ3Bx.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Reformulation of the No-Free-Lunch Theorem for Entangled Datasets

The No-Free-Lunch (NFL) theorem is a celebrated result in learning theory that limits one’s ability to learn a function with a training data set. With the recent rise of quantum machine learning, it is natural to ask whether there is a quantum analog of the NFL theorem, which would restrict a quantum computer’s ability to learn a unitary process with quantum training data. However, in the quantum setting, the training data can possess entanglement, a strong correlation with no classical analog. In this work, we show that entangled data sets lead to an apparent violation of the (classical) NFL theorem. This motivates a reformulation that accounts for the degree of entanglement in the training set. As our main result, we prove a quantum NFL theorem whereby the fundamental limit on the learnability of a unitary is reduced by entanglement. We employ Rigetti's quantum computer to test both the classical and quantum NFL theorems. In conclusion, our work establishes that entanglement is a commodity in quantum machine learning.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Acousto-optic laser projection systems for displaying TV information

This review addresses various approaches to television projection imaging on large screens using lasers. Results are presented of theoretical and experimental studies of an acousto-optic projection system operating on the principle of projecting an image of an entire amplitude-modulated television line in a single laser pulse. We consider characteristic features of image formation in such a system and the requirements for its individual components. Particular attention is paid to nonlinear distortions of the image signal, which show up most severely at low modulation signal frequencies. We discuss the feasibility of improving the process efficiency and image quality using acousto-optic modulators and pulsed lasers. Real-time projectors with pulsed line imaging can be used for controlling high-intensity laser radiation. (review)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Integration of physiologically relevant photosynthetic energy flows into whole genome models of light‐driven metabolism

SUMMARY Characterizing photosynthetic productivity is necessary to understand the ecological contributions and biotechnology potential of plants, algae, and cyanobacteria. Light capture efficiency and photophysiology have long been characterized by measurements of chlorophyll fluorescence dynamics. However, these investigations typically do not consider the metabolic network downstream of light harvesting. By contrast, genome‐scale metabolic models capture species‐specific metabolic capabilities but have yet to incorporate the rapid regulation of the light harvesting apparatus. Here, we combine chlorophyll fluorescence parameters defining photosynthetic and non‐photosynthetic yield of absorbed light energy with a metabolic model of the pennate diatom Phaeodactylum tricornutum. This integration increases the model predictive accuracy regarding growth rate, intracellular oxygen production and consumption, and metabolic pathway usage. Through the quantification of excess electron transport, we uncover the sequential activation of non‐radiative energy dissipation processes, cross‐compartment electron shuttling, and non‐photochemical quenching as the rapid photoacclimation strategy in P. tricornutum. Interestingly, the photon absorption thresholds that trigger the transition between these mechanisms were consistent at low and high incident photon fluxes. We use this understanding to explore engineering strategies for rerouting cellular resources and excess light energy towards bioproducts in silico . Overall, we present a methodology for incorporating a common, informative data type into computational models of light‐driven metabolism and show its utilization within the design–build–test–learn cycle for engineering of photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Nonequilibrium formulation of varying-temperature bit erasure

Landauer's principle states that erasing a bit of information at fixed temperature T costs at least $k$ B $T$ ln 2 units of work. Here we investigate erasure at varying temperature, to which Landauer's result does not apply. Here we formulate bit erasure as a stochastic nonequilibrium process involving a compression of configuration space, with physical and logical states associated in a symmetric way. Erasure starts and ends at temperature T, but temperature can otherwise vary with time in an arbitrary way. Defined in this way, erasure is governed by a set of nonequilibrium fluctuation relations that show that varying-temperature erasure can done with less work than $k$ B $T$ ln 2. As a result, erasure and the complementary process of bit randomization can be combined to form a work-producing engine cycle.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum logic gate synthesis as a Markov decision process

Reinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov decision processes (MDPs). Here, we investigate the feasibility of this assumption by exploring its consequences for single-qubit quantum state preparation and gate compilation. By forming discrete MDPs, we solve for the optimal policy exactly through policy iteration. We find optimal paths that correspond to the shortest possible sequence of gates to prepare a state or compile a gate, up to some target accuracy. Our method works in both the absence and presence of noise and compares favorably to other quantum compilation methods, such as the Ross–Selinger algorithm. This work provides theoretical insight into why reinforcement learning may be successfully used to find optimally short gate sequences in quantum programming.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Estimating the epidemic threshold on networks by deterministic connections

For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dephasing in Fluxonium Qubits from Coherent Quantum Phase Slips

Phase slips occur across all Josephson junctions (JJs) at a rate that increases with the impedance of the junction. In superconducting qubits composed of JJ-array superinductors—such as fluxonium—phase slips in the array can lead to decoherence. In particular, phase-slip processes at the individual array junctions can coherently interfere, each with an Aharonov-Casher phase that depends on the offset charges of the array islands. These coherent quantum phase slips (CQPS) perturbatively modify the qubit frequency, and therefore charge noise on the array islands will lead to dephasing. By varying the impedance of the array junctions, we design a set of fluxonium qubits in which the expected phase-slip rate within the JJ array changes by several orders of magnitude. We characterize the coherence times of these qubits and demonstrate that the scaling of CQPS-induced dephasing rates agrees with our theoretical model. Furthermore, we perform noise spectroscopy of two qubits in regimes dominated by either CQPS or flux noise. We find that the noise power spectrum associated with CQPS dephasing appears to be featureless at low frequencies and not 1 / f . Numerical simulations indicate that this behavior is consistent with charge noise generated by charge-parity fluctuations within the array. Our findings broadly inform JJ-array-design trade-offs, relevant for the numerous superconducting-qubit designs employing JJ-array superinductors. Published by the American Physical Society 2024

Physics↗

Stochastic nature of magnetic processes studied by full-field soft X-ray microscopy

In nanomagnetism, one of the crucial scientific questions is whether magnetic behaviors are deterministic or stochastic on a nanoscale. Apart from the exciting physical issue, this question is also of paramount highest relevance for using magnetic materials in a wealth of technological applications such as magnetic storage and sensor devices. In the past, the research on the stochasticity of a magnetic process has been mainly done by macroscopic measurements, which only offer ensemble-averaged information. To give more accurate answer for the question and to fully understand related underlying physics, the direct observation of statistical behaviors in magnetic structures and magnetic phenomena utilizing advanced characterization techniques is highly required. One of the ideal tools for such study is a full-field soft X-ray microscope since it enables imaging of magnetic structures on the large field of view within a few seconds. Here in this paper, we review the stochastic behaviors of various magnetic processes including magnetization reversal process in thin films, magnetic domain wall motions in nanowires, and magnetic vortex formations in nanodisks studied by full-field soft X-ray microscopy. The origin triggering the stochastic nature witnessed in each magnetic process and the way to control the intrinsic nature are also discussed.

36 MATERIALS SCIENCE↗

Magnon-based logic in a multi-terminal YIG/Pt nanostructure

Boolean logic is the foundation of modern digital information processing. Recently, there has been a growing interest in phenomena based on pure spin currents, which allows to move from charge to spin based logic gates. We study a proof-of-principle logic device based on the ferrimagnetic insulator Yttrium Iron Garnet, with Pt strips acting as injectors and detectors for non-equilibrium magnons. We experimentally observe incoherent superposition of magnons generated by different injectors. This allows to implement a fully functional majority gate, enabling multiple logic operations (AND and OR) in one and the same device. Clocking frequencies of the order of several GHz and straightforward down-scaling make our device promising for applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗