Search NASA⌕ Search

SEARCH · Search NASA

Results for “quantum optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68

Atomic-Layer-Deposited Aluminum Oxide Thin Films Probed with X-ray Scattering and Compared to Molecular Dynamics and Density Functional Theory Models

A better understanding of amorphous aluminum oxide’s structure and electronic properties is obtained through combined experimental and computational approaches. Grazing incidence X-ray scattering measurements were carried out on aluminum oxide thin films grown using thermal atomic layer deposition. The corresponding pair distribution functions (PDFs) showed structures similar to previously reported PDFs of solid-state amorphous alumina and molten alumina. Structural models based on crystalline alumina polymorphs (PDFgui) and amorphous alumina (molecular dynamics, MD) were examined for structural comparisons to the experimental PDF data. Smaller MD models were optimized and verified against larger models to allow for quantum chemical electronic structure calculations. The electronic structure of the amorphous alumina models yields additional insight into the band structure and electronic defects present in amorphous alumina that are not present in crystalline samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The ReaxFF reactive force-field: Development, applications, and future directions

The reactive force-field (ReaxFF) interatomic potential is a powerful computational tool for exploring, developing and optimizing material properties. Methods based on the principles of quantum mechanics (QM), while offering valuable theoretical guidance at the electronic level, are often too computationally intense for simulations that consider the full dynamic evolution of a system. Alternatively, empirical interatomic potentials that are based on classical principles require significantly fewer computational resources, which enables simulations to better describe dynamic processes over longer timeframes and on larger scales. Such methods, however, typically require a predefined connectivity between atoms, precluding simulations that involve reactive events. The ReaxFF method was developed to help bridge this gap. Approaching the gap from the classical side, ReaxFF casts the empirical interatomic potential within a bond-order formalism, thus implicitly describing chemical bonding without expensive QM calculations. As a result, this article provides an overview of the development, application, and future directions of the ReaxFF method.

97 MATHEMATICS AND COMPUTING↗

Quantum machine learning with differential privacy

Abstract Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. There exists the potential for a quantum advantage due to the intractability of quantum operations on a classical computer. Many datasets used in machine learning are crowd sourced or contain some private information, but to the best of our knowledge, no current QML models are equipped with privacy-preserving features. This raises concerns as it is paramount that models do not expose sensitive information. Thus, privacy-preserving algorithms need to be implemented with QML. One solution is to make the machine learning algorithm differentially private, meaning the effect of a single data point on the training dataset is minimized. Differentially private machine learning models have been investigated, but differential privacy has not been thoroughly studied in the context of QML. In this study, we develop a hybrid quantum-classical model that is trained to preserve privacy using differentially private optimization algorithm. This marks the first proof-of-principle demonstration of privacy-preserving QML. The experiments demonstrate that differentially private QML can protect user-sensitive information without signficiantly diminishing model accuracy. Although the quantum model is simulated and tested on a classical computer, it demonstrates potential to be efficiently implemented on near-term quantum devices [noisy intermediate-scale quantum (NISQ)]. The approach’s success is illustrated via the classification of spatially classed two-dimensional datasets and a binary MNIST classification. This implementation of privacy-preserving QML will ensure confidentiality and accurate learning on NISQ technology.

97 MATHEMATICS AND COMPUTING↗

Optimization of in-line phase contrast particle image velocimetry using a laboratory x-ray source

Phase contrast particle image velocimetry (PIV) using a laboratory x-ray microfocus source is investigated using a numerical model. Phase contrast images of 75 {mu}m air bubbles, embedded within water exhibiting steady-state vortical flow, are generated under the paraxial approximation using a tungsten x-ray spectrum at 30 kVp. Propagation-based x-ray phase-contrast speckle images at a range of source-object and object-detector distances are generated, and used as input into a simulated PIV measurement. The effects of source-size-induced penumbral blurring, together with the finite dynamic range of the detector, are accounted for in the simulation. The PIV measurement procedure involves using the cross-correlation between temporally sequential speckle images to estimate the transverse displacement field for the fluid. The global error in the PIV reconstruction, for the set of simulations that was performed, suggests that geometric magnification is the key parameter for designing a laboratory-based x-ray phase-contrast PIV system. For the modeled system, x-ray phase-contrast PIV data measurement can be optimized to obtain low error (<0.2 effective pixel of the detector) in the system with magnification lying in the range between 1.5 and 3. For large effective pixel size (>15 {mu}m) of the detector, high geometric magnification (>2.5) is desired, while for large source size system (FWHM > 30 {mu}m), low magnification (<1.5) would be suggested instead. The methods developed in this paper can be applied to optimizing phase-contrast velocimetry using a variety of laboratory x-ray sources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Femtosecond laser-induced size reduction of carbon nanodots in solution: Effect of laser fluence, spot size, and irradiation time

Photoluminescent carbon nanodots (C-dots) with size tunability and uniformity were fabricated in polyethylene glycol (PEG{sub 200N}) solution using femtosecond laser ablation method. The size distributions and photoluminescence (PL) properties of C-dots are well controlled by adjusting the combined parameters of laser fluence, spot size, and irradiation time. The size reduction efficiency of the C-dots progressively increases with decreasing laser fluence and spot size. The optimal PL spectra are red-shifted and the quantum yields decrease with the increase in C-dots size, which could be attributed to the more complex surface functional groups attached on C-dots induced at higher laser fluence and larger spot size. Moreover, an increase in irradiation time leads to a decrease in size of C-dots, but long-time irradiation will result in the generation of complex functional groups on C-dots, subsequently the PL spectra are red-shifted.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Topological superconductivity in Landau levels

The intense search for topological superconductivity is inspired by the prospect that it hosts Majorana quasiparticles. We explore in this work the optimal design for producing topological superconductivity by combining a quantum Hall state with an ordinary superconductor. To this end, we consider a microscopic model for a topologically trivial two-dimensional p-wave superconductor exposed to a magnetic field, and find that the interplay of superconductivity and Landau level physics yields a rich phase diagram of states as a function of μ/t and Δ/t, where μ, t and Δ are the chemical potential, hopping strength, and the amplitude of the superconducting gap. In addition to quantum Hall states and topologically trivial p-wave superconductor, the phase diagram also accommodates regions of topological superconductivity. Most importantly, we find that application of a non-uniform, periodic magnetic field produced by a square or a hexagonal lattice of h/e fluxoids greatly facilitates regions of topological superconductivity in the limit of Δ/t → 0. In contrast, a uniform magnetic field, a hexagonal Abrikosov lattice of h/2e fluxoids, or a one dimensional lattice of stripes produces topological superconductivity only for sufficiently large Δ/t.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

𝜂 and 𝜂′ Production in 𝐽/𝜓 Radiative Decays from Quantum Chromodynamics

We present a first principles calculation within quantum chromodynamics (QCD) of the radiative decays of the 𝐽/𝜓 into the light pseudoscalar mesons 𝜂 and 𝜂′. Within a lattice computation we obtain the transition form factors as a function of photon virtuality from the timelike region, accessible experimentally via the “Dalitz” decay 𝐽/𝜓 →𝑒 + ⁢𝑒 − ⁢𝜂 (′) , through to the real photon point corresponding to 𝐽/𝜓 →𝛾⁢𝜂 (′) . This is the first calculation in lattice QCD with two (heavier than physical) degenerate flavors of light quark and a heavier strange quark, in which the 𝜂′ appears as the first excited state with pseudoscalar isoscalar quantum numbers. We access it reliably by using variationally optimized operators , the use of which also improves the purity of the 𝐽/𝜓 and 𝜂 signals, reducing systematic uncertainties. High quality results at a large number of kinematic points are obtained in a typically noisy disconnected process by using a novel correlator averaging procedure. Our results show the expected enhanced production of the 𝜂′ over the 𝜂 in this process, and suggest that the demonstrated lattice technology is suitable for future calculations considering processes in which light meson resonances are produced.

form factors↗

Current Trends in Gamma Radiation Detection for Radiological Emergency Response

Passive and active detection of gamma rays from shielded radioactive materials, including special nuclear materials, is an important task for any radiological emergency response organization. This article reports on the current trends and status of gamma radiation detection objectives and measurement techniques as applied to nonproliferation and radiological emergencies. In recent years, since the establishment of the Domestic Nuclear Detection Office by the Department of Homeland Security, a tremendous amount of progress has been made in detection materials (scintillators, semiconductors), imaging techniques (Compton imaging, use of active masking and hybrid imaging), data acquisition systems with digital signal processing, field programmable gate arrays and embedded isotopic analysis software (viz. gamma detector response and analysis software [GADRAS]1), fast template matching, and data fusion (merging radiological data with geo-referenced maps, digital imagery to provide better situational awareness). In this stride to progress, a significant amount of interdisciplinary research and development has taken place–techniques and spin-offs from medical science (such as x-ray radiography and tomography), materials engineering (systematic planned studies on scintillators to optimize several qualities of a good scintillator, nanoparticle applications, quantum dots, and photonic crystals, just to name a few). No trend analysis of radiation detection systems would be complete without mentioning the unprecedented strategic position taken by the National Nuclear Security Administration (NNSA) to deter, detect, and interdict illicit trafficking in nuclear and other radioactive materials across international borders and through the global maritime transportation–the so-called second line of defense.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

QGLab v0.0.1

A software program for experimenting with holographic teleportation protocol on quantum computers. The code implements the protocol that was proposed in https://arxiv.org/abs/1911.06314. The code is an end-to-end software solution that facilitates conducting the holographic teleportation experiments on state-of-the-art and emergent generations of QPUs supported by the Qiskit and tket SDKs. The code bundles all stages of an experiment as a single configurable workflow allowing faster development and experimentation cycles. Features: 1. Easy switching between Qiskit and tket quantum compilers. 2. Semi-automatic facilities for finding optimal compilation solutions beyond what Qiskit and tket provide by default. 3. Experiment resolution scaling (based on automatic jobs' batching). 4. Automatic experiment scaling over qubits. 5. Automatic readout error mitigation. 6. Automatic reproducibility analysis. 7. Standalone error-mitigation tools (randomized compiling, mitigation with estimation circuits, zero-noise extrapolation)

Shapoval, Illya↗

A Comprehensive Analysis of the Physical Properties of Advanced GaAs/AlGaAs Junctions

Extensive studies have been performed on MQW junctions and structures because of their potential applications as avalanche photodetectors in optical communications and imaging systems. The role of the avalanche photodiode is to provide for the conversion of an optical signal into charge. Knowledge of junction physics, and the various carrier generation/recombination mechanisms, is crucial for effectively optimizing the conversion process and increasing the structure's quantum efficiency. In addition, the recent interest in the use of APDs in imaging systems has necessitated the development of semiconductor junctions with low dark currents and high gains for low light applications. Because of the high frame rate and high pixel density requirements in new imaging applications, it is necessary to provide some front-end gain in the imager to allow operation under reasonable light conditions. Understanding the electron/hole impact ionization process, as well as diffusion and surface leakage effects, is needed to help maintain low dark currents and high gains for such applications. In addition, the APD must be capable of operating with low power, and low noise. Knowledge of the effects of various doping configurations and electric field profiles, as well as the excess noise resulting from the avalanche process, are needed to help maintain low operating bias and minimize the noise output.

Menkara, Hicham M.↗

Number Partitioning via Quantum Adiabatic Computation

We study both analytically and numerically the complexity of the adiabatic quantum evolution algorithm applied to random instances of combinatorial optimization problems. We use as an example the NP-complete set partition problem and obtain an asymptotic expression for the minimal gap separating the ground and exited states of a system during the execution of the algorithm. We show that for computationally hard problem instances the size of the minimal gap scales exponentially with the problem size. This result is in qualitative agreement with the direct numerical simulation of the algorithm for small instances of the set partition problem. We describe the statistical properties of the optimization problem that are responsible for the exponential behavior of the algorithm.

Smelyanskiy, Vadim N.↗

Materials design concepts for efficient blue OLEDs: A joint theoretical and experimental study

Since their discovery, organic light emitting devices have evolved from a scientific curiosity into a technology with applications in flat panel displays and the potential to revolutionize the lighting market. During their relatively short history, the technology incorporated into OLEDs has rapidly advanced. Device quantum efficiencies have increased more than 20-fold since the first OLEDs, approaching the theoretical limit for internal quantum efficiencies. , , At this point, OLED research moves towards optimization of manufacturing processes, drive circuitry, light extraction, and overall cost reduction. However, finding the organic materials that provide both operational stability and high efficiency for the devices still remains one of the biggest challenges, particularly for blue emission. In this presentation, we will describe our approach to design functional OLED materials to meet the complex criteria set forth by device efficiency and stability goals.

Polikarpov, Evgueni↗

Visible light photoreduction of CO.sub.2 using heterostructured catalysts

The method provides for use of sensitized photocatalyst for the photocatalytic reduction of CO.sub.2 under visible light illumination. The photosensitized catalyst is comprised of a wide band gap semiconductor material, a transition metal co-catalyst, and a semiconductor sensitizer. The semiconductor sensitizer is photoexcited by visible light and forms a Type II band alignment with the wide band gap semiconductor material. The wide band gap semiconductor material and the semiconductor sensitizer may be a plurality of particles, and the particle diameters may be selected to accomplish desired band widths and optimize charge injection under visible light illumination by utilizing quantum size effects. In a particular embodiment, CO.sub.2 is reduced under visible light illumination using a CdSe/Pt/TiO2 sensitized photocatalyst with H.sub.2O as a hydrogen source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surpassing the Energy Resolution Limit with Ferromagnetic Torque Sensors

We discuss the fundamental noise limitations of a ferromagnetic torque sensor based on a levitated magnet in the tipping regime. We evaluate the optimal magnetic field resolution taking into account the thermomechanical noise and the mechanical detection noise at the standard quantum limit. We find that the energy resolution limit, pointed out in recent literature as a relevant benchmark for most classes of magnetometers, can be surpassed by many orders of magnitude. Moreover, similarly to the case of a ferromagnetic gyroscope, it is also possible to surpass the standard quantum limit for magnetometry with independent spins, arising from spin-projection noise. Our finding indicates that magnetomechanical systems optimized for magnetometry can achieve a magnetic field resolution per unit volume several orders of magnitude better than any conventional magnetometer. Here, we discuss possible implications, focusing on fundamental physics problems such as the search for exotic interactions beyond the standard model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem

Solving problems related to planning and operations of large-scale power systems is challenging on classical computers due to their inherent nature as mixed-integer and nonlinear problems. Quantum computing provides new avenues to approach these problems. We develop a hybrid quantum-classical algorithm for the Unit Commitment (UC) problem in power systems which aims at minimizing the total cost while optimally allocating generating units to meet the hourly demand of the power loads. The hybrid algorithm combines a variational quantum algorithm (VQA) with a classical Benders-type heuristic. The resulting algorithm computes approximate solutions to UC in three stages: i) a collection of UC vectors capable meeting the power demand with lowest possible operating costs is generated based on VQA; ii) a classical sequential least squares programming (SLSQP) routine is leveraged to find the optimal power level corresponding to a predetermined number of candidate vectors; iii) in the last stage, the approximate solution of UC along with generating units power level combination is given. To demonstrate the effectiveness of the presented method, three different systems with 3 generating units, 10 generating units, and 26 generating units were tested for different time periods. In addition, convergence of the hybrid quantum-classical algorithm for select time periods is proven out on IonQ's Forte system.

Aboumrad, Willie [IonQ, Inc]↗

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, despite significant progress and excitement, the path toward a full-stack scalable technology is largely unknown. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. These issues could seriously undermine the arrival of utility-scale quantum computers for the foreseeable future. Here, we provide a comprehensive review of these scaling challenges. We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits, employing system engineering approaches, and performing distributed quantum computation within heterogeneous high-performance computing infrastructures. These opportunities for research and development could unlock certain promising applications, in particular, efficient quantum simulation/learning of quantum data generated by natural or engineered quantum systems. To estimate the true cost of such promises, we provide a detailed resource and sensitivity analysis for classically hard quantum chemistry calculations on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. Furthermore, we argue that, to tackle industry-scale classical optimization and machine learning problems in a cost-effective manner, heterogeneous quantum-probabilistic computing with custom-designed accelerators should be considered as a complementary path toward scalability.

Mohseni, Masoud↗