Engineering Papers⌕ Search

SEARCH · Engineering Papers

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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Nonreciprocal signal routing in an active quantum network

As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. In this work, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Label-free quantum super-resolution imaging using entangled multi-mode squeezed light

Abstract In this study, we explore the theoretical application of entangled multi-mode squeezed light for label-free optical super-resolution imaging. By generating massively entangled multi-mode squeezed light through an array of balanced beam splitters, using a single-mode squeezed light input, we create a multi-mode quantum light state with exceptional entanglement and noise suppression below the shot noise level. This significantly reduces imaging measurement errors compared to classical coherent state light imaging when the same number of photons are used on the imaging sample. We demonstrate how to optimize the imaging system’s parameters to achieve the Heisenberg imaging error limit, taking into account the number of entangled modes and photons used. We also examine the effects of optical losses in the imaging system, necessitating adjustments to the optimized parameters based on the degree of optical loss. In practical applications, this new quantum imaging approach reduces the number of photons needed to achieve the same image quality by two orders of magnitude compared to classical imaging methods that use non-entangled, non-squeezed coherent state light.

Soh, Daniel (ORCID:0000000325625675)↗
DOE OSTI2018

Quantum estimation in an expanding spacetime

Highlights: • FI and QFI of estimation on Hubble parameter of de Sitter space are explored. • QFI degrades due to Gibbons–Hawking radiation. • QFI can be enhanced for proper coupling of scalar field to curvature. • Optimal QFI depends on the squeezed nature of de Sitter α-vacua. - Abstract: We investigate the quantum estimation on the Hubble parameter of an expanding de Sitter space by quantum metrological techniques. By exploring the dynamics of a freely falling Unruh–DeWitt detector, which interacts with a scalar field coupling to curvature, we calculate the Fisher information (FI) and quantum Fisher information (QFI) for the detector, which bound the highest precision of the estimation on Hubble parameter. In standard Bunch–Davies vacuum, we show that the maxima of FI/QFI are located for particular initial state of probe. Beside its dependence on the evolving time of detector and the energy spacing of atom ω, we show that the maxima of FI/QFI can be significantly enhanced once a proper coupling of scalar field to curvature is chosen. For instance, we show numerically that the estimation in the scenario with minimally/nearly minimally coupling scalar field can always outperform that with conformally coupling scalar field, corresponding to a higher FI/QFI in estimation. Moreover, we find that for general α-vacua of de Sitter space, a further improvement of estimation can be achieved, attributed to the squeezed nature of α-vacua that heavily constrains the measurement uncertainty. Some implications of our results are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Optically thick GaInAs/GaAsP strain-balanced quantum-well tandem solar cells with 29.2% efficiency under the AM0 space spectrum

GaAs is often used as a multijunction subcell due to its high material quality on GaAs substrates, despite having a non-optimal bandgap. The bandgap can be beneficially reduced using many layers of thin, strain-balanced GaInAs in a superlattice or quantum well device, but achieving excellent carrier collection without increased recombination has proven challenging. Here, we develop and demonstrate high performance, optically thick GaInAs/GaAsP strain-balanced solar cells. Excellent material quality is achieved in thick superlattices by using growth conditions that limit progressive thickness and composition fluctuations. Bandgap-voltage offsets as low as 0.31V are shown in superlattice cells using thin, highly strained GaP barriers. Optically thick superlattice cells with over 2500 nm of total GaInAs in the depletion region are developed, enabling 3.8 mA/cm 2 of extra photocurrent beyond the GaAs band edge under the AM0 space spectrum. Optimized superlattice solar cells are incorporated into two-junction devices that achieve 29.2% efficiency under the AM0 space spectrum due to their improved bandgap combination and high subcell voltages.

14 SOLAR ENERGY↗
DOE OSTI2021

Thermodynamic Implementations of Quantum Processes

Abstract Recent understanding of the thermodynamics of small-scale systems have enabled the characterization of the thermodynamic requirements of implementing quantum processes for fixed input states. Here, we extend these results to construct optimal universal implementations of a given process, that is, implementations that are accurate for any possible input state even after many independent and identically distributed (i.i.d.) repetitions of the process. We find that the optimal work cost rate of such an implementation is given by the thermodynamic capacity of the process, which is a single-letter and additive quantity defined as the maximal difference in relative entropy to the thermal state between the input and the output of the channel. Beyond being a thermodynamic analogue of the reverse Shannon theorem for quantum channels, our results introduce a new notion of quantum typicality and present a thermodynamic application of convex-split methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Toward an accurate equation of state and B1-B2 phase boundary for magnesium oxide up to terapascal pressures and electron-volt temperatures

By applying auxiliary-field quantum Monte Carlo, we calculate the equation of state (EOS) and B1-B2 phase transition of magnesium oxide (MgO) up to 1 TPa. Here, the results agree with available experimental data at low pressures and are used to benchmark the performance of various exchange-correlation functionals in density functional theory calculations. We determine PBEsol is an optimal choice for the exchange-correlation functional and perform extensive phonon and quantum molecular-dynamics calculations to obtain the thermal EOS. Our results provide a preliminary reference for the EOS and B1-B2 phase boundary of MgO from zero up to 10,500 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Digital quantum simulation of NMR experiments

Simulations of nuclear magnetic resonance (NMR) experiments can be an important tool for extracting information about molecular structure and optimizing experimental protocols but are often intractable on classical computers for large molecules such as proteins and for protocols such as zero-field NMR. We demonstrate the first quantum simulation of an NMR spectrum, computing the zero-field spectrum of the methyl group of acetonitrile using four qubits of a trapped-ion quantum computer. We reduce the sampling cost of the quantum simulation by an order of magnitude using compressed sensing techniques. We show how the intrinsic decoherence of NMR systems may enable the zero-field simulation of classically hard molecules on relatively near-term quantum hardware and discuss how the experimentally demonstrated quantum algorithm can be used to efficiently simulate scientifically and technologically relevant solid-state NMR experiments on more mature devices. Our work opens a practical application for quantum computation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Orchestrated trios: compiling for efficient communication in Quantum programs with 3-Qubit gates

Current quantum computers are especially error prone and require high levels of optimization to reduce operation counts and maximize the probability the compiled program will succeed. These computers only support operations decomposed into one- and two-qubit gates and only two-qubit gates between physically connected pairs of qubits. Typical compilers first decompose operations, then route data to connected qubits. We propose a new compiler structure, Orchestrated Trios, that first decomposes to the three-qubit Toffoli, routes the inputs of the higher-level Toffoli operations to groups of nearby qubits, then finishes decomposition to hardware-supported gates. This significantly reduces communication overhead by giving the routing pass access to the higher-level structure of the circuit instead of discarding it. A second benefit is the ability to now select an architecture-tuned Toffoli decomposition such as the 8-CNOT Toffoli for the specific hardware qubits now known after the routing pass. Furthermore, we perform real experiments on IBM Johannesburg showing an average 35% decrease in two-qubit gate count and 23% increase in success rate of a single Toffoli over Qiskit. We additionally compile many near-term benchmark algorithms showing an average 344% increase in (or 4.44x) simulated success rate on the Johannesburg architecture and compare with other architecture types.

compiler↗
DOE OSTI2013

Optimizing Tensor Contraction Expressions for Hybrid CPU-GPU Execution

Tensor contractions are generalized multidimensional matrix multiplication operations that widely occur in quantum chemistry. Efficient execution of tensor contractions on Graphics Processing Units (GPUs) requires several challenges to be addressed, including index permutation and small dimension-sizes reducing thread block utilization. Moreover, to apply the same optimizations to various expressions, we need a code generation tool. In this paper, we present our approach to automatically generate CUDA code to execute tensor contractions on GPUs, including management of data movement between CPU and GPU. To evaluate our tool, GPU-enabled code is generated for the most expensive contractions in CCSD(T), a key coupled cluster method, and incorporated into NWChem, a popular computational chemistry suite. For this method, we demonstrate speedup over a factor of 8.4 using one GPU (instead of one core per node) and over 2.6 when utilizing the entire system using hybrid CPU+GPU solution with 2 GPUs and 5 cores (instead of 7 cores per node). Finally, we analyze the implementation behavior on future GPU systems.

CUDA↗
DOE OSTI2014

Efficient charge carrier injection into sub-250 nm AlGaN multiple quantum well light emitting diodes

The design and Mg-doping profile of AlN/Al{sub 0.7}Ga{sub 0.3}N electron blocking heterostructures (EBH) for AlGaN multiple quantum well (MQW) light emitting diodes (LEDs) emitting below 250 nm was investigated. By inserting an AlN electron blocking layer (EBL) into the EBH, we were able to increase the quantum well emission power and significantly reduce long wavelength parasitic luminescence. Furthermore, electron leakage was suppressed by optimizing the thickness of the AlN EBL while still maintaining sufficient hole injection. Ultraviolet (UV)-C LEDs with very low parasitic luminescence (7% of total emission power) and external quantum efficiencies of 0.19% at 246 nm have been realized. This concept was applied to AlGaN MQW LEDs emitting between 235 nm and 263 nm with external quantum efficiencies ranging from 0.002% to 0.93%. After processing, we were able to demonstrate an UV-C LED emitting at 234 nm with 14.5 μW integrated optical output power and an external quantum efficiency of 0.012% at 18.2 A/cm{sup 2}.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Nonlinear Optimal Control Problem Arising from a Sterilization Process for Packaged Foods

In this paper we study an optimization problem arising from a sterilization process for packaged foods by using a microwave heating method. The goal of the optimal control is to find the optimal frequency function such that the temperature profile at the final stage has a relative uniform distribution in the food product. The underlying state variables are electric, magnetic fields and temperature which satisfy the coupled nonlinear Maxwell’s system and a nonlinear heat equation. The control variable for the system is chosen to be the electric frequency function. We show that there exists an optimal frequency which minimizes the cost functional. Moreover, an optimality condition is also derived.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Exponential concentration in quantum kernel methods

Kernel methods in Quantum Machine Learning (QML) have recently gained significant attention as a potential candidate for achieving a quantum advantage in data analysis. Among other attractive properties, when training a kernel-based model one is guaranteed to find the optimal model’s parameters due to the convexity of the training landscape. However, this is based on the assumption that the quantum kernel can be efficiently obtained from quantum hardware. In this work we study the performance of quantum kernel models from the perspective of the resources needed to accurately estimate kernel values. We show that, under certain conditions, values of quantum kernels over different input data can be exponentially concentrated (in the number of qubits) towards some fixed value. Thus on training with a polynomial number of measurements, one ends up with a trivial model where the predictions on unseen inputs are independent of the input data. We identify four sources that can lead to concentration including expressivity of data embedding, global measurements, entanglement and noise. For each source, an associated concentration bound of quantum kernels is analytically derived. Lastly, we show that when dealing with classical data, training a parametrized data embedding with a kernel alignment method is also susceptible to exponential concentration. Our results are verified through numerical simulations for several QML tasks. Altogether, we provide guidelines indicating that certain features should be avoided to ensure the efficient evaluation of quantum kernels and so the performance of quantum kernel methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Lossy compression of statistical data using quantum annealer

Abstract We present a new lossy compression algorithm for statistical floating-point data through a representation learning with binary variables. The algorithm finds a set of basis vectors and their binary coefficients that precisely reconstruct the original data. The optimization for the basis vectors is performed classically, while binary coefficients are retrieved through both simulated and quantum annealing for comparison. A bias correction procedure is also presented to estimate and eliminate the error and bias introduced from the inexact reconstruction of the lossy compression for statistical data analyses. The compression algorithm is demonstrated on two different datasets of lattice quantum chromodynamics simulations. The results obtained using simulated annealing show 3–3.5 times better compression performance than the algorithm based on neural-network autoencoder. Calculations using quantum annealing also show promising results, but performance is limited by the integrated control error of the quantum processing unit, which yields large uncertainties in the biases and coupling parameters. Hardware comparison is further studied between the previous generation D-Wave 2000Q and the current D-Wave Advantage system. Our study shows that the Advantage system is more likely to obtain low-energy solutions for the problems than the 2000Q.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

High efficiency low threshold current 1.3 μ m InAs quantum dot lasers on on-axis (001) GaP/Si

We demonstrate highly efficient, low threshold InAs quantum dot lasers epitaxially grown on on-axis (001) GaP/Si substrates using molecular beam epitaxy. Electron channeling contrast imaging measurements show a threading dislocation density of 7.3 × 106 cm−2 from an optimized GaAs template grown on GaP/Si. The high-quality GaAs templates enable as-cleaved quantum dot lasers to achieve a room-temperature continuous-wave (CW) threshold current of 9.5 mA, a threshold current density as low as 132 A/cm2, a single-side output power of 175 mW, and a wall-plug-efficiency of 38.4% at room temperature. As-cleaved QD lasers show ground-state CW lasing up to 80 °C. The application of a 95% high-reflectivity coating on one laser facet results in a CW threshold current of 6.7 mA, which is a record-low value for any kind of Fabry-Perot laser grown on Si.

Jung, Daehwan↗
NASA NTRSDate not supplied

Quantum-Accelerated Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Spanning Trees

We present two algorithms in the Quantum CONGEST-CLIQUE model of distributed computation that succeed with high probability; One for producing an approximately optimal Steiner Tree, and one for producing an exact Minimum Directed Spanning tree. These use O(n1/4) rounds of communication and O(n9/4) messages, leading to a quantum speedup in round and message complexity compared to any known algorithms in the classical CONGEST-CLIQUE model (vs O(n1/3) and O(n7/3)). At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Further, these problems can not be sped up in the CONGEST (non-clique) setting, and we characterize the constants involved.

Phillip Kerger↗
DOE OSTI2022

Investigation on the AgPt and AgPd hybrid alloy nanoparticles (HANPs) for the hybrid MoS 2 /ZnO/HANP UV photodetector application

We report hybrid photodetectors made of two or more nanomaterial components can offer the high potential for advanced photodetection applications with enhanced light absorption, improved efficiency and structural tunability. A hybrid UV photodetector (PD) configuration incorporating the plasmonic hybrid alloy nanoparticles (HANP), ZnO quantum dots (QDs) and MoS 2 nanoflakes, namely MoS2/ZnO/HANP PD, is demonstrated. The optimized MoS 2 /ZnO/HANP PD exhibits a high photocurrent of 5.66 mA at 0.34 mW/mm 2 under 385 nm illumination with two orders of improvement from the bare ZnO, which is one of the highest photocurrents by the ZnO-based PDs. It also demonstrates high figure-of-merits with the responsivity of 14,523 mA/W, detectivity of 8.13 x 10 11 jones, and external quantum efficiency (EQE) of 4,680 %, outperforming most of the ZnO-based hybrid architectures. The enhanced photoresponse is primarily attributed to the significantly enhanced hot electron generation by the AgPd HANPs and photocarrier collection through the ZnO QD layer. MoS 2 nanoflakes also provide additional photon absorption sites and boost the photo-carrier transfer process. HANPs are grown by adapting a dual-step solid-state dewetting process (SSD) approach and the superiority of AgPd HANPs is confirmed by systematic investigation, FDTD simulation and comparison of AgPt and AgPd HANPs.

MoS2↗
DOE OSTI2014

Computing single step operators of logic programming in radial basis function neural networks

Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A dynamic model for the optimization of oscillatory low grade heat engines

The efficiency of a thermodynamic system is a key quantity on which its usefulness and wider application relies. This is especially true for a device that operates with marginal energy sources and close to ambient temperatures. Various definitions of efficiency are available, each of which reveals a certain performance characteristic of a device. Of these, some consider only the thermodynamic cycle undergone by the working fluid, whereas others contain additional information, including relevant internal components of the device that are not part of the thermodynamic cycle. Yet others attempt to factor out the conditions of the surroundings with which the device is interfacing thermally during operation. In this paper we present a simple approach for the modeling of complex oscillatory thermal-fluid systems capable of converting low grade heat into useful work. We apply the approach to the NIFTE, a novel low temperature difference heat utilization technology currently under development. We use the results from the model to calculate various efficiencies and comment on the usefulness of the different definitions in revealing performance characteristics. We show that the approach can be applied to make design optimization decisions, and suggest features for optimal efficiency of the NIFTE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗