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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Mechanism of electronic-excitation transfer in organic light-emitting devices based on semiconductor quantum dots

The results of an experimental study of organic light-emitting diodes (LEDs) with luminescent layers based on two types of CdSe/CdS semiconductor quantum dots (QDs) with an average CdSe core diameter of 3 and 5 nm and a characteristic CdS shell thickness of 0.5 nm are presented. The dependences of the LED efficiency on the QD concentration are determined. The experimental data are used to determine the mechanism of electronic-excitation transfer from the organic matrix to the semiconductor QDs. Ways of optimizing the design of the LEDs in order to improve their efficiency are suggested on this basis.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-F-18C-05: Characterization of a Silicon Strip Photon-Counting Detector in the Presence of Compton Scatter: A Simulation Study

Purpose: To investigate the effect of Compton scatter on detection efficiency and charge-sharing for a Si strip photon-counting detector as a function of pixel pitch, slice thickness and total pixel length. Methods: A CT imaging system employing a silicon photon-counting detector was implemented using the GATE Monte Carlo package. A focal spot size of 300 µm, magnification of 1.33, and pixel pitches of 0.1 and 0.5mm were initially investigated. A 60 kVp spectrum with 3 mm Al filter was used and energy spectral degradation based on a prototype detector was simulated. To study charge-sharing, a single pixel was illuminated, and the detector response in neighboring pixels was investigated. A longitudinally semiinfinite detector was simulated to optimize the quantum detection efficiency of the imaging system as a function of pixel pitch, slice thickness and depth of interaction. A 2.5 mm thick tungsten plate with a 0.01 mm by 1.5 mm slit was implemented to calculate the modulation transfer function (MTF) from projection-based images. A threshold of 15 keV was implemented in the detector simulation. The preliminary charge sharing investigation results considered only scattering effects and the detector electronics related factors were neglected. Results: Using a 15 keV threshold, 1% of the pixel charge migrated into neighboring pixels with a pixel size of 0.1×0.1 mm{sup 2}. The quantum detection efficiency was 77%, 84%, 87% and 89% for 15 mm, 22.5 mm, 30 mm, and 45 mm length silicon detector pixels, respectively. For a pixel pitch of 0.1 mm, the spatial frequency at 10% of the maximum MTF was found to be 5.2 lp/mm. This agreed with an experimental MTF measurement of 5.3 lp/mm with a similar detector configuration. Conclusion: Using optimized design parameters, Si strip photon-counting detectors can offer high detection efficiency and spatial resolution even in the presence of Compton scatter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Optimization of barrier layer thickness in MgSe/CdSe quantum wells for intersubband devices in the near infrared region

The authors report the optimization of MgSe barrier thickness in CdSe/MgSe multiple quantum well structures and its effect on structural, optical qualities and intersubband (ISB) transition characteristics. Three samples with the MgSe thicknesses of 2 nm, 3 nm, and 4 nm were grown on InP substrates by molecular beam epitaxy. X-ray diffraction and photoluminescence measurements showed that the thinner the MgSe barrier thickness the better the structural quality. However, ISB absorption was only observed in the sample with a MgSe thickness of 3 nm. Failing to observe ISB absorption in the sample with a thicker MgSe barrier (≥4 nm) is due to the deteriorated material quality while the missing of ISB transition in the sample with thinner barrier (≤2 nm) is due to the tunneling of electrons out of the CdSe wells. The optimized MgSe barrier thickness of around 3 nm is found to be able to suppress the electron tunneling while maintaining a good material quality of the overall structure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quantum Simulators and Applications on Quantum Framework

Simulating quantum circuits is essential for validating quantum algorithms. However, no single simulator consistently performs best - efficiency depends on circuit structure, entanglement, and depth. In this work, we integrate Qiskit-Aer (state-vector and matrix product state) and QTensor, a tree-tensor-network based simulator, into the Quantum Framework (QFw), a modular platform that supports multiple quantum backends via a unified interface. We also enable distributed quantum approximate optimization algorithm (DQAOA) application compatibility with QFw, allowing sub-problems to be solved in parallel at scale. We then benchmark DQAOA and TFIM (transverse field Ising model) circuits across supported simulators, showing how performance varies significantly with problem type. All simulations are deployed on the Frontier supercomputer using QFw's MPI-based orchestration for distributed, multinode execution. These results underscore the need for simulatoragnostic infrastructure to enable systematic evaluation and highperformance scaling of quantum workloads. QFw provides a practical and extensible path toward reproducible quantum algorithm development across diverse application domains.

Chundury, Srikar [ORNL] (ORCID:0009000183359259)↗
DOE OSTI2023

Computation of forces and stresses in solids: Towards accurate structural optimization with auxiliary-field quantum Monte Carlo

The accurate computation of forces and other energy derivatives has been a long-standing challenge for quantum Monte Carlo methods. A number of technical obstacles contribute to this challenge. We discuss how these obstacles can be removed with the auxiliary-field quantum Monte Carlo (AFQMC) approach. AFQMC is a general, high-accuracy, many-body total-energy method for molecules and solids. The implementation of back-propagation for pure estimators allows direct calculation of gradients of the energy via the Hellmann-Feynman theorem. A planewave basis with norm-conserving pseudopotentials is used for the study of periodic bulk materials. Completeness of the planewave basis minimizes the effect of so-called Pulay terms. The ionic pseudopotentials, which can be incorporated in AFQMC in exactly the same manner as in standard independent-electron methods, regulate the force and stress estimators and eliminate any potential divergence of the Monte Carlo variances. The resulting approach allows applications of full geometry optimizations in bulk materials. As a result, it also paves the way for many-body computations of the phonon spectrum in solids.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗
DOE OSTI2024

Scaling whole-chip QAOA for higher-order ising spin glass models on heavy-hex graphs

Abstract We show that the quantum approximate optimization algorithm (QAOA) for higher-order, random coefficient, heavy-hex compatible spin glass Ising models has strong parameter concentration across problem sizes from 16 up to 127 qubits for p = 1 up to p = 5, which allows for computationally efficient parameter transfer of QAOA angles. Matrix product state (MPS) simulation is used to compute noise-free QAOA performance. Hardware-compatible short-depth QAOA circuits are executed on ensembles of 100 higher-order Ising models on noisy IBM quantum superconducting processors with 16, 27, and 127 qubits using QAOA angles learned from a single 16-qubit instance using the JuliQAOA tool. We show that the best quantum processors find lower energy solutions up to p = 2 or p = 3, and find mean energies that are about a factor of two off from the noise-free distribution. We show that p = 1 QAOA energy landscapes remain very similar as the problem size increases using NISQ hardware gridsearches with up to a 414 qubit processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

We present a benchmarking study of active learning (AL) schemes for designing planar multilayer nanophotonic metamaterials, where the design tasks are formulated as binary optimization problems. Different surrogate models, including factorization machine (FM), Gaussian process regression (GPR), and convolutional neural network (CNN), combined with different optimization methods, including exhaustive enumeration, discrete particle swarm optimization (DPSO), quantum annealing (QA), hybrid QA, and simulated annealing are studied. The benchmark cases investigated range from small problems with short binary lengths (N = 25) to large problems with N up to 100, focusing on the design of two classes of photonic structures, including antireflective coatings for the long-wavelength infrared region and transparent radiative coolers. For small problems, CNN coupled with DPSO in AL achieves the best performance. As N increases, FM with QA outperforms GPR and CNN. For FM-based AL, hybrid QA yields the best optimization results, particularly in high-dimensional cases (N = 100). These results demonstrate that the optimization method can significantly affect in AL performance as N increases, and that QA-based optimization can provide practical routes for mitigating the optimization bottleneck in high-dimensional problems.

Jung, Serang [Kyung Hee University, Korea]↗
DOE OSTI2026

Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations

We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut problem. Our main focus is on compilation with trapped-ion simulators using Pauli-X operations and all-to-all Ising Hamiltonian HIsing evolution generated by Molmer-Sorensen or optical dipole force interactions, though some of our results also apply to standard gate-based compilations. Our results are based on principles of graph sparsification and decomposition; the former reduces the number of edges in a graph while maintaining its cut structure, while the latter breaks a weighted graph into a small number of unweighted graphs. Though these techniques have been used as heuristics in various hybrid quantum algorithms, there have been no guarantees on their performance, to the best of our knowledge. This work provides the first provable guarantees using sparsification and decomposition to improve quantum noise resilience and reduce quantum circuit complexity. For quantum hardware that uses edge-by-edge QAOA compilations, sparsification leads to a direct reduction in circuit complexity. For trapped-ion quantum simulators implementing all-to-all HIsing pulses, we show that for a (1−ϵ) factor loss in the Max-Cut approximation (ϵ>0), our compilations improve the (worst-case) number of HIsing pulses from O(n2) to O(nlog(n/ϵ)) and the (worst-case) number of Pauli-X bit flips from O(n2) to O(nlog(n/ϵ)ϵ2) for n-node graphs. This is an asymptotic improvement for any constant ϵ>0. We demonstrate that significant improvements to the approximation ratio are obtained using decomposition in simulated trapped-ion experiments with dephasing noise. We further present a generic argument showing that sparsification results in an exponentially improved circuit fidelity lower bound in digital computing schemes based on one- and two-qubit gates, which are relevant to a wide variety of hardwares such as superconducting qubits and certain neutral atom or trapped ion setups, and more sophisticated noise models. We anticipate these approximate compilation techniques will be useful tools in a variety of future quantum computing experiments.

Moondra, Jai [Georgia Institute of Technology]↗
DOE OSTI2016

High-temperature operation of broadband bidirectional terahertz quantum-cascade lasers

Terahertz quantum cascade lasers (QCLs) with a broadband gain medium could play an important role for sensing and spectroscopy since then distributed-feedback schemes could be utilized to produce laser arrays on a single semiconductor chip with wide spectral coverage. QCLs can be designed to emit at two different frequencies when biased with opposing electrical polarities. Here, we develop terahertz QCLs with bidirectional operation to achieve broadband lasing from the same semiconductor chip. A three-well design scheme with shallow-well GaAs/Al 0.10 Ga 0.90 As superlattices is developed to achieve high-temperature operation for bidirectional QCLs. It is shown that shallow-well heterostructures lead to optimal quantum-transport in the superlattice for bidirectional operation compared to the prevalent GaAs/Al 0.15 Ga 0.85 As material system. Furthermore, broadband lasing in the frequency range of 3.1–3.7 THz is demonstrated for one QCL design, which achieves maximum operating temperatures of 147 K and 128 K respectively in opposing polarities. Dual-color lasing with large frequency separation is demonstrated for a second QCL, that emits at ~3.7 THz and operates up to 121 K in one polarity, and at ~2.7 THz up to 105 K in the opposing polarity. Finally, these are the highest operating temperatures achieved for broadband terahertz QCLs at the respective emission frequencies, and could lead to commercial development of broadband terahertz laser arrays.

42 ENGINEERING↗
DOE OSTI2015

Charge transport through exciton shelves in cadmium chalcogenide quantum dot-DNA nano-bioelectronic thin films

Quantum dot (QD), or semiconductor nanocrystal, thin films are being explored for making solution-processable devices due to their size- and shape-tunable bandgap and discrete higher energy electronic states. While DNA has been extensively used for the self-assembly of nanocrystals, it has not been investigated for the simultaneous conduction of multiple energy charges or excitons via exciton shelves (ES) formed in QD-DNA nano-bioelectronic thin films. Here, we present studies on charge conduction through exciton shelves, which are formed via chemically coupled QDs and DNA, between electronic states of the QDs and the HOMO-LUMO levels in the complementary DNA nucleobases. While several challenges need to be addressed in optimizing the formation of devices using QD-DNA thin films, a higher charge collection efficiency for hot-carriers and our detailed investigations of charge transport mechanism in these thin films highlight their potential for applications in nano-bioelectronic devices and biological transducers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Harnessing Quantum Computing for Energy Materials: Opportunities and Challenges

Developing high-performance materials is critical for diverse energy applications to increase efficiency, improve sustainability and reduce costs. Classical computational methods have enabled important breakthroughs in energy materials development, but they face scaling and time-complexity limitations, particularly for high-dimensional or strongly correlated material systems. Quantum computing (QC) promises to offer a paradigm shift by exploiting quantum bits with their superposition and entanglement to address challenging problems intractable for classical approaches. This Perspective discusses the opportunities in leveraging QC to advance energy materials research and the challenges QC faces in solving complex and high-dimensional problems. We present cases on how QC, when combined with classical computing methods, can be used for the design and simulation of practical energy materials. We also outline the outlook for error-corrected, fault-tolerant QC capable of achieving predictive accuracy and quantum advantage for complex material systems.

Algorithms↗
DOE OSTI2015

Single-photon emission at a rate of 143 MHz from a deterministic quantum-dot microlens triggered by a mode-locked vertical-external-cavity surface-emitting laser

We report on the realization of a quantum dot (QD) based single-photon source with a record-high single-photon emission rate. The quantum light source consists of an InGaAs QD which is deterministically integrated within a monolithic microlens with a distributed Bragg reflector as back-side mirror, which is triggered using the frequency-doubled emission of a mode-locked vertical-external-cavity surface-emitting laser (ML-VECSEL). The utilized compact and stable laser system allows us to excite the single-QD microlens at a wavelength of 508 nm with a pulse repetition rate close to 500 MHz at a pulse width of 4.2 ps. Probing the photon statistics of the emission from a single QD state at saturation, we demonstrate single-photon emission of the QD-microlens chip with g{sup (2)}(0) < 0.03 at a record-high single-photon flux of (143 ± 16) MHz collected by the first lens of the detection system. Our approach is fully compatible with resonant excitation schemes using wavelength tunable ML-VECSELs, which will optimize the quantum optical properties of the single-photon emission in terms of photon indistinguishability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Optimal discrimination of M coherent states with a small quantum computer

The ability to distinguish between coherent states optimally plays in important role in the efficient usage of quantum resources for classical communication and sensing applications. While it has been known since the early 1970’s how to optimally distinguish between two coherent states, generalizations to larger sets of coherent states have so far failed to reach optimality. In this work we outline how optimality can be achieved by using a small quantum computer, building on recent proposals for optimal qubit state discrimination with multiple copies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Computing molecular excited states on a D-Wave quantum annealer

Abstract The possibility of using quantum computers for electronic structure calculations has opened up a promising avenue for computational chemistry. Towards this direction, numerous algorithmic advances have been made in the last five years. The potential of quantum annealers, which are the prototypes of adiabatic quantum computers, is yet to be fully explored. In this work, we demonstrate the use of a D-Wave quantum annealer for the calculation of excited electronic states of molecular systems. These simulations play an important role in a number of areas, such as photovoltaics, semiconductor technology and nanoscience. The excited states are treated using two methods, time-dependent Hartree–Fock (TDHF) and time-dependent density-functional theory (TDDFT), both within a commonly used Tamm–Dancoff approximation (TDA). The resulting TDA eigenvalue equations are solved on a D-Wave quantum annealer using the Quantum Annealer Eigensolver (QAE), developed previously. The method is shown to reproduce a typical basis set convergence on the example $$\hbox {H}_2$$ H 2 molecule and is also applied to several other molecular species. Characteristic properties such as transition dipole moments and oscillator strengths are computed as well. Three potential energy profiles for excited states are computed for $$\hbox {NH}_3$$ NH 3 as a function of the molecular geometry. Similar to previous studies, the accuracy of the method is dependent on the accuracy of the intermediate meta-heuristic software called qbsolv.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Accelerating Noisy VQE Optimization with Gaussian Processes

Hybrid variational quantum algorithms, which combine a classical optimizer with evaluations on a quantum chip, are the most promising candidates to show quantum advantage on current noisy, intermediate-scale quantum (NISQ) devices. The classical optimizer is required to perform well in the presence of noise in the objective function evaluations, or else it becomes the weakest link in the algorithm. We introduce the use of Gaussian Processes (GP) as surrogate models to reduce the impact of noise and to provide high quality seeds to escape local minima, whether real or noise-induced. We build this as a framework on top of local optimizations, for which we choose Implicit Filtering (ImFil) in this study. ImFil is a state-of-the-art, gradient-free method, which in comparative studies has been shown to outperform on noisy VQE problems. The result is a new method: "GP+ImFil". We show that when noise is present, the GP+ImFil approach finds results closer to the true global minimum in fewer evaluations than standalone ImFil, and that it works particularly well for larger dimensional problems. Using GP to seed local searches in a multi-modal landscape shows mixed results: although it is capable of improving on ImFil standalone, it does not do so consistently and would only be preferred over other, more exhaustive, multistart methods if resources are constrained.

Muller, Juliane↗
DOE OSTI2020

Tuning the Quantum Dot (QD)/Mediator Interface for Optimal Efficiency of QD-Sensitized Near-Infrared-to-Visible Photon Upconversion Systems

Lead sulfide (PbS) quantum dots (QDs) have shown promising performance as a sensitizer in infrared-to-visible photon upconversion systems. To investigate the key design rules, we compare three PbS-sensitized upconversion systems using three mediator molecules with the same tetracene triplet acceptor at different distances from the QD. Using transient absorption spectroscopy, we directly measure the triplet energy-transfer rates and efficiencies from the QD to the mediator and from the mediator to the emitter. With increasing distance between the mediator and PbS QD, the efficiency of the first triplet energy transfer from the QD to the mediator decreases because of a decrease in the rate of this triplet energy-transfer step, while the efficiency of the second triplet energy transfer from the mediator to the emitter increases because of a reduction in the QD-induced mediator triplet state decay. The latter effect is a result of the slow rate constant of the second triplet energy-transfer process, which is 3 orders of magnitude slower than the diffusion-limited value. The combined results lead to a net decrease of the steady-state upconversion quantum yield with distance, which could be predicted by our kinetic model. Our result shows that the QD/mediator interface affects both the first and second triplet energy transfer processes in the photon upconversion system, and the QD/mediator distance has an opposite effect on the efficiencies of the first and second triplet energy transfer. Lastly, these findings provide important insight for the further rational improvement of the overall efficiency of QD-based upconversion systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Solving MaxCut with quantum imaginary time evolution

We introduce a method to solve the MaxCut problem efficiently based on quantum imaginary time evolution (QITE). We employ a linear Ansatz for unitary updates and an initial state involving no entanglement, as well as an imaginary-time-dependent Hamiltonian interpolating between a given graph and a subgraph with two edges excised. We apply the method to thousands of randomly selected graphs with up to fifty vertices. We show that our algorithm exhibits a 93% and above performance converging to the maximum solution of the MaxCut problem for all considered graphs. Our results compare favorably with the performance of classical algorithms, such as the greedy and Goemans–Williamson algorithms. We also discuss the overlap of the final state of the QITE algorithm with the ground state as a performance metric, which is a quantum feature not shared by other classical algorithms.

97 MATHEMATICS AND COMPUTING↗