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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quantum Divide and Compute: Exploring the Effect of Different Noise Sources

Abstract Our recent work (Ayral et al. in Proceedings of IEEE computer society annual symposium on VLSI, ISVLSI, pp 138–140, 2020. 10.1109/ISVLSI49217.2020.00034 ) showed the first implementation of the Quantum Divide and Compute (QDC) method, which allows to break quantum circuits into smaller fragments with fewer qubits and shallower depth. This accommodates the limited number of qubits and short coherence times of quantum processors. This article investigates the impact of different noise sources—readout error, gate error and decoherence—on the success probability of the QDC procedure. We perform detailed noise modeling on the Atos Quantum Learning Machine, allowing us to understand tradeoffs and formulate recommendations about which hardware noise sources should be preferentially optimized. We also describe in detail the noise models we used to reproduce experimental runs on IBM’s Johannesburg processor. This article also includes a detailed derivation of the equations used in the QDC procedure to compute the output distribution of the original quantum circuit from the output distribution of its fragments. Finally, we analyze the computational complexity of the QDC method for the circuit under study via tensor-network considerations, and elaborate on the relation the QDC method with tensor-network simulation methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Quantum 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 directed minimum spanning tree, each of which uses O ̃(n1/4) rounds of communication and O ̃(n9/4) messages, achieving a lower asymptotic round and message complexity than any known algorithms in the classical CONGEST-CLIQUE model. At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Additionally, we characterize the constants and logarithmic factors involved in our algorithms, as well as related classical algorithms, revealing that advances are needed to render both practical.

quantum computing↗
DOE OSTI2024

Direct pulse-level compilation of arbitrary quantum logic gates on superconducting qutrits

Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long gate sequence, which is typically a leading factor in the total accumulated error. Compiling a complex unitary for processors with higher-dimensional logical elements, such as qutrits, exacerbates the accumulated error per unitary, since an even longer gate sequence is required. Optimal control methods promise time- and resource-efficient compact gate sequences and, therefore, higher fidelity. These methods generate pulses that can directly implement any complex unitary on a quantum device. In this work, we demonstrate that any arbitrary qubit and qutrit gate can be realized with high fidelity, which can significantly reduce the length of a gate sequence. We generate and test pulses for a large set of randomly selected arbitrary unitaries on several quantum processing units (QPUs): the Lawrence Livermore National Laboratory Quantum Device and Integration Testbed’s (QuDIT’s) standard QPU and three of Rigetti’s QPUs: Ankaa-2, Ankaa-9Q-1, and Aspen-M-3. On the QuDIT platform’s standard QPU, the average fidelity of random qutrit gates is 97.9 ± 0.5% measured with conventional QPT and 98.8 ± 0.6% from QPT with gate folding. Rigetti’s Ankaa-2 achieves random qubit gates with an average fidelity of 98.4 ± 0.5% (conventional QPT) and 99.7 ± 0.1% (QPT with gate folding). On Ankaa-9Q-1 and Aspen-M-3, the average fidelities with conventional qubit QPT measurements were higher than 99% (see Appendix). Here we show that optimal control gates are robust to drift for at least 3 h and that the same calibration parameters can be used for all implemented gates. Our work promises that the calibration overheads for optimal control gates can be made small enough to enable efficient quantum circuits based on this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Backflow Transformations via Neural Networks for Quantum Many-Body Wave Functions

Obtaining an accurate ground state wave function is one of the great challenges in the quantum many-body problem. In this Letter, we propose a new class of wave functions, neural network backflow (NNB). Here, the backflow approach, pioneered originally by Feynman and Cohen [Phys. Rev. 102, 1189 (1956)], adds correlation to a mean-field ground state by transforming the single-particle orbitals in a configuration-dependent way. NNB uses a feed-forward neural network to learn the optimal transformation via variational Monte Carlo calculations. NNB directly dresses a mean-field state, can be systematically improved, and directly alters the sign structure of the wave function. It generalizes the standard backflow [L. F. Tocchio et al., Phys. Rev. B 78, 041101(R) (2008)], which we show how to explicitly represent as a NNB. We benchmark the NNB on Hubbard models at intermediate doping, finding that it significantly decreases the relative error, restores the symmetry of both observables and single-particle orbitals, and decreases the double-occupancy density. Finally, we illustrate interesting patterns in the weights and bias of the optimized neural network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Quantum 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 directed minimum spanning tree, each of which uses O ̃(n 1/4 ) rounds of communication and O ̃(n 9/4 ) messages, achieving a lower asymptotic round and message complexity than any known algorithms in the classical CONGEST-CLIQUE model. At a high level, we achieve these results by combining classical algorithms with fast quantum subroutines. Additionally, we characterize the constants and logarithmic factors involved in our algorithms, as well as related classical algorithms, revealing that advances are needed to render both practical.

quantum computing↗
DOE OSTI2022

CeTaN 3 and CeNbN 3 : Prospective Nitride Perovskites with Optimal Photovoltaic Band Gaps

Perovskites constitute an exceptionally tunable materials family with diverse applications in electronics, optoelectronics, energy, and quantum technologies. Out of the thousands of known perovskites, the majority of compounds are oxides, halides, and chalcogenides. In contrast, only two nitride perovskites are currently known. In this work we perform a thorough ab initio computational screening of possible nitride perovskites, and we identify two new compounds, CeNbN 3 and CeTaN 3 , with band gaps in the near-infrared to visible range, depending on temperature. In their room-temperature orthorhombic phase, we predict that both compounds exhibit direct or quasidirect band gaps in the range 1.1–2.0 eV, with the Pnma phases matching the Shockley–Queisser limit for photovoltaic energy conversion efficiency. Further, these compounds are also predicted to be strong light absorbers, with absorption coefficients surpassing those of high-performance semiconductors such as GaAs and CH 3 NH 3 PbI 3 . The present findings reveal a potentially new class of nitride semiconductors with promise for electronics, optoelectronics, and light harvesting and for integration with existing nitride-based lighting technology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanoscale solid-state nuclear quadrupole resonance spectroscopy using depth-optimized nitrogen-vacancy ensembles in diamond

Nuclear magnetic resonance (NMR) and nuclear quadrupole resonance (NQR) spectroscopy of bulk quantum materials have provided insight into phenomena, such as quantum phase criticality, magnetism, and superconductivity. With the emergence of nanoscale 2D materials with magnetic phenomena, inductively detected NMR and NQR spectroscopy are not sensitive enough to detect the smaller number of spins in nanomaterials. The nitrogen-vacancy (NV) center in diamond has shown promise in bringing the analytic power of NMR and NQR spectroscopy to the nanoscale. However, due to depth-dependent formation efficiency of the defect centers, noise from surface spins, band bending effects, and the depth dependence of the nuclear magnetic field, there is ambiguity regarding the ideal NV depth for surface NMR of statistically polarized spins. In this work, we prepared a range of shallow NV ensemble layer depths and determined the ideal NV depth by performing NMR spectroscopy on statistically polarized 19 F in Fomblin oil on the diamond surface. We found that the measurement time needed to achieve a signal-to-noise ratio of 3 using XY8-N noise spectroscopy has a minimum at an NV ensemble depth of 5.5 ± 1.5 nm for ensembles activated from 100 ppm nitrogen concentration. To demonstrate the sensing capabilities of NV ensembles, we perform NQR spectroscopy on the 11 B of hexagonal boron nitride flakes. We compare our best diamond to previous work with a single NV and find that this ensemble provides a shorter measurement time with excitation diameters as small as 4 μm. Furthermore, this analysis provides ideal conditions for further experiments involving NMR/NQR spectroscopy of 2D materials with magnetic properties.

2D materials↗
DOE OSTI2023

Optimal coupling of Ho W 10 molecular magnets to superconducting circuits near spin clock transitions

A central goal in quantum technologies is to maximize GT 2 , where G stands for the coupling of a qubit to control and readout signals and T 2 is the qubit’s coherence time. Furthermore, this is challenging, as increasing G (e.g., by coupling the qubit more strongly to external stimuli) often leads to deleterious effects on T 2 . Here, we study the coupling of pure and magnetically diluted crystals of Ho W 10 magnetic clusters to microwave superconducting coplanar waveguides. Absorption lines give a broadband picture of the magnetic energy level scheme and, in particular, confirm the existence of level anticrossings at equidistant magnetic fields determined by the combination of crystal field and hyperfine interactions. Such “spin clock transitions” are known to shield the electronic spins against magnetic field fluctuations. The analysis of the microwave transmission shows that the spin-photon coupling also becomes maximum at these transitions. The results show that engineering spin-clock states of molecular systems offers a promising strategy to combine sizable spin-photon interactions with a sufficient isolation from unwanted magnetic noise sources.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2022

Control Implemented on Quantum Computers: Effects of Noise, Non-Determinism, and Entanglement

Quantum computing has advanced in recent years to the point that there are now some quantum computers and quantum simulators available to the public for use. In addition, quantum computing is beginning to receive attention within the process systems engineering community for directions such as machine learning and optimization. A logical next step for its evaluation within process systems engineering is for control, specifically, for computing control actions to be applied to process systems. In this work, we provide some initial studies regarding the implementation of control on quantum computers, including the implementation of a single-input/single-output proportional control law on a quantum simulator with noise, evaluation of potential impacts of non-determinism on theory for advanced control laws, and discussion of consequences of the way that entanglement works for next-generation manufacturing communication objectives.

Kip Nieman↗
DOE OSTI2018

In Silico Optimization of Organic–Inorganic Hybrid Perovskites for Photocatalytic Hydrogen Evolution Reaction in Acidic Solution

We previously reported the atomistic reaction mechanism for the photocatalytic hydrogen evolution reaction (HER) on the CH 3 NH 3 PbI 3 organic-inorganic hybrid perovskites based on quantum mechanics (QM) calculations of the transition state barriers, including several layers of explicit acidic solvent. Here we extend these studies using in silico optimization to discover additional promising photocatalysts. We consider replacing • Pb with Sn, • I with Br, and • CH3NH3 cation with several organic cations, including NH 2 (CH)NH 2 cation as the photocatalyst for HER. We compared the activation barriers and reaction energies for each case. In our previous studies, we found that both H atoms of the H 2 product are extracted from surface organic cations with protons from the solution migrating along Grotthuss water chains to replace the H of the organic cations. This two-step reaction mechanism involves formation of an intermediate lead hydride bond, with the lead atoms and the surface organic cations both playing essential roles. Among the perovskites investigated here, we predict that NH 2 (CH)NH 2 PbI 3 exhibits the best HER performance with a predicted 10-fold improvement in the reaction rate compared to CH 3 NH 3 PbI 3 . We also suggest that the lead-free tin-iodide perovskites might exhibit a rate comparable to that of lead-iodide perovskites with the same organic cations. However, replacing iodine by bromine significantly increases the activation barrier. We find for these lead-iodide perovskites, the increased proton affinity of the surface organic cations enhances the photocatalytic efficiency, with NH 2 (CH)NH 2 the best case examined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unraveling Electronic and Vibrational Coherences Following a Charge Transfer Process in a Photosystem II Reaction Center

A reaction center is a unique biological system that performs the initial charge separation within a Photosystem II (PSII) multiunit enzyme, which eventually drives the catalytic water-splitting in plants and algae. The possible role of quantum coherences coinciding with the energy and charge transfer processes in PSII reaction center is one of the active areas of research. Here, we study these quantum coherences by using a numerically exact method on an excitonic dimer model, including linear vibronic coupling and employing optimal parameters from experimental two-dimensional coherent spectroscopic measurements. This enables us to precisely capture the excitonic interaction between pigments and the dissipation of the energy from electronic and charge-transfer (CT) states to the protein environment. We employ the time nonlocal (TNL) quantum master equation to calculate the population dynamics, which yields numerically reliable results. The calculated results show that, due to the strong dissipation, the lifetime of electronic coherence is too short to have direct participation in the charge transfer processes. However, there are long-lived vibrational coherences present in the system at frequencies close to the excitionic energy gap. These are strongly coupled with the electronic coherences, which makes the detection of the electronic coherences with conventional techniques very challenging. Additionally, we unravel the strong excitonic interaction of radical pair (PD1 and PD2) in the reaction center, which results in a long-lived electronic coherence of >100 fs, even at room temperature. Our work provide important physical insight to the charge separation process in PSII reaction center, which may be helpful for better understanding of photophysical processes in other natural and artificial light-harvesting systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, and so on, trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, comprising 25K circuit evaluations. In addition we also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Necessary Conditions of Optimality for Some Stochastic Integrodifferential Equations of Neutral Type on Hilbert Spaces

In this work, we develop the necessary conditions of optimality for partially observed control problems governed by stochastic integrodifferential equations of neutral type on Hilbert spaces driven by relaxed controls. Under suitable conditions, we establish the existence and the uniqueness of mild solution which has a continuous modification. We prove the continuity of the control to the solution map. Then we consider an optimal control problem of Bolza type. Using these results we give necessary conditions of optimality for a class of stochastic integrodifferential equations of neutral type on Hilbert spaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

Characteristics of AlGaAs/GaAs multiple quantum well infrared detectors

Researchers fabricated and characterized several AlGaAs/GaAs multiple quantum well infrared detectors to evaluate the ultimate performance of these devices for low infrared background applications. The detectors were designed to have a single bound state in the quantum well and the first excited state in the continuum above the AlGaAs conduction band edge. The difference in energy between the two levels, as determined by the quantum well width and aluminum mole fraction in the barrier, was chosen such that peak absorption would occur near 8 microns. The initial structures studied comprised 50 periods with 40 A well widths and 300 A Al(0.28)Ga(0.72)As barriers. The performance of these detectors are summarized. To better interpret these results and design optimized detectors, researchers modeled both the detector noise and tunneling currents. The noise model correctly predicts that multiple quantum well detectors will, indeed, exhibit noise lower than full shot noise. The tunneling current model predicts the dark current versus bias for any choice of design parameters in a multiple quantum well detector. This model predicts a substantially reduced dark current (x 10(exp 04)) for samples with 400 A barriers. To evaluate structures with thicker barriers, researchers fabricated and characterized detectors with 400 A and 500 A barriers; a comparison of detector dark currents is shown. These results are consistent with the predictions of the dark current model.

Janousek, Bruce K.↗
DOE OSTI2022

QuantumNAT: quantum noise-aware training with noise injection, quantization and normalization

Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-term quantum hardware. However, due to the large quantum noises (errors), the performance of PQC models has a severe degradation on real quantum devices. Take Quantum Neural Network (QNN) as an example, the accuracy gap between noise-free simulation and noisy results on IBMQ-Yorktown for MNIST-4 classification is over 60%. Existing noise mitigation methods are general ones without leveraging unique characteristics of PQC; on the other hand, existing PQC work does not consider noise effect. To this end, we present QuantumNAT, a PQC-specific framework to perform noise-aware optimizations in both training and inference stages to improve robustness. We experimentally observe that the effect of quantum noise to PQC measurement outcome is a linear map from noise-free outcome with a scaling and a shift factor. Motivated by that, we propose post-measurement normalization to mitigate the feature distribution differences between noise-free and noisy scenarios. Furthermore, to improve the robustness against noise, we propose noise injection to the training process by inserting quantum error gates to PQC according to realistic noise models of quantum hardware. Lastly, post-measurement quantization is introduced to quantize the measurement outcomes to discrete values, achieving the denoising effect. Extensive experiments on 8 classification tasks using 6 quantum devices demonstrate that QuantumNAT improves accuracy by up to 43%, and achieves over 94% 2-class, 80% 4-class, and 34% 10-class classification accuracy measured on real quantum computers. The code for construction and noise-aware training of PQC is available in the TorchQuantum library.

Wang, Hanrui↗
DOE OSTI2023

The Quantum Alternating Operator Ansatz for Satisfiability Problems

Here, we comparatively study, through large-scale numerical simulation, the performance across a large set of Quantum Alternating Operator Ansatz (QAOA) implementations for finding approximate and optimum solutions to unconstrained combinatorial optimization problems. Our survey includes over 100 different mixing unitaries, and we combine each mixer with both the standard phase separator unitary representing the objective function and a thresholded version. Our numerical tests for randomly chosen instances of the unconstrained optimization problems Max 2-SAT and Max 3-SAT reveal that the traditional transverse-field mixer with the standard phase separator performs best for problem sizes of 8 through 14 variables, while the recently introduced Grover mixer with thresholding wins at problems of size 6. This result (i) corrects earlier work suggesting that the Grover mixer is a superior mixer based only on results from problems of size 6, thus illustrating the need to push numerical simulation to larger problem sizes to more accurately predict performance; and (ii) it suggests that more complicated mixers and phase separators may not improve QAOA performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Optimizing Tensor Contractions in CCSD(T) for Efficient Execution on GPUs

Tensor contractions are higher dimensional analogs of matrix multiplications, used in many computational contexts such as high order models in quantum chemistry, deep learning, nite element methods etc. In contrast to the wide availability of high-performance libraries for matrix multiplication on GPUs, the same is not true for tensor contractions. In this paper, we address the optimization of a set of symmetrized tensor contractions that form the computational bottleneck in the CCSD(T) coupled-cluster method in computational chemistry suites like NWChem. Some of the challenges in optimizing tensor contractions that arise in practice from the variety of dimensionalities and shapes for tensors include effective mapping of the high-dimensional iteration space to threads, choice of data buffering in shared-memory and registers, and tile sizes for multi-level tiling. Furthermore, in the case of symmetrized tensor contractions in CCSD(T), it is also a challenge to fuse contractions to reduce data movement cost by exploiting reuse of intermediate tensors. In this paper, we developed an efficient GPU implementation of the tensor contractions in CCSD(T) using shared-memory buffering, register tiling, loop fusion and register transpose. Experimental results demonstrate significant improvement over the current state-of-the-art.

Kim, Jinsung↗
DOE OSTI2019

Measurements of differential Z boson production cross sections in proton-proton collisions at $\sqrt{s}$ = 13 TeV

Measurements are presented of the differential cross sections for Z bosons produced in proton-proton collisions at $\sqrt{s} =$ 13 TeV and decaying to muons and electrons. The data analyzed were collected in 2016 with the CMS detector at the LHC and correspond to an integrated luminosity of 35.9 fb$^{-1}$. The measured fiducial inclusive product of cross section and branching fraction agrees with next-to-next-to-leading order quantum chromodynamics calculations. Differential cross sections of the transverse momentum $p_\mathrm{T}$, the optimized angular variable $\phi^*_\eta$, and the rapidity of lepton pairs are measured. The data are corrected for detector effects and compared to theoretical predictions using fixed order, resummed, and parton shower calculations. The uncertainties of the measured normalized cross sections are smaller than 0.5% for $\phi^*_\eta <$ 0.5 and for $p_\mathrm{T}^\mathrm{Z} <$ 50 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗