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Results for “distributed quantum computing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Temperature dependence of nuclear quantum effects on liquid water via artificial neural network model based on SCAN meta-GGA functional

We investigate the temperature dependence of nuclear quantum effects (NQEs) on structural and dynamic properties of liquid water by training a neural network force field using first-principles molecular dynamics (FPMD) based on the strongly constrained and appropriately normed meta-generalized gradient approximation exchange-correlation approximation. The FPMD simulation based on density functional theory has become a powerful computational approach for studying a wide range of condensed phase systems. However, its large computational cost makes it difficult to incorporate NQEs in the simulation and investigate temperature dependence of various properties. To circumvent this difficulty, we use an artificial neural network model and employ the thermostatted ring polymer MD approach for studying the temperature dependence of NQEs on various properties. The NQEs generally bring the radial distribution functions closer to the experimental measurements. Translational diffusivity and rotational dynamics of water molecules are both slowed down by the NQEs. The competing inter-molecular and intra-molecular quantum effects on hydrogen bonds, as discussed by Habershon, Markland, and Manolopoulos [J. Chem. Phys. 131(2), 024501 (2019)], can explain the observed temperature dependence of the NQEs on the dynamical properties in our simulation.

Yao, Yi (ORCID:0000000299576979)↗
DOE OSTI2025

Characterization and thermometry of dissipatively stabilized steady states

In this work we study the properties of dissipatively stabilized steady states of noisy quantum algorithms, exploring the extent to which they can be well approximated as thermal distributions, and proposing methods to extract the effective temperature T. We study an algorithm called the relaxational quantum eigensolver (RQE), which is one of a family of algorithms that attempt to find ground states and balance error in noisy quantum devices. In RQE, we weakly couple a second register of auxiliary ‘shadow’ qubits to the primary system in Trotterized evolution, thus engineering an approximate zero-temperature bath by periodically resetting the auxiliary qubits during the algorithm’s runtime. Balancing the infinite temperature bath of random gate error, RQE returns states with an average energy equal to a constant fraction of the ground state. We probe the steady states of this algorithm for a range of base error rates, using several methods for estimating both T and deviations from thermal behavior. In particular, we both confirm that the steady states of these systems are often well-approximated by thermal distributions, and show that the same resources used for cooling can be adopted for thermometry, yielding a fairly reliable measure of the temperature. These methods could be readily implemented in near-term quantum hardware, and for stabilizing and probing Hamiltonians where simulating approximate thermal states is hard for classical computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Monte Carlo modeling of electron density in hypersonic rarefied gas flows

The electron density distribution around a vehicle employed in the RAM-C II flight test is calculated with the DSMC method. To resolve the mole fraction of electrons which is several orders lower than those of the primary species in the free stream, an algorithm named as trace species separation (TSS) is utilized. The TSS algorithm solves the primary and trace species separately, which is similar to the DSMC overlay techniques; however it generates new simulated molecules of trace species, such as ions and electrons in each cell, basing on the ionization and recombination rates directly, which differs from the DSMC overlay techniques based on probabilistic models. The electron density distributions computed by TSS agree well with the flight data measured in the RAM-C II test along a decent trajectory at three altitudes 81km, 76km, and 71km.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Bottomonium suppression in 5.02 and 8.16 TeV 𝑝-Pb collisions

Here, we compute the suppression of ϒ⁡(1⁢𝑆), ϒ⁡(2⁢𝑆), and ϒ⁡(3⁢𝑆) states in 𝑝-Pb collisions relative to 𝑝⁢𝑝 collisions, including nuclear parton distribution function (nPDF) effects, coherent energy loss, momentum broadening, and final-state interactions in the quark-gluon plasma. We employ the EPPS21 nPDFs and calculate the uncertainty resulting from variation over the associated error sets. To compute coherent energy loss and momentum broadening, we follow the approach of Arleo, Peigne, and collaborators. The 3+1⁢D viscous hydrodynamical background evolution of the quark-gluon plasma is generated by anisotropic hydrodynamics. The in-medium suppression of bottomonium in the quark-gluon plasma is computed using a next-to-leading-order open quantum system framework formulated within potential nonrelativistic quantum chromodynamics. We find that inclusion of all these effects provides a reasonable description of experimental data from the ALICE, ATLAS, CMS, and LHCb Collaborations for the suppression of ϒ⁡(1⁢𝑆), ϒ⁡(2⁢𝑆), and ϒ⁡(3⁢𝑆) as a function of both transverse momentum and rapidity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

FELIX-2.0: New version of the finite element solver for the time dependent generator coordinate method with the Gaussian overlap approximation

The time-dependent generator coordinate method (TDGCM) is a powerful method to study the largeamplitude collective motion of quantum many-body systems such as atomic nuclei. Under the GaussianOverlap Approximation (GOA), the TDGCM leads to a local, time-dependent Schrödinger equation in amulti-dimensional collective space. In this paper, we present the version 2.0 of the code FELIX that solvesthe collective Schrödinger equation in a finite element basis. This new version features: (i) the ability tosolve a generalized TDGCM+GOA equation with a metric term in the collective Hamiltonian, (ii) supportfor new kinds of finite elements and different types of quadrature to compute the discretized Hamiltonianand overlap matrices, (iii) the possibility to leverage the spectral element scheme, (iv) an explicit Krylovapproximation of the time propagator for time integration instead of the implicit Crank–Nicolson methodimplemented in the first version, (v) an entirely redesigned workflow. We benchmark this release on ananalytic problem as well as on realistic two-dimensional calculations of the low-energy fission of240Puand256Fm. Low to moderate numerical precision calculations are most efficiently performed with simplexelements with a degree 2 polynomial basis. Higher precision calculations should instead use the spectralelement method with a degree 4 polynomial basis. We emphasize that in a realistic calculation of fissionmass distributions of240Pu, FELIX-2.0 is about 20 times faster than its previous release (within a numericalprecision of a few percents).

Regnier, D.↗
DOE OSTI2021

Theoretical Insights for Improving the Schottky-Barrier Height at the Ga2O3/Pt Interface

In this work, we study the Schottky-barrier height (SBH) at the junction between ..beta..-Ga2O3 and platinum, a system of great importance for the next generation of high-power and high-temperature electronic devices. Specifically, we obtain interfacial atomic structures at different orientations using our structure-matching algorithm and compute their SBH using electronic structure calculations based on hybrid density-functional theory.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,P↗
DOE OSTI2015

Peculiarities of high-overtone transition probabilities in carbon monoxide revealed by high-precision calculation

In the recent work devoted to the calculation of the rovibrational line list of the CO molecule [G. Li et al., Astrophys. J., Suppl. Ser. 216, 15 (2015)], rigorous validation of the calculated parameters including intensities was carried out. In particular, the Normal Intensity Distribution Law (NIDL) [E. S. Medvedev, J. Chem. Phys. 137, 174307 (2012)] was employed for the validation purposes, and it was found that, in the original CO line list calculated for large changes of the vibrational quantum number up to Δn = 41, intensities with Δn > 11 were unphysical. Therefore, very high overtone transitions were removed from the published list in Li et al. Here, we show how this type of validation is carried out and prove that the quadruple precision is indispensably required to predict the reliable intensities using the conventional 32-bit computers. Based on these calculations, the NIDL is shown to hold up for the 0 → n transitions till the dissociation limit around n = 83, covering 45 orders of magnitude in the intensity. The low-intensity 0 → n transition predicted in the work of Medvedev [Determination of a new molecular constant for diatomic systems. Normal intensity distribution law for overtone spectra of diatomic and polyatomic molecules and anomalies in overtone absorption spectra of diatomic molecules, Institute of Chemical Physics, Russian Academy of Sciences, Chernogolovka, 1984] at n = 5 is confirmed, and two additional “abnormal” intensities are found at n = 14 and 23. Criteria for the appearance of such “anomalies” are formulated. The results could be useful to revise the high-overtone molecular transition probabilities provided in spectroscopic databases.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Improving qubit readout with hidden Markov models

We demonstrate the application of pattern recognition algorithms via hidden Markov models (HMM) for qubit readout. This scheme provides a state-path trajectory approach capable of detecting qubit-state transitions and makes for a robust classification scheme with higher starting-state assignment fidelity than when compared to a multivariate Gaussian or a support vector machine scheme. Therefore, the method also eliminates the qubit-dependent readout time optimization requirement in current schemes. Using a HMM state discriminator we estimate fidelities reaching the ideal limit. Unsupervised learning gives access to transition matrix, priors, and IQ distributions, providing a toolbox for studying qubit-state dynamics during strong projective readout.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Complexity-theoretic foundations of BosonSampling with a linear number of modes

BosonSampling is the leading candidate for demonstrating quantum computational advantage in photonic systems. While we have recently seen many impressive experimental demonstrations, there is still a formidable distance between the complexity-theoretic hardness arguments and current experiments. One of the largest gaps involves the ratio of {particles} to modes -- all current hardness evidence assumes a dilute regime in which the number of linear optical modes scales at least quadratically in the number of particles. By contrast, current experiments operate in a saturated regime with a linear number of modes. In this paper we bridge this gap, bringing the hardness evidence for experiments in the saturated regime to the same level as had been previously established for the dilute regime. This involves proving a new worst-to-average-case reduction for computing the Permanent which is robust to both large numbers of row repetitions and also to distributions over matrices with correlated entries. We also apply similar arguments to give evidence for hardness of Gaussian BosonSampling in the saturated regime.

Computational Complexity (cs.CC)↗
DOE OSTI2015

Self-consistent continuum solvation for optical absorption of complex molecular systems in solution

We introduce a new method to compute the optical absorption spectra of complex molecular systems in solution, based on the Liouville approach to time-dependent density-functional perturbation theory and the revised self-consistent continuum solvation model. The former allows one to obtain the absorption spectrum over a whole wide frequency range, using a recently proposed Lanczos-based technique, or selected excitation energies, using the Casida equation, without having to ever compute any unoccupied molecular orbitals. The latter is conceptually similar to the polarizable continuum model and offers the further advantages of allowing an easy computation of atomic forces via the Hellmann-Feynman theorem and a ready implementation in periodic-boundary conditions. The new method has been implemented using pseudopotentials and plane-wave basis sets, benchmarked against polarizable continuum model calculations on 4-aminophthalimide, alizarin, and cyanin and made available through the QUANTUM ESPRESSO distribution of open-source codes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Boltzmann-conserving classical dynamics in quantum time-correlation functions: “Matsubara dynamics”

We show that a single change in the derivation of the linearized semiclassical-initial value representation (LSC-IVR or “classical Wigner approximation”) results in a classical dynamics which conserves the quantum Boltzmann distribution. We rederive the (standard) LSC-IVR approach by writing the (exact) quantum time-correlation function in terms of the normal modes of a free ring-polymer (i.e., a discrete imaginary-time Feynman path), taking the limit that the number of polymer beads N → ∞, such that the lowest normal-mode frequencies take their “Matsubara” values. The change we propose is to truncate the quantum Liouvillian, not explicitly in powers of ħ{sup 2} at ħ{sup 0} (which gives back the standard LSC-IVR approximation), but in the normal-mode derivatives corresponding to the lowest Matsubara frequencies. The resulting “Matsubara” dynamics is inherently classical (since all terms O(ħ{sup 2}) disappear from the Matsubara Liouvillian in the limit N → ∞) and conserves the quantum Boltzmann distribution because the Matsubara Hamiltonian is symmetric with respect to imaginary-time translation. Numerical tests show that the Matsubara approximation to the quantum time-correlation function converges with respect to the number of modes and gives better agreement than LSC-IVR with the exact quantum result. Matsubara dynamics is too computationally expensive to be applied to complex systems, but its further approximation may lead to practical methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Path integral Monte Carlo simulations of dense carbon-hydrogen plasmas

Carbon-hydrogen plasmas and hydrocarbon materials are of broad interest to laser shock experimentalists, high energy density physicists, and astrophysicists. Accurate equations of state (EOSs) of hydrocarbons are valuable for various studies from inertial confinement fusion to planetary science. By combining path integral Monte Carlo (PIMC) results at high temperatures and density functional theory molecular dynamics results at lower temperatures, we compute the EOSs for hydrocarbons from simulations performed at 1473 separate (ρ, T)-points distributed over a range of compositions. These methods accurately treat electronic excitation effects with neither adjustable parameter nor experimental input. PIMC is also an accurate simulation method that is capable of treating many-body interaction and nuclear quantum effects at finite temperatures. These methods therefore provide a benchmark-quality EOS that surpasses that of semi-empirical and Thomas-Fermi-based methods in the warm dense matter regime. By comparing our first-principles EOS to the LEOS 5112 model for CH, we validate the specific heat assumptions in this model but suggest that the Grüneisen parameter is too large at low temperatures. Based on our first-principles EOSs, we predict the principal Hugoniot curve of polystyrene to be 2%-5% softer at maximum shock compression than that predicted by orbital-free density functional theory and SESAME 7593. By investigating the atomic structure and chemical bonding of hydrocarbons, we show a drastic decrease in the lifetime of chemical bonds in the pressure interval from 0.4 to 4 megabar. We find the assumption of linear mixing to be valid for describing the EOS and the shock Hugoniot curve of hydrocarbons in the regime of partially ionized atomic liquids. We make predictions of the shock compression of glow-discharge polymers and investigate the effects of oxygen content and C:H ratio on its Hugoniot curve. In conclusion, our full suite of first-principles simulation results may be used to benchmark future theoretical investigations pertaining to hydrocarbon EOSs and should be helpful in guiding the design of future experiments on hydrocarbons in the gigabar regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A kinetic line-driven radiation operator and its application to Gyrokinetics

A velocity dependent, kinetic model for line radiation is developed for continuum kinetic codes. It has been implemented in the full-f gyrokinetic code Gkeyll. The total radiation for a charge state is modeled as an advection in velocity space with a form of $\nabla_v \cdot(v\nu(v)f(v))$, guaranteeing particle conservation. The velocity dependence (in the form of an effective frequency $\nu(v)$) is found through fitting the energy loss of the operator, i.e. the second velocity moment, to the radiation data in the OpenADAS database. Therefore, each individual transition does not need to be evaluated every time step, significantly reducing the computational cost of including line radiation in a kinetic model. The dependence on velocity instead of the usual, temperature, allows the radiation to be computed from non-Maxwellian electron distribution functions: We benchmark the model against a collisional radiative model using isotropic non-Maxwellian distribution functions. A velocity dependent model of radiation can more accurately describe the radiation in the more kinetic regimes expected in reactor-scale devices. The velocity dependence qualitatively captures the quantum mechanical need for a minimum velocity before any radiation occurs.

kinetic↗
DOE OSTI2025

Visualization of Noisy and Less Noisy Computational Basis States in Quantum Computing

Quantum computing technology holds substantial promise as a reliable computational paradigm. However, current noisy intermediate scale quantum (NISQ) systems, are significantly impacted by noise originating from hardware inconsistencies. This noise causes errors and lowers output fidelity. So we must find which basis states cause errors. However, there are two main challenges in analyzing noise corresponding to basis states. First, the noise distribution data is high dimensional in nature, thereby making its analysis challenging. Second, although functional box plots have been used in the state of the art research to understand such a high dimensional data, they suffer from clutter and occlusion issues because of overplotting. In this study, we introduce an innovative visualization pipeline to address the aforementioned challenges to provide a clear depiction of noisy and less-noisy basis states. Specifically, our proposed visualization pipeline comprises three stages namely, low dimensional embedding, clustering, and violin plot visualization, to reduce visual clutter and effectively analyze high-dimensional noise distribution data. Our analysis uses quantum machine learning (QML) circuits as case study for drawing a distinction between noisy and less noisy basis states.

Senapati, Priyabrata [Kent State University]↗
DOE OSTI2022

Communication systems and methods

A communication system is provided that includes a first quantum key distribution device and a communication device. The first quantum key distribution device is configured to be coupled to a second quantum key distribution device over a quantum channel and to generate a quantum key based on a quantum state transmitted along the quantum channel. The communication device is communicatively connected to the first quantum key distribution device within a network. The communication device is configured to receive the quantum key from the first quantum key distribution device and transmit the quantum key to an end device in the network via a classical link to enable the end device to use the quantum key for encrypting and/or decrypting messages communicated through the network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications

Deep neural networks have been successfully employed in an extensive variety of research areas, including solving partial differential equations. Despite its significant success, there are some challenges in effectively training DNN, such as avoiding overfitting in over-parameterized DNNs and accelerating the optimization in DNNs with pathological curvature. Here, we propose a Bayesian type sparse deep learning algorithm. The algorithm utilizes a set of spike-and-slab priors for the parameters in the deep neural network. The hierarchical Bayesian mixture will be trained using an adaptive empirical method. That is, one will alternatively sample from the posterior using preconditioned stochastic gradient Langevin Dynamics (PSGLD), and optimize the latent variables via stochastic approximation. The sparsity of the network is achieved while optimizing the hyperparameters with adaptive searching and penalizing. A popular SG-MCMC approach is Stochastic gradient Langevin dynamics (SGLD). However, considering the complex geometry in the model parameter space in nonconvex learning, updating parameters using a universal step size in each component as in SGLD may cause slow mixing. To address this issue, we apply a computationally manageable preconditioner in the updating rule, which provides a step-size parameter to adapt to local geometric properties. Moreover, by smoothly optimizing the hyperparameter in the preconditioning matrix, our proposed algorithm ensures a decreasing bias, which is introduced by ignoring the correction term in the preconditioned SGLD. According to the existing theoretical framework, we show that the proposed algorithm can asymptotically converge to the correct distribution with a controllable bias under mild conditions. Numerical tests are performed on both synthetic regression problems and learning solutions of elliptic PDE, which demonstrate the accuracy and efficiency of the present work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗