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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Digital Twin of Scalable Quantum Clouds

Quantum computing has emerged as a transformative technology capable of solving complex problems beyond the limit of classical systems. The rapid development of quantum processors has led to the proliferation of cloud-based quantum computing services offered by platforms such as IBM, Google, and Amazon. These platforms introduce unique challenges in resource allocation, job scheduling, and multi-device orchestration as quantum workloads become increasingly complex. In this work, we present a digital twin of quantum cloud infrastructures: a framework designed to model and simulate the behavior of real quantum cloud systems. Developed in Python using the SimPy discrete-event simulation library, the framework replicates key aspects of quantum cloud environments, including detailed quantum device modeling, job lifecycle management, and job fidelity. It incorporates noise-aware fidelity estimation, making it the first of its kind to simulate superconducting gate-based quantum cloud systems at an administrative level with job fidelity. We present use cases as proof of concept, demonstrating that our quantum cloud simulation framework can act as a digital twin of a quantum cloud and support the modeling and implementation of practical systems.

Luo, Waylon [Kent State University]↗
DOE OSTI2023

An introduction to financial option pricing on a qudit-based quantum computer

The financial sector is anticipated to be one of the first industries to benefit from the increased computational power of quantum computers, in areas such as portfolio optimisation and risk management to financial derivative pricing. Financial mathematics, and derivative pricing in particular, are not areas quantum physicists are traditionally trained in despite the fact that they often have the raw technical skills needed to understand such topics. On the other hand, most quantum algorithms have largely focused on qubits, which are comprised of two discrete states, as the information carriers. However, discrete higher-dimensional qudits, in addition to possibly possessing increased noise robustness and allowing for novel error correction protocols in certain hardware implementations, also have logarithmically greater information storage and processing capacity. In the current NISQ era of quantum computing, a wide array of hardware paradigms are still being studied and any potential advantage a platform offers is worth exploring. Here we introduce the basic concepts behind financial derivatives for the unfamiliar enthusiast as well as outline in great detail the quantum algorithm routines needed to price a European option, the simplest derivative. This is done within the context of a quantum computer comprised of qudits and employing the natural higher-dimensional analogue of a qubit-based pricing algorithm with its various subroutines. From these pieces, one should relatively easily be able to tailor the scheme to more complex, realistic financial derivatives. Finally, the entire stack is numerically simulated with the results demonstrating how the qudit-based scheme's payoff quickly approaches that of both a similarly-resourced classical computer as well as the true payoff, within error, for a modest increase in qudit dimension.

Bornman, Nicholas↗
DOE OSTI2020

Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due to certain limitations of the hardware connectivity structure of the annealer. This paper studies a general framework for a decomposition algorithm for NP-hard graph problems aiming to identify an optimal set of vertices. Our generic algorithm allows us to recursively divide an instance until the generated subproblems can be embedded on the quantum annealer hardware and subsequently solved. Furthermore, the framework is applied to the maximum clique and minimum vertex cover problems, and we propose several pruning and reduction techniques to speed up the recursive decomposition. The performance of both algorithms is assessed in a detailed simulation study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Acoustic radiation force on a rigid elliptical cylinder in plane (quasi)standing waves

The acoustic radiation force on a 2D elliptical (non-circular) cylinder centered on the axis of wave propagation of plane quasi-standing and standing waves is derived, based on the partial-wave series expansion (PWSE) method in cylindrical coordinates. A non-dimensional acoustic radiation force function, which is the radiation force per unit length, per characteristic energy density and per unit cross-sectional surface of the ellipse, is defined in terms of the scattering coefficients that are determined by applying the Neumann boundary condition for an immovable surface. A system of linear equations involving a single numerical integration procedure is solved by matrix inversion. Numerical simulations showing the transition from the quasi-standing to the (equi-amplitude) standing wave behaviour are performed with particular emphasis on the aspect ratio a/b, where a and b are the ellipse semi-axes, as well as the dimensionless size parameter kb (where k is the wavenumber), without the restriction to a particular range of frequencies. It is found that at high kb values > 1, the radiation force per length with broadside incidence is larger, whereas the opposite situation occurs in the long-wavelength limit (i.e., kb < 1). The results are particularly relevant in acoustic levitation of elliptical cylinders, the acoustic stabilization of liquid columns in a host medium, acousto-fluidics devices, and other particle dynamics applications to name a few. Moreover, the formalism presented here may be effectively applied to compute the acoustic radiation force on other 2D surfaces of arbitrary shape such as super-ellipses, Chebyshev cylindrical particles, or other non-circular geometries.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

High frequency impedance characteristics of a tunable microplasma device

Computational studies on high frequency impedance characteristics of a microplasma device are reported. While microplasma is ignited using a primary excitation signal, frequency response of plasma impedance is determined by a secondary high frequency probe signal with significantly lower voltage amplitude such that it does not influence the plasma parameters. Here, the computational model utilizing the drift–diffusion approximation is first validated by comparing with experimental data for microplasmas ignited at pressures ranging from 1 to 5 Torr. In spite of quantitative discrepancies, good overall agreement is obtained between the measured frequency response of impedance of the discharge. Comparisons are also presented for various plasma parameters including mean electron number density, sheath thickness, mean electron temperature, and collision frequency that were inferred from the impedance measurements. The computational model is then used to perform simulations of near-atmospheric pressure microplasmas with the probe signal frequency ranging from 3 to 20 GHz. The simulations demonstrate the presence of a resonance frequency at which the impedance vanishes. More importantly, it is shown that this resonant frequency can be tuned effectively by suitably modifying the operating parameters (gap size, pressure, and excitation voltage). The simulated impedance characteristics are used to determine the effective plasma inductance and capacitance using a non-linear fitting approach, thereby showing the dependence of these electrical parameters on the plasma operating conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Adaptive hybrid simulations for multiscale stochastic reaction networks

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Quantum field as a quantum cellular automaton: The Dirac free evolution in one dimension

We present a quantum cellular automaton model in one space-dimension which has the Dirac equation as emergent. This model, a discrete-time and causal unitary evolution of a lattice of quantum systems, is derived from the assumptions of homogeneity, parity and time-reversal invariance. The comparison between the automaton and the Dirac evolutions is rigorously set as a discrimination problem between unitary channels. We derive an exact lower bound for the probability of error in the discrimination as an explicit function of the mass, the number and the momentum of the particles, and the duration of the evolution. Computing this bound with experimentally achievable values, we see that in that regime the QCA model cannot be discriminated from the usual Dirac evolution. Finally, we show that the evolution of one-particle states with narrow-band in momentum can be efficiently simulated by a dispersive differential equation for any regime. This analysis allows for a comparison with the dynamics of wave-packets as it is described by the usual Dirac equation. This paper is a first step in exploring the idea that quantum field theory could be grounded on a more fundamental quantum cellular automaton model and that physical dynamics could emerge from quantum information processing. In this framework, the discretization is a central ingredient and not only a tool for performing non-perturbative calculation as in lattice gauge theory. The automaton model, endowed with a precise notion of local observables and a full probabilistic interpretation, could lead to a coherent unification of a hypothetical discrete Planck scale with the usual Fermi scale of high-energy physics. - Highlights: • The free Dirac field in one space dimension as a quantum cellular automaton. • Large scale limit of the automaton and the emergence of the Dirac equation. • Dispersive differential equation for the evolution of smooth states on the automaton. • Optimal discrimination between the automaton evolution and the Dirac equation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Sequential experimental design based generalised ANOVA

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

An improved fast multipole method for electrostatic potential calculations in a class of coarse-grained molecular simulations

This paper presents a novel algorithm to approximate the long-range electrostatic potential field in the Cartesian coordinates applicable to 3D coarse-grained simulations of biopolymers. In such models, coarse-grained clusters are formed via treating groups of atoms as rigid and/or flexible bodies connected together via kinematic joints. Therefore, multibody dynamic techniques are used to form and solve the equations of motion of such coarse-grained systems. In this article, the approximations for the potential fields due to the interaction between a highly negatively/positively charged pseudo-atom and charged particles, as well as the interaction between clusters of charged particles, are presented. These approximations are expressed in terms of physical and geometrical properties of the bodies such as the entire charge, the location of the center of charge, and the pseudo-inertia tensor about the center of charge of the clusters. Further, a novel substructuring scheme is introduced to implement the presented far-field potential evaluations in a binary tree framework as opposed to the existing quadtree and octree strategies of implementing fast multipole method. Using the presented Lagrangian grids, the electrostatic potential is recursively calculated via sweeping two passes: assembly and disassembly. In the assembly pass, adjacent charged bodies are combined together to form new clusters. Then, the potential field of each cluster due to its interaction with faraway resulting clusters is recursively calculated in the disassembly pass. The method is highly compatible with multibody dynamic schemes to model coarse-grained biopolymers. Since the proposed method takes advantage of constant physical and geometrical properties of rigid clusters, improvement in the overall computational cost is observed comparing to the tradition application of fast multipole method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Surface-Controlled TiO 2 Nanocrystals with Catalytically Active Single-Site Co Incorporation for the Oxygen Evolution Reaction

The design of advanced electrocatalysts is often hindered by uncertainties in identifying and controlling the active surfaces and catalytic centers within heterogeneous materials. Here we present the synthesis of single-site Co catalysts, substitutionally doped into surface-controlled TiO 2 anatase nanocrystals, aimed at enhancing the oxygen evolution reaction (OER). Grand canonical quantum mechanics calculations reveal that the kinetics of the OER, following an adsorbate evolution mechanism, is markedly influenced by the coordination environment of Co. The simulations suggest significantly higher turnover frequencies when Co is doped into the (001) surface of TiO 2 compared to the (101) surface. Consistent with the computational findings, experimental results show that Co-doped TiO 2 (Co-TiO 2 ) nanoplates with selectively exposed {001} surfaces exhibit enhanced current densities and turnover frequencies compared to Co-TiO 2 nanobipyramids with {101} surfaces. This study highlights the synergy between theoretical calculations and precision synthesis in the development of more effective catalysts.

25 ENERGY STORAGE↗
DOE OSTI2014

Photonuclear reaction based high-energy x-ray spectrometer to cover from 2 MeV to 20 MeV

A photonuclear-reaction-based hard x-ray spectrometer is developed to measure the number and energy spectrum of fast electrons generated by interactions between plasma and intense laser light. In this spectrometer, x-rays are converted to neutrons through photonuclear reactions, and the neutrons are counted with a bubble detector that is insensitive to x-rays. The spectrometer consists of a bundle of hard x-ray detectors that respond to different photon-energy ranges. Proof-of-principle experiment was performed on a linear accelerator facility. A quasi-monoenergetic electron bunch (N{sub e} = 1.0 × 10{sup −6} C, E{sub e} = 16 ± 0.32 MeV) was injected into a 5-mm-thick lead plate. Bremsstrahlung x-rays, which emanate from the lead plate, were measured with the spectrometer. The measured spectral shape and intensity agree fairly well with those computed with a Monte Carlo simulation code. The result shows that high-energy x-rays can be measured absolutely with a photon-counting accuracy of 50%–70% in the energy range from 2 MeV to 20 MeV with a spectral resolution (Δhν/hν) of about 15%. Quantum efficiency of this spectrometer was designed to be 10{sup −7}, 10{sup −4}, 10{sup −5}, respectively, for 2–10, 11–15, and 15–25 MeV of photon energy ranges.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Influence of surface nano-patterning on the placement of InAs quantum dots

We have examined the influence of spontaneous nano-patterning on the placement of InAs quantum dots (QDs) on (Al)GaAs surfaces using an experimental-computational approach. Both atomically flat and mounded surfaces, generated via a surface instability induced by the Ehrlich- Schwoebel barrier, are employed as templates for the subsequent deposition of InAs QDs. Using height profiles from atomic-force micrographs, we simulate QD deposition with a 2D phase field model, which describes the time evolution of the InAs layer driven by a chemical potential gradient. For flat surfaces, phase-field simulations result in QD densities comparable to experimental observations. For mounded surfaces, the simulations reveal QDs preferentially positioned in regions of positive curvature (substrate valleys), e.g., at the edge of surface mounds, consistent with the anisotropic QD placement observed experimentally. We discuss the role of curvaturedriven diffusion in the spontaneous ordering of QDs, demonstrating the applicability of this mechanism to AlGaAs mounds.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Teaching Quantum Computing to High School Students

Quantum computing is a growing field at the intersection of physics and computer science. The goal of this article is to highlight a successfully trialled quantum computing course for high school students between the ages of 15 and 18 years old. This course was designed to bridge the gap between popular science articles and advanced undergraduate textbooks. Conceptual ideas in the text are reinforced with active learning techniques, such as interactive problem sets and simulation-based labs at various levels. The course is freely available for use and download under the Creative Commons “Attribution-NonCommercial-ShareAlike 4.0 International” license.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Matrix-isolation and ab initio study of HKrCCCl and HXeCCCl

We report on two new noble-gas molecules, HKrCCCl and HXeCCCl, prepared in low-temperature Kr and Xe matrices. These molecules are made by UV photolysis of HCCCl in the matrices and subsequent thermal annealing. The HCCCl precursor is produced by microwave discharge of a mixture of a matrix gas with trichloroethylene (HClC=CCl{sub 2}). The assignments of the new noble-gas molecules are supported by deuteration experiments and quantum chemical calculations at the MP2(full) and CCSD(T) levels of theory with the def2-TZVPPD basis set. No evidence of ClXeCCH, which is computationally reliably stable, is found in the experiments. ClKrCCH as well as the Ar compounds HArCCCl and ClArCCH are not observed either, which is in agreement with the calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Collisional transport across the magnetic field in drift-fluid models

Drift ordered fluid models are widely applied in studies of low-frequency turbulence in the edge and scrape-off layer regions of magnetically confined plasmas. Here, we show how collisional transport across the magnetic field is self-consistently incorporated into drift-fluid models without altering the drift-fluid energy integral. We demonstrate that the inclusion of collisional transport in drift-fluid models gives rise to diffusion of particle density, momentum, and pressures in drift-fluid turbulence models and, thereby, obviates the customary use of artificial diffusion in turbulence simulations. We further derive a computationally efficient, two-dimensional model, which can be time integrated for several turbulence de-correlation times using only limited computational resources. The model describes interchange turbulence in a two-dimensional plane perpendicular to the magnetic field located at the outboard midplane of a tokamak. The model domain has two regions modeling open and closed field lines. The model employs a computational expedient model for collisional transport. Numerical simulations show good agreement between the full and the simplified model for collisional transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Spiky electric and magnetic field structures in flux rope experiments

Magnetic flux ropes are structures that are common in the corona of the sun and presumably all stars. They can be thought of as the building blocks of solar structures. They have been observed in Earth’s magnetotail and near Mars and Venus. When multiple flux ropes are present magnetic field line reconnection, which converts magnetic energy to other forms, can occur when they collide. The structure of multiple magnetic ropes, the interactions between multiple ropes, and their topological properties such as helicity and writhing have been studied theoretically and in laboratory experiments. In this paper, we report on spiky potential and magnetic fields associated with the ropes. We show that the potential structures are chaotic for a range of their temporal half-widths and the probability density function (PDF) of their widths resembles the statistical distribution of crumpled paper. The spatial structure of the magnetic spikes is revealed using a correlation counting method. Computer simulation suggests that the potential structures are the nonlinear end result of an instability involving relative drift between ions and electrons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗