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Results for “quantum parameter estimation”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Two-frequency sub-Doppler spectroscopy of the caesium D{sub 1} line in various configurations of counterpropagating laser beams

Sub-Doppler resonances in caesium vapours are studied in a laser field produced by counterpropagating two-frequency light beams with mutually orthogonal linear polarisations. The beams are in resonance with optical transitions in the D{sub 1} line, the frequency difference of the field spectral components being equal to the hyperfine ground-state splitting in the Cs atom (∼9.2 GHz). It has already been shown that in this configuration, the hypercontrast effect can be observed for sub-Doppler resonances, which makes this configuration promising for the employment in new-generation miniature optical frequency standards. In the present work, two different two-frequency configurations are compared with each other and with the single-frequency configuration widely used in practice for observing saturated absorption resonances. The parameters of nonlinear resonances are measured at various temperatures of caesium vapours and at different optical field intensities. The results of the investigations performed make it possible to find an optimal two-frequency scheme for exciting nonlinear resonances and to estimate a potential of the scheme for its applications in quantum metrology. (laser spectroscopy of atoms)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Impact of bulk-edge coupling on observation of anyonic braiding statistics in quantum Hall interferometers

Abstract Quantum Hall interferometers have been used to probe fractional charge and statistics of quasiparticles. We present measurements of a small Fabry–Perot interferometer in which the electrostatic coupling constants which affect interferometer behavior can be determined experimentally. Near the center of the ν = 1/3 state this device exhibits Aharonov–Bohm interference interrupted by a few discrete phase jumps, and Φ 0 oscillations at higher and lower magnetic fields, consistent with theoretical predictions for detection of anyonic statistics. We estimate the electrostatic parameters K I and K I L by two methods: using the ratio of oscillation periods in compressible versus incompressible regions, and from finite-bias conductance measurements. We find that the extracted K I and K I L can account for the deviation of the phase jumps from the theoretical anyonic phase θ a = 2 π /3. At integer states, we find that K I and K I L can account for the Aharonov–Bohm and Coulomb-dominated behavior of different edge states.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Computing partition functions in the one-clean-qubit model

We present a method to approximate partition functions of quantum systems using mixed-state quantum computation. For positive-semidefinite Hamiltonians, our method has an expected running-time that is almost linear in [M/( ε rel Z )] 2 , where M is the dimension of the quantum system, Z is the partition function, and ε rel is the relative precision. It is based on approximations of the exponential operator as linear combinations of certain operators related to block-encoding of Hamiltonians or Hamiltonian evolutions. The trace of each operator is estimated using a standard algorithm in the one-clean-qubit model. For large values of Z , our method may run faster than exact classical methods, whose complexities are polynomial in M . We also prove that a version of the partition function estimation problem within additive error is complete for the so-called DQC1 complexity class, suggesting that our method provides a superpolynomial speedup for certain parameter values. Overall, to attain a desired relative precision, we develop a classical procedure based on a sequence of approximations within predetermined additive errors that may be of independent interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Informational approach to cosmological parameter estimation

Here, we introduce a new approach for cosmological parameter estimation based on the information-theoretical Jensen-Shannon divergence ($\mathscr{D}$ JS ), calculating it for models in the restricted parameter space {H 0 , w 0 , w a }, where H 0 is the value of the Hubble constant today, and w 0 and w a are dark energy parameters, with the other parameters held fixed at their best-fit values from the Planck 2018 data. As an application, we investigate the H 0 tension between the Planck temperature power spectrum data (TT) and the local astronomical data by comparing the ΛCDM model with the wCDM and the w 0 w a CDM dynamic dark energy models. We find agreement with other works using the standard Bayesian inference for parameter estimation; in addition, we show that while the $\mathscr{D}$ JS is equally minimized for both values of H 0 along the (w 0 , w a ) plane, the lines of degeneracy are different for each value of H 0 . This allows for distinguishing between the two, once the value of either w 0 or w a is known.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Adaptive pruning-based optimization of parameterized quantum circuits

Abstract Variational hybrid quantum–classical algorithms are powerful tools to maximize the use of noisy intermediate-scale quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been limited by the difficulty of optimizing in the vast parameter space. In this work, we propose a heuristic optimization strategy for such ansatze used in variational quantum algorithms, which we call ‘parameter-efficient circuit training (PECT)’. Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms, in which each iteration of the algorithm activates and optimizes a subset of the total parameter set. To update the parameter subset between iterations, we adapt the Dynamic Sparse Reparameterization scheme which was originally proposed for training deep convolutional neural networks. We demonstrate PECT for the Variational Quantum Eigensolver, in which we benchmark unitary coupled-cluster ansatze including UCCSD and k -UpCCGSD, as well as the Low-Depth Circuit Ansatz (LDCA), to estimate ground state energies of molecular systems. We additionally use a layerwise variant of PECT to optimize a hardware-efficient circuit for the Sycamore processor to estimate the ground state energy densities of the one-dimensional Fermi-Hubbard model. From our numerical data, we find that PECT can enable optimizations of certain ansatze that were previously difficult to converge and more generally can improve the performance of variational algorithms by reducing the optimization runtime and/or the depth of circuits that encode the solution candidate(s).

Physics↗
DOE OSTI2021

Adaptive hyperparameter updating for training restricted Boltzmann machines on quantum annealers

Restricted Boltzmann Machines (RBMs) have been proposed for developing neural networks for a variety of unsupervised machine learning applications such as image recognition, drug discovery, and materials design. The Boltzmann probability distribution is used as a model to identify network parameters by optimizing the likelihood of predicting an output given hidden states trained on available data. Training such networks often requires sampling over a large probability space that must be approximated during gradient based optimization. Quantum annealing has been proposed as a means to search this space more efficiently which has been experimentally investigated on D-Wave hardware. D-Wave implementation requires selection of an effective inverse temperature or hyperparameter (β) within the Boltzmann distribution which can strongly influence optimization. Here, we show how this parameter can be estimated as a hyperparameter applied to D-Wave hardware during neural network training by maximizing the likelihood or minimizing the Shannon entropy. We find both methods improve training RBMs based upon D-Wave hardware experimental validation on an image recognition problem. Neural network image reconstruction errors are evaluated using Bayesian uncertainty analysis which illustrate more than an order magnitude lower image reconstruction error using the maximum likelihood over manually optimizing the hyperparameter. The maximum likelihood method is also shown to out-perform minimizing the Shannon entropy for image reconstruction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Contributions to the optical linewidth of shallow donor-bound excitonic transition in ZnO

Neutral shallow donors in zinc oxide (ZnO) are spin qubits with optical access via the donor-bound exciton. This spin–photon interface enables applications in quantum networking, memories, and transduction. Essential optical parameters which impact the spin–photon interface include radiative lifetime, optical inhomogeneous and homogeneous linewidth, and optical depth. We study the donor-bound exciton optical linewidth properties of Al, Ga, and In donors in single-crystal ZnO. The ensemble photoluminescence linewidth ranges from 4 to 11 GHz, less than two orders of magnitude larger than the expected lifetime-limited linewidth. The ensemble linewidth remains narrow in absorption through samples with an estimated optical depth up to several hundred. The primary thermal relaxation mechanism is identified and found to have a negligible contribution to the total linewidth at 2 K. We find that inhomogeneous broadening due to the disordered isotopic environment in natural ZnO is significant, contributing 2 GHz. Two-laser spectral hole burning measurements indicate that the dominant mechanism, however, is homogeneous. Despite this broadening, the high homogeneity, large optical depth, and potential for isotope purification indicate that the optical properties of the ZnO donor-bound exciton are promising for a wide range of quantum technologies, and motivate a need to improve the isotope and chemical purity of ZnO for quantum technologies.

Niaouris, Vasileios (ORCID:000000015313748X)↗
DOE OSTI2023

$μ$ $\mathrm{SR}$ study of the dipole-octupole quantum spin ice candidate $\mathrm{Ce_2Zr_2O_7}$

The Ce 3+ pseudospin-1/2 degrees of freedom in Ce 2 Zr 2 O 7 possess both dipolar and octupolar character which enables the possibility of novel quantum spin liquid ground states in this material. In this study, we report muon spin relaxation and rotation (μSR) measurements on single-crystal samples of Ce 2 Zr 2 O 7 in zero magnetic field and in magnetic fields directed along the [1, $\overline{1}$, 0] and [1, 1, 1] crystallographic directions, and for magnetic fields directed both longitudinal and transverse to the direction of muon polarization. Our zero-field results show no signs of magnetic ordering or spin freezing, consistent with earlier zero-field μSR measurements on a powder sample of Ce 2 Zr 2 O 7 , and also with the expectations for a quantum spin ice. However, we measure a more gentle relaxation rate for Ce 2 Zr 2 O 7 in zero field at low temperatures than was previously reported. This difference in relaxation rate is likely due to the low oxidation and, correspondingly, the high stoichiometry of our singlecrystal samples. Longitudinal field measurements confirm that the magnetic dipole moments in Ce 2 Zr 2 O 7 remain dynamic at T = 0.1 K on the microsecond timescale. For both [1, $\overline{1}$, 0] and [1, 1, 1] magnetic fields, our μSR Knight shift measurements show a field-induced leveling off of the magnetic susceptibility at low temperature which is qualitatively consistent with corresponding calculations using the numerical-linked-cluster method in combination with recent estimates for the nearest-neighbor exchange parameters of Ce 2 Zr 2 O 7 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Semimetal–Mott insulator quantum phase transition of the Hubbard model on the honeycomb lattice

We take advantage of recent improvements in the grand canonical hybrid Monte Carlo algorithm, to perform a precision study of the single-particle gap in the hexagonal Hubbard model, with on-site electron-electron interactions. After carefully controlled analyses of the Trotter error, the thermodynamic limit, and finite-size scaling with inverse temperature, we find a critical coupling of U c /κ = 3.834(14) and the critical exponent zν = 1.185(43). Under the assumption that this corresponds to the expected antiferromagnetic Mott transition, we are also able to provide a preliminary estimate β = 1.095(37) for the critical exponent of the order parameter. We consider our findings in view of the SU(2) Gross-Neveu, or chiral Heisenberg, universality class. Here, we also discuss the computational scaling of the hybrid Monte Carlo algorithm, and possible extensions of our work to carbon nanotubes, fullerenes, and topological insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Study of SXR/EUV radiation of exploded foils and wires with spectral, spatial and temporal resolution simultaneously on KING electric discharge facility.

The results of studies of the soft X-ray and extreme ultraviolet (SXR/EUV) radiation of thin flat aluminum foils and wires under the explosion in an electric discharge on the compact high-current KING generator are presented. These studies were based on the SXR/EUV spectroscopy with a spectral resolution of 6 Å, a temporal resolution of 5 ns and a spatial resolution of 200 μm. To study the plasma radiation of exploded foils and wires in the SXR/EUV range, we used a transmission diffraction grating spectrograph which in combination with two additional slits provided spectral and spatial resolution. The spectrograph was coupled with a 4-frame recorder based on a microchannel plate for providing temporal resolution. The analysis and comparison of the spectral, spatial, temporal, and energy characteristics of the SXR/EUV radiation of plasma formed under the explosion of foils and wires of a similar mass made of aluminum was carried out. Here, the spectra were calculated as well and the plasma parameters and their changes in time and space were estimated on the basis of these calculations and comparison with relevant experimental results. Experiments have shown that when foils explode, a single intense source of SXR/EUV radiation is formed with radiated energy in the range of 10-20 J and a power of up to 100 MW in the quantum energy range from 30 to 250 eV. At the same time, the radiation power under the explosion of foils turned out to be about twice above the power under the explosion of wires of comparable mass.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions

Abstract The ability to efficiently load functions on quantum computers with high fidelity is essential for many quantum algorithms, including those for solving partial differential equations and Monte Carlo estimation. In this work, we introduce the Fourier series loader (FSL) method for preparing quantum states that exactly encode multi-dimensional Fourier series using linear-depth quantum circuits. Specifically, the FSL method prepares a (Dn)-qubit state encoding the 2 Dn -point uniform discretization of aD-dimensional function specified by aD-dimensional Fourier series. A free parameter,m, which must be less thann, determines the number of Fourier coefficients, 2 D ( m + 1 ) , used to represent the function. The FSL method uses a quantum circuit of depth at most 2 ( n − 2 ) + ⌈ log 2 ( n − m ) ⌉ + 2 D ( m + 1 ) + 2 − 2 D ( m + 1 ) , which is linear in the number of Fourier coefficients, and linear in the number of qubits (Dn) despite the fact that the loaded function’s discretization is over exponentially many (2 Dn ) points. The FSL circuit consists of at most D n + 2 D ( m + 1 ) + 1 − 1 single-qubit and D n ( n + 1 ) / 2 + 2 D ( m + 1 ) + 1 − 3 D ( m + 1 ) − 2 two-qubit gates; we present a classical compilation algorithm with runtime O ( 2 3 D ( m + 1 ) ) to determine the FSL circuit for a given Fourier series. The FSL method allows for the highly accurate loading of complex-valued functions that are well-approximated by a Fourier series with finitely many terms. We report results from noiseless quantum circuit simulations, illustrating the capability of the FSL method to load various continuous 1D functions, and a discontinuous 1D function, on 20 qubits with infidelities of less than 10 −6 and 10 −3 , respectively. We also demonstrate the practicality of the FSL method for near-term quantum computers by presenting experiments performed on the Quantinuum H1-1 and H1-2 trapped-ion quantum computers: we loaded a complex-valued function on 3 qubits with a fidelity of over 95 % , as well as various 1D real-valued functions on up to 6 qubits with classical fidelities ≈99%, and a 2D function on 10 qubits with a classical fidelity ≈94%.

Physics↗
DOE OSTI2021

Bottomonium suppression and elliptic flow using Heavy Quarkonium Quantum Dynamics

We introduce a framework called Heavy Quarkonium Quantum Dynamics (HQQD) which can be used to compute the dynamical suppression of heavy quarkonia propagating in the quark-gluon plasma using real-time in-medium quantum evolution. Using HQQD we compute large sets of real-time solutions to the Schrödinger equation using a realistic in-medium complex-valued potential. We sample 2 million quarkonia wave packet trajectories and evolve them through the QGP using HQQD to obtain their survival probabilities. The computation is performed using three different HQQD model parameter sets in order to estimate our systematic uncertainty. After taking into account final state feed down we compare our results to existing experimental data for the suppression and elliptic flow of bottomonium states and find that HQQD predictions are good agreement with available data for R AA as a function of N part and p T collected at \( \sqrt{s_{\mathrm{NN}}} \) = 5 . 02 TeV. In the case of v 2 for the various states, we find that the path-length dependence of ϒ(1 s ) suppression results in quite small v 2 for ϒ(1 s ). Our prediction for the integrated elliptic flow for ϒ(1 s ) in the 10 – 90% centrality class, which now includes an estimate of the systematic error, is v 2 [ϒ(1 s )] = 0 . 003 ± 0 . 0007 ± \( {}_{0.0013}^{0.0006} \) . We also find that, due to their increased suppression, excited bottomonium states have a larger elliptic flow. Based on this observation we make predictions for v 2 [ϒ(2 s )] and v 2 [ϒ(3 s )] as a function of centrality and transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Effective electric field: Quantifying the sensitivity of searches for new -odd physics with EuCl 3 ∙ 6H 2 O

Laboratory-scale precision experiments are a promising approach to searching for physics beyond the standard model. Noncentrosymmetric solids offer favorable statistical sensitivity for efforts that search for new fields, whose interactions violate the discrete parity and time-reversal symmetries. One example is the cosmic axion spin precession experiment (CASPEr), which can be sensitive to the defining interaction of the quantum chromodynamics (QCD) axion dark matter with gluons in atomic nuclei. The effective electric field is the parameter that quantifies the sensitivity of such experiments to new physics. We describe the theoretical approach to calculating the effective electric field for noncentrosymmetric sites in ionic insulating solids. We consider the specific example of the crystal, which is a particularly promising material. The optimistic estimate of the effective electric field for the isotope in this crystal is . The calculation uncertainty is estimated to be two orders of magnitude, dominated by the evaluation of the europium nuclear Schiff moment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Accessing scattering amplitudes using quantum computers

Future quantum computers may serve as a tool to access non-perturbative real-time correlation functions. In this talk, we discuss the prospects of using these to study Compton scattering for arbitrary kinematics. The restriction to a finite-volume spacetime, unavoidable in foreseeable quantum-computer simulations, must be taken into account in the formalism for extracting scattering observables. One approach is to work with a non-zero iϵ-prescription in the Fourier transform to definite momentum and then to estimate an ordered double limit, in which the spacetime volume is sent to infinity before ϵ is sent to 0. For the amplitudes and parameters considered here, we find that significant volume effects arise, making the required limit very challenging. We present a practical solution to this challenge that may allow for future determinations of deeply virtual Compton scattering amplitudes, as well as many other reactions that are presently outside the scope of standard lattice QCD calculations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bootstrap-determined p values in lattice QCD

We present a general method to determine the probability that stochastic Monte Carlo data, in particular those generated in a lattice QCD calculation, would have been obtained were that data drawn from the distribution predicted by a given theoretical hypothesis. Such a probability, or p -value, is often used as an important heuristic measure of the validity of that hypothesis. The proposed method offers the benefit that it remains usable in cases where the standard Hotelling T 2 methods based on the conventional χ 2 statistic do not apply, such as for uncorrelated fits. Specifically, we analyze q 2 , defined as the correlated χ 2 statistic obtained using an arbitrary covariance matrix estimator, and show how to use the bootstrap as a data-driven method to determine the expected distribution of q 2 for a given hypothesis with minimal assumptions. This distribution can then be used to determine the p -value for a fit to the data. We also describe a bootstrap approach for quantifying the impact upon this p -value of estimating population parameters from a single ensemble of N samples. The overall method is accurate up to a 1 / N bias which we do not attempt to quantify. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Diluted axion star collisions with neutron stars

Diluted axion star, a self-gravitating object with the quantum pressure balancing gravity, has been predicted in many models with a QCD axion or axion-like particle. It can be formed in the early universe and composes a sizable fraction of dark matter. One could detect the transient radio signals when it passes by a magnetar with the axion particle converted into photon in the magnetic field. Using both numerical and semi-analytic approaches, we simulate the axion star's dynamic evolution and estimate the fraction of axion particles that can have a resonance conversion during such a collision event. We have found that both self-gravity and quantum pressure are not important after the diluted axion star enters the Roche radius. A free-fall approximate can capture individual particle trajectories very well. Finally, with some optimistic cosmological and astrophysical assumptions, the QCD axion parameter space can be probed from detecting such a collision event by radio telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

NISQ algorithm for the matrix elements of a generic observable

The calculation of off-diagonal matrix elements has various applications in fields such as nuclear physics and quantum chemistry. In this paper, we present a noisy intermediate scale quantum algorithm for estimating the diagonal and off-diagonal matrix elements of a generic observable in the energy eigenbasis of a given Hamiltonian without explicitly preparing its eigenstates. By means of numerical simulations we show that this approach finds many of the matrix elements for the one and two qubits cases. Specifically, while in the first case, one can initialize the ansatz parameters over a broad interval, in the latter the optimization landscape can significantly slow down the speed of convergence and one should therefore be careful to restrict the initialization to a smaller range of parameters.

Physics↗