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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving Solution Accuracy and Convergence for Stochastic Physics Parameterizations with Colored Noise

Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. In previous studies, it has been demonstrated that a correction term, known in stochastic analysis as the Itô correction, can help improve solution accuracy for various deterministic numerical schemes and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by white noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. The formulation is applied to a test problem described by an advection–diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and, hence, helps to reduce the computational cost of the numerical simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The color of magnetic monopole noise

We relate the anomaly in the noise color of spin ice to the emergent nature of its magnetic monopoles and their random walk. Monopoles are quasi-particles, and the spin vacuum in which they wander is not structureless. Rather, the underlying spin ensemble filters the thermal white noise, leading to non-trivial coevolution. Thus, monopoles can be considered as "dressed" random walkers, activated by a non-trivial stochastic noise that subsumes mutual interactions and the coevolution of their spin vacuum. From this, we suggest that recent experimental results are interpretable in terms of monopole subdiffusion. Furthermore, we then conjecture relations between the color of the noise and other observables, such as relaxation time, monopole density, the dynamic exponent, and the order of the annihilation reaction, which suggests to us the introduction of spin-ice-specific critical exponents in a neighborhood of the ice manifold criticality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

Here, we report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback–Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid–structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models.

42 ENGINEERING↗
DOE OSTI2025

Data-Driven Closures and Assimilation for Stiff Multiscale Random Dynamics

Here, we introduce a data-driven and physics-informed framework for propagating uncertainty in stiff, multiscale random ordinary differential equations (RODEs) driven by correlated (colored) noise. Unlike systems subjected to Gaussian white noise, a deterministic equation for the joint probability density function (PDF) of RODE state variables does not exist in closed form. Moreover, such an equation would require as many phase-space variables as there are states in the RODE system. To alleviate this curse of dimensionality, we instead derive exact, albeit unclosed, reduced-order PDF (RoPDF) equations for low-dimensional observables/quantities of interest. The unclosed terms take the form of state-dependent conditional expectations, which are directly estimated from data at sparse observation times. However, for systems exhibiting stiff, multiscale dynamics, data sparsity introduces regression discrepancies that compound during RoPDF evolution. This is overcome by introducing a kinetic-like defect term to the RoPDF equation, which is learned by assimilating in sparse, low-fidelity RoPDF estimates. Two assimilation methods are considered, namely nudging and deep neural networks, which are successfully tested against Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Relaxation of stationary states on a quantum computer yields a unique spectroscopic fingerprint of the computer’s noise

Abstract Quantum computing has the potential to revolutionize computing, but its significant sensitivity to noise requires sophisticated error correction and mitigation. Traditionally, noise on the quantum device is characterized directly through qubit and gate measurements, but this approach has drawbacks in that it does not adequately capture the effect of noise on realistic multi-qubit applications. In this paper, we simulate the relaxation of stationary quantum states on a quantum computer to obtain a unique spectroscopic fingerprint of the computer’s noise. In contrast to traditional approaches, we obtain the frequency profile of the noise as it is experienced by the simulated stationary quantum states. Data from multiple superconducting-qubit IBM processors show that noise generates a bath within the simulation that exhibits both colored noise and non-Markovian behavior. Our results provide a direction for noise mitigation but also suggest how to use noise for quantum simulations of open systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Accurate numerical simulations of open quantum systems using spectral tensor trains

Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise. Q-ASPEN is arbitrarily accurate and can be applied to provide estimates for the resources needed to error-correct quantum computations. We employ spectral tensor trains, which combine the advantages of tensor networks and pseudospectral methods, as a variational ansatz to the quantum relaxation problem and optimize the ansatz using methods typically used to train neural networks. Here, the spectral tensor trains in Q-ASPEN make accurate calculations with tens of quantum levels feasible. We present benchmarks for Q-ASPEN on the spin-boson model in the presence of intrinsic noise and on a quantum chain of up to 32 sites in the presence of extrinsic noise. In our benchmark, the memory cost of Q-ASPEN scales as a low-order polynomial in the size of the system once the number of system states surpasses the number of basis functions used in the spectral expansion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Anomalous magnetic noise in an imperfectly flat landscape in the topological magnet Dy 2 Ti 2 O 7

Noise generated by motion of charge and spin provides a unique window into materials at the atomic scale. From temperature of resistors to electrons breaking into fractional quasiparticles, “listening” to the noise spectrum is a powerful way to decode underlying dynamics. Here, we use ultrasensitive superconducting quantum interference device (SQUIDs) to probe the puzzling noise in a frustrated magnet, the spin-ice compound Dy 2 Ti 2 O 7 (DTO), revealing cooperative and memory effects. DTO is a topological magnet in three dimensions—characterized by emergent magnetostatics and telltale fractionalized magnetic monopole quasiparticles—whose real-time dynamical properties have been an enigma from the very beginning. We show that DTO exhibits highly anomalous noise spectra, differing significantly from the expected Brownian noise of monopole random walks, in three qualitatively different regimes: equilibrium spin ice, a “frozen” regime extending to ultralow temperatures, and a high-temperature “anomalous” paramagnet. We present several distinct mechanisms that give rise to varied colored noise spectra. In addition, we identify the structure of the local spin-flip dynamics as a crucial ingredient for any modeling. Thus, the dynamics of spin ice reflects the interplay of local dynamics with emergent topological degrees of freedom and a frustration-generated imperfectly flat energy landscape, and as such, it points to intriguing cooperative and memory effects for a broad class of magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Quantum vibronic effects on the electronic properties of solid and molecular carbon

Here, we study the effect of quantum vibronic coupling on the electronic properties of carbon allotropes, including molecules and solids, by combining path integral first principles molecular dynamics (FPMD) with a colored noise thermostat. In addition to avoiding several approximations commonly adopted in calculations of electron-phonon coupling, our approach only adds a moderate computational cost to FPMD simulations and hence it is applicable to large supercells, such as those required to describe amorphous solids. We predict the effect of electron-phonon coupling on the fundamental gap of amorphous carbon, and we show that in diamond the zero-phonon renormalization of the band gap is larger than previously reported.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stochastic hydrodynamics and hydro-kinetics: Similarities and differences

The hydro-kinetic formalism has been used as a complementary approach to solving the Stochastic Differential Equations (SDE) corresponding to noisy hydrodynamics. The hydro-kinetic formalism consists of a deterministic set of relaxation type equations that tracks the evolution of 2-point correlation functions of stochastic hydrodynamic quantities. Hence they are comparatively easier to solve than the SDEs, which are computationally intensive and need to deal with arbitrarily large gradients. This work compares the two approaches for the propagation and diffusion of conserved charge fluctuations in the Bjorken hydrodynamic model. For white noise, the two approaches agree. For colored Catteneo noise, which is causal, the two approaches diverge. This is because white noise only induces two-point correlations, while Catteneo noise also induces higher-order correlations. Furthermore, this difference is quantified from the effects of causal evolution and influence from higher-order correlations induced by the Catteneo noise.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Mesoscopic-scale complexity in macroscopically-uniform plastic flow of an Al 0.3 CoCrFeNi high-entropy alloy

The concept of a smooth and homogeneous plastic flow of solids is nowadays constantly challenged by various observations of the self-organization of crystal defects on mesoscopic scales pertaining, e.g., to acoustic emission or the evolution of the local strain field. Such investigations would be of particular interest for High-Entropy Alloys (HEAs) characterized by extremely complex microstructures. However, the complexity of their deformation has been only studied in relation to the jerky flow. The present work explores a mesoscale complexity of the macroscopically-smooth plastic flow of an Al 0.3 CoCrFeNi alloy. Here, an inclusive approach involving various experimental methods and complementary nonlinear analyses allowed to reveal transitions between distinct dynamical regimes, which may be assimilated with noises of different colors, in particular the blue noise that is rarely observed in complex systems, and various kinds of reddened behavior. Such findings provide significant new insights into the micro/macro transition in the deformation behavior of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Practical On-line Framework for a Modified Energy Detector by Whitening Ambient PMU Data

A key application of Phasor Measurement Units (PMUs) is power system oscillation detection. An energy detector is a straightforward detection method, but setting thresholds requires extensive and time consuming baselining of data. This paper proposes a novel on-line method of whitening PMU measurements supporting a framework for detecting forced oscillations without requiring extensive baselining. An example of 24 hours of actual PMU data illustrates how a forced oscillation is very visible in the energy signal of the whitened data, while being hard to detect in the colored ambient noise. With this framework, the statistical theory for setting thresholds without baselining is much more straightforward and is the focus of future work.

Xu, Zikai↗
DOE OSTI2026

Data Driven Correlated Noise Simulation for the ICEBERG LArTPC

Accurate electronic-noise simulation is essential for low-energy physics in liquid-argon TPCs. More realistic noise modeling allows us to better tune reconstruction algorithms and more reliably assess and optimize signal-detection thresholds. We present a data-driven noise simulation framework developed for the ICEBERG test stand for DUNE that generates synthetic noise waveforms that reproduce both (i) the measured per-channel magnitude of the Fast Fourier Transform (FFT) and (ii) frequency-dependent channel-to-channel correlations observed in ICEBERG noise data. Using a dedicated noise-only dataset, we build a compact noise model containing per-channel FFT-magnitude targets together with a small set of band-wise cross-wire color matrices. White noise is generated in the frequency domain by drawing circular-symmetric complex Gaussian coefficients with random phases and scaling them to match the measured FFT-magnitude targets, and cross-wire correlations are subsequently imposed using the stored color matrices. The model and algorithm were integrated into the LArSoft + Wire-Cell Toolkit simulation chain and validated by comparing waveform structure, frequency-domain spectra, and band-limited correlation matrices from simulated noise and ICEBERG data. This approach can be extended to other LArTPC operating conditions.

Ghosh, Avik [Iowa State U.]↗
DOE OSTI2022

Cross-correlation spectra in interacting quantum dot systems

Two-color spin-noise spectroscopy of interacting electron spins in singly charged semiconductor quantum dots provides information on the interquantum dot interactions. We investigate the spin cross-correlation function in a quantum dot ensemble employing a modified semiclassical approach. Spin-correlation functions are calculated using a Hamilton quaternion approach that maintains local quantum mechanical properties of the spins. This method takes into account the effects of the nuclear-electric quadrupolar interactions, the randomness of the coupling constants, and the variation of the electron g factor on the spin-noise power spectra. We demonstrate that the quantum dot ensemble can be mapped on an effective two-quantum dot problem and discuss how the characteristic length scale of the interdot interaction modifies the low-frequency cross-correlation spectrum. Here, we argue that details on the interaction strength distribution can be extracted from the cross-correlation spectrum when applying a longitudinal or a transversal external magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Anatomy of Continuous Mars SEIS and Pressure Data from Unsupervised Learning

The seismic noise recorded by the Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) seismometer (Seismic Experiment for Interior Structure [SEIS]) has a strong daily quasi-periodicity and numerous transient microevents, associated mostly with an active Martian environment with wind bursts, pressure drops, in addition to thermally induced lander and instrument cracks. That noise is far from the Earth’s microseismic noise. Quantifying the importance of nonstochasticity and identifying these microevents is mandatory for improving continuous data quality and noise analysis techniques, including autocorrelation. Cataloging these events has so far been made with specific algorithms and operator’s visual inspection. We investigate here the continuous data with an unsupervised deep-learning approach built on a deep scattering network. This leads to the successful detection and clustering of these microevents as well as better determination of daily cycles associated with changes in the intensity and color of the background noise. We first provide a description of our approach, and then present the learned clusters followed by a study of their origin and associated physical phenomena. We show that the clustering is robust over several Martian days, showing distinct types of glitches that repeat at a rate of several tens per sol with stable time differences. We show that the clustering and detection efficiency for pressure drops and glitches is comparable to or better than manual or targeted detection techniques proposed to date, noticeably with an unsupervised approach. Finally, here we discuss the origin of other clusters found, especially glitch sequences with stable time offsets that might generate artifacts in autocorrelation analyses. We conclude with presenting the potential of unsupervised learning for long-term space mission operations, in particular, for geophysical and environmental observatories.

58 GEOSCIENCES↗
DOE OSTI2025

Nitridation of atomically smooth (111) diamond surfaces using a low temperature Penning plasma discharge

Diamond is a material with a wide band gap that can host a variety of isolated paramagnetic defects, called “color centers”1. These color centers have attractive optical and magnetic properties suitable for quantum applications including quantum computing, nanophotonics and quantum sensing. The most common one is the negatively charged nitrogen vacancy (NV) color center. For quantum sensing, it is desirable to reduce the distance between the NV center and the analyte by using shallow color centers in order to increase sensitivity. In this context, the diamond surface termination is especially critical. The appropriate surface termination is required to stabilize the color centers and mitigate surface magnetic noise. The nitrogen termination of diamond has been postulated as highly desirable for the NV color center. The goal of this project is to take advantage of an electron beam-generated ExB low temperature plasma developed by the Princeton Collaborative Low Temperature Plasma Research Facility (PCRF) at the Princeton Plasma Physics Laboratory (PPPL) to nitridate the surface of (100) diamond single crystals with minimal surface damage. In this reactor, the use of a magnetized plasma enables gentle processing of materials sensitive to ion damage. This is in strong contrast to radiofrequency plasma processing reactors which are known to etch and sputter the surface. XPS measurements indicate the incorporation of nitrogen and oxygen atoms at the surface in similar amounts. XAS measurements confirm the nitridation and indicate that the nitrogen termination is different from the nitrogen termination obtained using radiofrequency plasma treatment4. The combination of these results indicates the formation of amid species at the (100) diamond surface that are promising for the stabilization of NV centers for quantum sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

ZTF-SEDm Type Ia supernova sample for Twins Embedding spectrophotometric standardization

Aims. This paper has two aims: the first aim is to build a large homogeneous spectrophotometric sample of Type Ia supernovae (SNe Ia) from the second data release of the Zwicky Transient Facility (ZTF DR2). We used the spectrum sample from the low-resolution ( R ∼ 100) SEDmachine (SEDm) Integral Field Spectrograph (IFS) that gathered 3069 spectra. This is one of the largest samples of such collections that can attempt to reproduce the Twins Embedding (TE) spectrophotometric standardization method. This is our second objective. The method was developed based on high-quality spectra from 200 SNe Ia of the Nearby Supernova factory (SNfactory) and led to an exceptionally low value of 0.073 mag for the intrinsic scatter. Methods. As the SEDm is not designed as a spectrophotometric instrument, we first improved the flux-calibration accuracy of the SN Ia spectrum sample using the ZTF photometric data, which were calibrated at the percent level. We corrected the spectra for second-order polynomials, fitted by comparing the synthetic photometry in the ZTF g , r , i filters with the light-curve (LC) data. We then applied the three steps of the TE parameterization to a subset of 783 ZTF SN spectra near maximum light while comparing results from SNfactory and ZTF. We finally analyzed the standardization methods based on the TE parameters. Results. The precision of the phase-correction model, which is the first step of the TE, is estimated at 0.01 mag in g band based on ZTF data. Despite the challenge posed by the spectrum-extraction pipeline associated with the SEDm (flux calibration, leftover host signal, low signal-to-noise ratio, and low resolution), we applied a first standardization in color based on the second step of the TE, called read between the lines (RBTL), to the ZTF sample. We reached a Hubble residual scatter of 0.153 mag, all in normalized median absolute deviation, which is to be compared to the ∼0.11 mag obtained with the SNfactory data. The SALT color and stretch standardization reaches a scatter of 0.164 mag for the same ZTF SN Ia sample, and its host steps are ∼0.1 mag and zero for RBTL. When considering the scatter due to the redshift error and flux calibration error, we estimated a RBTL scatter of ∼0.129 mag for this ZTF sample as an upper limit because we identified an additional contribution from a systematic error in color. We tested the standardization based on the nonlinear TE parameters, and, as expected from the low spectrum quality, it did not improve the overall dispersion. Conclusions. We release 1897 flux calibrated spectra of 1607 SNe Ia with an estimated photometric accuracy of 0.07 mag. We further demonstrate that some amount of spectrophotometric SN Ia standardization can be done with limited-quality spectra. The RBTL standardization is more efficient than that of SALT with one parameter less, and the resulting host steps are consistent with zero. This makes it less prone to astrophysical bias. For future spectroscopic surveys, targeting the extraction pipeline for a thorough flux calibration and good signal-to-noise ratio would enable us to compute the full TE standardization, which would further reduce the scatter in the distance estimate.

Ganot, C↗
DOE OSTI2023

Measurement of Telescope Transmission Using a Collimated Beam Projector

With the increasingly large number of Type Ia supernova being detected by current-generation survey telescopes, and even more expected with the upcoming Rubin Observatory Legacy Survey of Space and Time, the precision of cosmological measurements will become limited by systematic uncertainties in flux calibration rather than statistical noise. One major source of systematic error in determining SNe Ia color evolution (needed for distance estimation) is uncertainty in telescope transmission, both within and between surveys. We introduce here the Collimated Beam Projector (CBP), which is meant to measure a telescope transmission with collimated light. The collimated beam more closely mimics a stellar wave front as compared to flat-field-based instruments, allowing for more precise handling of systematic errors such as those from ghosting and filter angle-of-incidence dependence. As a proof of concept, we present CBP measurements of the StarDICE prototype telescope, achieving a standard (1σ) uncertainty of 3% on average over the full wavelength range measured with a single beam illumination.

79 ASTRONOMY AND ASTROPHYSICS↗