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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Power spectrum of electrical discharges seen on earth and at Saturn

A technique is described for deriving the radio spectrum of electrical discharges by using the properties of the time series of charges crossing the discharge gap. The method was applied to the spectrum of lightning and to the Saturn's electrical discharges (SEDs). It is shown that the occurrence and the power density of SEDs have subtle, but important, differences from these observables described in the last five years. The reasons for these differences are discussed.

Warwick, James W.↗
NASA NTRS2010

Interplanetary Magnetic Field Power Spectrum Variations: A VHO Enabled Study

The newly reprocessed high time resolution (11/22 vectors/sec) Wind mission interplanetary magnetic field data and the solar wind key parameter search capability of the Virtual Heliospheric Observatory (VHO) affords an opportunity to study magnetic field power spectral density variations as a function of solar wind conditions. In the reprocessed Wind Magnetic Field Investigation (MFI) data, the spin tone and its harmonics are greatly reduced that allows the meaningful fitting of power spectra to the approx.2 Hz limit above which digitization noise becomes apparent. The power spectral density is computed and the spectral index is fitted for the MHD and ion inertial regime separately along with the break point between the two for various solar wind conditions . The time periods of fixed solar wind conditions are obtained from VHO searches that greatly simplify the process. The functional dependence of the ion inertial spectral index and break point on solar wind plasma and magnetic field conditions will be discussed

Szabo, A.↗
NASA NTRS2011

Interplanetary Magnetic Field Power Spectrum Variations: A VHO Enabled Study

The newly reprocessed high time resolution (11/22 vectors/sec) Wind mission interplanetary magnetic field data and the solar wind key parameter search capability of the Virtual Heliospheric Observatory (VHO) affords an opportunity to study magnetic field power spectral density variations as a function of solar wind conditions. In the reprocessed Wind Magnetic Field Investigation (MFI) data, the spin tone and its harmonics are greatly reduced that allows the meaningful fitting of power spectra to the ~2 Hz limit above which digitization noise becomes apparent. The power spectral density is computed and the spectral index is fitted for the MHD and ion inertial regime separately along with the break point between the two for various solar wind conditions. The time periods of fixed solar wind conditions are obtained from VHO searches that greatly simplify the process. The functional dependence of the ion inertial spectral index and break point on solar wind plasma and magnetic field conditions will be discussed

Szabo, A.↗
DOE OSTI2021

Aging power spectrum of membrane protein transport and other subordinated random walks

Single-particle tracking offers detailed information about the motion of molecules in complex environments such as those encountered in live cells, but the interpretation of experimental data is challenging. One of the most powerful tools in the characterization of random processes is the power spectral density. However, because anomalous diffusion processes in complex systems are usually not stationary, the traditional Wiener-Khinchin theorem for the analysis of power spectral densities is invalid. Here, we employ a recently developed tool named aging Wiener-Khinchin theorem to derive the power spectral density of fractional Brownian motion coexisting with a scale-free continuous time random walk, the two most typical anomalous diffusion processes. Using this analysis, we characterize the motion of voltage-gated sodium channels on the surface of hippocampal neurons. Our results show aging where the power spectral density can either increase or decrease with observation time depending on the specific parameters of both underlying processes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Interplanetary Magnetic Field Power Spectrum Variations in the Inner Heliosphere: A Wind and MESSENGER Study

The newly reprocessed high time resolution (11/22 vectors/sec) Wind mission interplanetary magnetic field data and the similar observations made by the MESSENGER spacecraft in the inner heliosphere affords an opportunity to compare magnetic field power spectral density variations as a function of radial distance from the Sun under different solar wind conditions. In the reprocessed Wind Magnetic Field Investigation (MFI) data, the spin tone and its harmonics are greatly reduced that allows the meaningful fitting of power spectra to the approx.2 Hz limit above which digitization noise becomes apparent. The powe'r spectral density is computed and the spectral index is fitted for the MHD and ion inertial regime separately along with the break point between the two for various solar wind conditions. Wind and MESSENGER magnetic fluctuations are compared for times when the two spacecraft are close to radial and Parker field alignment. The functional dependence of the ion inertial spectral index and break point on solar wind plasma and magnetic field conditions will be discussed.

Szabo, Adam↗
DOE OSTI2024

The Simons Observatory: impact of bandpass, polarization angle and calibration uncertainties on small-scale power spectrum analysis

We study the effects due to mismatches in passbands, polarization angles, and temperature and polarization calibrations in the context of the upcoming cosmic microwave background experiment Simons Observatory (SO). Using the SO multi-frequency likelihood, we estimate the bias and the degradation of constraining power in cosmological and astrophysical foreground parameters assuming different levels of knowledge of the instrumental effects. We find that incorrect but reasonable assumptions about the values ofall the systematics examined here can have significant effects on cosmologicalanalyses, hence requiring marginalization approaches at the likelihood level.When doing so, we find that the most relevant effect is due to bandpass shifts. When marginalizing over them, the posteriors of parameters describing astrophysical microwave foregrounds (such as radio point sources or dust) get degraded, while cosmological parameters constraints are not significantly affected.Marginalization over polarization angles with up to 0.25$^{°}$ uncertainty causes an irrelevant bias ≲ 0.05 σ in all parameters.Marginalization over calibration factors in polarization broadens the constraints on the effective number of relativistic degrees of freedom N$_{eff}$ by a factor 1.2, interpreted here as a proxy parameter for non standard model physics targeted by high-resolution CMB measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2014

Discovery of a Similar to 5 Day Characteristic Timescale in the Kepler Power Spectrum of Zw 229-15

We present time series analyses of the full Kepler dataset of Zw 229− 15. This Kepler light curve- with a baseline greater than three years, composed of virtually continuous, evenly sampled 30-minute measurements - is unprecedented in its quality and precision. We utilize two methods of power spectral analysis to investigate the optical variability and search for evidence of a bend frequency associated with a characteristic optical variability timescale. Each method yields similar results. The first interpolates across data gaps to use the standard Fourier periodogram. The second, using the CARMA-based time-domain modeling technique of Kelly et al., does not need evenly-sampled data. Both methods find excess power at high frequencies that may be due to Kepler instrumental effects. More importantly both also show strong bends (delta alpha is approx. 2) at timescales of approx. 5 days, a feature similar to those seen in the X-ray PSDs of AGN but never before in the optical. This observed approx. 5 day timescale may be associated with one of several physical processes potentially responsible for the variability. A plausible association could be made with light -crossing, dynamical or thermal timescales, depending on the assumed value of the accretion disk size and on unobserved disk parameters such as alpha and H¬R. This timescale is not consistent with the viscous timescale, which would be years in a approx. 10(exp7) solar mass AGN such as Zw 229− 15. However there must be a second bend on long (& 1 year) timescales, and that feature could be associated with the viscous timescale.

timescale↗
DOE OSTI2021

Model-independent versus model-dependent interpretation of the SDSS-III BOSS power spectrum: Bridging the divide

The traditional clustering analyses of galaxy redshift surveys compress the clustering data into a set of late-time physical variables in a model-independent way. This approach has recently been extended by an additional shape variable encoding early-time physics information. Here we apply this new technique, ShapeFit, to SDSS-III BOSS data and show that it matches the constraining power of alternative, model-dependent approaches, which directly constrain the model’s parameters adopting a cosmological model ab initio. ShapeFit is ~30 times faster, model independent, naturally splits early- and late-time variables, and enables a better control of observational systematics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Inferring dark matter substructure with astrometric lensing beyond the power spectrum

Abstract Astrometry—the precise measurement of positions and motions of celestial objects—has emerged as a promising avenue for characterizing the dark matter population in our Galaxy. By leveraging recent advances in simulation-based inference and neural network architectures, we introduce a novel method to search for global dark matter-induced gravitational lensing signatures in astrometric datasets. Our method based on neural likelihood-ratio estimation shows significantly enhanced sensitivity to a cold dark matter population and more favorable scaling with measurement noise compared to existing approaches based on two-point correlation statistics. We demonstrate the real-world viability of our method by showing it to be robust to non-trivial modeled as well as unmodeled noise features expected in astrometric measurements. This establishes machine learning as a powerful tool for characterizing dark matter using astrometric data.

convolutional neural networks (1938)↗