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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

MAGNETIC FIELD COMPONENTS ANALYSIS OF THE SCUPOL 850 μm POLARIZATION DATA CATALOG

We present an extensive analysis of the 850 μm polarization maps of the SCUBA Polarimeter Legacy (SCUPOL) Catalogue produced by Matthews et al., focusing exclusively on the molecular clouds and star-forming regions. For the sufficiently sampled regions, we characterize the depolarization properties and the turbulent-to-mean magnetic field ratio of each region. Similar sets of parameters are calculated from two-dimensional synthetic maps of dust-emission polarization produced with three-dimensional magnetohydrodynamics (MHD) numerical simulations scaled to the S106, OMC-2/3, W49, and DR21 molecular cloud polarization maps. For these specific regions, the turbulent MHD regimes retrieved from the simulations, as described by the turbulent Alfvén and Sonic Mach numbers, are consistent within a factor one to two with the values of the same turbulent regimes estimated from the analysis of Zeeman measurements data provided by Crutcher. Constraints on the values of the inclination angle α of the mean magnetic field with respect to the line of sight are also given. The values obtained from the comparison of the simulations with the SCUPOL data are consistent with the estimates made by using two observational methods provided by other authors. Our main conclusion is that simple, ideal, isothermal, and non-self-gravitating MHD simulations are sufficient in order to describe the large-scale observed physical properties of the envelopes of this set of regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Feedback Controllability Components Analysis (FCCA) v1.0

FCCA is a linear dimensionality reduction method that find subspaces of high-dimensional time-series data that are most feedback controllable. The key innovation is to formulate an objective function that quantifies the joint cost of state reconstruction and state regulation that can be evaluated from purely observational data. To do this, it leverages the duality between controllability and observability. We provide analytic results demonstrating the validity of the cost function. We evaluated this method in both synthetic and real neural data (from multiple organisms and brain areas).

Kumar, Ankit↗