Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>This is the second of a series of three papers that present a methodology with the aim of creating a set of maps of the coronal density over a period of many years. This paper describes a method for reconstructing the coronal electron density based on spherical harmonics. By assuming a radial structure to the corona at the height of interest, line-of-sight integrations can be made individually on each harmonic basis prior to determining coefficients, i.e., the computationally expensive integrations are calculated only once during initialization. This approach reduces the problem to finding the set of coefficients that best match the observed brightness using a regularized least-squares approach and is very efficient. The method is demonstrated on synthetic data created from both a simple and an intricate coronal density model. The quality of reconstruction is found to be reasonable in the presence of noise and large gaps in the data. The method is applied to both Large Angle and Spectrometric Coronagraph Experiment C2 and <jats:italic>Solar</jats:italic> <jats:italic>Terrestrial Relations Observatory</jats:italic> Cor2 coronagraph observations from 2009 March 20, and the results from both spacecraft compared. Future work will apply the method to large data sets.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Geodetic/astrometric very long baseline interferometry (VLBI) has been routinely observing using various global networks for 40 yr, and it has produced more than 10 million baseline group delay, phase, and amplitude observables. These group delay observables are analyzed worldwide for geodetic and astrometric applications, for instance, to create the International Celestial Reference Frame (ICRF). The phase and amplitude observables are used in this paper, by means of closure analysis, to study intrinsic source structures and their evolution over time. The closure amplitude rms, CARMS, indicating how far away a source is from being compact in terms of morphology, is calculated for each individual source. The overall structure-effect magnitudes for 3417 ICRF radio sources are quantified. CARMS values larger than 0.3 suggest significant source structures and those larger than 0.4 indicate very extended source structures. The 30 most frequently observed sources, which constitute 40% of current geodetic VLBI observables, are studied in detail. The quality of ICRF sources for astrometry is evaluated by examining the CARMS values. It is confirmed that sources with CARMS values larger than 0.30 can contribute residual errors of about 15 ps to geodetic VLBI data analysis and those with the CARMS values larger than 0.4 generally can contribute more than 20 ps. We recommend CARMS values as an indicator of the astrometric quality for the ICRF sources and the continuous monitoring of the ICRF sources to update CARMS values with new VLBI observations as they become available.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In this paper, we present a curated data set from the NASA <jats:italic>Solar Dynamics Observatory</jats:italic> (<jats:italic>SDO</jats:italic>) mission in a format suitable for machine-learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, down-sampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We illustrate the use of this data set with two example applications: forecasting future extreme ultraviolet (EUV) Variability Experiment (EVE) irradiance from present EVE irradiance and translating Helioseismic and Magnetic Imager observations into Atmospheric Imaging Assembly observations. For each application, we provide metrics and baselines for future model comparison. We anticipate this curated data set will facilitate machine-learning research in heliophysics and the physical sciences generally, increasing the scientific return of the <jats:italic>SDO</jats:italic> mission. This work is a direct result of the 2018 NASA Frontier Development Laboratory Program. Please see the Appendix for access to the data set, totaling 6.5TBs.</jats:p>