Solar energy paper index
Payne4GAIN: NLTE Corrections for Red Giants in Milky Way Mapper using H-Band Neural Network Emulators
One-line summary
A solar energy research paper on Payne4GAIN: NLTE Corrections for Red Giants in Milky Way Mapper using H-Band Neural Network Emulators.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
The majority of spectroscopic surveys assume local thermodynamic equilibrium (LTE) during the modeling of stellar spectra. This assumption begins to break down for luminous stars, like the red giants targeted by SDSS-V's Milky Way Mapper Survey in its Galactic Genesis program. In this work, we present non-LTE (NLTE) abundances for 360,000 red giant stars in Milky Way Mapper DR19, from infrared APOGEE spectra. We generate NLTE spectra using precomputed departure coefficient grids for Na, Mg, Si, Al, Ca, Ti, Mn, and Ni. To fit APOGEE spectra at scale, we train neural network emulators (NNEs) to synthesize LTE and NLTE H-band spectra. After verifying that the NNEs are accurate, we fit the APOGEE spectra with ASPCAP results that fall within the same parameter range as the training data. We find strong NLTE effects on the order of 0.1\,dex for Al, Mn, and Ti, and smaller effects for Si and Ni. We provide a catalog of the results of our LTE and NLTE fits, as well as NLTE-corrected ASPCAP abundances using a polynomial fit correction.
Links and sources
Need this topic turned into a technical roadmap?
Power for Solar can prepare a custom solar energy literature review, simulation code map, dataset map, and B2B photovoltaic technology assessment.
Request B2B research
Comments