The Payne Zero Project I: Stellar Spectra from Physical Models in Seconds

Modern stellar surveys measure millions of spectra, yet one self-consistent atmosphere and spectrum can require tens of minutes. This cost has motivated grids, spectral emulators, and data-driven models. We present Payne Zero, which reorganizes one-dimensional LTE Kurucz calculations for GPU-native synthesis and multicore atmosphere iteration, and validate it against the original Fortran programs. A 300–1000~nm solar spectrum sampled at \(R_{\rm grid}=300{,}000\) takes about 14~s on an NVIDIA H100 GPU, while the APOGEE 1500–1700~nm interval takes about 1~s. Physical atmosphere iterations take 2–5~s on 16 AMD CPU threads, and learned initializers reduce the iterations required for convergence. Final spectra remain in practical parity across the tested dwarf and giant regimes. These speeds place direct synthesis inside an optimizer without a label-to-flux spectral emulator. We demonstrate direct many-element fitting of reduced APOGEE spectra and recover multi-element abundance trends broadly consistent with the survey catalog. GPU-resident velocity shifts, broadening, line-spread-function convolution, and detector sampling add negligible cost relative to synthesis. The direct-synthesis search takes less than one minute per star on an H100, while atmosphere verification runs independently on multicore CPUs. The same computational graph calibrates more than \(10^5\) oscillator-strength and damping corrections jointly against the Sun and Arcturus in about one minute on an H100. Payne Zero therefore brings direct physical fitting and atomic-data calibration to survey scale. The code is available at this url.