Algorithmic approaches to avoiding bad local minima in nonconvex inconsistent feasibility
Thi Lan Dinh, Wiebke Bennecke, G. S. Matthijs Jansen, D. Russell Luke, Stefan Mathias · arXiv (Cornell University) · 2025
This dataset contains the simulated and experimental input data for 3D photoemission orbital tomography reconstructions using the ProxPython framework, as presented in the publication "Algorithmic approaches to avoiding bad local minima in nonconvex inconsistent feasibility" (JOTA, 2026). The dataset includes: - Simulated ARPES momentum-space intensity distributions for test orbitals. - Experimental photoemission data, spatial masks, and real-space support constraints. Usage: To use this data with ProxPython, place the downloaded files into the `ot3d_proxtoolbox/` directory and run the demo scripts using Python 3.9+.