TRAVOLTA: GPU acceleration and algorithmic improvements for constructing quantum optimal control fields in photo-excited systems

The TRAVOLTA software package is a significant overhaul of our previous NIC-CAGE algorithm and also includes algorithmic improvements to the gradient ascent procedure to enable faster convergence.

We examine three different variants of GPU parallelization to assess their performance in constructing optimal control fields in a variety of quantum systems. In addition, we provide several examples with extensive benchmarks of our GPU-enhanced TRAVOLTA code to show that it generates the same results as previous CPU-based algorithms but with a speedup that is more than ten times faster. Our GPU enhancements and algorithmic improvements enable large quantum optimal control calculations that can be efficiently and routinely executed on modern multi-core computational hardware.