Polynomial speedup in Torontonian calculation by a scalable recursive algorithm
arXiv:2109.04528
Abstract
Evaluating the Torontonian function is a central computational challenge in the simulation of Gaussian Boson Sampling (GBS) with threshold detection. In this work, we propose a recursive algorithm providing a polynomial speedup in the exact calculation of the Torontonian compared to state-of-the-art algorithms. According to our numerical analysis the complexity of the algorithm is proportional to with being the size of the problem. We also show that the recursive algorithm can be scaled up to HPC use cases making feasible the simulation of threshold GBS up to photon clicks without the needs of large-scale computational capacities.
13 pages, 7 pages
References in corpus (8)
- Photonic Boson Sampling in a Tunable Circuit
- Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light
- Experimental Scattershot Boson Sampling
- Quantum computing and the entanglement frontier
- Scalable boson-sampling with time-bin encoding using a loop-based architecture
- The Boundary for Quantum Advantage in Gaussian Boson Sampling
- Benchmarking 50-Photon Gaussian Boson Sampling on the Sunway TaihuLight
- Marginal probabilities in boson samplers with arbitrary input states