RIKEN physicists have put quantum computing and deep learning through their paces and found that they are powerful tools for gleaning insights into new theories of quantum gravity [1]. They could thus help solve one of the most formidable challenges in modern physics—developing a theory of gravity that jives with quantum physics.

When Einstein nutted out his theory of general relativity in 1915, his only tools were pen and paper. The same was true of the pioneers of quantum theory. But the next major breakthrough in theoretical physics could be made with help from emerging technologies such as quantum computers and machine learning, Enrico Rinaldi of RIKEN Theoretical Quantum Physics Laboratory thinks. “I believe these technologies are poised to transform the way we do theoretical physics,” he says.

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  1. Enrico Rinaldi, Xizhi Han, Mohammad Hassan, Yuan Feng, Franco Nori, Michael McGuigan, Masanori Hanada, Matrix-Model Simulations Using Quantum Computing, Deep Learning, and Lattice Monte Carlo, PRX Quantum 3, 010324 (2022), doi: 10.1103/PRXQuantum.3.010324