Study proves the difficulty of simulating random quantum circuits for classical computers

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Study proves the difficulty of simulating random quantum circuits for classical computers
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Quantum computers, technologies that perform computations leveraging quantum mechanical phenomena, could eventually outperform classical computers on many complex computational and optimization problems. While some quantum computers have attained remarkable results on some tasks, their advantage over classical computers is yet to be conclusively and consistently demonstrated.

Ramis Movassagh, a researcher at Google Quantum AI, who was formerly at IBM Quantum, recently carried out a theoretical study aimed at mathematically demonstrating the notable advantages of quantum computers. His paper, published in, mathematically shows that simulating random quantum circuits and estimating their outputs is so-called #P-hard for classical computers .

"In 2018 a colleague gave a talk at MIT on, at the time, a recent result which tried to provide evidence for the hardness of random circuit sampling ," Movassagh explained."RCS is the task of sampling from the output of a random quantum circuit and Google had just proposed it as the lead candidate for demonstrating quantum primacy.

"The idea is that you can use the Cayley path proposed in the paper to interpolate between any two arbitrary circuits, which in this case is taken to be between the worst-case and average-case," Movassagh said."Cayley path is a low-degree algebraic function. Since the worst -case is known to be #P hard , using the Cayley path one can interpolate to the average-case and show that the random circuits are essentially as hard as the worst case with high probability.

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