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Quantum computers promise to directly simulate systems governed by quantum principles, such as molecules or materials, since the quantum bits themselves are quantum objects. Recent experiments have demonstrated the power of these devices when performing carefully chosen tasks. But a new study shows that for problems of real-world interest, such as calculating the energy states of a cluster of atoms, quantum simulations are no more accurate than those of classical computers [1]. The results offer a benchmark for judging how close quantum computers are to becoming useful tools for chemists and materials scientists.
Richard Feynman proposed the idea of quantum computers in 1982, suggesting they might be used to calculate the properties of quantum matter. Today, quantum processors are available with several hundred quantum bits (qubits), and some can, in principle, represent quantum states that are impossible to encode in any classical device. The 53-qubit Sycamore processor developed by Google has demonstrated the potential to perform calculations in a few days that would take many millennia on current classical computers [2]. But this “quantum advantage” is achieved only for selected computational tasks that play to these devices’ strengths. How well do such quantum computers fare for the sorts of everyday challenges that researchers studying molecules and materials actually wish to solve?
Garnet Chan of the California Institute of Technology and his co-workers set out to answer this question by performing simulations of a molecule and a material using a 53-qubit Google processor called Weber, based on Sycamore. “We did not anticipate learning anything new chemically, given how complex these systems are and how good classical algorithms are,” says Chan. “The goal was to understand how well the Sycamore hardware performs for a physically relevant class of circuits with a physically relevant metric of success.” Read More..
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