This article introduces a new benchmark called the “V-score,” developed by a team of scientists led by Giuseppe Carleo at EPFL, to help solve complex quantum many-body problems. These problems involve predicting the behavior of large numbers of interacting quantum particles, which is crucial for advancements in fields like chemistry and materials science. The V-score provides a universal method for comparing the accuracy of different computational approaches, including quantum Monte Carlo simulations and tensor networks, by evaluating the energy and energy fluctuations of quantum systems. This benchmark highlights the hardest quantum problems to solve with classical methods, while also identifying areas where emerging technologies like quantum computing could excel. The research, published in Science, paves the way for advancements in quantum simulations and could guide industries such as pharmaceuticals and energy to leverage quantum computing for competitive advantage.
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