Performing simulations of quantum systems on an ordinary computer is fundamentally difficult. The resources required to track the state of a quantum system grow exponentially with the size of the system. Therefore, even modest-sized simulations can exceed the capacity of the largest supercomputers. In 1982, Richard Feynman proposed using a controllable quantum system as the computer, so that the quantum mechanics of the machine itself performs the computation [1]. This proposal has grown into a worldwide effort to build quantum computers made up of large numbers of quantum bits, or qubits. But simulating fundamental physics poses a special challenge, as the two classes of particles—fermions and bosons—map to qubits in distinctly different ways. A new theoretical proposal by Eleanor Crane from MIT and colleagues describes a hybrid approach in which the components of the hardware match the fermions and bosons that are being simulated [2]. The researchers model the performance of this hybrid computer for a specific problem in particle physics, and they find that this strategy could perform better than traditional architectures that contain only qubits.
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