A Photonic Quantum Simulator of Quantum Field Theory and Spin Physics

This NSF award, “A photonic quantum simulator of quantum field theory and spin physics,” will tackle the co-design of specialized quantum computing processors, termed quantum simulators, to solve specific, hard physics problems such as quantum field theory in subatomic physics and quantum magnetism in condensed-matter physics. Quantum computing is set in an ultracompetitive international context, promising deeply disruptive exponential speed-ups of intractable classical tasks such as quantum simulation (whose applications such to nitrogen fixation or superconductivity have societal importance) as well as code-breaking by integer factoring (which directly impacts national security). While quantum computing is now the object of large-scale industrial efforts focused toward commercial applications, academic “blue sky research” remains crucial to explore more easily reachable, specialized, yet powerful quantum machines in the service of the advancement of fundamental science. The co-design effort will consist of conceptualizing quantum photonic circuits, specialized in the implementation of quantum evolution per specific Hamiltonians of interest, as opposed to generic universal quantum gates. This approach is based on recent advances by the PI’s group, generating record-size entanglement in cluster quantum states which constitute complete substrates for measurement-based quantum computing. This large-scale entanglement directly translates into the quantum computing “volume” (number of qubits times circuit depth). The other essential component is the generation of nonlinear (“non-Gaussian”) quantum gates to simulate quantum evolution that is hard to calculate classically, such as the seminal quartic phase gate that describes the self-interaction of the Higgs field in the standard electroweak theory. The PI’s research has shown that a central resource to enable the realization of non-Gaussian gates is photon-number-resolving (PNR) detection, a sophisticated technical resource featured in the PI’s laboratory. Recent results by the PI’s group show that cluster states and PNR detection can be used to form specific quantum optical circuits, driven by a neural network that was trained by reinforcement learning. Such circuits are predicted to generate the desired non-Gaussian quantum gates with success probability rates above 95%, far outperforming all other proposals. This fundamental research on co-designed quantum photonic circuits will pave the way to subsequent implementations at very large scale in integrated “on-chip” photonics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.