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Quantum expectation-value estimation by computational basis sampling
Masaya Kohda, Ryosuke Imai, Keita Kanno +3
Measuring expectation values of observables is an essential ingredient in variational quantum algorithms. A practical obstacle is the necessity of a large number of measurements fo…
Quantifying fermionic nonlinearity of quantum circuits
Shigeo Hakkaku, Yuichiro Tashima, Kosuke Mitarai +2
Variational quantum algorithms (VQAs) have been proposed as one of the most promising approaches to demonstrate quantum advantage on noisy intermediate-scale quantum (NISQ) devices…
Quantum tangent kernel
Norihito Shirai, Kenji Kubo, Kosuke Mitarai +1
Quantum kernel method is one of the key approaches to quantum machine learning, which has the advantages that it does not require optimization and has theoretical simplicity. By vi…
Parent Hamiltonian as a benchmark problem for variational quantum eigensolvers
Fumiyoshi Kobayashi, Kosuke Mitarai, Keisuke Fujii
Variational quantum eigensolver (VQE), which attracts attention as a promising application of noisy intermediate-scale quantum devices, finds a ground state of a given Hamiltonian…
Nonlinear transformation of complex amplitudes via quantum singular value transformation
Naixu Guo, Kosuke Mitarai, Keisuke Fujii
Due to the linearity of quantum operations, it is not straightforward to implement nonlinear transformations on a quantum computer, making some practical tasks like a neural networ…
Sampling-based quasiprobability simulation for fault-tolerant quantum error correction on the surface codes under coherent noise
Shigeo Hakkaku, Kosuke Mitarai, Keisuke Fujii
We propose a sampling-based simulation for fault-tolerant quantum error correction under coherent noise. A mixture of incoherent and coherent noise, possibly due to over-rotation,…