3.3k citations · 6.9k across the 56 of their papers we have counts for
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Learning temporal data with variational quantum recurrent neural network
Yuto Takaki, Kosuke Mitarai, Makoto Negoro +2
We propose a method for learning temporal data using a parametrized quantum circuit. We use the circuit that has a similar structure as the recurrent neural network which is one of…
Quadratic Clifford expansion for efficient benchmarking and initialization of variational quantum algorithms
Kosuke Mitarai, Yasunari Suzuki, Wataru Mizukami +2
Variational quantum algorithms are considered to be appealing applications of near-term quantum computers. However, it has been unclear whether they can outperform classical algori…
Variational Quantum Algorithms
M. Cerezo, Andrew Arrasmith, Ryan Babbush +8
Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers due to the extremely high co…
Qulacs: a fast and versatile quantum circuit simulator for research purpose
Yasunari Suzuki, Yoshiaki Kawase, Yuya Masumura +17
To explore the possibilities of a near-term intermediate-scale quantum algorithm and long-term fault-tolerant quantum computing, a fast and versatile quantum circuit simulator is n…
Deep Variational Quantum Eigensolver: a divide-and-conquer method for solving a larger problem with smaller size quantum computers
Keisuke Fujii, Kaoru Mizuta, Hiroshi Ueda +3
We propose a divide-and-conquer method for the quantum-classical hybrid algorithm to solve larger problems with small-scale quantum computers. Specifically, we concatenate a variat…
Overhead for simulating a non-local channel with local channels by quasiprobability sampling
Kosuke Mitarai, Keisuke Fujii
As the hardware technology for quantum computing advances, its possible applications are actively searched and developed. However, such applications still suffer from the noise on…