3.3k citations · 6.9k across the 56 of their papers we have counts for
14 papers · 2 filters
Quantum Kernel t-Distributed Stochastic Neighbor Embedding
Yoshiaki Kawase, Kosuke Mitarai, Keisuke Fujii
Data visualization is important in understanding the characteristics of data that are difficult to see directly. It is used to visualize loss landscapes and optimization trajectori…
End-to-end complexity for simulating the Schwinger model on quantum computers
Kazuki Sakamoto, Hayata Morisaki, Junichi Haruna +3
The Schwinger model is one of the simplest gauge theories. It is known that a topological term of the model leads to the infamous sign problem in the classical Monte Carlo method.…
Continuous optimization by quantum adaptive distribution search
Kohei Morimoto, Yusuke Takase, Kosuke Mitarai +1
In this paper, we introduce the quantum adaptive distribution search (QuADS), a quantum continuous optimization algorithm that integrates Grover adaptive search (GAS) with the cova…
Quantum Circuit Unoptimization
Yusei Mori, Hideaki Hakoshima, Kyohei Sudo +3
Optimization of circuits is an essential task for both quantum and classical computers to improve their efficiency. In contrast, classical logic optimization is known to be difficu…
Classical variational optimization of PREPARE circuit for quantum phase estimation of quantum chemistry Hamiltonians
Hayata Morisaki, Kosuke Mitarai, Keisuke Fujii +1
We propose a method for constructing circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of q…
Algorithmic error mitigation for quantum eigenvalues estimation
Adam Siegel, Kosuke Mitarai, Keisuke Fujii
When estimating the eigenvalues of a given observable, even fault-tolerant quantum computers will be subject to errors, namely algorithmic errors. These stem from approximations in…
Accelerating Grover Adaptive Search: Qubit and Gate Count Reduction Strategies with Higher-Order Formulations
Yuki Sano, Kosuke Mitarai, Naoki Yamamoto +1
Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. In this paper, we propose higher-order binary formulations tha…
A comprehensive survey on quantum computer usage: How many qubits are employed for what purposes?
Tsubasa Ichikawa, Hideaki Hakoshima, Koji Inui +18
Quantum computers (QCs), which work based on the law of quantum mechanics, are expected to be faster than classical computers in several computational tasks such as prime factoring…
Experimental demonstration of a high-fidelity virtual two-qubit gate
Akhil Pratap Singh, Kosuke Mitarai, Yasunari Suzuki +4
We experimentally demonstrate a virtual two-qubit gate and characterize it using quantum process tomography~(QPT). The virtual two-qubit gate decomposes an actual two-qubit gate in…
MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ era
Leonardo Placidi, Ryuichiro Hataya, Toshio Mori +4
We introduce the first large-scale dataset, MNISQ, for both the Quantum and the Classical Machine Learning community during the Noisy Intermediate-Scale Quantum era. MNISQ consists…
QAOA-MC: Markov chain Monte Carlo enhanced by Quantum Alternating Operator Ansatz
Yuichiro Nakano, Hideaki Hakoshima, Kosuke Mitarai +1
Quantum computation is expected to accelerate certain computational task over classical counterpart. Its most primitive advantage is its ability to sample from classically intracta…
Quantum-Selected Configuration Interaction: classical diagonalization of Hamiltonians in subspaces selected by quantum computers
Keita Kanno, Masaya Kohda, Ryosuke Imai +4
We propose quantum-selected configuration interaction (QSCI), a class of hybrid quantum-classical algorithms for calculating the ground- and excited-state energies of many-electron…
VQE-generated quantum circuit dataset for machine learning
Akimoto Nakayama, Kosuke Mitarai, Leonardo Placidi +2
Quantum machine learning has the potential to computationally outperform classical machine learning, but it is not yet clear whether it will actually be valuable for practical prob…
Almost optimal measurement scheduling of molecular Hamiltonian via finite projective plane
Wataru Inoue, Koki Aoyama, Yusuke Teranishi +3
We propose an efficient and almost optimal scheme for measuring molecular Hamiltonians in quantum chemistry on quantum computers, which requires distinct measurements in the…