25 citations · 89 across the 20 of their papers we have counts for
21 papers
Copy-scarce learning of ground states
Kaito Wada, Nobuyuki Yoshioka
Probing multiple properties of ground states is central to understanding quantum matter, yet conventional readout can be prohibitively costly because it consumes many independently…
Provably Efficient Learning of Fermionic Correlations under Particle-Number Symmetry
Yuki Koizumi, Kaito Wada, Toshinori P. Takama +1
Predicting local fermionic correlations is a central task in quantum many-body physics, as these correlations encode many physically relevant local observables. The ubiquitous part…
Adaptive identification of low-degree polynomials in quantum singular value transformation: application to nonlinear quantum properties estimation
Jumpei Kato, Akira Tanji, Hiroyuki Harada +3
Estimating properties of unknown quantum states via quantum singular value transformation (QSVT) often requires high-degree polynomials to handle small eigenvalues of density matri…
Learning Enables Exponential-to-Polynomial Sampling Overhead Scaling in Quantum Divide-and-Conquer for Tree-Structured Circuits
Hiroyuki Harada, Kaito Wada, Naoki Yamamoto +1
Quantum circuit cutting and knitting are divide-and-conquer methods that enable large-scale quantum computations on hardware with limited qubit resources and connectivity by decomp…
Trade-offs between Quantum and Classical Resources in the Linear Combination of Unitaries
Kaito Wada, Hiroyuki Harada, Yasunari Suzuki +3
The randomized linear combination of unitaries (LCU) method with many applications to early fault-tolerant quantum computing algorithms has been proposed. This quantum algorithm co…
State-to-Hamiltonian conversion with a few copies
Kaito Wada, Jumpei Kato, Hiroyuki Harada +1
Density matrix exponentiation (DME) is a general procedure that converts an unknown quantum state into the Hamiltonian evolution. This enables state-dependent operations and can re…
Near-Heisenberg-limited parallel amplitude estimation with logarithmic depth circuit
Kohei Oshio, Kaito Wada, Naoki Yamamoto
Quantum amplitude estimation is one of the core subroutines in quantum algorithms. This paper gives a parallelized amplitude estimation (PAE) algorithm that simultaneously achieves…
Quantum phase estimation based filtering: performance analysis and application to low-energy spectral calculation
Rei Sakuma, Kaito Wada, Shu Kanno +5
Filtering is an important technique in quantum computing used for isolating or enhancing some specific states of quantum many-body systems. In this paper, we analyze the performanc…
Comprehensive Study on Heisenberg-limited Quantum Algorithms for Multiple Observables Estimation
Yuki Koizumi, Kaito Wada, Wataru Mizukami +1
In the accompanying paper of arXiv:2505.00697, we have presented a generalized scheme of adaptive quantum gradient estimation (QGE) algorithm, and further proposed two practical va…
Faster Quantum Algorithm for Multiple Observables Estimation in Fermionic Problems
Yuki Koizumi, Kaito Wada, Wataru Mizukami +1
Achieving quantum advantage in efficiently estimating collective properties of quantum many-body systems remains a fundamental goal in quantum computing. While the quantum gradient…
Exponentially accurate open quantum simulation via randomized dissipation with minimal ancilla
Jumpei Kato, Kaito Wada, Kosuke Ito +1
Simulating open quantum systems is an essential technique for understanding complex physical phenomena and advancing quantum technologies. Some quantum algorithms simulate Lindblad…
Optimizing a parameterized controlled gate using Free Quaternion Selection
Hiroyoshi Kurogi, Katsuhiro Endo, Yuki Sato +6
In variational quantum algorithms, parameterization is typically applied to single-qubit gates.In this study, we instead parameterize a generalized controlled gate and propose an a…
Heisenberg-limited adaptive gradient estimation for multiple observables
Kaito Wada, Naoki Yamamoto, Nobuyuki Yoshioka
In quantum mechanics, measuring the expectation value of a general observable has an inherent statistical uncertainty that is quantified by variance or mean squared error of measur…
Adaptive measurement strategy for noisy quantum amplitude estimation with variational quantum circuits
Kohei Oshio, Yohichi Suzuki, Kaito Wada +3
In quantum computation, amplitude estimation is a fundamental subroutine that is utilized in various quantum algorithms. A general important task of such estimation problems is to…
Quantum conjugate gradient method using the positive-side quantum eigenvalue transformation
Kiichiro Toyoizumi, Kaito Wada, Naoki Yamamoto +1
Quantum algorithms are still challenging to solve linear systems of equations on real devices. This challenge arises from the need for deep circuits and numerous ancilla qubits. We…
Optimal Parameter Configurations for Sequential Optimization of Variational Quantum Eigensolver
Katsuhiro Endo, Yuki Sato, Rudy Raymond +3
Variational Quantum Eigensolver (VQE) is a hybrid algorithm for finding the minimum eigenvalue/vector of a given Hamiltonian by optimizing a parametrized quantum circuit (PQC) usin…
Doubly optimal parallel wire cutting without ancilla qubits
Hiroyuki Harada, Kaito Wada, Naoki Yamamoto
A restriction in the quality and quantity of available qubits presents a substantial obstacle to the application of near-term and early fault-tolerant quantum computers in practica…
Variational quantum algorithm for generalized eigenvalue problems and its application to the finite element method
Yuki Sato, Hiroshi C. Watanabe, Rudy Raymond +5
Generalized eigenvalue problems (GEPs) play an important role in the variety of fields including engineering, machine learning and quantum chemistry. Especially, many problems in t…
Quantum-enhanced mean value estimation via adaptive measurement
Kaito Wada, Kazuma Fukuchi, Naoki Yamamoto
Quantum-enhanced (i.e., higher performance by quantum effects than any classical methods) mean value estimation of observables is a fundamental task in various quantum technologies…
Sequential optimal selection of a single-qubit gate and its relation to barren plateau in parameterized quantum circuits
Kaito Wada, Rudy Raymond, Yuki Sato +1
We propose an algorithm for variational quantum algorithms (VQAs) to optimize the structure of parameterized quantum circuits (PQCs) efficiently. The algorithm optimizes the PQC st…
Simulating Time Evolution with Fully Optimized Single-Qubit Gates on Parameterized Quantum Circuits
Kaito Wada, Rudy Raymond, Yu-ya Ohnishi +4
We propose a novel method to sequentially optimize arbitrary single-qubit gates in parameterized quantum circuits for simulating real and imaginary time evolution. The method utili…