9 papers
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…
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…
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…
Efficient Quantum Circuit Construction of Controlled Time-Evolution for Arbitrary Pauli-Sum Hamiltonians
Shintaro Fujiwara, Naoki Yamamoto, Naoki Ishikawa
Controlled time-evolution circuits select forward or backward Hamiltonian time evolution according to the state of an ancilla qubit. They are fundamental building blocks in quantum…
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…
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…