activity
20242026
collaborators

7 papers

quant-ph2026

Classical Simulation and Design Frontiers for IBM's Doped Clifford Sampling Experiment

Hidetaka Manabe, Hanfeng Gu, Feng Pan

We classically simulate the IBM doped Clifford random circuit sampling experiment, comprising qubits, entangling layers, and inserted gates. A deterministic tem…

quant-ph2025

Tensor Network Formulation of Dequantized Algorithms for Ground State Energy Estimation

Hidetaka Manabe, Takanori Sugimoto, Keisuke Fujii

Verifying quantum advantage for practical problems, particularly the ground state energy estimation (GSEE) problem, is one of the central challenges in quantum computing theory. Fo…

quant-ph2025

The State Preparation of Multivariate Normal Distributions using Tree Tensor Network

Hidetaka Manabe, Yuichi Sano

The quantum state preparation of probability distributions is an important subroutine for many quantum algorithms. When embedding -dimensional multivariate probability distribut…

quant-ph2025

TTNOpt: Tree tensor network package for high-rank tensor compression

Ryo Watanabe, Hidetaka Manabe, Toshiya Hikihara +1

We have developed TTNOpt, a software package that utilizes tree tensor networks (TTNs) for quantum spin systems and high-dimensional data analysis. TTNOpt provides efficient and po…

quant-ph2025

Learning functions of Hamiltonians with Hamiltonian Fourier features

Yuto Morohoshi, Akimoto Nakayama, Hidetaka Manabe +1

We propose a quantum machine learning task that is provably easy for quantum computers and arguably hard for classical ones. The task involves predicting quantities of the form $\m…

quant-ph2025

Efficient Simulation of Leakage Errors in Quantum Error Correcting Codes Using Tensor Network Methods

Hidetaka Manabe, Yasunari Suzuki, Andrew S. Darmawan

Leakage errors, in which a qubit is excited to a level outside the qubit subspace, represent a significant obstacle in the development of robust quantum computers. We present a com…