10 citations · 27 across the 11 of their papers we have counts for
12 papers
CT-bMPS: Approximate Tensor Network Contraction with Boundary MPS on Contraction Trees
Hidetaka Manabe, Feng Pan
We introduce contraction tree boundary matrix product states (CT-bMPS), a scalable approximate contraction method for general closed tensor networks. CT-bMPS represents the boundar…
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…
Sampling hard circuits with verifiably high fidelity
Simon Martiel, Jay-U Chung, Alireza Seif +9
Sampling-based proposals are prominent candidates for demonstrating quantum computations beyond the reach of classical supercomputers. However, it has been difficult to combine the…
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…
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…
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…
Tensor-network decoders for process tensor descriptions of non-Markovian noise
Fumiyoshi Kobayashi, Hidetaka Manabe, Gregory A. L. White +3
Quantum error correction (QEC) is essential for fault-tolerant quantum computation. Often in QEC errors are assumed to be independent and identically distributed and can be discret…
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…
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…
Quantum Circuit Simulation by SGEMM Emulation on Tensor Cores and Automatic Precision Selection
Hiroyuki Ootomo, Hidetaka Manabe, Kenji Harada +1
Quantum circuit simulation provides the foundation for the development of quantum algorithms and the verification of quantum supremacy. Among the various methods for quantum circui…
Entanglement distillation toward minimal bond cut surface in tensor networks
Takato Mori, Hidetaka Manabe, Hiroaki Matsueda
In tensor networks, a geometric operation of pushing a bond cut surface toward a minimal surface corresponds to entanglement distillation. Cutting bonds defines a reduced transitio…
Implicit Regularization in Over-parameterized Neural Networks
Masayoshi Kubo, Ryotaro Banno, Hidetaka Manabe +1
Over-parameterized neural networks generalize well in practice without any explicit regularization. Although it has not been proven yet, empirical evidence suggests that implicit r…