6 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…
Exploiting Translational Symmetry for Quantum Computing with Squeezed Cat Qubits
Tomohiro Shitara, Gabriel Mintzer, Yuuki Tokunaga +1
Translational symmetry plays an essential role in bosonic quantum error correction (QEC), most notably in the Gottesman-Kitaev-Preskill code. Squeezed cat (SC) codes provide a comp…
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…
Non-Markovianity in Quantum Information Processing: Interplay with Quantum Error Mitigation
Suguru Endo, Hideaki Hakoshima, Tomohiro Shitara
Non-Markovian dynamics are typically present in the dynamics of open quantum systems. Despite the rich structure of non-Markovian dynamics, their relevance to quantum information p…
Data-driven adaptive quantum error mitigation for probability distribution
Rion Shimazu, Suguru Endo, Shigeo Hakkaku +1
Quantum error mitigation (QEM) has been proposed as a class of hardware-friendly error suppression techniques. While QEM has been primarily studied for mitigating errors in the est…
Data-Efficient Error Mitigation for Physical and Algorithmic Errors in a Hamiltonian Simulation
Shigeo Hakkaku, Yasunari Suzuki, Yuuki Tokunaga +1
Quantum dynamics simulation via Hamilton simulation algorithms is one of the most crucial applications in the quantum computing field. While this task has been relatively considere…