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Updated: Sep 8, 2025
06:42
Generation and Coherent Control of Pulsed Quantum Frequency Combs
Published on: June 8, 2018
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Tensor-based quantum phase difference estimation for large-scale demonstration
Shu Kanno1,2, Kenji Sugisaki2,3,4,5, Hajime Nakamura2
1Mitsubishi Chemical Corporation, Science & Innovation Center, Yokohama 227-8502, Japan.
Summary
This study introduces a quantum algorithm for energy calculations, significantly reducing noise and enabling larger quantum computations. It advances quantum computing capabilities on real devices for complex simulations.
Area of Science:
- Quantum Computing
- Computational Chemistry
- Condensed Matter Physics
Background:
- Quantum phase estimation (QPE) is crucial for quantum algorithms but faces limitations on current hardware.
- Noise and qubit count restrict the scale of quantum simulations.
Purpose of the Study:
- To develop an efficient quantum algorithm for energy calculations.
- To enhance the scalability and noise resilience of quantum simulations on superconducting devices.
Main Methods:
- Utilizing a quantum phase difference estimation (QPDE) scheme.
- Employing tensor-network-based unitary compression for state preparation and time-evolution gates.
- Implementing Q-CTRL error suppression modules.
Main Results:
- Demonstrated energy gap calculations for 1D Hubbard models on up to 32 qubits, a five-fold increase over prior QPE.
- Achieved simulations of linear polyenes up to 21 qubits using spatial orbital localization and index sorting.
- Showcased exponential reduction in depolarization noise effects.
Conclusions:
- The QPDE algorithm offers a significant advancement for quantum computing on real devices.
- The method enables larger-scale quantum simulations for condensed matter and molecular systems.
- This work overcomes key limitations of existing quantum algorithms for practical applications.
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