With the advent of real quantum computer (QC) simulations with demonstrated quantum supremacy, it is expected that many materials systems, beyond the hydrogen molecule, will become possible for the first time. Although QC can reshape the landscape of molecular/materials simulations, many issues of QC related to the decoherence time or
quantum gate depth of existing algorithms preclude purely quantum algorithms from being applied to realistic size systems. To overcome these limitations new approaches, which combine the maturity of conventional computing with the power of quantum hardware (hybrid-QC), are being developed. In this collection in Materials Theory, we are accepting manuscripts that focus on the development and use of QC and hybrid-QC algorithms for materials modeling. Topics of interest include, but are not limited to, techniques such as down-folding to reduce the complexity of many-body Hamiltonians, domain decomposition/embedding methods, the use of ML to improve the use of NISQ (Noisy Intermediate-Scale Quantum) devices, and application benchmarks and analysis of algorithms for QC. We are also interested manuscripts focused on long term challenges, especially related to new methods for simulating ground and excited state Hamiltonians for materials systems on hybrid quantum/classical hardware.
Topics in this collection might include, but are not limited to:
- QC and hybrid-QC algorithms for materials modeling
- Down-folding many-body Hamiltonians
- Domain decomposition/embedding methods
- Benchmarks and analysis of algorithms for QC
1 June 2021
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