python-repository-hub / cvqe

Quantum snake algorithm: Collective variational quantum eigensolvers for quantum chemistry

Quantum snake algorithm:

• This is the source code for the paper:

Dan-Bo Zhang and Tao Yin, Collective optimization for variational quantum eigensolvers, Phys. Rev. A 101, 032311(2020). (arXiv: 1910.14030)

Collective variational quantum eigensolvers (CVQE) for quantum chemistry

We propose a hybrid quantum-classical algorithm that can provide collective optimization for the VQE to solve a group of related Hamiltonians more efficiently.

A brief introduction for VQE can be found in QuContractor's github repository.

Simulate molecules with varied bond lengths

We simulated different molecules (H2, LiH, HeH+) with CVQE. Numeral simulations show that the CVQE exhibits clear collective behavior in the optimization process of updating parameters.

The numerical simulations are mostly performed by using the Huawei HiQ simulator framework.

• The calculation for H2 can be found in CVQE_H2, and CVQE_H2 with IBM Qiskit
• The calculation for LiH can be found in CVQE_LiH
• The calculation for HeH+ can be found in CVQE_HeH+

Avoid local minimum

The snake algorithm gives rise to collective motion of parameters of different tasks that can avoid being trapped in local minimums.

The example with H2 can be found in CVQE_H2.

Cite:

@article{PhysRevA.101.032311, title = {Collective optimization for variational quantum eigensolvers}, author = {Zhang, Dan-Bo and Yin, Tao}, journal = {Phys. Rev. A}, volume = {101}, issue = {3}, pages = {032311}, numpages = {8}, year = {2020}, month = {Mar}, publisher = {American Physical Society}, doi = {10.1103/PhysRevA.101.032311}, url = {https://link.aps.org/doi/10.1103/PhysRevA.101.032311} }