SSVQE-BLFQ public repository

WQ 06/26/2022

About

The Subspace-search variational quantum eigensolver (SSVQE) algorithm is a recently proposed VQE variant that enables finding the full hadronic spectroscopy in nuclear physics. The algorithm is described in Subspace-search variational quantum eigensolver for excited states

This repository contains source code implementation of SSVQE using Qiskit and application demos on using SSVQE to solve hadronic observables in nuclear physics. See a recent paper in Solving hadron structures using the basis light-front quantization approach on quantum computers

Demos

• SSVQE optimizations: demo_ssvqe_basic.ipynb
• SSVQE BLFQ observables: demo_ssvqe_blfq_observables.ipynb

Installation Tips

1. For Qiskit installation, follow the official guide. Be sure to install both qiskit and qiskit[visualization]. Usually, it is recommended to install Python libraries in a virtual environment.

2. To use Qiskit for physical problems, install qiskit[nature]; see official doc

3. To use Qiskit for optimization such as VQE, install qiskit[optimization]; see official doc

4. Related tutorials on Qiskit Nature and Optimization: Qiskit nature tutorials, Qiskit optimization tutorials  

5. Another competing algorithm, such as the VQD approach (arXiv:2002.11724), has already been implemented in Qiskit. See tutorial