Addressing hard classical problems with Adiabatically Assisted Variational Quantum Eigensolvers

Abstract

We present a hybrid classical-quantum algorithm to solve optimization problems in current quantum computers, whose basic idea is to assist variational quantum eigensolvers (VQE) with adiabatic change of the Hamiltonian. The rational for this new algorithm is to circumvent the problem of facing very small gradients in the classical optimization piece of a VQE, while being able to run in current hardware efficient devices. A discrete concatenation of VQEs adapted to interpolating Hamiltonians provides a method to keep the quantum state always close to a path faithfully directed to find the final solution. We benchmark this Adiabatically Assisted Variational Quantum Eigensolver (AAVQE) on quantum Hamiltonians and hard classical problems, for which our approach shows fast convergence.

7 pages, 8 figures

Cited by in corpus (18)

• Noisy intermediate-scale quantum (NISQ) algorithms
• Quantum computational chemistry
• Variational Fast Forwarding for Quantum Simulation Beyond the Coherence Time
• Variational algorithms for linear algebra
• Variational Quantum State Eigensolver
• Qibo: a framework for quantum simulation with hardware acceleration
• Filtering variational quantum algorithms for combinatorial optimization
• Quantum Singular Value Decomposer
• Quantum variational optimization: The role of entanglement and problem hardness
• Low depth mechanisms for quantum optimization
• Variational Quantum Classifiers Through the Lens of the Hessian
• Improving the variational quantum eigensolver using variational adiabatic quantum computing
• An application benchmark for fermionic quantum simulations
• Evaluation of Parameterized Quantum Circuits with Cross-Resonance Pulse-Driven Entanglers
• Variational Quantum Eigensolver for SU($N$) Fermions
• Qibolab: an open-source hybrid quantum operating system
• Sequence of penalties method to study excited states using VQE
• Hot-Start Optimization for Variational Quantum Eigensolver