Encoding-Independent Optimization Problem Formulation for Quantum Computing

TL;DR

This paper introduces a versatile, hardware-agnostic framework for formulating optimization problems in quantum computing, enabling automatic Hamiltonian construction tailored to various hardware platforms.

Contribution

It provides a generalized, encoding-independent approach and a library of optimization problems with derived spin encodings, facilitating automatic Hamiltonian generation.

Findings

Developed an encoding-independent formulation for quantum optimization problems.

Created a library of problems and spin encodings for quantum hardware.

Enabled automatic construction of Hamiltonians for diverse optimization tasks.

Abstract

We present an encoding and hardware-independent formulation of optimization problems for quantum computing. Using this generalized approach, we present an extensive library of optimization problems and their various derived spin encodings. Common building blocks that serve as a construction kit for building these spin Hamiltonians are identified. This paves the way towards a fully automatic construction of Hamiltonians for arbitrary discrete optimization problems. The presented freedom in the problem formulation is a key step for tailoring optimal spin Hamiltonians for different hardware platforms.