QUBO.jl: A Julia Ecosystem for Quadratic Unconstrained Binary Optimization

TL;DR

QUBO.jl is a comprehensive Julia package that facilitates conversion, modeling, and interfacing of quadratic unconstrained binary optimization problems with various quantum and classical hardware platforms.

Contribution

It introduces a Julia-based ecosystem that seamlessly converts JuMP problems into QUBO format and interfaces with multiple hardware solutions, enhancing optimization workflows.

Findings

Supports a wide range of hardware platforms

Enables straightforward conversion from JuMP problems to QUBO

Provides an end-to-end workflow for optimization and analysis

Abstract

We present QUBO.jl, an end-to-end Julia package for working with QUBO (Quadratic Unconstrained Binary Optimization) instances. This tool aims to convert a broad range of JuMP problems for straightforward application in many physics and physics-inspired solution methods whose standard optimization form is equivalent to the QUBO. These methods include quantum annealing, quantum gate-circuit optimization algorithms (Quantum Optimization Alternating Ansatz, Variational Quantum Eigensolver), other hardware-accelerated platforms, such as Coherent Ising Machines and Simulated Bifurcation Machines, and more traditional methods such as simulated annealing. Besides working with reformulations, QUBO.jl allows its users to interface with the aforementioned hardware, sending QUBO models in various file formats and retrieving results for subsequent analysis. QUBO.jl was written as a JuMP / MathOptInterface (MOI) layer that automatically maps between the input and output frames, thus providing a smooth modeling experience.