Quantum Isomer Search
arXiv:1908.00542 · doi:10.1371/journal.pone.0226787
Abstract
Isomer search or molecule enumeration refers to the problem of finding all the isomers for a given molecule. Many classical search methods have been developed in order to tackle this problem. However, the availability of quantum computing architectures has given us the opportunity to address this problem with new (quantum) techniques. This paper describes a quantum isomer search procedure for determining all the structural isomers of alkanes. We first formulate the structural isomer search problem as a quadratic unconstrained binary optimization (QUBO) problem. The QUBO formulation is for general use on either annealing or gate-based quantum computers. We use the D-Wave quantum annealer to enumerate all structural isomers of all alkanes with fewer carbon atoms (n < 10) than Decane (C10H22). The number of isomer solutions increases with the number of carbon atoms. We find that the sampling time needed to identify all solutions scales linearly with the number of carbon atoms in the alkane. We probe the problem further by employing reverse annealing as well as a perturbed QUBO Hamiltonian and find that the combination of these two methods significantly reduces the number of samples required to find all isomers.
20 pages, 9 figures
References in corpus (11)
- A variational eigenvalue solver on a quantum processor
- Ising formulations of many NP problems
- A Quantum Approximate Optimization Algorithm
- Subspace-search variational quantum eigensolver for excited states
- What is the Computational Value of Finite Range Tunneling?
- Exact Ising model simulation on a quantum computer
- Quantum annealing correction for random Ising problems
- Detecting Multiple Communities Using Quantum Annealing on the D-Wave System
- Next-Generation Topology of D-Wave Quantum Processors
- Quantum-Assisted Genetic Algorithm
- Ground-state statistics from annealing algorithms: Quantum vs classical approaches
Cited by in corpus (6)
- Combinatorial Optimization with Physics-Inspired Graph Neural Networks
- Multilevel Combinatorial Optimization Across Quantum Architectures
- Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems
- Vacancies in graphene: an application of adiabatic quantum optimization
- A QUBO formulation for top- eigencentrality nodes
- Computing Canonical Averages with Quantum and Classical Optimizers: Thermodynamic Reweighting for QUBO Models of Physical Systems