Quantum isomer search

  title={Quantum isomer search},
  author={Jason Patrick Terry and Prosper D Akrobotu and Christian Francisco Andres Negre and Susan M. Mniszewski},
  journal={PLoS ONE},
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… 

Figures and Tables from this paper

A multi-commodity network model for optimal quantum reversible circuit synthesis
An application of an optimization model for synthesizing quantum circuits with minimum implementation costs to lower the error rates by forming a simpler circuit, which has a unique structure that combines the arc-subset selection problem with a conventional multi-commodity network flow model.
Limitations of existing solvers on many dense graphs as well as those of the Digital Annealer on sparse graphs are demonstrated which opens an avenue to hybridize these approaches.
Leveraging special-purpose hardware for local search heuristics
This work proposes a new meta-heuristic to model local search in the Ising form for the special-purpose hardware devices, and demonstrates that this method takes the limitations of the Ised model and current hardware into account, and utilizes a given hardware more efficiently compared to previous approaches, while also producing high quality solutions compared to other well-known meta- heuristics.
A QUBO formulation for top-τ eigencentrality nodes
The results focus on correctly identifying a given number of the most important nodes in numerous networks given by the sparse vector solution of the quadratic unconstrained binary optimization formulation of the problem of identifying the top-τ highest eigencentrality nodes in a network on both the D-Wave and IBM quantum computers.
A QUBO Formulation for Eigencentrality
This work lays the foundations for the calculation of eigenvector centrality using quantum computational paradigms such as quantum annealing and gate-based quantum computing, reformulated as a quadratic unconstrained binary optimization (QUBO) that can be solved on both quantum architectures.
Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems
The feasibility of a hybrid system with a real hardware prototype using one of the most advanced experimentally available techniques today, reverse quantum annealing is explored, showing approximately 2-10x better performance in terms of processing time than prior published results.
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
The graph neural network optimizer performs on par or outperforms existing solvers, with the ability to scale beyond the state of the art to problems with millions of variables.
Vacancies in graphene: an application of adiabatic quantum optimization.
A simple model is used, compatible with the capability of current quantum annealers, to study the relative stability of graphene vacancy defects, and provides a stepping stone towards applications of quantumAnnealing to problems of physical-chemical interest.
Compressed Quadratization of Higher Order Binary Optimization Problems
This work proves that in Ising space the degree reduction of one term requires the introduction of two variables, which results in a more compact representation of the resultant QUBO problem, which is crucial for utilizing resource-constrained QUBO solvers.


Stochastic Generator of Chemical Structure, 2. Using Simulated Annealing To Search the Space of Constitutional Isomers
  • J. Faulon
  • Computer Science
    J. Chem. Inf. Comput. Sci.
  • 1996
A stochastic algorithm based on the simulated annealing method that searches constitutional isomers with desired properties and is general enough to be used for any class of organic and inorganic compounds, including cyclic and cross-linked structures.
What is the Computational Value of Finite Range Tunneling
It is demonstrated how finite range tunneling can provide considerable computational advantage over classical processors for a crafted problem designed to have tall and narrow energy barriers separating local minima, the D-Wave 2X quantum annealer achieves significant runtime advantages relative to Simulated Annealing.
A Quantum Approximate Optimization Algorithm
A quantum algorithm that produces approximate solutions for combinatorial optimization problems that depends on a positive integer p and the quality of the approximation improves as p is increased, and is studied as applied to MaxCut on regular graphs.
A Tutorial on Formulating QUBO Models
It is shown how many different types of constraints arising in practice can be embodied within the “unconstrained” QUBO formulation in a very natural manner using penalty functions, yielding exact model representations in contrast to the approximate representations produced by customary uses of penalty functions.
A variational eigenvalue solver on a photonic quantum processor
The proposed approach drastically reduces the coherence time requirements and combines this method with a new approach to state preparation based on ansätze and classical optimization, enhancing the potential of quantum resources available today and in the near future.
Detecting multiple communities using quantum annealing on the D-Wave system
It turns out that the problem of detecting at most two communities naturally fits into the architecture of a quantum annealer with almost no need of reformulation.
Quantum annealing for problems with ground-state degeneracy
We study the performance of quantum annealing for systems with ground-state degeneracy by directly solving the Schr?dinger equation for small systems and quantum Monte Carlo simulations for larger
Fully Automated Structure Elucidation - A Spectroscopist's Dream Comes True
SpecSolv, as this program was titled, represents a new module for the multidimensional spectroscopic interpretation system SpecInfo, a self-learning, artificially intelligent system based exclusively on 13C-NMR chemical shift, intensity and multiplicity information which is readily available from 13C -NMR-DEPT spectra.
Generation and enumeration of carbon skeletons
Two different programs were written to enumerate all possible carbon skeletons, i.e., saturated hydrocarbons, and various ways of classifying the data into subsets are illustrated as are superstructure searches from seed skeletons.
Elucidation of Drug Metabolite Structural Isomers Using Molecular Modeling Coupled with Ion Mobility Mass Spectrometry.
The results present that IM-MS and molecular modeling can inform on the identity of drug metabolites and highlight the limitations of this approach in differentiating structural isomers.