Quantum isomer search

@article{Terry2020QuantumIS,
  title={Quantum isomer search},
  author={Jason Patrick Terry and Prosper D Akrobotu and Christian Francisco Andres Negre and Susan M. Mniszewski},
  journal={PLoS ONE},
  year={2020},
  volume={15}
}
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… 

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References

SHOWING 1-10 OF 73 REFERENCES
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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
TLDR
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.
TLDR
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.
...
...