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Mapping Quantum Chemical Dynamics Problems to Spin-Lattice Simulators.

Debadrita Saha1, Srinivasan S Iyengar1, Philip Richerme2

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This study introduces a new quantum computing framework to solve complex quantum chemical nuclear dynamics problems. It maps these dynamics to quantum spin-lattice simulators, enabling more accurate computational chemistry for health and environmental applications.

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Area of Science:

  • Quantum Computing
  • Computational Chemistry
  • Quantum Mechanics

Background:

  • Accurate computational determination of chemical, materials, biological, and atmospheric properties is crucial for health and environmental issues.
  • Current quantum mechanical methods face limitations due to steep computational scaling, particularly in electron correlation, nuclear dynamics, and molecular flexibility.
  • Existing quantum hardware applications for chemistry have primarily addressed electron correlation.

Purpose of the Study:

  • To develop a novel framework for solving quantum chemical nuclear dynamics problems.
  • To enable the application of quantum spin-lattice simulators to nuclear dynamics.
  • To overcome the computational scaling limitations of traditional quantum mechanical methods.

Main Methods:

  • Mapping quantum chemical nuclear dynamics to quantum spin-lattice simulators.
  • Constructing a Hamiltonian for nuclear degrees of freedom on a Born-Oppenheimer surface for a hydrogen-bonded system.
  • Transforming the molecular Hamiltonian to a generalized Ising model Hamiltonian.
  • Determining local fields and spin-spin couplings for Hamiltonian matching.
  • Developing a protocol to extract Ising Hamiltonian parameters from potential energy surfaces and kinetic energy operators.

Main Results:

  • A framework enabling the solution of quantum chemical nuclear dynamics via quantum spin-lattice simulators was established.
  • A method to transform molecular nuclear dynamics problems into generalized Ising models was demonstrated.
  • A protocol for parameter extraction from quantum chemical data for the Ising model was described.

Conclusions:

  • This approach offers a paradigm shift in studying quantum nuclear dynamics.
  • It opens possibilities for solving both electronic structure and nuclear dynamics using quantum computing systems.
  • The framework has the potential to significantly advance computational chemistry and its applications.