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Resource Optimization for Quantum Dynamics with Tensor Networks: Quantum and Classical Algorithms.

Anurag Dwivedi1,2, Miguel Angel Lopez-Ruiz1,2, Srinivasan S Iyengar1,2

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This summary is machine-generated.

This study introduces a tensor network method to efficiently simulate quantum dynamics in complex chemical systems. The approach reduces computational cost and storage, enabling accurate simulations of nuclear motion.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Chemical Physics

Background:

  • Exponential scaling of quantum degrees of freedom poses a major challenge in computational chemistry and quantum dynamics.
  • Simulating the time-evolution of nuclear degrees of freedom in multiconfigurational systems requires significant computational resources.

Purpose of the Study:

  • To develop a tensor network approach for efficient time-evolution of nuclear degrees of freedom in multiconfigurational chemical systems.
  • To present quantum algorithms for the resultant dynamics.
  • To introduce an adaptive regularization algorithm to maintain compression advantages and prevent exponential growth of bond dimensions.

Main Methods:

  • Utilized tensor network decompositions for reduced storage and computational complexity.
  • Developed an adaptive algorithm for regularization of nonphysical bond dimensions.
  • Applied the method to ab initio potentials for a symmetric hydrogen-bonded system (protonated 2,2'-bipyridine).

Main Results:

  • Demonstrated reduced storage and computational complexity for quantum dynamics simulations.
  • Successfully preserved compression advantages through adaptive regularization.
  • The algorithm's performance was validated against exact diagonalization for the chosen chemical system.

Conclusions:

  • The tensor network approach offers a valuable tool for dynamical simulations of nuclear chemical systems.
  • The adaptive regularization algorithm effectively manages bond dimensions, preventing exponential growth.
  • This method provides a more efficient pathway for tackling complex quantum dynamical problems.