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Quantum computing in pharma: A multilayer embedding approach for near future applications.

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Summary
This summary is machine-generated.

This study introduces an automated method for selecting active spaces in quantum chemistry simulations. This approach enhances the accuracy of quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms for complex molecules.

Keywords:
drugsembeddingenzymesphotochemistryquantum computers

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Area of Science:

  • Quantum computing
  • Computational chemistry
  • Quantum algorithms

Background:

  • Quantum computers offer potential for simulating complex chemical systems.
  • Accurate simulation requires careful selection of active orbital spaces.
  • Current quantum methods face limitations in active space size.

Purpose of the Study:

  • To develop an automated scheme for active space selection in quantum chemical simulations.
  • To apply and validate this scheme using quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms.
  • To enable accurate quantum mechanical treatment of strongly correlated chemical systems.

Main Methods:

  • Developed an automated protocol for active space selection based on molecular fragments and perturbation theory.
  • Performed quantum phase estimation (QPE) and variational quantum eigensolver (VQE) calculations.
  • Utilized a subtractive method to incorporate environmental effects.

Main Results:

  • Demonstrated a method for selecting occupied and virtual orbitals for quantum computation.
  • Applied the protocol to F2, [Fe] hydrogenase, and temoporfin.
  • Simulated results show the potential for accurate quantum simulations with optimized active spaces.

Conclusions:

  • The automated active space selection protocol is crucial for efficient quantum simulations.
  • This method is applicable to various quantum algorithms (QPE, VQE) and molecular systems.
  • While quantum advantage is not yet achieved, the protocol scales to larger, classically intractable active spaces.