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Dynamical Uncertainty Propagation with Noisy Quantum Parameters.

Mogens Dalgaard1, Carrie A Weidner1, Felix Motzoi2

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This study introduces a faster method for simulating quantum dynamics, overcoming limitations of Monte Carlo sampling. The new approach efficiently reveals how experimental uncertainties impact quantum systems.

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Area of Science:

  • Quantum physics
  • Computational science

Background:

  • Quantum technologies require high-precision dynamics.
  • Experimental uncertainties affect quantum system behavior.
  • Monte Carlo sampling is a common but computationally expensive method to assess uncertainty effects.

Purpose of the Study:

  • To develop a more efficient method for simulating quantum dynamics under uncertainty.
  • To provide insights into the impact of individual uncertainty parameters on quantum systems.
  • To compare the new method with experimental results from quantum computers.

Main Methods:

  • Incorporating propagation of uncertainty directly into quantum dynamics simulations.
  • Developing a novel computational approach to analyze uncertainty effects.
  • Validating the method using experimental data from IBM quantum computers.

Main Results:

  • The new method is orders of magnitude faster than traditional Monte Carlo simulations.
  • The approach directly quantifies the influence of each uncertainty parameter on system dynamics.
  • The simulation results show good agreement with experimental data.

Conclusions:

  • The developed method offers a significant speedup for simulating quantum dynamics with uncertainties.
  • This technique provides a more direct understanding of uncertainty impacts in quantum systems.
  • The findings are relevant for advancing the precision and reliability of quantum technologies.