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Constraining quantum control field fluence impacts the control landscape topology. Optimal quantum control may require advanced algorithms due to complex landscape features under resource constraints.

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Area of Science:

  • Quantum Control
  • Quantum Dynamics
  • Quantum Information Science

Background:

  • Quantum system control relies on favorable quantum control landscape topology.
  • Resource constraints are inevitable in laboratory settings, necessitating study of their effects.
  • Understanding landscape topology under constraints is crucial for effective quantum control.

Purpose of the Study:

  • To investigate the impact of control field fluence constraints on the quantum control landscape topology.
  • To analyze the effects of these constraints on pure-state population transfer in a two-level system.
  • To identify how resource limitations influence the search for optimal quantum controls.

Main Methods:

  • Numerical simulations were employed to explore the control landscape.
  • The study focused on pure-state population transfer in a two-level quantum system.
  • Optimization involved control field fluence and three phase variables.

Main Results:

  • No local optima were found on the landscape; saddle features were prevalent at low fluence.
  • Global landscape optima were identified in two distinct, disconnected fluence regions.
  • Optimal level set connectivity decreased with more constrained fluence.

Conclusions:

  • Control field fluence constraints significantly alter quantum control landscape topology and features.
  • Complex landscape features arise under resource limitations, challenging optimal control searches.
  • Sophisticated algorithms are needed to efficiently find optimal controls with constrained resources.