An Application of Pontryagin Neural Networks to Solve Optimal Quantum
Control Problems
- URL: http://arxiv.org/abs/2302.09143v1
- Date: Wed, 1 Feb 2023 17:48:07 GMT
- Title: An Application of Pontryagin Neural Networks to Solve Optimal Quantum
Control Problems
- Authors: Nahid Binandeh Dehaghani and A. Pedro Aguiar
- Abstract summary: Pontryagin maximum principle has proved to play an important role to achieve the maximum fidelity in an optimum time or energy.
We formulate a control constrained optimal control problem where we aim to minimize time and also energy subjected to a quantum system satisfying the bilinear Schrodinger equation.
We make use of the so-called "qutip" package in python, and the newly developed "tfc" python package.
- Score: 1.5469452301122175
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Reliable high-fidelity quantum state transformation has always been
considered as an inseparable part of quantum information processing. In this
regard, Pontryagin maximum principle has proved to play an important role to
achieve the maximum fidelity in an optimum time or energy. Motivated by this,
in this work, we formulate a control constrained optimal control problem where
we aim to minimize time and also energy subjected to a quantum system
satisfying the bilinear Schrodinger equation. We derive the first order
optimality conditions through the application of Pontryagin Maximum (minimum)
Principle, which results in a boundary value problem. Next, in order to obtain
efficient numerical results, we exploit a particular family of physics-informed
neural networks that are specifically designed to tackle the indirect method
based on the Maximum Principle of Pontryagin. This method has not yet been
studied in the quantum context, but it can significantly speed up the process.
To this end, we first obtain a set of relations which finally let us compute
the optimal control strategy to determine the time- and energy-optimal protocol
driving a general initial state to a target state by a quantum Hamiltonian with
bounded control. We make use of the so-called "qutip" package in python, and
the newly developed "tfc" python package.
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