One-qubit quantum gates in a circular graphene quantum dot: genetic algorithm approach

Area of Science:

• Quantum Computing
• Condensed Matter Physics
• Materials Science

Background:

• Quantum logic gates are fundamental operations in quantum computing.
• Graphene quantum dots offer a promising platform for qubit implementation due to their unique electronic properties.
• Controlling qubit states with high fidelity is essential for building scalable quantum computers.

Purpose of the Study:

• To design and control quantum logic gates (σx, σy, σz) for a one-charge-qubit system.
• To utilize circular graphene quantum dots within a homogeneous magnetic field as the qubit space.
• To optimize gate parameters using a genetic algorithm (GA).

Main Methods:

• Implementation of quantum gates through dynamic control of the qubit subspace.
• Application of an oscillating electric field and a modulated gate voltage pulse.
• Parameter optimization via a genetic algorithm (GA) for amplitude and time width modulation.

Main Results:

• Achieved high gate fidelity values, approaching 1, for σx, σy, and σz gates.
• Successfully avoided leakage to higher energy states during gate operations.
• Demonstrated system evolution through probability density dynamics and pseudospin current visualization.

Conclusions:

• Graphene quantum dot states are suitable for designing and controlling qubit subspaces.
• The combination of electric field and gate voltage pulses enables optimal parameter selection.
• Genetic algorithm optimization is effective for achieving high fidelity quantum gates in graphene quantum dots.