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Related Experiment Video

Updated: May 11, 2026

Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots

Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots

Published on: November 1, 2013

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

Gibrán Amparán¹, Fernando Rojas, Antonio Pérez-Garrido

¹Departamento de Física Aplicada, Antiguo Hospital de la Marina, Campo Muralla del Mar, UPCT, Cartagena, 30202, Murcia, Spain. frojas@cnyn.unam.mx.

Nanoscale Research Letters

|May 18, 2013

Summary

Researchers optimized quantum logic gates (σx, σy, σz) for graphene quantum dots using a genetic algorithm (GA). This method achieves high gate fidelity, crucial for quantum computing advancements.

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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.

Related Experiment Videos

Last Updated: May 11, 2026

Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots

Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots

Published on: November 1, 2013

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.