Курс по квантовому машинному обучению
Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.
Simulate and optimize quantum communication networks using quantum computers.
Qiskit implementation of classical shadow formalism with VQE for calculating ground state energies of molecules
Comparative study: Quantum vs. classical models for Cart Pole. Examining entanglement layers and data re-uploading, highlighting quantum model superiority.
An advanced exploration of Quantum Fourier Transform (QFT) using Quantum Machine Learning (QML). This project delves into the optimization of variational quantum circuits, leveraging machine learning techniques to evaluate and visualize the transformation capabilities of QFT in quantum computing.
DDQCL implementation using Qiskit. Variational quantum circuit that maps a randomly generated set of four 4-qubit input states to four 4-qubit output states. Circuit parameters are refined over time to get the lowest cost parameter set.
A demonstration of using variational quantum optimization (VQO) to find a quantum protocol that maximally violates the CHSH inequality.
The code for the article "Certified variational quantum algorithms for eigenstate preparation"
Dissertation for MSc Mathematical and Theoretical Physics at Oxford University: 'Numerical Analysis of Variational Quantum Optimisation Using the Natural Gradient/QFI Technique'
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