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A quantum computing learning platform that integrates Python and machine learning libraries to simulate, program, and run quantum algorithms on real (or in my case simulated) hardware.

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⚛️ My PennyLane Quantum Computing Notes

Welcome to my personal repository for the PennyLane Quantum Computing course! This collection contains my solutions for the exercises found in the PennyLane Codebook.


📂 Repository Structure

The repository is organized based on the modules of the course I completed. Each Python file corresponds to a specific topic.

  • 00_Pennylane_Fundamentals.py: Basic concepts of PennyLane

  • 01_Introduction.py: Introduction to key theoretical concepts such as qubits and quantum circuit construction.

  • 02_Single_Qbit_Gates.py: Exploration of the most important single-qubit gates (X, H, Z), phase gates, rotations (RX, RY) and state preparation.

  • 03_Circuits_With_Many_Qbits.py: Handling multi-qubit systems and controlled gates like CNOT, CZ, SWAP, and Toffoli.

  • 04_Hamiltonian_Evolution.py: Simulation of physical systems, unitaries, Hamiltonians, energy calculation, etc

  • 05_Noicy_Imput.py: Introduction to noisy quantum theory and working with mixed states, operations


🌐 Key Concepts Covered

Throughout these scripts, I explored the following fundamental topics:

🧠 Theoretical and Practical Concepts

  • Qubits and Superposition
  • 🕹️ Quantum Gates (single and multi-qubit)
  • 🔗 Entanglement
  • 📏 Measurements and Expectation Values
  • 📉 Circuit Optimization
  • ⚛️ Hamiltonians and Time Evolution
  • 🎛️ Mixed States and Noisy Computation

This project is distributed under the Apache 2.0 License. You can find more details in the LICENSE file.

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A quantum computing learning platform that integrates Python and machine learning libraries to simulate, program, and run quantum algorithms on real (or in my case simulated) hardware.

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