Tutorials#
These tutorials provide step-by-step learning paths for ATLAS-Q. Each tutorial is self-contained and builds from basic to advanced concepts.
- Beginner’s Tutorial
- Prerequisites
- Learning Objectives
- Installation Verification
- Part 1: Understanding Matrix Product States
- Part 2: Quantum Gates
- Part 3: Measurement and Sampling
- Part 4: Building Quantum Circuits
- Part 5: Period-Finding and Factorization
- Part 6: Understanding Truncation
- Part 7: Memory Management
- Next Steps
- Troubleshooting
- See Also
- MPS Basics
- VQE Tutorial
- Coherence-Aware Quantum Computing
- TDVP Tutorial
- Prerequisites
- Learning Objectives
- Part 1: TDVP Fundamentals
- Part 2: 1-Site vs 2-Site TDVP
- Part 3: Real vs Imaginary Time
- Part 4: Krylov Subspace Methods
- Part 5: Time-Dependent Hamiltonians
- Part 6: Quantum Quenches
- Part 7: Observables and Correlations
- Part 8: Performance Optimization
- Part 9: Troubleshooting
- Summary
- Next Steps
- Practice Exercises
- See Also
- Molecular VQE Tutorial
- Prerequisites
- Learning Objectives
- Part 1: Fundamentals of Molecular VQE
- Part 2: Electronic Structure Representation
- Part 3: PySCF Integration
- Part 4: UCCSD Ansatz for Molecules
- Part 5: Optimization for Molecules
- Part 6: Multiple Molecule Examples
- Part 7: Advanced Topics
- Part 8: Performance and Accuracy
- Part 9: Troubleshooting
- Summary
- Next Steps
- Practice Exercises
- See Also
- QAOA Tutorial
- Prerequisites
- Learning Objectives
- Part 1: Fundamentals of QAOA
- Part 2: The QAOA Ansatz
- Part 3: MaxCut Problem
- Part 4: Other Combinatorial Problems
- Part 5: Parameter Optimization
- Part 6: Depth vs Performance Trade-offs
- Part 7: Advanced QAOA Techniques
- Part 8: Interpreting Results
- Part 9: Troubleshooting
- Summary
- Next Steps
- Practice Exercises
- See Also
- Advanced Features Tutorial
- Prerequisites
- Learning Objectives
- Part 1: Circuit Cutting and Distribution
- Part 2: PEPS for 2D Systems
- Part 3: Stabilizer Backend
- Part 4: Distributed MPS
- Part 5: Noise Models
- Part 6: Advanced Optimization Techniques
- Part 7: Performance Profiling
- Part 8: Troubleshooting
- Summary
- Next Steps
- Practice Exercises
- See Also
Tutorials Overview#
- Beginner’s Tutorial
Introduction to quantum simulation with ATLAS-Q. Covers basic concepts, installation verification, and first simulations. Start here if you are new to ATLAS-Q.
- MPS Basics
Matrix Product States fundamentals. Learn tensor network representation, bond dimensions, truncation, and gate application.
- VQE Tutorial
Variational Quantum Eigensolver for ground state finding. Covers ansätze selection, parameter optimization, and convergence analysis.
- TDVP Tutorial
Time-Dependent Variational Principle for quantum dynamics. Learn real-time evolution, quench dynamics, and correlation functions.
- Molecular VQE Tutorial
Quantum chemistry with VQE. Build molecular Hamiltonians using PySCF, choose appropriate ansätze (Hardware-Efficient vs UCCSD), and compute ground state energies.
- QAOA Tutorial
Quantum Approximate Optimization Algorithm for combinatorial problems. Apply QAOA to MaxCut, graph coloring, and other optimization problems.
- Advanced Features Tutorial
Advanced simulation techniques: circuit cutting, PEPS for 2D circuits, distributed MPS, stabilizer backend, and noise models.
Prerequisites#
All tutorials assume:
Python 3.9+ installed
ATLAS-Q installed (see Installation)
Basic understanding of quantum mechanics (qubits, gates, measurements)
Familiarity with NumPy and PyTorch
For molecular chemistry tutorials, install PySCF:
pip install pyscf openfermion openfermionpyscf
Jupyter Notebooks#
Many tutorials are available as interactive Jupyter notebooks in the repository:
git clone https://github.com/followthesapper/ATLAS-Q.git
cd ATLAS-Q
jupyter notebook ATLAS_Q_Demo.ipynb
Or open directly in Google Colab: