psiqit 1.0.2

PSIQIT - Quantum Information Toolkit

PSIQIT - Quantum Information Toolkit

PSIQIT (Quantum Information Toolkit) is a comprehensive Python library for quantum computing, quantum information theory, and quantum mechanics simulations. It provides a complete set of tools for research, education, and development in quantum technologies.

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✨ Features

Category	Description
🔢 Mathematics	Linear algebra, calculus, ODE/PDE solvers, symbolic math
⚛️ Quantum States	Ket/Bra, Bell states, GHZ, W, coherent, squeezed, Fock states
🚪 Quantum Gates	Pauli, Hadamard, rotations, CNOT, Toffoli, Fredkin
🔌 Quantum Circuits	Circuit builder, simulation, visualization
📊 Measurements	POVM, projective measurements, tomography
🧠 Algorithms	Grover, Shor, Deutsch-Jozsa, QFT, QPE, Simon
📈 Variational Methods	VQE, QAOA, SSVQE, ADAPT-VQE, TDVP
🔗 Entanglement	Concurrence, negativity, Schmidt decomposition
🌊 Open Systems	Lindblad equation, quantum trajectories, Monte Carlo
🛡️ Error Correction	Bit flip, phase flip, Shor code, Steane code
🤖 Quantum ML	QSVM, QNN, VQC, QGAN, quantum kernels
📊 Visualization	Bloch sphere, Wigner function, circuit drawing

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📦 Installation

Basic Installation

pip install psiqit

With Optional Dependencies

# For visualization
pip install psiqit[viz]

# For machine learning
pip install psiqit[ml]

# For symbolic mathematics
pip install psiqit[symbolic]

# Install all features
pip install psiqit[full]

From Source

git clone https://github.com/psiqit/psiqit.git
cd psiqit
pip install -e .

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🚀 Quick Start

Quantum Circuit

from psiqit.circuits.circuit import QuantumCircuit

# Create Bell state
circ = QuantumCircuit(2)
circ.h(0)
circ.cx(0, 1)

# Run simulation
state = circ.run()
print(state)  # 0.707|00⟩ + 0.707|11⟩

# Measure
results = circ.measure(shots=1024)
print(results['counts'])  # {'00': 512, '11': 512}

VQE (Variational Quantum Eigensolver)

from psiqit.variational import VQE

# Hamiltonian for 2-qubit system
hamiltonian = {'Z0Z1': 1.0, 'X0': 0.5, 'X1': 0.5}

vqe = VQE(n_qubits=2, hamiltonian=hamiltonian)
result = vqe.run(n_iterations=100)

print(f"Ground state energy: {result.optimal_energy:.6f}")

Grover's Search

from psiqit.algorithms.grover import grover_search

# Search for |101⟩ in 3-qubit system
result = grover_search(n_qubits=3, target=5, shots=1024)

print(f"Found: {result.most_likely}")  # 5

Bloch Sphere Visualization

from psiqit.visualization import bloch_sphere
from psiqit.quantum.state import plus

bloch_sphere(plus(), title="|+⟩ State")

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📚 Documentation

Full documentation is available at: https://psiqit.github.io

Section	Description
Getting Started	Installation and quick start
User Guide	In-depth tutorials
API Reference	Complete API documentation
Examples	Code examples
Tutorials	Jupyter notebooks

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📁 Project Structure

psiqit/
├── algorithms/       # Quantum algorithms (Grover, Shor, QFT, ...)
├── circuits/         # Quantum circuits and simulation
├── dynamics/         # Quantum dynamics (Lindblad, Schrödinger)
├── error_correction/ # Error correction codes
├── info/             # Information theory (entropy, entanglement)
├── interface/        # CLI, LaTeX, Jupyter tools
├── lab/              # Virtual quantum laboratory
├── math/             # Mathematical toolkit
├── noise_canceling/  # Noise models and mitigation
├── qml/              # Quantum machine learning
├── quantum/          # Quantum foundations (states, operators)
├── utils/            # Utilities
├── variational/      # Variational methods (VQE, QAOA)
└── visualization/    # Visualization tools

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🤝 Contributing

Contributions are welcome! Please see our Contributing Guide.

Development Setup

git clone https://github.com/psiqit/psiqit.git
cd psiqit
pip install -e .[dev]
pytest tests/

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📄 License

PSIQIT is released under the MIT License.

Copyright (c) 2025-2026 Mahdi Azadmarzabadi and PSIQIT Contributors

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📧 Contact

• Author: Mahdi Azadmarzabadi
• Maintainer: PSIQIT Developer Team
• Email: [e-mail]
• GitHub: https://github.com/psiqit/psiqit

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🌟 Citation

If you use PSIQIT in your research, please cite:

@software{psiqit2025,
  title = {PSIQIT: Quantum Information Toolkit},
  author = {Azadmarzabadi, Mahdi and PSIQIT Contributors},
  year = {2025},
  url = {https://github.com/psiqit/psiqit},
  version = {1.0.2}
}

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🙏 Acknowledgments

PSIQIT builds upon the rich ecosystem of Python scientific computing:

• NumPy - Numerical computing
• SciPy - Scientific computing
• Matplotlib - Visualization
• SymPy - Symbolic mathematics

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⭐ Star Us

If you find PSIQIT useful, please consider giving us a star on GitHub!

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Happy Quantum Computing! 🚀