HybridSuperQubits 0.1.6

Package to simulate hybrid superconducting qubits

HybridSuperQubits 🌀⚡

A Python framework for simulating hybrid semiconductor-superconductor quantum circuits.

Key Features ✨

• Hybrid Circuit Simulation 🔬
  Unified framework for semiconductor-superconductor systems.

• Advanced Noise Analysis 📉

  • Capacitive losses (t1_capacitive).
  • Inductive losses (t1_inductive).
  • Flux noise (tphi_1_over_f_flux).
  • Coherence Quantum Phase Slip (tphi_CQPS).

• Professional Visualization 📊

  • Wavefunction plotting (plot_wavefunction).
  • Matrix element analysis (plot_matelem_vs_paramvals).
  • Spectrum vs parameter sweeps.

• SC-Qubits Compatibility 🔄
  API-inspired interface for users familiar with scqubits

🚀 Installation

Follow these steps to install or contribute to the HybridSuperQubits library.

For End Users

If you only plan to use HybridSuperQubits (i.e., you do not need to modify or extend its functionality), you can install it directly from PyPI:

1. (Optional) Create a Virtual Environment

   Conda example:

   conda create --name hsq_env python=3.10
   conda activate hsq_env
   

   Or using venv:

   python3 -m venv hsq_env
   source hsq_env/bin/activate  # macOS/Linux
   hsq_env/Scripts/activate     # Windows
   

2. Install HybridSuperQubits via pip:

   pip install hybridsuperqubits
   

   To upgrade:

   pip install --upgrade hybridsuperqubits
   

   Note (macOS M1/M2/M3): If you run into issues with SciPy on Apple Silicon, install OpenBLAS first:

   brew install openblas
   pip install scipy
   

For Contributors or Developers

If you want to contribute to the project or modify the code:

1. Fork and Clone the repository from GitHub (see detailed steps in CONTRIBUTING.md).

2. Create a new branch for your feature or bug fix.

3. (Optional) Set up a development environment:

   conda create --name hsq_dev python=3.10
   conda activate hsq_dev
   

4. Install in Editable Mode:

   pip install -e .
   

   This lets you test changes locally without reinstalling the package each time.

5. Run Tests (if applicable):

   pytest tests/
   

For more details on contributing guidelines, code style, testing, and pull requests, please read our CONTRIBUTING.md.

Basic Usage 🚀

Supported Qubit Types

1. Andreev
2. Gatemon
3. Gatemonium
4. Fermionic bosonic qubit

Initialize a hybrid qubit

from HybridSuperQubits import Andreev, Gatemon, Gatemonium, Ferbo

# Fermionic-Bosonic Qubit (Ferbo)
qubit = Ferbo(
    Ec=1.2,          # Charging energy [GHz]
    El=0.8,          # Inductive energy [GHz]
    Gamma=5.0,       # Coupling strength [GHz]
    delta_Gamma=0.1, # Asymmetric coupling [GHz]
    er=0.05,         # Fermi detuning [GHz]
    phase=0.3,       # External phase (2 pi Φ/Φ₀)
    dimension=100    # Hilbert space dimension
)

# Andreev Pair Qubit
andreev_qubit = Andreev(
    EJ=15.0,        # Josephson energy [GHz]
    EC=0.5,         # Charging energy [GHz]
    delta=0.1,      # Superconducting gap [GHz]
    ng=0.0,         # Charge offset
    dimension=50
)

# Gatemonium
gatemonium = Gatemonium(
    EJ=10.0,        # Josephson energy [GHz]
    EC=1.2,         # Charging energy [GHz]
    ng=0.0,         # Charge offset
    dimension=100
)

Documentation 📚

Full API reference and theory background available at: hybridsuperqubits.readthedocs.io

Contributing 🤝

We welcome contributions! Please see:

CONTRIBUTING.md for development guidelines

License

This project is licensed under the MIT License. However, it includes portions of code derived from scqubits, which is licensed under the BSD 3-Clause License.

For more details, please refer to the LICENSE file.