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Quantum Color Centers Analysis Toolbox

Project description

Quantum Color Centers Analysis Toolbox

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QuaCCAToo is a Python library for simulating and analyzing spin dynamics of color centers for quantum technology applications, without using rotating wave approximations. The software serves as an extension for QuTip, inheriting its object-oriented framework and the Qobj class. This way, the software combines accessibility from the high level of abstraction and human-readability of Python with the efficiency of compiled programming languages provided by Qutip's parallelization and the matrix algebra from Scipy and Numpy.

Documentation and usage tutorial available at https://qiss-hzb.github.io/QuaCCAToo/

Installation

We strongly recommend using a virtual environment (use whichever tool like venv/conda/uv that you prefer) so that the system Python remains untouched.

pip install quaccatoo

Check here for detailed installation instructions.

Class Hierarchy

The package is organized as follows:

  • QSys defines the quantum system of the problem. It has an obligatory intrinsic internal Hamiltonian $H_0$, optional initial state, observable and a set of collapse operators. On QSys, one can calculate the eigenstates and eigenvalues of the system. QuaCCAToo provides NV(NV_Sys) as a predefined system for nitrogen vacancy centers in diamonds, more systems will be provided soon.
  • PulsedSim contains the logic for performing the simulation of pulsed experiments upon a QSys object. It has attributes of a pulse sequence containing a set of pulses and free evolutions, control Hamiltonian $H_1$, experiment variable and simulation results. Many predefined common pulse sequences are given in PredefSeqs and PredefDDSeqs.
  • ExpData is a class to load experimental data and perform basic data processing.
  • Analysis can be used either on simulation or experimental results, with a series of methods like FFT, fits, data comparison and plotting.

Class diagram

Contribution guidelines

Any contribution or bug report are welcome.

  • To contribute, fork the main branch and make a pull request.
  • We use hatch/hatchling as the build backend. The other development dependencies include pytest and ruff. They can be installed by running pip install -e '.[dev]' from within the cloned repository.
  • Properly document everything in details following the numpy docstring format.
  • Test your branch by running pytest and the tutorial notebooks. Feel free to add more tests.
  • Please pay attention to linter warnings (ruff check) and format your code with ruff format.
  • Module level refactors require corresponding changes in the sphinx setup, too.
  • Use US-English, not British-English. Eg: analyze instead of analyse, color instead of colour, center instead of centre.

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