unitaria 0.1.0

Linear algebra on quantum computers using block encodings

unitaria :rainbow:

unitaria is a library for working with so called "block encodings" of matrices and vectors. These are format for performing linear algebra calculations on quantum computers. It allows constructing quantum algorithms using a simple, numpy-like syntax.

>>> import unitaria as ut
>>> import numpy as np
>>> result = ut.Identity(ut.Subspace.from_dim(2)) @ ut.ConstantVector(np.array([3, 4]))
>>> print(result.draw())
Mul
├── Identity{'subspace': Subspace("#")}
└── ConstantVector{'vec': array([3, 4])}
>>> result.toarray().real
array([3., 4.])
>>> result.normalization
np.float64(5.0)
>>> result.circuit()
Circuit(_tq_circuit=circuit: 
GlobalPhase(target=(), control=(), parameter=0.0)
Ry(target=(0,), parameter=1.854590436003224)
, n_qubits=1)

Documentation

Installation

The best way to install this library is using pip:

pip install unitaria

This installs everything needed to work with unitaria, including the simulation backend qulacs. Additional backends compatible with tequila, which is used for communcating with the backends, can also be installed, see tequila.

Python versions

unitaria requires at least Python version 3.12, and follows Numpy's deprecation policy, i.e. at least Python 3.13 will be required starting April 2027.

Versioning

Unitaria follows SemVer conventions.

Development

To install this library locally, clone this repository and run

pip install --editable .

To run the test suite you can then execute

pytest

To build the documentation, some additional dependencies are required, which can be installed using

pip install --group docs --editable .

Then navigate to the /docs folder and run

rm -r generated
make html

If you get the error locale.Error: unsupported locale setting, try adding the environment variable LC_ALL=C.UTF-8:

LC_ALL=C.UTF-8 make html