Thewalrus

New features

* Adds a new algorithm for hafnians of matrices with low rank. [166](https://github.com/XanaduAI/thewalrus/pull/166)

* Adds a function to calculate the fidelity between two Gaussian quantum states. [169](https://github.com/XanaduAI/thewalrus/pull/169)

* Adds a new module, `thewalrus.random`, to generate random unitary, symplectic and covariance matrices. [169](https://github.com/XanaduAI/thewalrus/pull/169)

* Adds new functions `normal_ordered_expectation`, ` photon_number_expectation` and `photon_number_squared_expectation` in `thewalrus.quantum` to calculate expectation values of products of normal ordered expressions and number operators and their squares. [175](https://github.com/XanaduAI/thewalrus/pull/175)

* Adds the function `hafnian_sample_graph_rank_one` in `thewalrus.samples` to sample from rank-one adjacency matrices. [174](https://github.com/XanaduAI/thewalrus/pull/169)

Improvements

* Adds parallelization support using Dask for `quantum.probabilities`. [161](https://github.com/XanaduAI/thewalrus/pull/161)

* Removes support for Python 3.5. [163](https://github.com/XanaduAI/thewalrus/pull/163)

* Changes in the interface and speed ups in the functions in the `thewalrus.fock_gradients` module. [164](https://github.com/XanaduAI/thewalrus/pull/164/files)

* Improves documentation of the multidimensional Hermite polynomials. [166](https://github.com/XanaduAI/thewalrus/pull/166)

* Improves speed of `fock_tensor` when the symplectic matrix passed is also orthogonal. [166](https://github.com/XanaduAI/thewalrus/pull/166)

Bug fixes

* Fixes Numba decorated functions not rendering properly in the documentation. [173](https://github.com/XanaduAI/thewalrus/pull/173)

* Solves the issue with `quantum` and `samples` not being rendered in the documentation or the TOC. [173](https://github.com/XanaduAI/thewalrus/pull/173)

Breaking changes

* The functions in `thewalrus.fock_gradients` are now separated into functions for the gradients and the gates. Moreover, they are renamed, for instance `Dgate` becomes `displacement` and its gradient is now `grad_displacement`. [164](https://github.com/XanaduAI/thewalrus/pull/164/files)

Contributors

This release contains contributions from (in alphabetical order):

Theodor Isacsson, Filippo Miatto, Nicolas Quesada

New features

* Adds the ability to calculate the mean number of photons in a given mode of a Gaussian state. [148](https://github.com/XanaduAI/thewalrus/pull/148)

* Adds the ability to calculate the photon number distribution of a pure or mixed state using `generate_probabilities`. [152](https://github.com/XanaduAI/thewalrus/pull/152)

* Allows to update the photon number distribution when undergoing loss by using `update_probabilities_with_loss`. [152](https://github.com/XanaduAI/thewalrus/pull/152)

* Allows to update the photon number distribution when undergoing noise `update_probabilities_with_noise`. [153](https://github.com/XanaduAI/thewalrus/pull/153)

* Adds a brute force sampler `photon_number_sampler` that given a (multi-)mode photon number distribution generates photon number samples. [152](https://github.com/XanaduAI/thewalrus/pull/152)

* Adds the ability to perform the Autonne-Takagi decomposition of a complex-symmetric matrix using `autonne` from the `symplectic` module. [154](https://github.com/XanaduAI/thewalrus/pull/154)

Improvements


* Improves the efficiency of Hermite polynomial calculation in `hermite_multidimensional.hpp`. [141](https://github.com/XanaduAI/thewalrus/pull/141)

* Implements parallelization with Dask for sampling from the Hafnian/Torontonian of a Gaussian state. [145](https://github.com/XanaduAI/thewalrus/pull/145)

Bug fixes

* Corrects the issue with hbar taking a default value when calling `state_vector`, `pure_state_amplitude`, and `density_matrix_element` [149](https://github.com/XanaduAI/thewalrus/pull/149)

Contributors

This release contains contributions from (in alphabetical order):


Theodor Isacsson, Nicolas Quesada, Kieran Wilkinson

New features

* Introduces the renormalized hermite polynomials. These new polynomials improve the speed and accuracy of `thewalrus.quantum.state_vector` and `thewalrus.quantum.density_matrix` and also `hafnian_batched` and `hermite_multimensional` when called with the optional argument `renorm=True`. [108](https://github.com/XanaduAI/thewalrus/pull/108)

* Adds functions for calculating the covariance for the photon number distribution of a Gaussian state including a function for the full covariance matrix. [137](https://github.com/XanaduAI/thewalrus/pull/137)

* Adds support for Python 3.8. [138](https://github.com/XanaduAI/thewalrus/pull/138)

Improvements

* Updates the reference that should be used when citing The Walrus. [102](https://github.com/XanaduAI/thewalrus/pull/102)

* Updates and improves the speed and accuracy of `thewalrus.quantum.fock_tensor`. [107](https://github.com/XanaduAI/thewalrus/pull/107)

* Add OpenMP support to the repeated moment hafnian code. [120](https://github.com/XanaduAI/thewalrus/pull/120)

* Improves speed of the functions in `hermite_multidimensional.hpp`. [123](https://github.com/XanaduAI/thewalrus/pull/123)

* Improves speed of the functions in `thewalrus.fock_gradients` by doing calls to optimized functions in `hermite_multidimensional.hpp`. [123](https://github.com/XanaduAI/thewalrus/pull/123)

* Further improves speed of the functions `thewalrus.fock_gradients` by writing explicit recursion relations for a given number of modes. [129](https://github.com/XanaduAI/thewalrus/pull/129)

* Adds the functions `find_scaling_adjacency_matrix_torontonian` and `mean_number_of_clicks` that allow to fix the mean number of clicks when doing threshold detection sampling and allow to calculate the mean of clicks generated by a scaled adjacency matrix. [136](https://github.com/XanaduAI/thewalrus/pull/136/)


Bug fixes

* Corrects typos in the random number generation in the C++ unit tests. [118](https://github.com/XanaduAI/thewalrus/pull/118)

* Corrects typos in describing the repeated-moment algorithm of Kan in the documentation. [104](https://github.com/XanaduAI/thewalrus/pull/104)

* Removes paper.{md,pdf,bib} from the repository now that The Walrus paper is published in Journal of Open Source Software [106](https://github.com/XanaduAI/thewalrus/pull/106)

* Updates the S2gate to use the correct definition. [130](https://github.com/XanaduAI/thewalrus/pull/130)

* Corrects the issue with hbar taking a default value when calculating mu in the density matrix function [134](https://github.com/XanaduAI/thewalrus/pull/134)

Contributors

This release contains contributions from (in alphabetical order):

Theodor Isacsson, Josh Izaac, Filippo Miatto, Nicolas Quesada, Trevor Vincent, Kieran Wilkinson

Small release to add a DOI on Zenodo.

New features
* Adds the function `thewalrus.quantum.fock_tensor` that returns the Fock space tensor corresponding to a Symplectic transformation in phase space. [90](https://github.com/XanaduAI/thewalrus/pull/90)

* Adds the `thewalrus.fock_gradients` module which provides the Fock representation of a set of continuous-variable universal gates in the Fock representation and their gradients. [96](https://github.com/XanaduAI/thewalrus/pull/96)

Improvements

* Unifies return values of all symplectic gates in the `thewalrus.symplectic` module. [81](https://github.com/XanaduAI/thewalrus/pull/81)

* Removes unnecessary citations in the tutorials. [92](https://github.com/XanaduAI/thewalrus/pull/92)

* Improves the efficiency of the multidimensional Hermite polynomials implementation and simplifies a number of derived functions. [93](https://github.com/XanaduAI/thewalrus/pull/93)

Bug fixes

* Fixes a bug in the calculation of the state vector in `thewalrus.quantum.state_vector`. This bug was found and fixed while implementing `thewalrus.quantum.fock_tensor`. [90](https://github.com/XanaduAI/thewalrus/pull/90)

Contributors

This release contains contributions from (in alphabetical order):

Josh Izaac, Nicolas Quesada

New features
* Adds a symplectic module `symplectic` which allows easy access to symplectic transformations and covariance matrices of Gaussian states. [78](https://github.com/XanaduAI/thewalrus/pull/78)

Improvements

* Adds a quick reference section in the documentation. [75](https://github.com/XanaduAI/thewalrus/pull/75)

Bug fixes

* Solves issue [70](https://github.com/XanaduAI/thewalrus/issues/70) related to the index ordering in `thewalrus.quantum.density_matrix`.

Contributors
This release contains contributions from (in alphabetical order):

Josh Izaac, Nicolas Quesada