forked from pool/python-thewalrus
Steve Kowalik
5332446785
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-thewalrus?expand=0&rev=12
233 lines
11 KiB
Plaintext
233 lines
11 KiB
Plaintext
-------------------------------------------------------------------
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Tue Apr 26 05:35:43 UTC 2022 - Steve Kowalik <steven.kowalik@suse.com>
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- No longer skip Python 3.10, dask is now available.
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-------------------------------------------------------------------
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Fri Feb 4 22:23:56 UTC 2022 - Ben Greiner <code@bnavigator.de>
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- Update to 0.18.0:
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* Python module for the La Budde method of computing
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characteristic polynomials. #304
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* Permanent algorithms are implemented in Python using Numba
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just-in-time compilation. #300
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* Hafnian algorithms are implemented in Python using Numba
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just-in-time compilation. #311
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* Documentation is updated to include the characteristic
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polynomials and decompositions modules. #312
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* Makes modules reachable via the global namespace, instead of
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requiring importing the modules explicitly. #312
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import thewalrus as tw
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tw.samples.generate_torontonian_sample
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* The Walrus is no longer dependent on C++, and all C++-related
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code and documentation is removed. Instead, all code has been
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ported to Python using just-in-time compilation to improve
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performance. #311
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- Release 0.17.0
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* Python installation no longer requires repoze.lru. #293
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* Multidimensional Hermite polynomials are now implemented in
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Numba, hence reducing the C++ dependencies of The Walrus. #295
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* Updates missing figures in the "Basics of Hafnians and Loop
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Hafnians" documentation. #288
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-------------------------------------------------------------------
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Wed Oct 27 08:01:52 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>
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- Update to version 0.16.2:
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* Bug fixes
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* hermite_multidimensional_numba can now handle a cutoff of
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type np.ndarray with shape=[]. #283
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- Version 0.16.1:
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* Improvements
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* Faster implementation of hermite_multidimensional_numba and
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hermite_multidimensional_numba_grad. #280
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* Bug fixes
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* Updates the samples.generate_torontonian_sample function to
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ensure probabilities are normalized. #250
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* Pins Numba to version <0.54 to avoid binary imcompatibilities
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with the 1.21 release of NumPy. #250
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- Version 0.16.0:
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* New features
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* Adds the function hafnian_sparse to compute sparse loop hafnians
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(pure Python implementation). #245
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* The symplectic.squeezing function is now generalized to multiple
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modes of single mode squeezing. #249
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* Adds a function symplectic.passive_transformation which allows for
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Gaussian states to be transformed by arbitrary non-unitary, non-square
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linear optical transformations. #249
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* The torontonian_sample_state function now can sample displaced
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Gaussian states. #248
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* Adds the function hafnian_banded to calculate the hafnian of a
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banded matrix. #246
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* Adds the functions hermite_multidimensional_numba and
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grad_hermite_multidimensional_numba to calculate renormalized
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multidimensional Hermite polynomials and its gradients using numba. #251
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* Adds the functions mzgate and grad_mzgate to calculate the Fock
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representation of the Mach-Zehnder gate and its gradients. #257
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* Adds the ability to calculate n-body photon number distributions
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using the function n_body_marginals. #253
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* Adds the ability to calculate cumulants and arbitrary expectation
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values of products of powers of photon numbers with the functions
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photon_number_cumulant and photon_number_moment respectively. #264
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* Adds support for calculating the permanent using the BBFG
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algorithm and changes this to the default method for calculating
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permanents. #267
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* Adds the ability to calculate click cumulants in threshold
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detection with the function click_cumulant. #264
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* Improvements
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* Speeds up the calculation of photon number variances/covariances. #244
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* Updates documentation for the the tor function. #265
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* Numba methods for multidimensional hermite can now detect
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dtype automatically. #271
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* Bug fixes
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* Corrects bug in the function photon_number_covar that gave
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incorrect results when the covariance between two modes with
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finite displacements was calculated. #264
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* Fixes a bug in setup.py that would cause the build to fail when
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using miniforge for M1 macs. #273
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* Updates the samples.generate_hafnian_sample function to renormalizing
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probabilities. #250
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* Breaking changes
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* Torontonians and approximations to the hafnian for non-negative
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matrices are no longer calculated in C++ using the Eigen software
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library. Instead, they are now calculated in pure Python using Numba.
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These changes have the nice result of making The Walrus compilable
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from source using only a C++ compiler. #262 #259.
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- Version 0.15.1
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* Bug fixes
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* Builds The Walrus binaries against an older version of NumPy, to avoid
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a breaking ABI change in NumPy 1.20. #240
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- Version 0.15.0
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* New features
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* Adds the function random_banded_interferometer to generate unitary
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matrices with a given bandwidth. #208
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* Adds the function tvd_cutoff_bounds to calculate bounds in the total
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variation distance between a Fock-truncated and an ideal GBS
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distribution. #210
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* Adds function for calculating threshold detection probabilities
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for Gaussian states with displacement. #220
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* Adds new functions total_photon_number_distribution and
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characteristic_function to study properties of the total photon
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number distribution of a k identical lossy squeezers. #230
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* Adds new functions xxpp_to_xpxp and xpxp_to_xxpp in the symplectic
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module to swap the ordering of the quadrature operators in vectors
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and matrices. #237
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* Improvements
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* The hafnians and loop hafnians of diagonal matrices are now calculated
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in polynomial time. #212
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* Refactors setup.py to avoid issues with CFLAGS. #229
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* The fidelity function in quantum/gaussian_checks.py is rewritten to
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add clarity. #226
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* Simplifies logic of normal_ordered_expectation by removing mutually
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cancelling np.conj. #228
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* Bug fixes
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* Removes unnecessary np.real_if_close statements in quantum/fock_tensors.py
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causing the probabilities to not be normalized. #215
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* Fixes the prefactor in pure_state_amplitude. #231
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-------------------------------------------------------------------
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Mon Feb 8 14:35:31 UTC 2021 - andy great <andythe_great@pm.me>
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- Disable build for python 3.6 because numpy does not support it.
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-------------------------------------------------------------------
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Thu Nov 26 07:51:50 UTC 2020 - andy great <andythe_great@pm.me>
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- Update to version 0.14.0.
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* New features
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* Adds the function find_classical_subsystem that tries to find
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a subset of the modes with a classical covariance matrix.
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* Adds the functions mean_number_of_clicks and
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variance_number_of_clicks that calculate the first and second
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statistical moments of the total number of clicks in a
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Gaussian state centered at the origin.
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* Adds the module decompositions with the function williamson
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to find the Williamson decomposition of an even-size
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positive-semidefinite matrix.
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* Adds the loop_hafnian_quad function to the Python interface
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for converting double precision matrices into quad precision,
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doing the calculations in quad precision, and then return the
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result as a double.
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* Improvements
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* Introduces a new faster and significantly more accurate
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algorithm to calculate power traces allowing to speed up the
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calculation of loop hafnians
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* The quantum module has been refactored and organized into
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sub-modules. Several functions have been renamed, while the
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old names are being deprecated.
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* Adds support for C++14
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* pytest-randomly is added to the test suite to improve testing
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and avoid stochastically failing tests.
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* Modifies the function input_validation to use np.allclose for
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checking the symmetry of the input matrices.
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* Modifies the function _hafnian to calculate efficiently loop
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hafnians of diagonal matrices.
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* Breaking changes
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* Removes the redundant function normal_ordered_complex_cov.
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* Renames the function mean_number_of_clicks to be
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mean_number_of_click_graph.
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-------------------------------------------------------------------
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Thu Sep 24 21:14:01 UTC 2020 - Matej Cepl <mcepl@suse.com>
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- Actually manually adding "-fopenmp" to CFLAGS allows us to use
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even the standard SUSE CFLAGS (workaround found in the same
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bug).
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-------------------------------------------------------------------
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Mon Sep 21 15:08:09 UTC 2020 - Matej Cepl <mcepl@suse.com>
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- Standard OpenSUSE CFLAGS break the build
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(gh#XanaduAI/thewalrus#198).
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-------------------------------------------------------------------
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Thu Sep 17 19:35:47 UTC 2020 - andy great <andythe_great@pm.me>
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- Fix spec file typo.
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-------------------------------------------------------------------
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Fri Sep 11 20:38:18 UTC 2020 - andy great <andythe_great@pm.me>
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- Update to version 0.13.0.
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* Adds a new algorithm for hafnians of matrices with low rank.
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* Adds a function to calculate the fidelity between two Gaussian
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quantum states.
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* Adds a new module, thewalrus.random, to generate random
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unitary, symplectic and covariance matrices.
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* Adds new functions normal_ordered_expectation,
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photon_number_expectation and photon_number_squared_expectation
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in thewalrus.quantum to calculate expectation values of
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products of normal ordered expressions and number operators and
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their squares.
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* Adds the function hafnian_sample_graph_rank_one in
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thewalrus.samples to sample from rank-one adjacency matrices.
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* Adds parallelization support using Dask for
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quantum.probabilities.
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* Removes support for Python 3.5.
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* Changes in the interface and speed ups in the functions in the
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thewalrus.fock_gradients module.
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* Improves documentation of the multidimensional Hermite
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polynomials.
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* Improves speed of fock_tensor when the symplectic matrix passed
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is also orthogonal.
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* Fixes Numba decorated functions not rendering properly in the
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documentation.
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* Solves the issue with quantum and samples not being rendered in
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the documentation or the TOC.
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* Fix bug where quantum and samples were not showing up in the
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documentation.
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* The functions in thewalrus.fock_gradients are now separated
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into functions for the gradients and the gates. Moreover, they
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are renamed, for instance Dgate becomes displacement and its
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gradient is now grad_displacement.
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-------------------------------------------------------------------
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Wed Aug 5 16:12:15 UTC 2020 - andy great <andythe_great@pm.me>
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- Use pytest for %check
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-------------------------------------------------------------------
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Sun Aug 2 10:05:38 UTC 2020 - andy great <andythe_great@pm.me>
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- Initial package release.
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