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@josh146 josh146 released this 15 Apr 16:54
· 317 commits to master since this release
v0.13.0
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New features since last release

  • Adds initial support for the Xanadu's photonic quantum hardware. (#101) (#148) (#294) (#327) (#328) (#329) (#330) (#334) (#336) (#337) (#339)

    Jobs can now be submitted to the Xanadu Quantum Cloud platform to be run on supported hardware using the new RemoteEngine:

    import strawberryfields as sf
from strawberryfields import ops
from strawberryfields.utils import random_interferometer

# replace AUTH_TOKEN with your Xanadu Quantum Cloud access token
con = sf.api.Connection(token="AUTH_TOKEN")
eng = sf.RemoteEngine("X8", connection=con)
prog = sf.Program(8)

U = random_interferometer(4)

with prog.context as q:
    ops.S2gate(1.0) | (q[0], q[4])
    ops.S2gate(1.0) | (q[1], q[5])
    ops.S2gate(1.0) | (q[2], q[6])
    ops.S2gate(1.0) | (q[3], q[7])

    ops.Interferometer(U) | q[:4]
    ops.Interferometer(U) | q[4:]
    ops.MeasureFock() | q

result = eng.run(prog, shots=1000)

    For more details, see the photonic hardware quickstart and tutorial.

  • Significantly speeds up the Fock backend of Strawberry Fields, through a variety of changes:

    • The Fock backend now uses The Walrus high performance implementations of the displacement, squeezing, two-mode squeezing, and beamsplitter operations. (#287) (#289)

    • Custom tensor contractions which make use of symmetry relations for the beamsplitter and the two-mode squeeze gate have been added, as well as more efficient contractions for diagonal operations in the Fock basis. (#292)


  • New sf command line program for configuring Strawberry Fields for access to the Xanadu cloud platform, as well as submitting and executing jobs from the command line. (#146) (#312)

    The new Strawberry Fields command line program sf provides several utilities including:

    • sf configure [--token] [--local]: configure the connection to the cloud platform

    • sf run input [--output FILE]: submit and execute quantum programs from the command line

    • sf --ping: verify your connection to the Xanadu cloud platform

    For more details, see the documentation.

  • New configuration functions to load configuration from keyword arguments, environment variables, and configuration files. (#298) (#306)

    This includes the ability to automatically store Xanadu cloud platform credentials in a configuration file using the new function

    sf.store_account("AUTHENTICATION_TOKEN")

    as well as from the command line,

    $ sf configure --token AUTHENTICATION_TOKEN

    Configuration files can be saved globally, or locally on a per-project basis. For more details, see the configuration documentation

  • Adds configuration functions for resetting, deleting configurations, as well as displaying available configuration files. (#359)

  • Adds the x_quad_values and p_quad_values methods to the state class. This allows calculation of x and p quadrature probability distributions by integrating across the Wigner function. (#270)

  • Adds support in the applications layer for node-weighted graphs.

    Sample from graphs with node weights using a special-purpose encoding (#295):

    from strawberryfields.apps import sample

# generate a random graph
g = nx.erdos_renyi_graph(20, 0.6)
a = nx.to_numpy_array(g)

# define node weights
# and encode into the adjacency matrix
w = [i for i in range(20)]
a = sample.waw_matrix(a, w)

s = sample.sample(a, n_mean=10, n_samples=10)
s = sample.postselect(s, min_count=4, max_count=20)
s = sample.to_subgraphs(s, g)

    Node weights can be input to search algorithms in the clique and subgraph modules (#296) (#297):

    from strawberryfields.apps import clique
c = [clique.shrink(s_, g, node_select=w) for s_ in s]
[clique.search(c_, g, iterations=10, node_select=w) for c_ in c]
    from strawberryfields.apps import subgraph
subgraph.search(s, g, min_size=5, max_size=8, node_select=w)

Improvements

  • Moved Fock backend apply-gate functions to Circuit class, and removed apply_gate_einsum and Circuits._apply_gate, since they were no longer used. (#293)

  • Results returned from all backends now have a unified type and shape. In addition, attempting to use batching, post-selection and feed-foward together with multiple shots now raises an error. (#300)

  • Modified the rectangular decomposition to ensure that identity-like unitaries are implemented with no swaps. (#311)

Bug fixes

  • Symbolic Operation parameters are now compatible with TensorFlow 2.0 objects. (#282)

  • Added sympy>=1.5 to the list of dependencies. Removed the sympy.functions.atan2 workaround now that SymPy has been fixed. (#280)

  • Removed two unnecessary else statements that pylint complained about. (#290)

  • Fixed a bug in the MZgate, where the internal and external phases were in the wrong order in both the docstring and the argument list. The new signature is MZgate(phase_in, phase_ex), matching the existing rectangular_symmetric decomposition. (#301)

  • Updated the relevant methods in RemoteEngine and Connection to derive shots from the Blackbird script or Program if not explicitly specified. (#327)

  • Fixed a bug in homodyne measurements in the Fock backend, where computed probability values could occasionally include small negative values due to floating point precision error. (#364)

  • Fixed a bug that caused an exception when printing results with no state. (#367)

  • Improves the Takagi decomposition, by making explicit use of the eigendecomposition of real symmetric matrices. (#352)

Contributors

This release contains contributions from (in alphabetical order):

Ville Bergholm, Tom Bromley, Jack Ceroni, Theodor Isacsson, Josh Izaac, Nathan Killoran, Shreya P Kumar,
Leonhard Neuhaus, Nicolás Quesada, Jeremy Swinarton, Antal Száva, Paul Tan, Zeid Zabaneh.

Assets 2