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Release 0.11
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@co9olguy co9olguy released this 10 Jul 15:56
· 662 commits to master since this release
v0.11.0
9b46f82

This is a significant release, with breaking changes to how quantum programs are constructed and executed. For example, the following Strawberry Fields program, <= version 0.10:

eng, q = sf.Engine(2, hbar=0.5)

with eng:
    Sgate(0.5) | q[0]
    MeasureFock() | q[0]

state = eng.run("fock", cutoff_dim=5)
ket = state.ket()
print(q[0].val)

would now be written, in v0.11, as follows:

sf.hbar = 0.5
prog = sf.Program(2)
eng = sf.Engine("fock", backend_options={"cutoff_dim": 5})

with prog.context as q:
    Sgate(0.5) | q[0]
    MeasureFock() | q[0]

results = eng.run(prog)
ket = results.state.ket()
print(results.samples[0])

New features

  • The functionality of the Engine class has been divided into two new classes: Program, which represents a quantum circuit or a fragment thereof, and Engine, which executes Program instances.

  • Introduced the BaseEngine abstract base class and the LocalEngine child class. Engine is kept as an alias for LocalEngine.

  • The Engine API has been changed slightly:

    • The engine is initialized with the required backend, as well as a backend_options dictionary, which is passed to the backend:

      eng = sf.Engine("fock", backend_options={"cutoff_dim": 5}

    • LocalEngine.run() now accepts a program to execute, and returns a Result object that contains both a state object (Result.state) and measurement samples (Result.samples):

      results = eng.run(prog)
state = results.state
samples = results.samples

    • compile_options can be provided when calling LocalEngine.run(). These are passed to the compile() method of the program before execution.

    • run_options can be provided when calling LocalEngine.run(). These are used to determine the characteristics of the measurements and state contained in the Results object returned after the program is finished executing.

    • shots keyword argument can be passed to run_options, enabling multi-shot sampling. Supported only
      in the Gaussian backend, and only for Fock measurements.

  • The Gaussian backend now officially supports Fock-basis measurements (MeasureFock), but does not update the quantum state after a Fock measurement.

  • Added the io module, which is used to save/load standalone Blackbird scripts from/into Strawberry Fields. Note that the Blackbird DSL has been spun off as an independent package and is now a dependency of Strawberry Fields.

  • Added a new interferometer decomposition mach_zehnder to the decompositions module.

  • Added a Configuration class, which is used to load, store, save, and modify configuration options for Strawberry Fields.

  • hbar is now set globally for the entire session, by setting the value of sf.hbar (default is 2).

  • Added the ability to generate random real (orthogonal) interferometers and random block diagonal symplectic and covariance matrices.

  • Added two top-level functions:

    • about(), which prints human-readable system info including installed versions of various Python packages.
    • cite(), which prints a bibtex citation for SF.

  • Added a glossary to the documentation.

API Changes

  • Added the circuitspecs subpackage, containing the CircuitSpecs class and a quantum circuit database.

    The database can be used to

    • Validate that a Program belongs in a specific circuit class.
    • Compile a Program for a desired circuit target, e.g., so that it can be executed on a given backend.
      The database includes a number of compilation targets, including Gaussian Boson Sampling circuits.

  • The way hbar is handled has been simplified:

    • The backend API is now entirely hbar-independent, i.e., every backend API method is defined in terms of a and a^\dagger only, not x and p.
    • The backends always explicitly use hbar=2 internally.
    • hbar is now a global, frontend-only variable that the user can set at the beginning of the session. It is used at the Operation.apply() level to scale the inputs and outputs of the backend API calls as needed, and inside the State objects.
    • The only backend API calls that need to do hbar scaling for the input parameters are the X, Z, and V gates, the Gaussian state decomposition, and homodyne measurements (both the returned value and postselection argument are scaled).

Improvements

  • Removed TensorFlow as an explicit dependency of Strawberry Fields. Advanced users can still install TensorFlow manually using pip install tensorflow==1.3 and use as before.

  • The behaviour and function signature of the GraphEmbed operation has been updated.

  • Remove the unused Command.decomp instance attribute.

  • Better error messages for the New operation when used outside of a circuit.

  • Docstrings updated in the decompositions module.

  • Docstrings for Fock backend reformatted and cleaned up.

  • Cleaning up of citations and references.bib file.

  • Typos in documentation fixed.

Bug fixes

  • Fixed a bug with installation on Windows for certain locales.
  • Fixed a bug in the New operation.
  • Bugfix in Gate.merge()
  • Fixed bugs in measure_fock in the TensorFlow backend which caused samples to be evaluated independently and for conditional states to be potentially decoupled from the measurement results.
  • Fixed a latent bug in graph_embed.
  • Bugfix for Bloch-Messiah returning non-symplectic matrices when input is passive.

Contributors

This release contains contributions from (in alphabetical order):

Ville Bergholm, Tom Bromley, Ish Dhand, Karel Dumon, Xueshi Guo, Josh Izaac, Nathan Killoran, Leonhard Neuhaus, Nicolás Quesada.

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