bqskit 0.5.1

Berkeley Quantum Synthesis Toolkit

Berkeley Quantum Synthesis Toolkit (BQSKit)

BQSKit allows you to use high-quality synthesis algorithms with ease to compile quantum circuits. It is designed to be highly customizable to find a compiler-flow that suites your needs well.

Installation

BQSKit is available for Python 3.7+ on Linux, MacOS, and Windows. BQSKit and its dependencies are listed on the Python Package Index, and as such, can be installed with pip:

pip install bqskit

Basic Usage

BQSKit can be used as a quantum compiler and so much more. Below we have examples for the common use cases in BQSKit.

Circuit Optimization Example

The most obvious use for an optimizing quantum compiler is to optimize a quantum program. Here we can optimize a program given as a circuit in qasm:

from bqskit.compiler import Compiler
from bqskit.compiler import CompilationTask
from bqskit.ir import Circuit

# Load a circuit from QASM
circuit = Circuit.from_file("tfim.qasm")

# Create a standard CompilationTask to optimize the circuit
task = CompilationTask.optimize(circuit)

# Spawn a compiler and compile the task
if __name__ == '__main__':
    with Compiler() as compiler:
        optimized_circuit = compiler.compile(task)

We first load the qasm program into a Circuit object. Then we create a CompilationTask object, which encapsulates an entire compilation flow. This includes the circuit to be compiled, as well as, the configured algorithms that are desired to be used to compile the program.

We provide some default constructors for the common cases, such as CompilationTask.optimize and the ones you will see in the following sections. These these default configurations aim to be widely applicable, and as a result, may be far from the best. The best compilation flow for your use case will likely require some experimentation. Once you are familiar with the basics, we recommend you explore how these defaults are built and toy with them.

The last block of the program spawns a Compiler object which is responsible for executing the CompilationTask. This will handle the execution efficiently.

Unitary Synthesis Example

A compiler built around the concept of synthesis should definitely support synthesis. In fact, the BQSKit compiler does support a variety of ways to perform synthesis. The following example uses the default flow for synthesizing a toffoli unitary:

import numpy as np
from bqskit.compiler import Compiler
from bqskit.compiler import CompilationTask

# Construct the unitary as an NumPy array
toffoli = np.array([
    [1, 0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0, 0],
    [0, 0, 0, 0, 0, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1],
    [0, 0, 0, 0, 0, 0, 1, 0],
])

# Create a standard synthesis CompilationTask
task = CompilationTask.synthesize(toffoli)

# Spawn a compiler and compile the task
if __name__ == '__main__':
    with Compiler() as compiler:
        synthesized_circuit = compiler.compile(task)

Verifying Results

All of BQSKit's synthesis algorithms are approximate, which mean the compiled results might be slightly different than what was inputted. For most cases, these differences are close to floating point thresholds, but can be greater in magnitude. Most algorithms will offer some sort of control over this error, but it is important to be able to measure it.

For simulatable circuits, we can compare the unitaries directly:

dist = synthesized_circuit.get_unitary().get_distance_from(toffoli)
assert dist < 1e-10

Copyright

Berkeley Quantum Synthesis Toolkit (BQSKit) Copyright (c) 2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy) and Massachusetts Institute of Technology (MIT). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at [e-mail].

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit others to do so.