Quantum Computing for Classical Programmers

Source code for the book project by Robert Hundt. In this project, we build infrastructure from the ground up, implement standard algorithms, such as Quantum Teleportation, Grover's Search, QFT, and Shor's integer factorization. We also implement high performance quantum simulation and a transpilation technique to compile our circuits to other infrastructures, such as Qiskit or Cirq. The book itself details this implementation, its motivation and the underlying math, in great detail. At this point, the book has not yet been published.

The code organization is fairly simple.

• src is the main source directory. All key algorithms are in this directory.
• src/lib contains the library functions for tensors, states, operators, circuits, and so on, as well as their corresponding tests. The algorithms only depend on these library functions.
• src/libq contains the implementation based on a sparse representation.
• src/benchmarks contains just a few benchmarks, as they were mentioned in the book.

Installation

These instructions focus on Debian Linux. CentOS is also supported, see the corresponding README.CentOS.md file. We may add Other OS'es in the future.

To run the code we need a few tools:

• The bazel build system. Install from bazel's homepage

• We will need Python's pip tool to install packages and git to manage the source. Here is one way to install them:

    sudo apt-get install python3-pip
    sudo apt-get install git

• We need Google's absl library, as well as numpy and scipy. Install with

   sudo python3 -m pip install absl-py
   sudo python3 -m pip install numpy
   sudo python3 -m pip install scipy

• Finally, to get these source onto your computer:

    git clone https://github.com/qcc4cp/qcc.git

Build

Much of the code is in Python and will run out of the box. There is some C++ for the high performance simulation which requires configuration.

The file src/lib/BUILD contains the build rule for the C++ xgates extension module. This module needs to be able to access the Python header (Python.h), as well as some numpy headers. These files' location might be different on your build machine. Please set the command-line parameter -I... below appropriately to point to your Python installation.

cc_library(
    name = "xgates",
    srcs = [
        "xgates.cc",
    ],
    copts = [
        "-O3",
        "-ffast-math",
    	"-march=skylake",
        "-DNPY_NO_DEPRECATED_API",
        "-DNPY_1_7_API_VERSION",
        # Configure:
        "-I/usr/include/python3.7m",
    ],
    deps = [
        "@third_party_numpy//:numpy",
    ],
)

There is a subtlety about bazel: All headers must be within the source tree, or in /usr/include/... To work around this, we have to point bazel to the installation directory for numpy. The specification for the external numpy installation is in the WORKSPACE file. Point path to your numpy installation's header files, excluding the final include part of the path. The include path is specified in the co-located file numpy.BUILD.

new_local_repository(
    name = "third_party_numpy",
    path = "/usr/local/lib/python3.7/dist-packages/numpy/core/",
    build_file = __workspace_dir__ + "/numpy.BUILD", 
)

Once xgates builds successfully, it is imported into circuit.py. At the top of this file is the import statement that might need to be adjusted:

# Configure: This line might have to change, depending on
#            the current build environment.
#
# Google internal:
# import xgates
#
# GitHub Linux:
import libxgates as xgates

Additionally, to enable Python to find the extension module, make sure to include in PYTHONPATH the directory where the generated xgates.so or libxgates.so is being generated. For example:

export PYTHONPATH=$PYTHONPATH:/home/usrname/qcc/bazel-bin/src/lib

bazel also attempts to use the Python 2 interpreter python. If it is not available on a system, install via:

sudo apt-get install python

Run

To build the library and test for correct installation, go to src/lib and run:

    bazel build all
    bazel test ...
    
    # Make sure to set PYTHONPATH (once):
    export PYTHONPATH=$PYTHONPATH:/home/usrname/qcc/bazel-bin/src/lib
    
    # Ensure xgates was built properly:
    bazel run circuit_test

The main algorithms are all in src. To run individual algorithms, run any of these command lines (note the missing .py extensions):

   bazel run arith_classic
   bazel run arith_quantum
   bazel run bernstein
   bazel run deutsch
   bazel run deutsch_jozsa
   bazel run grover
   bazel run order_finding
   bazel run phase_estimation
   bazel run phase_kick
   bazel run shor_classic
   bazel run superdense
   bazel run supremacy
   bazel run swap_test
   bazel run teleportation
   bazel run vqe_simple

To test aspects of the sparse implementation:

  cd src/libq
  bazel test ...

To run the benchmarks:

  cd src/benchmarks
  bazel run larose_benchmark
  bazel run tensor_math

About

This code and book were written by Robert Hundt. At the time of this writing, Robert is a Distinguished Enginer at Google. However, this is a private project, developed on personal infrastructure and in private time. It is completely independent of Robert's work at Google.

Reach Robert at

• https://www.linkedin.com/in/robert-hundt-2000/
• [email protected] (site specific email account)