Installation#

QMAP is mainly developed as a C++ library that builds upon MQT Core, which forms the backbone of the MQT. In order to make the tool as accessible as possible, it comes with an easy-to-use Python interface.

We encourage installing QMAP via pip (preferably in a virtual environment):

(venv) $ pip install mqt.qmap

In most practical cases (under 64-bit Linux, MacOS incl. Apple Silicon, and Windows), this requires no compilation and merely downloads and installs a platform-specific pre-built wheel.

Note

In order to set up a virtual environment, you can use the following commands:

$ python3 -m venv venv
$ source venv/bin/activate

If you are using Windows, you can use the following commands instead:

$ python3 -m venv venv
$ venv\Scripts\activate.bat

It is recommended to make sure that you are using the latest version of pip, setuptools, and wheel before trying to install the project:

(venv) $ pip install --upgrade pip setuptools wheel

Warning

As of version 2.1.0, support for Python 3.7 has been officially dropped. We strongly recommend that users upgrade to a more recent version of Python to ensure compatibility and continue receiving updates and support. Thank you for your understanding.

A Detailed Walk Through#

First, save the following lines as ghz_3.py in a folder where you want to install QMAP and run the example:

from qiskit import QuantumCircuit
from qiskit.providers.fake_provider import FakeLondon
from mqt import qmap

# create your quantum circuit
circ = QuantumCircuit(3)
circ.h(0)
circ.cx(0, 1)
circ.cx(0, 2)
circ.measure_all()
print(circ.draw(fold=-1))

# compile circuit to 5-qubit London Architecture
circ_mapped, results = qmap.compile(circ, FakeLondon())
print(circ_mapped.draw(fold=-1))

# print the result
print("Additional Gates: %d" % (results.json()["statistics"]["additional_gates"]))

Then, the following snippet shows the installation process from setting up the virtual environment to running a small example program.

$ python3 -m venv venv
$ . venv/bin/activate
(venv) $ pip install -U pip setuptools wheel
(venv) $ pip install mqt.qmap
(venv) $ python3 ghz_3.py
        ┌───┐           ░ ┌─┐
   q_0: ┤ H ├──■────■───░─┤M├──────
        └───┘┌─┴─┐  │   ░ └╥┘┌─┐
   q_1: ─────┤ X ├──┼───░──╫─┤M├───
             └───┘┌─┴─┐ ░  ║ └╥┘┌─┐
   q_2: ──────────┤ X ├─░──╫──╫─┤M├
                  └───┘ ░  ║  ║ └╥┘
meas: 3/═══════════════════╩══╩══╩═
                           0  1  2

            ┌───┐┌───┐          ┌─┐
   q_0 -> 0 ┤ H ├┤ X ├──■───────┤M├──────
            └───┘└─┬─┘┌─┴─┐     └╥┘┌─┐
   q_1 -> 1 ───────■──┤ X ├──■───╫─┤M├───
                      └───┘┌─┴─┐ ║ └╥┘┌─┐
   q_2 -> 2 ───────────────┤ X ├─╫──╫─┤M├
                           └───┘ ║  ║ └╥┘
   q_3 -> 3 ─────────────────────╫──╫──╫─
                                 ║  ║  ║
   q_4 -> 4 ─────────────────────╫──╫──╫─
                                 ║  ║  ║
       c: 3/═════════════════════╩══╩══╩═
                                 1  0  2

Additional Gates: 1

Building from Source for Performance#

In order to get the best performance out of QMAP and enable platform-specific compiler optimizations that cannot be enabled on portable wheels, it is recommended to build the package from source via:

(venv) $ pip install mqt.qmap --no-binary mqt.qmap

This requires a C++ compiler compiler supporting C++17, a minimum CMake version of 3.19 and the SMT solver Z3. Z3 has to be installed and the dynamic linker has to be able to find the library. This can be accomplished in a multitude of ways:

  • Under Ubuntu 20.04 and newer: sudo apt-get install libz3-dev

  • Under macOS: brew install z3

  • Alternatively: pip install z3-solver in the virtual environment

  • Download pre-built binaries from https://github.com/Z3Prover/z3/releases and copy the files to the respective system directories

  • Build Z3 from source and install it to the system

The library is continuously tested under Linux, MacOS, and Windows using the latest available system versions for GitHub Actions. In order to access the latest build logs, visit mqt-qmap/actions/workflows/ci.yml.

Note

We noticed some issues when compiling with Microsoft’s MSCV compiler toolchain. If you want to start development on this project under Windows, consider using the clang compiler toolchain. A detailed description of how to set this up can be found here.