Quick Start

Try without installing: You can try PyQBPP immediately in the browser using the PyQBPP Playground — no installation required.

This page provides an overview of the Quick Start procedure for PyQBPP. More detailed instructions for installing PyQBPP on WSL on Windows 11 are available in Quick Start for Windows (WSL).

Installation

Install PyQBPP by following the instructions in Installation. For Windows users, see Quick Start for Windows (WSL).

PyQBPP is distributed on PyPI and can typically be installed with:

pip install pyqbpp

PyQBPP bundles the libqbpp*.so shared libraries and loads them at runtime via ctypes.

Create and run a sample program

Create a PyQBPP sample program

Create a PyQBPP sample program below and save as file test.py:

import pyqbpp as qbpp

a = qbpp.var("a")
b = qbpp.var("b")
c = qbpp.var("c")
f = qbpp.sqr(a + 2 * b + 3 * c - 4)
f = qbpp.simplify_as_binary(f)
print("f =", f)

solver = qbpp.EasySolver(f)
sol = solver.search(time_limit=10, target_energy=0)
print("sol =", sol)

This program expands and simplifies the following expression $f$ into a QUBO formula, then solves it using the EasySolver.

\[\begin{aligned} f &= (a+2b+3c-4)^2 \end{aligned}\]

The key API calls used in this example are:

qbpp.var(name): Creates a binary variable with the given name.
qbpp.sqr(expr): Returns the squared expression, expanded into a sum of terms.
qbpp.simplify_as_binary(expr): Applies binary (0/1) simplification rules such as x*x = x and x*~x = 0, and merges like terms.
qbpp.EasySolver(expr): Constructs a solver for the given QUBO expression.
solver.search(**kwargs): Runs the solver. Parameters such as time_limit (seconds) and target_energy are passed as keyword arguments.

Run the program

Run test.py as follows to display the expanded expression and the solution:

python3 test.py
f = 16 -7*a -12*b -15*c +4*a*b +6*a*c +12*b*c
sol = Sol(energy=0, {a: 1, b: 0, c: 1})

The first line of the output is the expanded QUBO form of $f$. The second line shows the solution found by the solver: the energy value (0 in this case, which matches the target_energy) together with the variable assignment $(a, b, c) = (1, 0, 1)$.

Next steps

Activate your license. See License Management for details.
Learn the basics of PyQBPP. Start with Basics in PyQBPP (Python).
Explore example PyQBPP programs in the Case Studies.