Videos (Hands-on)

The Python version of a series for beginners: type a program into the Python Playground in your browser, run it, look at the result, and then learn what happened. Nothing has to be installed, so you can type along with the videos. The same episodes in C++ are on the C++ version of this page. They are published on the YouTube channel QUBO++ and collected, together with the C++ version, in the playlist QUBO++ Hands-on (English). Click an image to play the video on this page. Videos that explain QUBO++ systematically are on the Videos (Tutorials) page, and videos that solve concrete problems are on the Videos (Case Studies) page.

QUBO++ Hands-on #1: Making and Tidying Expressions (Python)(7:04, YouTube)Type a program into the Playground, run it, and learn from the output: the square of (2x+3y-2) in variables x and y, expanded automatically, tidied up with qbpp.simplify, qbpp.simplify_as_binary and qbpp.sqr, and evaluated for given values of the variables.

QUBO++ Hands-on #2: Solving with a Solver (Python)(4:57, YouTube)ExhaustiveSolver finds the values that make the square of (x+2y+3z-3) from episode 1 smallest: the output of print(sol), sol(x) and sol.energy, every best solution with best_energy_sols=0 and every solution with all_sols=1, then EasySolver, and a comparison of the two solvers.

QUBO++ Hands-on #3: Arrays of Variables (Python)(5:15, YouTube)An array of variables splits eight numbers into two groups with equal sums: shape in qbpp.var makes the array, qbpp.array and qbpp.sum give the sums P and Q of the two groups, and ExhaustiveSolver minimizes the square of (P − Q). sol(x) takes out the values of the array, all the best solutions are shown, and EasySolver splits forty numbers.

QUBO++ Hands-on #4: Constraints (Python)(5:02, YouTube)Choose from ten items the most valuable choice with a total weight of 50 or less (the knapsack problem): minimize the total value with a minus sign, add the weight constraint with qbpp.cons, and see how the value of a constraint and its weight act on the expression. sol.energy and f.cons(sol) are printed, a small weight lets a solution that breaks the constraint win, and a constraint on the number of items is added.