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Quantum Approximate Optimization Algorithm (QAOA) for Quadratic Unconstrained Binary Optimization with PyTorch

In the attached Jupyter notebook, I have presented the Quantum Approximate Optimization Algorithm (QAOA) [1] for a Quadratic Unconstrained Binary Optimization (QUBO) problem. A QUBO belongs to the NP-hard class, and it is equivalent to find the minimum energy (ground) state of a spin (Ising) Hamiltonian [2]. Here, the implementation of QAOA is done using PyTorch.

Problem instance

prob_qaoa

Algorithm: QAOA

QAOA

Solution

sol_qaoa

[1] E. Farhi, J. Goldstone, and S. Gutmann, A Quantum Approximate Optimization Algorithm

[2] Lucas A (2014) Ising formulations of many NP problems. Front. Physics 2:5.

[3] Marcello Benedetti et al 2019 Quantum Sci. Technol. 4 043001