Andreas Bärtschi

Nov 5, 2024 | nature.com | Elijah Pelofske |Andreas Bärtschi |John Golden

AbstractWe show that the quantum approximate optimization algorithm (QAOA) for higher-order, random coefficient, heavy-hex compatible spin glass Ising models has strong parameter concentration across problem sizes from 16 up to 127 qubits for p = 1 up to p = 5, which allows for computationally efficient parameter transfer of QAOA angles. Matrix product state (MPS) simulation is used to compute noise-free QAOA performance.

Feb 15, 2024 | arxiv.org | John Golden |Andreas Bärtschi |Stephan Eidenbenz

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