Charles Moussa
@mousscharles.bsky.social
Quantum Research Software Engineer working at Pasqal
chmoussa.github.io
chmoussa.github.io
Thanks to Pasqal for supporting this work!
May 26, 2025 at 8:42 AM
Thanks to Pasqal for supporting this work!
Also thanks to @pasqal.bsky.social for supporting
May 23, 2025 at 8:31 AM
Also thanks to @pasqal.bsky.social for supporting
pyqtorch repository: github.com/pasqal-io/py...
pyqtorch documentation: pasqal-io.github.io/pyqtorch/
pyqtorch documentation: pasqal-io.github.io/pyqtorch/
GitHub - pasqal-io/pyqtorch: PyTorch-based state vector simulator
PyTorch-based state vector simulator. Contribute to pasqal-io/pyqtorch development by creating an account on GitHub.
github.com
May 23, 2025 at 8:23 AM
pyqtorch repository: github.com/pasqal-io/py...
pyqtorch documentation: pasqal-io.github.io/pyqtorch/
pyqtorch documentation: pasqal-io.github.io/pyqtorch/
Also worth looking a few works from Bravyi on recursive QAOA. For instance arxiv.org/abs/2011.13420, where they had good results on MAX-k-CUT using classical simulation of level-1 rQAOA against the best
known generic classical algorithm based on rounding an SDP relaxation.
known generic classical algorithm based on rounding an SDP relaxation.
Hybrid quantum-classical algorithms for approximate graph coloring
We show how to apply the recursive quantum approximate optimization algorithm (RQAOA) to MAX-$k$-CUT, the problem of finding an approximate $k$-vertex coloring of a graph. We compare this proposal to ...
arxiv.org
January 9, 2025 at 3:23 PM
Also worth looking a few works from Bravyi on recursive QAOA. For instance arxiv.org/abs/2011.13420, where they had good results on MAX-k-CUT using classical simulation of level-1 rQAOA against the best
known generic classical algorithm based on rounding an SDP relaxation.
known generic classical algorithm based on rounding an SDP relaxation.
@mvscerezo.bsky.social I worked on a quantum-enhanced version of a heuristic (tabu search) where QAOA is used at a local sampler, from which I could obtain in principle a gain in QUBO problems. There are probably a few other similar works. link.springer.com/chapter/10.1...
Tabu-Driven Quantum Neighborhood Samplers
Combinatorial optimization is an important application targeted by quantum computing. However, near-term hardware constraints make quantum algorithms unlikely to be competitive when compared to high-p...
link.springer.com
January 9, 2025 at 3:23 PM
@mvscerezo.bsky.social I worked on a quantum-enhanced version of a heuristic (tabu search) where QAOA is used at a local sampler, from which I could obtain in principle a gain in QUBO problems. There are probably a few other similar works. link.springer.com/chapter/10.1...
1. I think the QAOA algorithm is quite useful. Especially it can exhibit a form of quantum supremacy (Quantum supremacy through the quantum approximate optimization algorithm, Farhi and Harrow), which can be quite useful when developing heuristics using it as a sampler.
January 8, 2025 at 6:34 PM
1. I think the QAOA algorithm is quite useful. Especially it can exhibit a form of quantum supremacy (Quantum supremacy through the quantum approximate optimization algorithm, Farhi and Harrow), which can be quite useful when developing heuristics using it as a sampler.