Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem. Shaydulin, R., Li, C., Chakrabarti, S., Herman, D., Kumar, N., Larson, J., Lykov, D., Minssen, P., Sun, Y., Alexeev, Y., DeCross, M., Dreiling, J. M., Gaebler, J. P., Gatterman, T. M., Gerber, J. A., Gilmore, K., Gresh, D., Hewitt, N., Horst, C. V., Hu, S., Johansen, J., Matheny, M., Mengle, T., Mills, M., Moses, S. A., Neyenhuis, B., Siegfried, P., Yalovetzky, R., & Pistoia, M. Science Advances, 2024.
Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem [link]Paper  doi  bibtex   
@article{Shaydulin2024,
  doi = {10.1126/sciadv.adm6761},
  adoi = {10.48550/arXiv.2308.02342},
  url = {https://arxiv.org/abs/2308.02342},
  author = {Ruslan Shaydulin and Changhao Li and Shouvanik Chakrabarti and Dylan Herman and Niraj Kumar and Jeffrey Larson and Danylo Lykov and Pierre Minssen and Yue Sun and Yuri Alexeev and Matthew DeCross and Joan M. Dreiling and John P. Gaebler and Thomas M. Gatterman and Justin A. Gerber and Kevin Gilmore and Dan Gresh and Nathan Hewitt and Chandler V. Horst and Shaohan Hu and Jacob Johansen and Mitchell Matheny and Tanner Mengle and Michael Mills and Steven A. Moses and Brian Neyenhuis and Peter Siegfried and Romina Yalovetzky and Marco Pistoia},
  title = {Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem},
  year = {2024},
  journal = {Science Advances},
  number = {22},
  volume = {10},
}

Downloads: 0