Quantum approximate optimization of non-planar graph problems on a planar superconducting processor

• Published in: Nature physics Vol. 17; no. 3; pp. 332 - 336
• Main Authors: Harrigan, Matthew P., Sung, Kevin J., Neeley, Matthew, Satzinger, Kevin J., Arute, Frank, Arya, Kunal, Atalaya, Juan, Bardin, Joseph C., Barends, Rami, Boixo, Sergio, Broughton, Michael, Buckley, Bob B., Buell, David A., Burkett, Brian, Bushnell, Nicholas, Chen, Yu, Chen, Zijun, Ben Chiaro, Collins, Roberto, Courtney, William, Demura, Sean, Dunsworth, Andrew, Eppens, Daniel, Fowler, Austin, Foxen, Brooks, Gidney, Craig, Giustina, Marissa, Graff, Rob, Habegger, Steve, Ho, Alan, Hong, Sabrina, Huang, Trent, Ioffe, L. B., Isakov, Sergei V., Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Kafri, Dvir, Kechedzhi, Kostyantyn, Kelly, Julian, Kim, Seon, Klimov, Paul V., Korotkov, Alexander N., Kostritsa, Fedor, Landhuis, David, Laptev, Pavel, Lindmark, Mike, Leib, Martin, Martin, Orion, Martinis, John M., McClean, Jarrod R., McEwen, Matt, Megrant, Anthony, Mi, Xiao, Mohseni, Masoud, Mruczkiewicz, Wojciech, Mutus, Josh, Naaman, Ofer, Neill, Charles, Neukart, Florian, Niu, Murphy Yuezhen, O’Brien, Thomas E., O’Gorman, Bryan, Ostby, Eric, Petukhov, Andre, Putterman, Harald, Quintana, Chris, Roushan, Pedram, Rubin, Nicholas C., Sank, Daniel, Skolik, Andrea, Smelyanskiy, Vadim, Strain, Doug, Streif, Michael, Szalay, Marco, Vainsencher, Amit, White, Theodore, Yao, Z. Jamie, Yeh, Ping, Zalcman, Adam, Zhou, Leo, Neven, Hartmut, Bacon, Dave, Lucero, Erik, Farhi, Edward, Babbush, Ryan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.03.2021; Nature Publishing Group
• Subjects: 639/705/1042; 639/766/483/481; Algorithms; Atomic; Classical and Continuum Physics; Combinatorial analysis; Complex Systems; Condensed Matter Physics; Gates (circuits); Graph theory; Graphs; Hardware; Logistics; Machine learning; Mathematical and Computational Physics; Microprocessors; Molecular; Optical and Plasma Physics; Optimization; Optimization algorithms; Physics; Physics and Astronomy; Quantum computers; Qubits (quantum computing); Superconductivity; Theoretical

Faster algorithms for combinatorial optimization could prove transformative for diverse areas such as logistics, finance and machine learning. Accordingly, the possibility of quantum enhanced optimization has driven much interest in quantum technologies. Here we demonstrate the application of the Go...