E-viri
Odprti dostop
-
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; Chiaro, Ben; Collins, Roberto; Courtney, William; Demura, Sean; Dunsworth, Andrew; Eppens, Daniel; Fowler, Austin; Brooks Foxen; Gidney, Craig; Giustina, Marissa; Graff, Rob; Habegger, Steve; Ho, Alan; Hong, Sabrina; Huang, Trent; Ioffe, L B; Isakov, Sergei V; Evan, Jeffrey; Zhang, Jiang; 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; Xiao Mi; 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; Ryan Babbush
arXiv.org, 01/2021Paper, Journal Article
We demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). Like past QAOA experiments, we study performance for problems defined on the (planar) connectivity graph of our hardware; however, we also apply the QAOA to the Sherrington-Kirkpatrick model and MaxCut, both high dimensional graph problems for which the QAOA requires significant compilation. Experimental scans of the QAOA energy landscape show good agreement with theory across even the largest instances studied (23 qubits) and we are able to perform variational optimization successfully. For problems defined on our hardware graph we obtain an approximation ratio that is independent of problem size and observe, for the first time, that performance increases with circuit depth. For problems requiring compilation, performance decreases with problem size but still provides an advantage over random guessing for circuits involving several thousand gates. This behavior highlights the challenge of using near-term quantum computers to optimize problems on graphs differing from hardware connectivity. As these graphs are more representative of real world instances, our results advocate for more emphasis on such problems in the developing tradition of using the QAOA as a holistic, device-level benchmark of quantum processors.
Avtor
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Vnos na polico
Trajna povezava
- URL:
Faktor vpliva
Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Baze podatkov, v katerih je revija indeksirana
Ime baze podatkov | Področje | Leto |
---|
Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
---|
Vir: Osebne bibliografije
in: SICRIS
To gradivo vam je dostopno v celotnem besedilu. Če kljub temu želite naročiti gradivo, kliknite gumb Nadaljuj.