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Purification-based quantum error mitigation of pair-correlated electron simulations
Thomas E. O’Brien, Gian-Luca Anselmetti, Fotios Gkritsis, Vincent E. Elfving, Stefano Polla, William J. Huggins, Oumarou Oumarou, Kostyantyn Kechedzhi, Dmitry A. Abanin, Rajeev Acharya, I. L. Aleǐner, R. M. Allen, T. I. Andersen, K. R. Anderson, M. Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Juan Atalaya, Dave Bacon, Joseph C. Bardin, Andreas Bengtsson, Sergio Boixo, Gina Bortoli, Alexandre Bourassa, Jenna Bovaird, L. Brill, Michael Broughton, Bob B. Buckley, David A. Buell, Tim Burger, Brian Burkett, Nicholas Bushnell, Juan Campero, Yu Chen, Zijun Chen, B. Chiaro, Desmond Chik, Josh Cogan, Roberto Collins, Paul Conner, William Courtney, Alexander L. Crook, Ben Curtin, Dripto M. Debroy, Alexander Del Toro Barba, Sean Demura, Ilya Drozdov, A. Dunsworth, Daniel Eppens, Catherine Erickson, Lara Faoro, Edward Farhi, Reza Fatemi, Vinicius Ferreira, Leslie Flores Burgos, Ebrahim Forati, Austin G. Fowler, Brooks Foxen, William Giang, Craig Gidney, D. Gilboa, Marissa Giustina, Raja Gosula, Alejandro Grajales Dau, Jonathan A. Gross, Steve Habegger, Michael C. Hamilton, Monica Hansen, Matthew P. Harrigan, Sean D. Harrington, Paula Heu, Jeremy Hilton, M. R. Hoffmann, Sabrina Hong, Trent Huang, Ashley Huff, L. B. Ioffe, Sergei V. Isakov, Justin Iveland, E. Jeffrey, Jiang Zhang, Cody Jones, Pavol Juhás, Dvir Kafri, J. Kelly, Tanuj Khattar, Mostafa Khezri, Marika Kieferova, Seon Kim, Paul V. Klimov, Andrey Klots, Alexander N. Korotkov, Fedor Kostritsa, John Mark Kreikebaum, David Landhuis, Pavel Laptev, Kim-Ming Lau, Lily Laws, Joonho Lee, Brian Lester, Alexander T. Lill, Wayne Liu, W. Livingston, Aditya Locharla, Erik Lucero, Fionn D. Malone, Salvatore Mandrà, Orion Martin, Steven W. Martin, Jarrod R. McClean, Trevor McCourt, Matthew McEwen, A. Megrant, Xiao Mi, Kevin C. Miao, Amanda Mieszala, Masoud Mohseni, Shirin Montazeri, Alexis Morvan, Ramis Movassagh, Wojciech Mruczkiewicz, Ofer Naaman, M. Neeley, Charles Neill, Ani Nersisyan, Hartmut Neven, Michael Newman, Jiun How Ng, A. Nguyen, Murray Nguyen, Murphy Yuezhen Niu, Seun Omonije, Alex Opremcak, Andre Petukhov, R. Potter, Leonid P. Pryadko, Chris Quintana, Charles Rocque, P. Roushan, Negar Saei, D. Sank, Kannan Sankaragomathi, Kevin J. Satzinger, Henry F. Schurkus, Michael J. Shearn, Aaron Shorter, Noah Shutty, Shvarts Vladimir, Jindra Skruzny, Vadim Smelyanskiy, W. Clarke Smith, Rolando Somma, G. Sterling, Doug Strain, Marco Szalay, Douglas Thor, A. Torres, Guifré Vidal, Benjamin Villalonga, Catherine Vollgraff Heidweiller, T. White, Bryan W. K. Woo, Cheng Xing, Z. Jamie Yao, P. Yeh, Juhwan Yoo, Grayson Young, Adam Zalcman, Yaxing Zhang, Ningfeng Zhu, Nicholas Zobrist, Christian Gogolin, Ryan Babbush, Nicholas C. Rubin
Bibliographic record
VenueResearch Square · 2022
Typepreprint
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsUniversité de Sherbrooke
FundersKavli Institute for Theoretical Physics, University of California, Santa BarbaraNational Science Foundation
KeywordsElectronQuantumStatistical physicsPhysicsComputer scienceQuantum mechanics
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.039
GPT teacher head0.360
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
Study designSimulation or modeling
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations3
Published2022
Admission routes1
Has abstractno