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ORCIDRyan Babbush
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- affiliation: Google Quantum AI, Mountain View, CA, USA
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2020 – today
- 2025
[j6]Nathan Lacroix
, Alexandre Bourassa, Francisco J. H. Heras, L. M. Zhang, Johannes Bausch, Andrew W. Senior, Thomas Edlich, Noah Shutty, V. Sivak, Andreas Bengtsson, Matthew J. McEwen, O. Higgott, Dvir Kafri, Jahan Claes, Alexis Morvan, Zijun Chen, Adam Zalcman, S. Madhuk, R. Acharya, Laleh Aghababaie Beni, G. Aigeldinger, R. Alcaraz, Trond I. Andersen, Markus Ansmann, Frank Arute, Kunal Arya, A. Asfaw, Juan Atalaya, Ryan Babbush, B. Ballard, Joseph C. Bardin, A. Bilmes, Sam Blackwell, J. Bovaird, D. Bowers, L. Brill, M. Broughton, D. A. Browne, B. Buchea, B. B. Buckley, T. Burger, Brian Burkett, N. Bushnell, A. Cabrera, J. Campero, Hung-Shen Chang, Benjamin Chiaro, Liang-Ying Chih, A. Y. Cleland, J. Cogan, Roberto Collins, P. Conner, W. Courtney, A. L. Crook, Benjamin Curtin, Sayan Das, Sean Demura, L. De Lorenzo, Agustin Di Paolo, P. Donohoe, Ilya K. Drozdov, Andrew Dunsworth, A. Eickbusch, A. Moshe Elbag, M. Elzouka, Catherine Erickson, V. S. Ferreira, L. Flores Burgos, E. Forati, Austin G. Fowler, Brooks Foxen, S. Ganjam, G. Garcia, R. Gasca, Élie Genois, W. Giang, Dar Gilboa, Raja Gosula, A. Grajales Dau, D. Graumann, Amy L. Greene, Jonathan A. Gross, T. Ha, Stephen Habegger, M. Hansen, Matthew P. Harrigan, Sean D. Harrington, S. Heslin, P. Heu, R. Hiltermann, J. Hilton, Sabrina Hong, H.-Y. Huang, A. Huff, William J. Huggins, Evan Jeffrey, Zhang Jiang, X. Jin, C. Joshi, Pavol Juhas, A. Kabel, H. Kang, Amir H. Karamlou, Kostyantyn Kechedzhi, T. Khaire, Tanuj Khattar, M. Khezri, S. Kim, Paul V. Klimov, B. Kobrin, Alexander N. Korotkov, F. Kostritsa, J. Mark Kreikebaum, V. D. Kurilovich, David Landhuis, T. Lange-Dei, B. W. Langley, P. Laptev, K.-M. Lau, J. Ledford, K. Lee, Brian Lester, Loïck Le Guevel, W. Yan Li, Y. Li, A. T. Lill, William P. Livingston, Aditya Locharla, Erik Lucero, D. Lundahl, A. Lunt, A. Maloney, Salvatore Mandrà, L. S. Martin, O. Martin, C. Maxfield, Jarrod R. McClean, S. Meeks, Anthony Megrant, K. C. Miao, R. Molavi, S. Molina, Shirin Montazeri, Ramis Movassagh, Charles J. Neill, Michael Newman, A. Nguyen, M. Nguyen, C.-H. Ni, Murphy Yuezhen Niu, L. Oas, W. D. Oliver, R. Orosco, K. Ottosson, A. Pizzuto, R. Potter, O. Pritchard, Chris Quintana, G. Ramachandran, Matthew J. Reagor, R. Resnick, David M. Rhodes, G. Roberts, E. Rosenberg, E. Rosenfeld, E. Rossi, Pedram Roushan, Kannan A. Sankaragomathi, Henry F. Schurkus, M. J. Shearn, A. Shorter, V. Shvarts, S. Small, W. Clarke Smith, S. Springer, George Sterling, J. Suchard, Aaron Szasz, A. Sztein, D. Thor, E. Tomita, A. Torres, Mustafa Mert Torunbalci, A. Vaishnav, J. Vargas, S. Vdovichev, G. Vidal, Catherine Vollgraff Heidweiller, S. Waltman, Jonathan Waltz, S. X. Wang, Brayden Ware, T. Weidel, Ted White, K. Wong, Bryan W. K. Woo, Madison Woodson, C. Xing, Z. Jamie Yao, Ping Yeh, B. Ying, J. Yoo, Noureldin Yosri, G. Young, Y. Zhang, Ningfeng Zhu, N. Zobrist, Hartmut Neven, Pushmeet Kohli, Alex Davies, Sergio Boixo, Julian Kelly, Cody Jones, Craig Gidney, Kevin J. Satzinger:
Scaling and logic in the colour code on a superconducting quantum processor. Nat. 645(8081): 614-619 (2025)- [j5]Stephen P. Jordan, Noah Shutty, Mary Wootters, Adam Zalcman, Alexander Schmidhuber, Robbie King, Sergei V. Isakov, Tanuj Khattar, Ryan Babbush:
Optimization by decoded quantum interferometry. Nat. 646(8086): 831-836 (2025) - [j4]Pedro C. S. Costa, Dong An, Ryan Babbush, Dominic W. Berry:
The discrete adiabatic quantum linear system solver has lower constant factors than the randomized adiabatic solver. Quantum 9: 1887 (2025) - [c4]Alexander Schmidhuber, Ryan O'Donnell, Robin Kothari, Ryan Babbush:
Quartic quantum speedups for planted inference. SODA 2025: 905-913 - [c3]Robbie King, David Gosset, Robin Kothari, Ryan Babbush:
Triply efficient shadow tomography. SODA 2025: 914-946 - [i11]Hsin-Yuan Huang, Michael Broughton, Norhan Eassa, Hartmut Neven, Ryan Babbush, Jarrod R. McClean:
Generative quantum advantage for classical and quantum problems. CoRR abs/2509.09033 (2025) - [i10]Robbie King, Robin Kothari, Ryan Babbush, Sergio Boixo, Kostyantyn Kechedzhi, Thomas E. O'Brien, Vadim Smelyanskiy:
A simplified version of the quantum OTOC(2) problem. CoRR abs/2510.19751 (2025) - 2024
- [i9]Alexander Schmidhuber, Ryan O'Donnell, Robin Kothari, Ryan Babbush:
Quartic quantum speedups for planted inference. CoRR abs/2406.19378 (2024) - [i8]Matthew P. Harrigan, Tanuj Khattar, Charles Yuan, Anurudh Peduri, Noureldin Yosri, Fionn D. Malone, Ryan Babbush, Nicholas C. Rubin:
Expressing and Analyzing Quantum Algorithms with Qualtran. CoRR abs/2409.04643 (2024) - 2023
- [c2]Ryan Babbush, Dominic W. Berry, Robin Kothari, Rolando D. Somma, Nathan Wiebe:
Exponential quantum speedup in simulating coupled classical oscillators*. FOCS 2023: 405-414 - 2021
- [j3]Nicholas C. Rubin, Klaas Gunst, Alec F. White, Leon Freitag, Kyle Throssell, Garnet Kin-Lic Chan, Ryan Babbush, Toru Shiozaki:
The Fermionic Quantum Emulator. Quantum 5: 568 (2021) - [i7]Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean:
Quantum advantage in learning from experiments. CoRR abs/2112.00778 (2021) - 2020
- [j2]Ian D. Kivlichan, Craig Gidney, Dominic W. Berry, Nathan Wiebe, Jarrod R. McClean, Wei Sun, Zhang Jiang, Nicholas C. Rubin, Austin G. Fowler, Alán Aspuru-Guzik, Hartmut Neven, Ryan Babbush:
Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization. Quantum 4: 296 (2020) - [i6]Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, Jarrod R. McClean:
Power of data in quantum machine learning. CoRR abs/2011.01938 (2020) - [i5]Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles:
Variational Quantum Algorithms. CoRR abs/2012.09265 (2020)
2010 – 2019
- 2019
- [j1]Dominic W. Berry, Craig Gidney, Mario Motta, Jarrod R. McClean, Ryan Babbush:
Qubitization of Arbitrary Basis Quantum Chemistry Leveraging Sparsity and Low Rank Factorization. Quantum 3: 208 (2019) - [i4]Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, Masoud Mohseni:
Learning to learn with quantum neural networks via classical neural networks. CoRR abs/1907.05415 (2019) - 2018
- [i3]Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, Hartmut Neven:
Barren plateaus in quantum neural network training landscapes. CoRR abs/1803.11173 (2018) - 2014
- [c1]Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D. Skeel, Hartmut Neven:
Bayesian Sampling Using Stochastic Gradient Thermostats. NIPS 2014: 3203-3211 - [i2]Ryan Babbush, Vasil S. Denchev, Nan Ding, Sergei Isakov, Hartmut Neven:
Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing. CoRR abs/1406.4203 (2014) - [i1]Bryan O'Gorman, Alejandro Perdomo-Ortiz, Ryan Babbush, Alán Aspuru-Guzik, Vadim Smelyanskiy:
Bayesian Network Structure Learning Using Quantum Annealing. CoRR abs/1407.3897 (2014)
Coauthor Index
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