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ORCIDNathan Wiebe
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2020 – today
- 2024
[j21]Gumaro Rendon, Jacob Watkins, Nathan Wiebe:
Improved Accuracy for Trotter Simulations Using Chebyshev Interpolation. Quantum 8: 1266 (2024)- 2023
- [j20]Mohammad Hassan Khatami
, Udson C. Mendes, Nathan Wiebe, Philip M. Kim:
Gate-based quantum computing for protein design. PLoS Comput. Biol. 19(4) (2023) - [j19]Nishchay Suri, Joseph Barreto, Stuart Hadfield, Nathan Wiebe, Filip A. Wudarski, Jeffrey Marshall:
Two-Unitary Decomposition Algorithm and Open Quantum System Simulation. Quantum 7: 1002 (2023) - [j18]Matthew Hagan, Nathan Wiebe:
Composite Quantum Simulations. Quantum 7: 1181 (2023) - [c17]Ryan Babbush, Dominic W. Berry, Robin Kothari, Rolando D. Somma, Nathan Wiebe:
Exponential quantum speedup in simulating coupled classical oscillators*. FOCS 2023: 405-414 - [c16]Samuel Alexander Stein, Nathan Wiebe, Yufei Ding, James A. Ang, Ang Li:
Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum. ISCA 2023: 8:1-8:13 - [i26]Mohsen Bagherimehrab, Kouhei Nakaji, Nathan Wiebe, Alán Aspuru-Guzik:
Fast quantum algorithm for differential equations. CoRR abs/2306.11802 (2023) - 2022
- [j17]Torin F. Stetina, Anthony Ciavarella, Xiaosong Li, Nathan Wiebe:
Simulating Effective QED on Quantum Computers. Quantum 6: 622 (2022) - [j16]Alessandro Roggero, Jakub Filipek, Shih-Chieh Hsu, Nathan Wiebe:
Quantum Machine Learning with SQUID. Quantum 6: 727 (2022) - [j15]Abhishek Rajput, Alessandro Roggero, Nathan Wiebe:
Hybridized Methods for Quantum Simulation in the Interaction Picture. Quantum 6: 780 (2022) - [c15]Timothy J. Stavenger, Eleanor Crane, Kevin Smith, Christopher T. Kang, Steven M. Girvin, Nathan Wiebe:
C2QA - Bosonic Qiskit. HPEC 2022: 1-8 - [c14]Nathan Wiebe:
QCCC 2022 Keynote Talk: Hybrid Quantum / Classical Algorithms for Machine Learning. IPDPS Workshops 2022: 599 - [c13]Samuel Alexander Stein, Nathan Wiebe, James A. Ang, Ang Li:
Improving Variational Quantum Algorithms performance through Weighted Quantum Ensembles. IPDPS Workshops 2022: 616-617 - [c12]Samuel Alexander Stein, Nathan Wiebe, James A. Ang, Ang Li:
Benchmarking Quantum Processor Performance through Quantum Distance Metrics Over An Algorithm Suite. IPDPS Workshops 2022: 618-624 - [c11]Samuel Alexander Stein, Nathan Wiebe, Yufei Ding, Bo Peng, Karol Kowalski, Nathan A. Baker, James A. Ang, Ang Li:
EQC: ensembled quantum computing for variational quantum algorithms. ISCA 2022: 59-71 - [i25]Priyanka Mukhopadhyay, Nathan Wiebe, Hong-Tao Zhang:
Synthesizing efficient circuits for Hamiltonian simulation. CoRR abs/2209.03478 (2022) - [i24]Timothy J. Stavenger, Eleanor Crane, Kevin Smith, Christopher T. Kang, Steven M. Girvin, Nathan Wiebe:
Bosonic Qiskit. CoRR abs/2209.11153 (2022) - 2021
- [i23]Brian Flynn, Antonio Andrea Gentile, Nathan Wiebe, Raffaele Santagati, Anthony Laing:
Quantum Model Learning Agent: characterisation of quantum systems through machine learning. CoRR abs/2112.08409 (2021) - 2020
- [j14]Dominic W. Berry, Andrew M. Childs, Yuan Su, Xin Wang, Nathan Wiebe:
Time-dependent Hamiltonian simulation withL1-norm scaling. Quantum 4: 254 (2020) - [j13]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) - [j12]Alexander F. Shaw, Pavel Lougovski, Jesse R. Stryker, Nathan Wiebe:
Quantum Algorithms for Simulating the Lattice Schwinger Model. Quantum 4: 306 (2020) - [j11]Olivia Di Matteo, John King Gamble, Christopher E. Granade, Kenneth M. Rudinger, Nathan Wiebe:
Operational, gauge-free quantum tomography. Quantum 4: 364 (2020) - [i22]Antonio A. Gentile, Brian Flynn, Sebastian Knauer, Nathan Wiebe, Stefano Paesani, Christopher E. Granade, John G. Rarity, Raffaele Santagati, Anthony Laing:
Learning models of quantum systems from experiments. CoRR abs/2002.06169 (2020) - [i21]Yu Tong, Dong An, Nathan Wiebe, Lin Lin:
Fast inversion, preconditioned quantum linear system solvers, and fast evaluation of matrix functions. CoRR abs/2008.13295 (2020) - [i20]Ramakrishna Tipireddy, Nathan Wiebe:
Bayesian phase estimation with adaptive grid refinement. CoRR abs/2009.07898 (2020) - [i19]Carlos Ortiz Marrero, Mária Kieferová, Nathan Wiebe:
Entanglement Induced Barren Plateaus. CoRR abs/2010.15968 (2020)
2010 – 2019
- 2019
- [j10]Andrew Tranter, Peter J. Love, Florian Mintert, Nathan Wiebe, Peter V. Coveney:
Ordering of Trotterization: Impact on Errors in Quantum Simulation of Electronic Structure. Entropy 21(12): 1218 (2019) - [j9]Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli:
LUT-Based Hierarchical Reversible Logic Synthesis. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(9): 1675-1688 (2019) - [c10]András Gilyén, Srinivasan Arunachalam, Nathan Wiebe:
Optimizing quantum optimization algorithms via faster quantum gradient computation. SODA 2019: 1425-1444 - [c9]András Gilyén, Yuan Su, Guang Hao Low, Nathan Wiebe:
Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics. STOC 2019: 193-204 - [c8]John King Gamble, Christopher E. Granade, Nathan Wiebe:
Bayesian ACRONYM Tuning. TQC 2019: 7:1-7:19 - [i18]Guang Hao Low, Nicholas P. Bauman, Christopher E. Granade, Bo Peng, Nathan Wiebe, Eric J. Bylaska, Dave Wecker, Sriram Krishnamoorthy, Martin Roetteler, Karol Kowalski, Matthias Troyer, Nathan A. Baker:
Q# and NWChem: Tools for Scalable Quantum Chemistry on Quantum Computers. CoRR abs/1904.01131 (2019) - [i17]Nathan Wiebe, Leonard Wossnig:
Generative training of quantum Boltzmann machines with hidden units. CoRR abs/1905.09902 (2019) - [i16]Dominic W. Berry, Andrew M. Childs, Yuan Su, Xin Wang, Nathan Wiebe:
Time-dependent Hamiltonian simulation with $L^1$-norm scaling. CoRR abs/1906.07115 (2019) - [i15]Andrew M. Childs, Yuan Su, Minh C. Tran, Nathan Wiebe, Shuchen Zhu:
A Theory of Trotter Error. CoRR abs/1912.08854 (2019) - 2018
- [c7]Giulia Meuli, Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli:
A best-fit mapping algorithm to facilitate ESOP-decomposition in Clifford+T quantum network synthesis. ASP-DAC 2018: 664-669 - [i14]András Gilyén, Yuan Su, Guang Hao Low, Nathan Wiebe:
Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics. CoRR abs/1806.01838 (2018) - 2017
- [j8]Jacob D. Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, Seth Lloyd:
Quantum machine learning. Nat. 549(7671): 195-202 (2017) - [j7]Nathan Wiebe, Christopher Grandade:
Can small quantum systems learn. Quantum Inf. Comput. 17(7&8): 567-594 (2017) - [c6]Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli:
Hierarchical Reversible Logic Synthesis Using LUTs. DAC 2017: 78:1-78:6 - [c5]Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli:
Design automation and design space exploration for quantum computers. DATE 2017: 470-475 - [c4]Martin Rötteler, Krysta M. Svore, Dave Wecker, Nathan Wiebe:
Design automation for quantum architectures. DATE 2017: 1312-1317 - [i13]Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli:
Logic Synthesis for Quantum Computing. CoRR abs/1706.02721 (2017) - [i12]András Gilyén, Srinivasan Arunachalam, Nathan Wiebe:
Optimizing quantum optimization algorithms via faster quantum gradient computation. CoRR abs/1711.00465 (2017) - [i11]Nathan Wiebe, Ram Shankar Siva Kumar:
Hardening Quantum Machine Learning Against Adversaries. CoRR abs/1711.06652 (2017) - [i10]Iris Agresti, Niko Viggianiello, Fulvio Flamini, Nicolò Spagnolo, Andrea Crespi, Roberto Osellame, Nathan Wiebe, Fabio Sciarrino:
Pattern recognition techniques for Boson Sampling validation. CoRR abs/1712.06863 (2017) - [i9]Alessandro Lumino, Emanuele Polino, Adil S. Rab, Giorgio Milani, Nicolò Spagnolo, Nathan Wiebe, Fabio Sciarrino:
Experimental Phase Estimation Enhanced By Machine Learning. CoRR abs/1712.07570 (2017) - 2016
- [j6]Nathan Wiebe, Martin Roetteler:
Quantum arithmetic and numerical analysis using Repeat-Until-Success circuits. Quantum Inf. Comput. 16(1&2): 134-178 (2016) - [j5]Nathan Wiebe, Ashish Kapoor, Krysta M. Svore:
Quantum deep learning. Quantum Inf. Comput. 16(7&8): 541-587 (2016) - [c3]Ashish Kapoor, Nathan Wiebe, Krysta M. Svore:
Quantum Perceptron Models. NIPS 2016: 3999-4007 - [i8]Nathan Wiebe, Ashish Kapoor, Krysta M. Svore:
Quantum Perceptron Models. CoRR abs/1602.04799 (2016) - [i7]Mathias Soeken, Martin Rötteler, Nathan Wiebe, Giovanni De Micheli:
Design Automation and Design Space Exploration for Quantum Computers. CoRR abs/1612.00631 (2016) - 2015
- [j4]Nathan Wiebe, Ashish Kapoor, Krysta M. Svore:
Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning. Quantum Inf. Comput. 15(3&4): 316-356 (2015) - [j3]David Poulin, Matthew B. Hastings, Dave Wecker, Nathan Wiebe, Andrew C. Doberty, Matthias Troyer:
The Trotter step size required for accurate quantum simulation of quantum chemistry. Quantum Inf. Comput. 15(5&6): 361-384 (2015) - [i6]Nathan Wiebe, Ashish Kapoor, Christopher E. Granade, Krysta M. Svore:
Quantum Inspired Training for Boltzmann Machines. CoRR abs/1507.02642 (2015) - [i5]Nathan Wiebe, Christopher E. Granade, Ashish Kapoor, Krysta M. Svore:
Bayesian inference via rejection filtering. CoRR abs/1511.06458 (2015) - [i4]Ilia N. Zintchenko, Matthew B. Hastings, Nathan Wiebe, Ethan Brown, Matthias Troyer:
Partial Reinitialisation for Optimisers. CoRR abs/1512.03025 (2015) - 2014
- [j2]Nathan Wiebe:
Using Quantum Computing to Learn Physics. Bull. EATCS 112 (2014) - [i3]Nathan Wiebe, Martin Roetteler:
Quantum arithmetic and numerical analysis using Repeat-Until-Success circuits. CoRR abs/1406.2040 (2014) - [i2]Nathan Wiebe, Ashish Kapoor, Krysta M. Svore:
Quantum Deep Learning. CoRR abs/1412.3489 (2014) - 2013
- [c2]Christopher E. Granade, Christopher Ferrie, Nathan Wiebe, David G. Cory:
Robust Online Hamiltonian Learning. TQC 2013: 106-125 - 2012
- [j1]Andrew M. Childs, Nathan Wiebe:
Hamiltonian simulation using linear combinations of unitary operations. Quantum Inf. Comput. 12(11-12): 901-924 (2012) - [i1]Christopher E. Granade, Christopher Ferrie, Nathan Wiebe, David G. Cory:
Robust Online Hamiltonian Learning. CoRR abs/1207.1655 (2012)
2000 – 2009
- 2007
- [c1]Nathan Wiebe, John Anderson:
A local approach to developing grounded spatial references in multi-robot systems. IROS 2007: 1357-1364
Coauthor Index
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last updated on 2024-10-07 22:12 CEST by the dblp team
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