Nathan Wiebe

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 57

Top Topics

Boltzmann Machines

Quantum Computing

Design Automation

Machine Learning

Top Venues

Quantum Inf. Comput.

IPDPS Workshops

Publications

Gumaro Rendon, Jacob Watkins, Nathan Wiebe
Improved Accuracy for Trotter Simulations Using Chebyshev Interpolation. Quantum 8 (2024)
Ryan Babbush, Dominic W. Berry, Robin Kothari, Rolando D. Somma, Nathan Wiebe
. FOCS (2023)
Matthew Hagan, Nathan Wiebe
Composite Quantum Simulations. Quantum 7 (2023)
Samuel Alexander Stein, Nathan Wiebe, Yufei Ding, James Ang, Ang Li
Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum. ISCA (2023)
Mohammad Hassan Khatami, Udson C. Mendes, Nathan Wiebe, Philip M. Kim
Gate-based quantum computing for protein design. PLoS Comput. Biol. 19 (4) (2023)
Mohsen Bagherimehrab, Kouhei Nakaji, Nathan Wiebe, Alán Aspuru-Guzik
Fast quantum algorithm for differential equations. CoRR (2023)
Nishchay Suri, Joseph Barreto, Stuart Hadfield, Nathan Wiebe, Filip A. Wudarski, Jeffrey Marshall
Two-Unitary Decomposition Algorithm and Open Quantum System Simulation. Quantum 7 (2023)
Timothy J. Stavenger, Eleanor Crane, Kevin Smith, Christopher T. Kang, Steven M. Girvin, Nathan Wiebe
C2QA - Bosonic Qiskit. HPEC (2022)
Abhishek Rajput, Alessandro Roggero, Nathan Wiebe
Hybridized Methods for Quantum Simulation in the Interaction Picture. Quantum 6 (2022)
Torin F. Stetina, Anthony Ciavarella, Xiaosong Li, Nathan Wiebe
Simulating Effective QED on Quantum Computers. Quantum 6 (2022)
Nathan Wiebe
QCCC 2022 Keynote Talk: Hybrid Quantum / Classical Algorithms for Machine Learning. IPDPS Workshops (2022)
Priyanka Mukhopadhyay, Nathan Wiebe, Hong-Tao Zhang
Synthesizing efficient circuits for Hamiltonian simulation. CoRR (2022)
Samuel Alexander Stein, Nathan Wiebe, Yufei Ding, Bo Peng, Karol Kowalski, Nathan A. Baker, James Ang, Ang Li
EQC: ensembled quantum computing for variational quantum algorithms. ISCA (2022)
Samuel Alexander Stein, Nathan Wiebe, James Ang, Ang Li
Improving Variational Quantum Algorithms performance through Weighted Quantum Ensembles. IPDPS Workshops (2022)
Timothy J. Stavenger, Eleanor Crane, Kevin Smith, Christopher T. Kang, Steven M. Girvin, Nathan Wiebe
Bosonic Qiskit. CoRR (2022)
Samuel Alexander Stein, Nathan Wiebe, James Ang, Ang Li
Benchmarking Quantum Processor Performance through Quantum Distance Metrics Over An Algorithm Suite. IPDPS Workshops (2022)
Alessandro Roggero, Jakub Filipek, Shih-Chieh Hsu, Nathan Wiebe
Quantum Machine Learning with SQUID. Quantum 6 (2022)
Brian Flynn, Antonio Andrea Gentile, Nathan Wiebe, Raffaele Santagati, Anthony Laing
Quantum Model Learning Agent: characterisation of quantum systems through machine learning. CoRR (2021)
Yu Tong, Dong An, Nathan Wiebe, Lin Lin
Fast inversion, preconditioned quantum linear system solvers, and fast evaluation of matrix functions. CoRR (2020)
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 (2020)
Ian D. Kivlichan, Craig Gidney, Dominic W. Berry, Nathan Wiebe, Jarrod R. McClean, Wei Sun, Zhang Jiang, Nicholas 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 (2020)
Carlos Ortiz Marrero, Mária Kieferová, Nathan Wiebe
Entanglement Induced Barren Plateaus. CoRR (2020)
Ramakrishna Tipireddy, Nathan Wiebe
Bayesian phase estimation with adaptive grid refinement. CoRR (2020)
Dominic W. Berry, Andrew M. Childs, Yuan Su, Xin Wang, Nathan Wiebe
Time-dependent Hamiltonian simulation withL1-norm scaling. Quantum 4 (2020)
Olivia Di Matteo, John Gamble, Christopher E. Granade, Kenneth M. Rudinger, Nathan Wiebe
Operational, gauge-free quantum tomography. Quantum 4 (2020)
Alexander F. Shaw, Pavel Lougovski, Jesse R. Stryker, Nathan Wiebe
Quantum Algorithms for Simulating the Lattice Schwinger Model. Quantum 4 (2020)
Andrew M. Childs, Yuan Su, Minh C. Tran, Nathan Wiebe, Shuchen Zhu
A Theory of Trotter Error. CoRR (2019)
András Gilyén, Yuan Su, Guang Hao Low, Nathan Wiebe
Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics. STOC (2019)
John Gamble, Christopher E. Granade, Nathan Wiebe
Bayesian ACRONYM Tuning. TQC (2019)
Nathan Wiebe, Leonard Wossnig
Generative training of quantum Boltzmann machines with hidden units. CoRR (2019)
Dominic W. Berry, Andrew M. Childs, Yuan Su, Xin Wang, Nathan Wiebe
Time-dependent Hamiltonian simulation with $L^1$-norm scaling. CoRR (2019)
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) (2019)
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) (2019)
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 (2019)
András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
Optimizing quantum optimization algorithms via faster quantum gradient computation. SODA (2019)
András Gilyén, Yuan Su, Guang Hao Low, Nathan Wiebe
Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics. CoRR (2018)
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)
András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
Optimizing quantum optimization algorithms via faster quantum gradient computation. CoRR (2017)
Alessandro Lumino, Emanuele Polino, Adil S. Rab, Giorgio Milani, Nicolò Spagnolo, Nathan Wiebe, Fabio Sciarrino
Experimental Phase Estimation Enhanced By Machine Learning. CoRR (2017)
Nathan Wiebe, Ram Shankar Siva Kumar
Hardening Quantum Machine Learning Against Adversaries. CoRR (2017)
Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli
Logic Synthesis for Quantum Computing. CoRR (2017)
Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli
Design automation and design space exploration for quantum computers. DATE (2017)
Iris Agresti, Niko Viggianiello, Fulvio Flamini, Nicolò Spagnolo, Andrea Crespi, Roberto Osellame, Nathan Wiebe, Fabio Sciarrino
Pattern recognition techniques for Boson Sampling validation. CoRR (2017)
Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli
Hierarchical Reversible Logic Synthesis Using LUTs. DAC (2017)
Martin Rötteler, Krysta M. Svore, Dave Wecker, Nathan Wiebe
Design automation for quantum architectures. DATE (2017)
Jacob D. Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, Seth Lloyd
Quantum machine learning. Nat. 549 (7671) (2017)
Nathan Wiebe, Christopher Grandade
Can small quantum systems learn. Quantum Inf. Comput. 17 (7&8) (2017)
Mathias Soeken, Martin Rötteler, Nathan Wiebe, Giovanni De Micheli
Design Automation and Design Space Exploration for Quantum Computers. CoRR (2016)
Nathan Wiebe, Martin Roetteler
Quantum arithmetic and numerical analysis using Repeat-Until-Success circuits. Quantum Inf. Comput. 16 (1&2) (2016)
Nathan Wiebe, Ashish Kapoor, Krysta M. Svore
Quantum Perceptron Models. CoRR (2016)
Ashish Kapoor, Nathan Wiebe, Krysta M. Svore
Quantum Perceptron Models. NIPS (2016)
Nathan Wiebe, Ashish Kapoor, Krysta M. Svore
Quantum deep learning. Quantum Inf. Comput. 16 (7&8) (2016)
Nathan Wiebe, Ashish Kapoor, Krysta M. Svore
Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning. Quantum Inf. Comput. 15 (3&4) (2015)
Nathan Wiebe, Christopher E. Granade, Ashish Kapoor, Krysta M. Svore
Bayesian inference via rejection filtering. CoRR (2015)
Nathan Wiebe, Ashish Kapoor, Christopher E. Granade, Krysta M. Svore
Quantum Inspired Training for Boltzmann Machines. CoRR (2015)
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) (2015)
Ilia N. Zintchenko, Matthew B. Hastings, Nathan Wiebe, Ethan Brown, Matthias Troyer
Partial Reinitialisation for Optimisers. CoRR (2015)
Nathan Wiebe
Using Quantum Computing to Learn Physics. Bull. EATCS 112 (2014)
Nathan Wiebe, Martin Roetteler
Quantum arithmetic and numerical analysis using Repeat-Until-Success circuits. CoRR (2014)
Nathan Wiebe, Ashish Kapoor, Krysta M. Svore
Quantum Deep Learning. CoRR (2014)
Christopher E. Granade, Christopher Ferrie, Nathan Wiebe, David G. Cory
Robust Online Hamiltonian Learning. TQC (2013)
Christopher E. Granade, Christopher Ferrie, Nathan Wiebe, David G. Cory
Robust Online Hamiltonian Learning CoRR (2012)
Andrew M. Childs, Nathan Wiebe
Hamiltonian simulation using linear combinations of unitary operations. Quantum Inf. Comput. 12 (11-12) (2012)
Nathan Wiebe, John Anderson
A local approach to developing grounded spatial references in multi-robot systems. IROS (2007)