Nathan Wiebe

According to our database, Nathan Wiebe authored at least 57 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Improved Accuracy for Trotter Simulations Using Chebyshev Interpolation.

Gumaro Rendon, Jacob Watkins, Nathan Wiebe

Quantum, February, 2024

2023

Composite Quantum Simulations.

Matthew Hagan, Nathan Wiebe

Quantum, November, 2023

Two-Unitary Decomposition Algorithm and Open Quantum System Simulation.

Nishchay Suri, Joseph Barreto, Stuart Hadfield, Nathan Wiebe, Filip A. Wudarski, Jeffrey Marshall

Quantum, May, 2023

Gate-based quantum computing for protein design.

Mohammad Hassan Khatami, Udson C. Mendes, Nathan Wiebe, Philip M. Kim

PLoS Comput. Biol., 2023

Fast quantum algorithm for differential equations.

Mohsen Bagherimehrab, Kouhei Nakaji, Nathan Wiebe, Alán Aspuru-Guzik

CoRR, 2023

Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum.

Samuel Alexander Stein, Nathan Wiebe, Yufei Ding, James A. Ang, Ang Li

Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

Exponential quantum speedup in simulating coupled classical oscillators^*.

Ryan Babbush, Dominic W. Berry, Robin Kothari, Rolando D. Somma, Nathan Wiebe

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

2022

Simulating Effective QED on Quantum Computers.

Torin F. Stetina, Anthony Ciavarella, Xiaosong Li, Nathan Wiebe

Quantum, 2022

Quantum Machine Learning with SQUID.

Alessandro Roggero, Jakub Filipek, Shih-Chieh Hsu, Nathan Wiebe

Quantum, 2022

Hybridized Methods for Quantum Simulation in the Interaction Picture.

Abhishek Rajput, Alessandro Roggero, Nathan Wiebe

Quantum, 2022

Bosonic Qiskit.

Timothy J. Stavenger, Eleanor Crane, Kevin Smith, Christopher T. Kang, Steven M. Girvin, Nathan Wiebe

CoRR, 2022

Synthesizing efficient circuits for Hamiltonian simulation.

Priyanka Mukhopadhyay, Nathan Wiebe, Hong-Tao Zhang

CoRR, 2022

EQC: ensembled quantum computing for variational quantum algorithms.

Samuel Alexander Stein, Nathan Wiebe, Yufei Ding, Bo Peng, Karol Kowalski, Nathan A. Baker, James A. Ang, Ang Li

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

QCCC 2022 Keynote Talk: Hybrid Quantum / Classical Algorithms for Machine Learning.

Nathan Wiebe

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Benchmarking Quantum Processor Performance through Quantum Distance Metrics Over An Algorithm Suite.

Samuel Alexander Stein, Nathan Wiebe, James A. Ang, Ang Li

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Improving Variational Quantum Algorithms performance through Weighted Quantum Ensembles.

Samuel Alexander Stein, Nathan Wiebe, James A. Ang, Ang Li

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

C2QA - Bosonic Qiskit.

Timothy J. Stavenger, Eleanor Crane, Kevin Smith, Christopher T. Kang, Steven M. Girvin, Nathan Wiebe

Proceedings of the IEEE High Performance Extreme Computing Conference, 2022

2021

Quantum Model Learning Agent: characterisation of quantum systems through machine learning.

Brian Flynn, Antonio Andrea Gentile, Nathan Wiebe, Raffaele Santagati, Anthony Laing

CoRR, 2021

2020

Quantum Algorithms for Simulating the Lattice Schwinger Model.

Alexander F. Shaw, Pavel Lougovski, Jesse R. Stryker, Nathan Wiebe

Quantum, 2020

Operational, gauge-free quantum tomography.

Olivia Di Matteo, John King Gamble, Christopher E. Granade, Kenneth M. Rudinger, Nathan Wiebe

Quantum, 2020

Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization.

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

Quantum, 2020

Time-dependent Hamiltonian simulation withL1-norm scaling.

Dominic W. Berry, Andrew M. Childs, Yuan Su, Xin Wang, Nathan Wiebe

Quantum, 2020

Entanglement Induced Barren Plateaus.

Carlos Ortiz Marrero, Mária Kieferová, Nathan Wiebe

CoRR, 2020

Bayesian phase estimation with adaptive grid refinement.

Ramakrishna Tipireddy, Nathan Wiebe

CoRR, 2020

Fast inversion, preconditioned quantum linear system solvers, and fast evaluation of matrix functions.

Yu Tong, Dong An, Nathan Wiebe, Lin Lin

CoRR, 2020

Learning models of quantum systems from experiments.

Antonio A. Gentile, Brian Flynn, Sebastian Knauer, Nathan Wiebe, Stefano Paesani, Christopher E. Granade, John G. Rarity, Raffaele Santagati, Anthony Laing

CoRR, 2020

2019

LUT-Based Hierarchical Reversible Logic Synthesis.

Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2019

Ordering of Trotterization: Impact on Errors in Quantum Simulation of Electronic Structure.

Andrew Tranter, Peter J. Love, Florian Mintert, Nathan Wiebe, Peter V. Coveney

Entropy, 2019

A Theory of Trotter Error.

Andrew M. Childs, Yuan Su, Minh C. Tran, Nathan Wiebe, Shuchen Zhu

CoRR, 2019

Time-dependent Hamiltonian simulation with $L^1$-norm scaling.

Dominic W. Berry, Andrew M. Childs, Yuan Su, Xin Wang, Nathan Wiebe

CoRR, 2019

Generative training of quantum Boltzmann machines with hidden units.

Nathan Wiebe, Leonard Wossnig

CoRR, 2019

Q# and NWChem: Tools for Scalable Quantum Chemistry on Quantum Computers.

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

CoRR, 2019

Bayesian ACRONYM Tuning.

John King Gamble, Christopher E. Granade, Nathan Wiebe

Proceedings of the 14th Conference on the Theory of Quantum Computation, 2019

Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics.

András Gilyén, Yuan Su, Guang Hao Low, Nathan Wiebe

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Optimizing quantum optimization algorithms via faster quantum gradient computation.

András Gilyén, Srinivasan Arunachalam, Nathan Wiebe

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

2018

A best-fit mapping algorithm to facilitate ESOP-decomposition in Clifford+T quantum network synthesis.

Giulia Meuli, Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli

Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018

2017

Can small quantum systems learn.

Nathan Wiebe, Christopher Grandade

Quantum Inf. Comput., 2017

Quantum machine learning.

Jacob D. Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, Seth Lloyd

Nat., 2017

Experimental Phase Estimation Enhanced By Machine Learning.

Alessandro Lumino, Emanuele Polino, Adil S. Rab, Giorgio Milani, Nicolò Spagnolo, Nathan Wiebe, Fabio Sciarrino

CoRR, 2017

Pattern recognition techniques for Boson Sampling validation.

Iris Agresti, Niko Viggianiello, Fulvio Flamini, Nicolò Spagnolo, Andrea Crespi, Roberto Osellame, Nathan Wiebe, Fabio Sciarrino

CoRR, 2017

Hardening Quantum Machine Learning Against Adversaries.

Nathan Wiebe, Ram Shankar Siva Kumar

CoRR, 2017

Logic Synthesis for Quantum Computing.

Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli

CoRR, 2017

Design automation and design space exploration for quantum computers.

Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017

Design automation for quantum architectures.

Martin Rötteler, Krysta M. Svore, Dave Wecker, Nathan Wiebe

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017

Hierarchical Reversible Logic Synthesis Using LUTs.

Mathias Soeken, Martin Roetteler, Nathan Wiebe, Giovanni De Micheli

Proceedings of the 54th Annual Design Automation Conference, 2017

2016

Quantum arithmetic and numerical analysis using Repeat-Until-Success circuits.

Nathan Wiebe, Martin Roetteler

Quantum Inf. Comput., 2016

Quantum deep learning.

Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

Quantum Inf. Comput., 2016

Quantum Perceptron Models.

Ashish Kapoor, Nathan Wiebe, Krysta M. Svore

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning.

Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

Quantum Inf. Comput., 2015

The Trotter step size required for accurate quantum simulation of quantum chemistry.

David Poulin, Matthew B. Hastings, Dave Wecker, Nathan Wiebe, Andrew C. Doherty, Matthias Troyer

Quantum Inf. Comput., 2015

Partial Reinitialisation for Optimisers.

Ilia N. Zintchenko, Matthew B. Hastings, Nathan Wiebe, Ethan Brown, Matthias Troyer

CoRR, 2015

Quantum Inspired Training for Boltzmann Machines.

Nathan Wiebe, Ashish Kapoor, Christopher E. Granade, Krysta M. Svore

CoRR, 2015

Bayesian inference via rejection filtering.

Nathan Wiebe, Christopher E. Granade, Ashish Kapoor, Krysta M. Svore

CoRR, 2015

2014

Using Quantum Computing to Learn Physics.

Nathan Wiebe

Bull. EATCS, 2014

2013

Robust Online Hamiltonian Learning.

Christopher E. Granade, Christopher Ferrie, Nathan Wiebe, David G. Cory

Proceedings of the 8th Conference on the Theory of Quantum Computation, 2013

2012

Hamiltonian simulation using linear combinations of unitary operations.

Andrew M. Childs, Nathan Wiebe

Quantum Inf. Comput., 2012

2007

A local approach to developing grounded spatial references in multi-robot systems.

Nathan Wiebe, John Anderson

Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29, 2007