World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
60
Citations
19926
World Ranking
2127
National Ranking
85

Overview

Nathan Wiebe is a researcher affiliated with the University of Toronto in Canada. Their work spans a range of topics primarily in the fields of computer science and physics and astronomy, focusing heavily on quantum computing and its associated disciplines.

Their research contributions cover several main fields of study including:

  • Computer Science
  • Physics and Astronomy

Within these broad fields, their subfields of study include:

  • Artificial Intelligence
  • Atomic and Molecular Physics, and Optics
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering
  • Nuclear and High Energy Physics

Their primary research topics involve quantum computing methodologies and phenomena, as reflected in the following main topics of work:

  • Quantum Computing Algorithms and Architecture
  • Quantum Information and Cryptography
  • Quantum and electron transport phenomena
  • Quantum many-body systems
  • Quantum-Dot Cellular Automata
  • Quantum Mechanics and Applications
  • Spectroscopy and Quantum Chemical Studies

Nathan Wiebe has published extensively, with frequent appearances in specific venues. The venues where they have published multiple works include:

  • arXiv (Cornell University)
  • PRX Quantum
  • Quantum
  • Physical Review Research
  • 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

Their recent papers illustrate the scope and themes of their research. Notable publications include:

  • "Circuit-centric quantum classifiers," published in 2020 in Physical Review A/Physical Review, A
  • "Entanglement-Induced Barren Plateaus," published in 2023 in OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
  • "Quantum Simulation for High-Energy Physics," published in 2023 in PRX Quantum
  • "Drug design on quantum computers," published in 2024 in Nature Physics
  • "Real-Time Evolution for Ultracompact Hamiltonian Eigenstates on Quantum Hardware," published in 2022 in PRX Quantum

In their collaborative work, Nathan Wiebe has frequently co-authored with several researchers, indicating sustained partnerships with:

  • Raffaele Santagati
  • Alessandro Roggero
  • Matthias Degroote
  • Nikolaj Moll
  • Michael Streif

Best Publications

  • Quantum machine learning

    Jacob D. Biamonte;Jacob D. Biamonte;Peter Wittek;Nicola Pancotti;Patrick Rebentrost

  • Circuit-centric quantum classifiers

    Maria Schuld;Alex Bocharov;Krysta M. Svore;Nathan Wiebe;Nathan Wiebe;Nathan Wiebe

  • Hartree-Fock on a superconducting qubit quantum computer

    Frank Arute;Kunal Arya

  • Elucidating reaction mechanisms on quantum computers

    Markus Reiher;Nathan Wiebe;Krysta M. Svore;Dave Wecker

  • Hartree-Fock on a superconducting qubit quantum computer

    Frank Arute;Kunal Arya;Ryan Babbush;Dave Bacon

  • Quantum Algorithm for Data Fitting

    Nathan Wiebe;Daniel Braun;Daniel Braun;Seth Lloyd

  • A Theory of Trotter Error.

    Andrew M. Childs;Yuan Su;Minh C. Tran;Nathan Wiebe

  • Quantum Simulation of Electronic Structure with Linear Depth and Connectivity

    Ian D. Kivlichan;Ian D. Kivlichan;Jarrod McClean;Nathan Wiebe;Craig Michael Gidney

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

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

  • Encoding Electronic Spectra in Quantum Circuits with Linear T Complexity

    Ryan Babbush;Craig Michael Gidney;Dominic W. Berry;Nathan Wiebe

  • Low-Depth Quantum Simulation of Materials

    Ryan Babbush;Nathan Wiebe;Jarrod McClean;James McClain

  • Solving strongly correlated electron models on a quantum computer

    Dave Wecker;Matthew B. Hastings;Nathan Wiebe;Bryan K. Clark;Bryan K. Clark

  • Hamiltonian simulation using linear combinations of unitary operations

    Andrew M. Childs;Nathan Wiebe

  • Hamiltonian Simulation Using Linear Combinations of Unitary Operations

    Nathan Wiebe;Andrew Childs

  • Experimental quantum Hamiltonian learning

    Jianwei Wang;Stefano Paesani;Raffaele Santagati;Sebastian Knauer

  • Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers

    William J. Huggins;William J. Huggins;Jarrod R. McClean;Nicholas C. Rubin;Zhang Jiang

  • Even more efficient quantum computations of chemistry through tensor hypercontraction

    Joonho Lee;Dominic W. Berry;Craig Michael Gidney;William J. Huggins

  • Tomography and generative training with quantum Boltzmann machines

    Mária Kieferová;Nathan Wiebe

  • Hamiltonian learning and certification using quantum resources.

    Nathan Wiebe;Nathan Wiebe;Christopher Granade;Christopher Ferrie;D. G. Cory

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

    Nathan Wiebe;Ashish Kapoor;Krysta M. Svore

  • Witnessing eigenstates for quantum simulation of Hamiltonian spectra.

    Raffaele Santagati;Jianwei Wang;Antonio A. Gentile;Stefano Paesani

  • Low Depth Quantum Simulation of Electronic Structure

    Ryan Babbush;Nathan Wiebe;Jarrod McClean;James McClain

  • Robust Online Hamiltonian Learning.

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

  • Elucidating Reaction Mechanisms on Quantum Computers

    Nathan Wiebe;Markus Reiher;Krysta Svore;Dave Wecker

Frequent Co-Authors

Mark G. Thompson
Mark G. Thompson University of Bristol
Krysta M. Svore
Krysta M. Svore Microsoft (United States)
Matthias Troyer
Matthias Troyer Microsoft (United States)
John Rarity
John Rarity University of Bristol
Jeremy L. O'Brien
Jeremy L. O'Brien University of Bristol
Fabio Sciarrino
Fabio Sciarrino Sapienza University of Rome
Ashish Kapoor
Ashish Kapoor Microsoft (United States)
Hartmut Neven
Hartmut Neven Google (United States)
David P. Tew
David P. Tew University of Oxford
David G. Cory
David G. Cory University of Waterloo

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