Search Results for author: Nathan Wiebe

Found 22 papers, 4 papers with code

Even more efficient quantum computations of chemistry through tensor hypercontraction

no code implementations6 Nov 2020 Joonho Lee, Dominic Berry, Craig Gidney, William J. Huggins, Jarrod R. McClean, Nathan Wiebe, Ryan Babbush

We describe quantum circuits with only $\widetilde{\cal O}(N)$ Toffoli complexity that block encode the spectra of quantum chemistry Hamiltonians in a basis of $N$ arbitrary (e. g., molecular) orbitals.

Quantum Physics Chemical Physics

Entanglement Induced Barren Plateaus

no code implementations29 Oct 2020 Carlos Ortiz Marrero, Mária Kieferová, Nathan Wiebe

In particular, we show that quantum neural networks that satisfy a volume-law in the entanglement entropy will give rise to models not suitable for learning with high probability.

Well-conditioned multiproduct Hamiltonian simulation

1 code implementation26 Jul 2019 Guang Hao Low, Vadym Kliuchnikov, Nathan Wiebe

We introduce well-conditioned multiproduct formulas, which are a linear combination of product formulas, where a single step has polynomial cost $\mathcal{O}(m^2\log{(m)})$ and succeeds with probability $\Omega(1/\operatorname{log}^2{(m)})$.

Quantum Physics Computational Physics

Generative training of quantum Boltzmann machines with hidden units

no code implementations23 May 2019 Nathan Wiebe, Leonard Wossnig

In this article we provide a method for fully quantum generative training of quantum Boltzmann machines with both visible and hidden units while using quantum relative entropy as an objective.

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

no code implementations1 Apr 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

Fault-tolerant quantum computation promises to solve outstanding problems in quantum chemistry within the next decade.

Quantum Physics Emerging Technologies Chemical Physics Computational Physics

Downfolding of many-body Hamiltonians using active-space models: extension of the sub-system embedding sub-algebras approach to unitary coupled cluster formalisms

no code implementations5 Feb 2019 Nicholas P. Bauman, Eric J. Bylaska, Sriram Krishnamoorthy, Guang Hao Low, Nathan Wiebe, Karol Kowalski

In analogy to the standard single-reference SES-CC formalism, its unitary CC extension allows one to include the dynamical (outside the active space) correlation effects in an SES induced complete active space (CAS) effective Hamiltonian.

Quantum Physics

Circuit-centric quantum classifiers

3 code implementations2 Apr 2018 Maria Schuld, Alex Bocharov, Krysta Svore, Nathan Wiebe

In this paper, we propose a low-depth variational quantum algorithm for supervised learning.

Quantum Physics

Pattern recognition techniques for Boson Sampling validation

no code implementations19 Dec 2017 Iris Agresti, Niko Viggianiello, Fulvio Flamini, Nicolò Spagnolo, Andrea Crespi, Roberto Osellame, Nathan Wiebe, Fabio Sciarrino

The difficulty of validating large-scale quantum devices, such as Boson Samplers, poses a major challenge for any research program that aims to show quantum advantages over classical hardware.

Hardening Quantum Machine Learning Against Adversaries

no code implementations17 Nov 2017 Nathan Wiebe, Ram Shankar Siva Kumar

Finally, we provide a private form of $k$--means clustering that can be used to prevent an all powerful adversary from learning more than a small fraction of a bit from any user.

Quantum Machine Learning

Optimizing quantum optimization algorithms via faster quantum gradient computation

no code implementations1 Nov 2017 András Gilyén, Srinivasan Arunachalam, Nathan Wiebe

We also show that in a continuous phase-query model, our gradient computation algorithm has optimal query complexity up to poly-logarithmic factors, for a particular class of smooth functions.

Quantum Physics Computational Complexity

Quantum Machine Learning

no code implementations28 Nov 2016 Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, Seth Lloyd

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data.

Quantum Machine Learning

Elucidating Reaction Mechanisms on Quantum Computers

no code implementations11 May 2016 Markus Reiher, Nathan Wiebe, Krysta M. Svore, Dave Wecker, Matthias Troyer

We show how a quantum computer can be employed to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example.

Quantum Physics

Quantum Perceptron Models

no code implementations NeurIPS 2016 Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

We demonstrate how quantum computation can provide non-trivial improvements in the computational and statistical complexity of the perceptron model.

Partial Reinitialisation for Optimisers

no code implementations9 Dec 2015 Ilia Zintchenko, Matthew Hastings, Nathan Wiebe, Ethan Brown, Matthias Troyer

Heuristic optimisers which search for an optimal configuration of variables relative to an objective function often get stuck in local optima where the algorithm is unable to find further improvement.

Quantum Inspired Training for Boltzmann Machines

no code implementations9 Jul 2015 Nathan Wiebe, Ashish Kapoor, Christopher Granade, Krysta M. Svore

We present an efficient classical algorithm for training deep Boltzmann machines (DBMs) that uses rejection sampling in concert with variational approximations to estimate the gradients of the training objective function.

Quantum Deep Learning

no code implementations10 Dec 2014 Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

In recent years, deep learning has had a profound impact on machine learning and artificial intelligence.

Quantum Algorithms for Nearest-Neighbor Methods for Supervised and Unsupervised Learning

2 code implementations9 Jan 2014 Nathan Wiebe, Ashish Kapoor, Krysta Svore

In the worst case, our quantum algorithms lead to polynomial reductions in query complexity relative to the corresponding classical algorithm.

Quantum Physics

Hamiltonian Simulation Using Linear Combinations of Unitary Operations

1 code implementation27 Feb 2012 Andrew M. Childs, Nathan Wiebe

We present a new approach to simulating Hamiltonian dynamics based on implementing linear combinations of unitary operations rather than products of unitary operations.

Quantum Physics

Quantum-circuit design for efficient simulations of many-body quantum dynamics

no code implementations22 Aug 2011 Sadegh Raeisi, Nathan Wiebe, Barry C. Sanders

We construct an efficient autonomous quantum-circuit design algorithm for creating efficient quantum circuits to simulate Hamiltonian many-body quantum dynamics for arbitrary input states.

Quantum Physics

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