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20182026
most citedThe power of quantum neural networks

1k citations · 4.8k across the 38 of their papers we have counts for

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Showing 2020 · quant-phShow all

11 papers · 2 filters

quant-ph2020★ 105 cited

A Threshold for Quantum Advantage in Derivative Pricing

Shouvanik Chakrabarti, Rajiv Krishnakumar, Guglielmo Mazzola +3

We give an upper bound on the resources required for valuable quantum advantage in pricing derivatives. To do so, we give the first complete resource estimates for useful quantum d…

quant-ph2020★ 1 cited

Quantum speedups for convex dynamic programming

David Sutter, Giacomo Nannicini, Tobias Sutter +1

We present a quantum algorithm to solve dynamic programming problems with convex value functions. For linear discrete-time systems with a -dimensional state space of size , t…

quant-ph2020★ 1k cited

The power of quantum neural networks

Amira Abbas, David Sutter, Christa Zoufal +3

Fault-tolerant quantum computers offer the promise of dramatically improving machine learning through speed-ups in computation or improved model scalability. In the near-term, howe…

quant-ph2020★ 282 cited

Warm-starting quantum optimization

Daniel J. Egger, Jakub Marecek, Stefan Woerner

There is an increasing interest in quantum algorithms for problems of integer programming and combinatorial optimization. Classical solvers for such problems employ relaxations, wh…

quant-ph2020★ 49 cited

Enhancing the Quantum Linear Systems Algorithm using Richardson Extrapolation

Almudena Carrera Vazquez, Ralf Hiptmair, Stefan Woerner

We present a quantum algorithm to solve systems of linear equations of the form , where is a tridiagonal Toeplitz matrix and results from d…

quant-ph2020

Quantum algorithm for alchemical optimization in material design

Panagiotis Kl. Barkoutsos, Fotios Gkritsis, Pauline J. Ollitrault +3

The development of tailored materials for specific applications is an active field of research in chemistry, material science and drug discovery. The number of possible molecules t…

quant-ph2020★ 99 cited

Variational Quantum Boltzmann Machines

Christa Zoufal, Aurélien Lucchi, Stefan Woerner

This work presents a novel realization approach to Quantum Boltzmann Machines (QBMs). The preparation of the required Gibbs states, as well as the evaluation of the loss function's…

quant-ph2020★ 366 cited

Quantum Computing for Finance: State of the Art and Future Prospects

Daniel J. Egger, Claudio Gambella, Jakub Marecek +6

This article outlines our point of view regarding the applicability, state-of-the-art, and potential of quantum computing for problems in finance. We provide an introduction to qua…

quant-ph2020★ 2 cited

Quantum Legendre-Fenchel Transform

David Sutter, Giacomo Nannicini, Tobias Sutter +1

We present a quantum algorithm to compute the discrete Legendre-Fenchel transform. Given access to a convex function evaluated at points, the algorithm outputs a quantum-mechan…

quant-ph2020★ 14 cited

Quantum-Enhanced Simulation-Based Optimization

Julien Gacon, Christa Zoufal, Stefan Woerner

In this paper, we introduce a quantum-enhanced algorithm for simulation-based optimization. Simulation-based optimization seeks to optimize an objective function that is computatio…

quant-ph2020★ 50 cited

Efficient State Preparation for Quantum Amplitude Estimation

Almudena Carrera Vazquez, Stefan Woerner

Quantum Amplitude Estimation (QAE) can achieve a quadratic speed-up for applications classically solved by Monte Carlo simulation. A key requirement to realize this advantage is ef…