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Open AccessJournal ArticleDOI

Quantum Computing in the NISQ era and beyond

TLDR
Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future as mentioned in this paper, which will be useful tools for exploring many-body quantum physics, and may have other useful applications.
Abstract
Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass the capabilities of today's classical digital computers, but noise in quantum gates will limit the size of quantum circuits that can be executed reliably. NISQ devices will be useful tools for exploring many-body quantum physics, and may have other useful applications, but the 100-qubit quantum computer will not change the world right away --- we should regard it as a significant step toward the more powerful quantum technologies of the future. Quantum technologists should continue to strive for more accurate quantum gates and, eventually, fully fault-tolerant quantum computing.

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Citations
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Supplementary information for "Quantum supremacy using a programmable superconducting processor"

TL;DR: In this paper, an updated version of supplementary information to accompany "Quantum supremacy using a programmable superconducting processor", an article published in the October 24, 2019 issue of Nature, is presented.
Journal ArticleDOI

Quantum computational advantage using photons

TL;DR: In this paper, the authors proposed to use quantum computers to perform certain tasks that are believed to be intractable to classical computers, such as Boson sampling, which is considered a strong candidate to demonstrate the capabilities of quantum computers.
Journal ArticleDOI

Quantum computational chemistry

TL;DR: This review presents strategies employed to construct quantum algorithms for quantum chemistry, with the goal that quantum computers will eventually answer presently inaccessible questions, for example, in transition metal catalysis or important biochemical reactions.
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Quantum Chemistry in the Age of Quantum Computing.

TL;DR: This Review provides an overview of the algorithms and results that are relevant for quantum chemistry and aims to help quantum chemists who seek to learn more about quantum computing and quantum computing researchers who would like to explore applications in quantum chemistry.
Journal ArticleDOI

Quantum Machine Learning in Feature Hilbert Spaces

TL;DR: This Letter interprets the process of encoding inputs in a quantum state as a nonlinear feature map that maps data to quantum Hilbert space and shows how it opens up a new avenue for the design of quantum machine learning algorithms.
References
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Journal ArticleDOI

Deep learning

TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
Book

Deep Learning

TL;DR: Deep learning as mentioned in this paper is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts, and it is used in many applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.
Journal ArticleDOI

Simulating physics with computers

TL;DR: In this paper, the authors describe the possibility of simulating physics in the classical approximation, a thing which is usually described by local differential equations, and the possibility that there is to be an exact simulation, that the computer will do exactly the same as nature.
Journal ArticleDOI

Quantum Mechanics Helps in Searching for a Needle in a Haystack

TL;DR: In this article, a phone directory containing $N$ names arranged in completely random order is presented, and the desired phone number can be obtained in only O(sqrt{N})$ accesses to the database.
Journal ArticleDOI

A variational eigenvalue solver on a photonic quantum processor

TL;DR: The proposed approach drastically reduces the coherence time requirements and combines this method with a new approach to state preparation based on ansätze and classical optimization, enhancing the potential of quantum resources available today and in the near future.
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