Quantum computational supremacy

By Aram Wettroth Harrow, Ashley Montanaro. Nature, 2017

847 citations recorded by the source corpus.

The field of quantum algorithms aims to find ways to speed up the solution of computational problems by using a quantum computer. A key milestone in this field will be when a universal quantum computer performs a computational task that is beyond the capability of any classical computer, an event known as quantum supremacy. This would be easier to achieve experimentally than full-scale quantum computing, but involves new theoretical challenges. Here we present the leading proposals to achieve quantum supremacy, and discuss how we can reliably compare the power of a classical computer to the power of a quantum computer.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/3679db100b2c3be93bfa1bee15e6738654155002

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Citations in the corpus

Toward the first quantum simulation with quantum speedup (2017, background): “Our work is also distinct from recent work on quantum computational supremacy (7), where the goal is merely to accomplish a superclassical task, regardless of its practicality.”
Microscopic Control and Detection of Ultracold Strontium in Optical-Tweezer Arrays (2018, background): “This new approach would prove advantageous for studies of many-body phenomena at low energy scales — such as magnetism — for which tailored state preparation can be useful [55, 56], for scaling of protocols to measure and quantify entanglement [9, 17, 57], as well as for novel directions like atom-b”
Circuit-centric quantum classifiers (2018, background): “While many of those small-scale algorithms have the sole purpose of demonstrating the power of quantum computing over classical information processing [5], an important goal is to find quantum solutions to useful applications.”
Parameterized quantum circuits as machine learning models (2019, background): “For example, under well-believed complexity-theoretic assumptions, the class of PQCs called instantaneous quantum polynomial-time cannot be eﬃciently simulated by classical resources (see Lund et al. [3] and Harrow and Montanaro [4] for accessible Reviews of quantum supremacy proposals).”
Transfer learning in hybrid classical-quantum neural networks (2019, background): “Indeed today we are in a situation in which intermediate-scale quantum computers are approaching the quantum supremacy milestone [6, 19] and, at the same time, we have at our disposal the very successful and well-tested tools of classical deep learning.”
Quantum computational advantage using photons (2020, background): “This sample size dependence of the computational advantage—an analog to the loopholes in Bell tests ( 13 )—suggests that a quantum computational advantage would require long-term competitions between faster classical simulations and improved quantum devices.”
Integrated photonic quantum technologies (2019, neutral): “tasks [88].”