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Nature Computational Science

Are quantum computers really energy efficient?

Sophia Chen

Published Jun 26, 2023• 17 citations
Publisher
DOI
10.1038/s43588-023-00459-6

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Conclusion and Outlook

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This chapter gives a summary, conclusion, and outlook on the interplay between AI and physics overall. As an impact of physics on AI, the most recent quantum computer is described. It is the first to exhibit more than 100 qubits and is thus so superior that it can no longer be simulated by a conventional supercomputer. A quantum computer breaking through the “sound barrier” of 1,000 qubits is announced for 2023; experts claim this is the barrier a quantum processor must overcome to be of first efficient use. These advancements will allow the current shortcomings of AI to be overcome and make it more similar to human intelligence which is still superior to AI in various ways. Most of all, human brains are a million times more energy efficient than AI and thus really high-tech! However, the power of AI is increasing exponentially, and technological singularity may be achieved within a few decades. AI researchers expect that artificial general intelligence would be developed by 2040–50. Following thoughts by Stephen Hawking, we could come to the point at which AI would drive science forward by itself, for the sake of technology and human knowledge; the power of AI for physics would then fully unfold.

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Will We Ever Have a Quantum Computer?

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SpringerBriefs in physics•Jan 1, 2020•12 citations
This chapter gives a summary, conclusion, and outlook on the interplay between AI and physics overall. As an impact of physics on AI, the most recent quantum computer is described. It is the first to exhibit more than 100 qubits and is thus so superior that it can no longer be simulated by a conventional supercomputer. A quantum computer breaking through the “sound barrier” of 1,000 qubits is announced for 2023; experts claim this is the barrier a quantum processor must overcome to be of first efficient use. These advancements will allow the current shortcomings of AI to be overcome and make it more similar to human intelligence which is still superior to AI in various ways. Most of all, human brains are a million times more energy efficient than AI and thus really high-tech! However, the power of AI is increasing exponentially, and technological singularity may be achieved within a few decades. AI researchers expect that artificial general intelligence would be developed by 2040–50. Following thoughts by Stephen Hawking, we could come to the point at which AI would drive science forward by itself, for the sake of technology and human knowledge; the power of AI for physics would then fully unfold.
Deterministic quantum computation with one quantum bit (DQC1) [E. Knill and R. Laflamme, Phys. Rev. Lett. 81, 5672 (1998)] is a model of quantum computing where the input is restricted to containing a single qubit in a pure state and has all other qubits in a completely mixed state. Only the single pure qubit is measured at the end of the computation. While it is known that DQC1 can efficiently solve several problems for which no known classical efficient algorithms exist, the question of whether DQC1 is really more powerful than classical computation remains open. In this Letter, we introduce a slightly modified version of DQC1, which we call DQC1(k), where k output qubits are measured, and show that DQC1(k) cannot be classically efficiently simulated for any k≥3 unless the polynomial hierarchy collapses at the third level.