Abstract
Richard P. Feynman, a Nobel Prize winner in physics, was a physicist thought leader in the areas of quantum mechanics and quantum electrodynamics. In 1982, he published a research paper with the title “Simulating Physics with Computers”. In this paper, he asks the question if a quantum computer could be built (which he believed to be the case) or if classical computers can simulate the probabilistic behavior of a true quantum system (which he answered with a clear no). This research paper sparked interest in the scientific research community, which started to seriously explore whether or not a quantum computer can actually be built.
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Notes
- 1.
You can find the paper from Richard Feynman here [1].
- 2.
A quick introduction between CPU and GPU can be found here [2].
- 3.
An introduction to Google TPUs can be found here [3].
- 4.
See this reference [4] for further details.
- 5.
The homepage of the OpenPower Foundation can be found here [5].
- 6.
You can find more on the ARM company and the ARM architecture here [6].
- 7.
If you are really interested to get the basics of calculating this, we recommend you to read Noson Yanofsky’s “Introduction to Quantum Computing.” The preceding formula is from Noson Yanofsky’s excellent introduction on this subject. With just a tiny bit of basic graph concepts and matrix calculations, this paper introduces the foundation of quantum computing including one of the most basic quantum algorithms, the Deutsch algorithm. Using the double slit experiment for illustrating interesting angles of superposition was inspired by this article. You can find the paper here [7].
- 8.
If you want to get a summary overview, this research paper would be a good starting point [8].
- 9.
Picture taken by one of the authors at the IBM Think Conference in February 2019.
- 10.
You can find the research paper from Peter W. Shor here [9].
- 11.
A good introduction to this topic can be found here [10].
- 12.
For topics on cryptography, Applied Cryptography by Bruce Schneier is a must-read book. It also contains a wonderful section on the factorization problem and encryption algorithms using it. For the methods mentioned here, see the references [11], [12], [13], and [14], respectively.
- 13.
This public key encryption algorithm is named after its inventors Ron Rivest, Adi Shamir, and Leonard Adleman.
- 14.
Matthew Dozer produced a nice video introducing lattice-based cryptography and how it can be used which you can find here [15].
- 15.
You can find the press announcement from the Fraunhofer Research Institute here [16].
- 16.
You can download Qiskit here [17].
- 17.
You can find the research paper from the Google scientists here [18].
- 18.
You can watch this YouTube video to get an introduction on this topic [19].
- 19.
You can read more on this here [20].
- 20.
Watch this YouTube video to get an introduction on the topic [21].
- 21.
This paper provides you more details on Variational Quantum Eigensolver algorithm [22].
- 22.
Nielsen wrote two books on deep learning and quantum computing which are excellent introductions on both topics [23] and [24]. A good introduction on quantum machine learning is [25].
- 23.
You can find their paper here [26].
- 24.
The announcement from KPN and QuTech is located here [27].
- 25.
More details on QRAM can be found in this paper [28].
- 26.
In this YouTube video, you can find the perspective of Seth Lloyd [29].
- 27.
A very good overview on necessary hardware and software enhancements for quantum computing can be found in this research article from 2019 [30].
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© 2020 Eberhard Hechler, Martin Oberhofer, Thomas Schaeck
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Hechler, E., Oberhofer, M., Schaeck, T. (2020). AI and Quantum Computing. In: Deploying AI in the Enterprise. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-6206-1_12
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DOI: https://doi.org/10.1007/978-1-4842-6206-1_12
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