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The usage of RSQF [1] instead of semiconductor electronics allows reduction of energy use up to 6 orders of magnitude. It is reported that 10^5 Josephson junctions in RSQF architecture
have been implemented on one chip by AIST. Certain steady development of superconducting quantum computer is observed and it is thus promising implementation of quantum Turing
machine [2]. Quantum state is fragile against decoherence and quantum computing chip is thus small and costly [3][4]. Therefore big quantum computer is unlikely and one needs to
use both superconducting classical and quantum chips. Flux superconducting qubit can be integrated with RSQF electronics on one chip [5]. Thus qubit state can be set and read by RSFQ chips [5]. In that framework we obtain hybrid classicalquantum superconducting computer on big scale on the same chip. This drives need for mixed classicalquantum computer algorithms robust against various types of noise. Since Josephson junctions in RSQF architecture can simulate Spiking Neural network [6][7] it is possible to represent classical mind in superconductor in analogy to semiconductor SPINNAKER [2]. Limited tests on hypothesis of quantum features in human brain become accessible. Therefore it is possible to obtain hybrid classicalquantum mind implemented in superconductor what can be represented by classicalquantum neural networks. We present the methodologies necessary to model proposed system and design new experiments that can be conducted using London, GinzburgLandau, Bogoliubovde Gennes & nonequilibrium Green formalisms implemented in numerical relaxation method. Execution of quantum algorithms is expected to be traced. New hardware architectures [8] and various approaches are analyzed [9][11].
References:
1. K. K. Likharev, NATO ASI Series, Series E: App. Sci. 251, 221 (1993).
2. J. Q. You, F. Nori, Phys. Today 58, 11, 42 (2005).
3. B. Foxen et al., Quantum Sci. Technol. 3, 014005 (2018).
4. J. Martinis, www.technologyreview.com/s/544421/googlesquantumdreammachine (2017)
5. N. V. Klenova et al., Low Temp. Phys. 43, 789 (2017).
6. P. Crotty, et al., Phys. Rev. E 82, 011914 (2010).
7. T. Hirose, et al., Physica C 463–465, 1072 (2007).
8. A. Grübl, PhD thesis, Heidelber University (2010).
9. K. Pomorski, et al., arxiv.org/abs/1607.05013 (2016).
10. J. M. Shainline, et al., Phys. Rev. App. 7, 034013 (2017).
11. Z. He, D. Fan, arxiv.org/pdf/1705.02995.pdf (2017).
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