Monitoring particle trajectories for wave function parameter aquisition in quantum edge computation

Artificial intelligence(AI) technology expected as a robot brain is advancing day by day. However, computers are insufficient to drive AI without the dramatic development of their processing power. On the other hand, the development of quantum computers is progressing to break the barrier of classical computers. Moreover, there has been an argument that quantum mechanics is one of the leading ideas to explain human mental power and such an argument has become active recently. But unfortunately we cannot mount the quantum processor on the robot brain as its edge computer. This is because large-scale equipments that guarantee ultra-low temperature are required to maintain superposition, which is a key point of quantum computers. In this paper, we show a method of performing quantum computation with a classical mechanical device. We found that wave function parameters can be determined by monitoring particles trajectories under quantum fluctuations. We take up Deutsch's coin authenticity decision problem. We emphasize that it can be developed as hardware, not just an algorithm.

[1]  Hiroyuki Miyamoto,et al.  Holonomic Omnidirectional Vehicle with Ball Wheel Drive Mechanism , 2012 .

[2]  Nobuyuki Matsui,et al.  Performance of Qubit Neural Network in Chaotic Time Series Forecasting , 2016, ICONIP.

[3]  Travis S. Humble,et al.  Quantum supremacy using a programmable superconducting processor , 2019, Nature.

[4]  Peter Stone,et al.  Reinforcement learning , 2019, Scholarpedia.

[5]  J. Cirac,et al.  Restricted Boltzmann machines in quantum physics , 2019, Nature Physics.

[6]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[7]  Nobuyuki Matsui,et al.  Qubit Neural Network: Its Performance and Applications , 2009 .

[8]  J. Mompart,et al.  Overview of Bohmian Mechanics , 2012, Applied Bohmian Mechanics.

[9]  Takashi Maeno.  How to Make a Conscious Robot , 2005 .

[10]  D. Harris,et al.  Droplets walking in a rotating frame: from quantized orbits to multimodal statistics , 2013, Journal of Fluid Mechanics.

[11]  Nobuyuki Matsui,et al.  Qubit neural network and its learning efficiency , 2005, Neural Computing & Applications.

[12]  Tomoaki Nakamura,et al.  Symbol emergence in robotics: a survey , 2015, Adv. Robotics.

[13]  Takashi Maeno.  How to Make a Conscious Robot — Fundamental Idea based on Passive Consciousness Model — , 2005 .

[14]  Yvonne Feierabend.  State Functions And Linear Control Systems , 2016 .

[15]  Jerome R. Busemeyer,et al.  Quantum Models of Cognition and Decision: Frontmatter , 2012 .

[16]  K. Berndl,et al.  On the global existence of Bohmian mechanics , 1995, quant-ph/9503013.

[17]  Maria Schuld,et al.  Supervised Learning with Quantum Computers , 2018 .

[18]  Noriaki Kouda,et al.  Measuring weighting factor of eigenstates in quantum superposition by classical mechanical ‘quantum’ computer , 2020, 2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

[19]  Peter W. Shor.  Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer , 1999 .

[20]  Hitoshi Yoshino,et al.  Field Trial on 5G Low Latency Radio Communication System Towards Application to Truck Platooning , 2019, IEICE Trans. Commun..

[21]  D. Deutsch.  Quantum theory, the Church–Turing principle and the universal quantum computer , 1985, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[22]  H. Stapp.  Mind, matter, and quantum mechanics , 1982 .

[23]  Nobuyuki Matsui,et al.  Quantum Computation by Classical Mechanical Apparatuses , 2020, 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR).

[24]  R. Penrose,et al.  Consciousness in the universe: a review of the 'Orch OR' theory. , 2014, Physics of life reviews.

[25]  Ievgeniia Oshurko.  Quantum Machine Learning , 2020, Quantum Computing.

[26]  Bryce S. DeWitt,et al.  The Many-worlds interpretation of quantum mechanics , 2015 .

[27]  Jerome R. Busemeyer,et al.  Quantum Models of Cognition and Decision , 2012 .

[28]  D. Harris,et al.  Wavelike statistics from pilot-wave dynamics in a circular corral. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  D. Bohm.  A SUGGESTED INTERPRETATION OF THE QUANTUM THEORY IN TERMS OF "HIDDEN" VARIABLES. II , 1952 .

[30]  J. M. Bush.  Pilot-Wave Hydrodynamics , 2015 .

[31]  James L. Melsa,et al.  State Functions and Linear Control Systems , 1967 .