・Stochastic resonance   - Counterintuitive bio-functionality to survive in harsh environment

Stochastic resonance is a nonlinear phenomenon in which the response of a system is enhanced or optimized by adding noise and fluctuation. The mechanism of this counterintuitive phenomenon was proposed in 1982, to explain the periodic occurrence of ice ages on the earth.  In 1990's, stochastic resonance was found to appear in biological systems, such as sensory neurons in a cricket and a crayfish. From these findings, stochastic resonance has been considered as a bio-functionality to survive in harsh environment involving various temporal fluctuations.

In many electronic devices, noise is a big problem because it makes difficult to detect and/or process electronic signals. A lot of efforts have been made to remove noise.  However, if stochastic resonance is available the electron device, the problem can be solved, which should reduce the power consumption and the size of the equipment.

We have investigated to cause stochastic resonance in the electron devices and its application. We have also investigated to clarify the origin of the counterintuitive nature of the phenomenon.

Research and achievement

・First demonstration of stochastic resonance on a semiconductor nanowire FET

・Theoretical modeling and experimental demonstration of thermally driven single-electron stochastic resonance

・Discovering the mathematical origin of the counterintuitive behavior of stochastic resonance in a bistable system and development of a quantitative model (JSAP Outstanding paper award 2020)

・Development of the robust surface myoelectric signal detection technique using stochastic resonance  (MNC2013 Outstanding paper award)

・Electronic amoeba  - Reproduce the intelligence of amoeboid organism on electronic circuit

The finding that a single-celled amoeboid organism, slime mold, can solve a maze, by Prof. Nakagaki  in Hokkaido University surprised people in the world. After that, many researches has revealed that the amoeboid organism has high computing capacity. Our “electronic amoeba” is a novel bio-inspired electronic computing system in which the computing capacity of the amoeboid organism is electronically reproduced in an analog electronic circuit.

The electronic amoeba is expected to achieve high computing performance in terms of searching for the solution of optimization problems by the good combination of the high efficient computing ability of the organism and the fast computing capability of the electronics. We have attempted to increase the system size to solve a large problem. We have also investigated to apply this system to autonomous robot for its motion deduction and behavior development.

Research and achievement

・Invention of the analog electronic computer "electronic amoeba" that electronically mimics the behavior of an amoeboid organism

・Successful demonstration of  solution search for satisfiability problem (SAT), maximum cut problem (Max-cut), and traveling salesman problem (SAT) by electronic amoeba (Sci. Rep. ,Top 100 in Physics 2020 (Top #9))

・Demonstration of autonomous walking of a four-legged robot than searches for gait in real time using an amoeba-inspired computer

・Now we are investigating the theoretical understanding of the efficient search in the amoeboid organism using an electronic amoeba

・Nano artifact metrics  - Highly secure identifier too small to copy

A negative aspect of the evolution of the fabrication technology is to make counterfeiting easy.  This increases the security issue.  To overcome this problem, a national project for “nano-artifact metrics”, in which a two dimensional random nanostructure is used for the identifier, is going on.  The random nanostructure is so small, thus it is difficult to counterfeit and achieves high clone resistance. 

A technical issue in nano-artifact metrics is readout. It is not possible to equip a scanning electron microscope everywhere. Therefore, we recently proposed a novel electrical nanostructure readout technique by applying Si MOSFET device physics. Our basic concept is that, when the random 2D nanostructure is embedded in the gate/channel interface, information of the nanostructure is involved in the drain current.  Now we are fabricating and characterizing the test device for proof of our concept.

 Research and achievement

・Invention of an MOSFET-based device that can electronically readout of the 2D random nanostructure

・Experimental demonstration of electric discrimination of a nanoscale convex structure embedded in a Si MOSFET

・We are now fabricating and characterizing a Si MOSFET embedding two or more nano-convexs 

・Electronic reservoir computing - Novel versatile computing paradigm that makes things computing resources 

Reservoir computing is a unique time-series machine learning framework using a recurrent neural network. This is distinguished from the conventional machine learning in terms of physical implementation, because  it can be implemented using various materials and devices that have not been involved in the current Si CMOS-based von-Neumann computer; it can be implemented even by octopus leg,  water, and concrete in a building.

We investigate a unique technique to control a myoelectric bionic hand as imagined by using the reservoir computing where the recurrent neural network is the motor nerve system inside the body; complicated active potentials dealing with the intended action serves the output of the reservoir. Now we are integrating a multi-channel surface myoelectric signal detection system and a learning mechanism.

・1/ƒ fluctuation    -Development of an analog electronic computer to figure out why 1/ƒ fluctuation is universal

1/ƒ fluctuation is often observed in nature, organisms, and also semiconductor materials and electron devices. Understanding of the origin of its universality is a long standing issue, although many researches have been made to disclose it. 

To figure out the mechanism of the universality, we attempt to cause 1/ƒ fluctuation in an artificial manner using an analog electronic computer; an electronic nonlinear oscillator network.  If the previous theoretical models, such as self-organized criticality (SOC) model and McWhorter model, are correct, our computer should generate 1/ƒ fluctuation at an appropriate network topology and connection strengths. The universality is measured by the range of variations  of network parameters.

Faculty (Research Center for Integrated Quantum Electronics) 

   Professor    Seiya Kasai (Dr. Eng., Electron device)    kasai(-at-)rciqe.hokudai.ac.jp     Room 301, RCIQE

        Advisor to the president

        Professor, Research Center for Integrated Quantum Electronics (RCIQE)

        Deputy DIrector, Institute for Frontier Education and Research on Semiconductors

        Researcher data base in Hokkaido Univ. 

        Research map

        KAKEN data base

        ORCiD

   Associate Professor  Zenji Yatabe (Ph.D. in Biochemistry and Biotechnology)     zenji.yatabe(-at-)rciqe.hokudai.ac.jp     Room 203 RCIQE

        Researcher data base in Hokkaido Univ. 

        Research map

        KAKEN data base

        ORCiD

Graduate School Students (Graduate School of Information Science & Technology)

   DC1  Renxiang Lyu  (Nano artifact metrics)     renxiang.lyu.b7(-at-)elms.hokudai.ac.jp     Room 306, RCIQE

   MC2   Yusuke Hoshika  (Myoelectric bionichand/RC)     hoshika.yusuke.q3(-at-)elms.hokudai.ac.jp     Room 306, RCIQE

   MC1   Tokushi Maruoka  (Electronic amoeba)    maruoka.tokushi.j8(-at-)elms.hokudai.ac.jp   Room 306, RCIQE

   MC1   Yui Iida  (Myoelectric bionichand/RC)   iida.yui.p8(-at-)elms.hokudai.ac.jp   Room 306, RCIQE

   MC1   Shu Nagasawa  (Electronic amoeba)   nagasawa.shu.y7(-at-)elms.hokudai.ac.jp   Room 306, RCIQE

   MC1   Hyoto Yamaguchi  (Electronic amoeba robot)  yamaguchi.hyoto.b5(-at-)elms.hokudai.ac.jp    Room 306, RCIQE 

Undergraduate School Students（Faculty of Engineering）

   B4   Taichi Shigekane  (Electronic amoeba robot)   shigekane.taichi.l4(-at-)elms.hokudai.ac.jp   Room 306, RCIQE

   B4   Haruki Shirahase  (1/ƒ fluctuation)  shirahase.haruki.h4(-at-)elms.hokudai.ac.jp    Room 306, RCIQE 

*E-mail address: replace (-at-) by @            Oct. 30, 2025

2024

Research Articles

1. T. Mitsuya, R. Lyu and S. Kasai, “A study on sensitivity to an embedded nanostructure in a micrometer-channel-length Si MOSFET”, Jpn. J. Appl. Phys. 63, p.03SP60  (2024)  (DOI 10.35848/1347-4065/ad2650)

International Conference Papers

1.  K. Matsuda and S. Kasai, “Development of Walking Behavior in A Four-Legged Robot Controlled by Amoeba-inspired Optimization System”, 2024 Asia-Pacific Workshop on Advanced Semiconductor Devices (AWAD2024), Jul. 7 – 10, 2024, Gangneung, Korea. 

2.  S. Kasai, “Machine learning and optimization utilizing non-linear dynamics in electron devices and their networks”, Workshop on Unconventional Computing, Jul. 6–12, 2024, Erice, Italy + Online (invited).

3. S. Kasai, “Physical computing based on dynamics in analog electronic devices and circuits”, IEEE World Congress on Computational Intelligence (WCCI 2024), Jun. 30–Jul. 5, 2024, Yokohama, Japan (invited). 

4. H. Ueda and S. Kasai, “Effect of external stimulation on 1/ƒ dynamics in 2D cellular automaton”, 15th Topical Workshop on Heterostructure Microelectronics (TWHM2024), Aug. 26-29, 2024, Miyagi, Japan.

5. S. Kasai, “Amoeba-inspired optimization computer and its application”, Workshop on Neuromorphic In-Material Computation: Theory, Physics, Chemistry, Materials, Electronics, Information Science, Oct. 28-30, 2024, San Gimignano, Italy (Keynote).

2023

International Conference Papers

1. T. Yoshida and S. Kasai, “Readout of Voluntary Motion From Myoelectric Signals Based on Reservoir Computing Framework”, 2023 Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD2023), July 10-11, 2023, Yokohama, Japan.

2. T. Mitsuya, R.  Lyu, and S. Kasai, “Sensitivity to an embedded nanostructure in a micrometer-channel-length Si MOSFET”, 36th International Microprocesses and Nanotechnology Conference (MNC 2023) , November 14-17, Sapporo, Japan.

2022

Research Articles

1. S. Kasai, “Semiconductor technologies and related topics for implementation of electronic reservoir computing systems”, Semicond. Sci. Technol. 37,  p.103001  (2022). (Review)

2. S. Kasai, “Thermally driven single-electron stochastic resonance”, Nanotechnology 33 , p.505203 (2022) .

International Conference Papers

2. S. Kasai and S. Saito, “Fabrication and Characterizations of Tunnel Diode-based Oscillator Nodes for Electronic Reservoir Computing”, 2022 Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD2022), July 7-8, 2022, Online.

3. S. Kasai and M. Aono, “Amoeba-Inspired Electronic Computing System for Combinatorial Optimization”, 242nd ECS Meeting, Oct. 9-13, 2022, Atlanta, USA (Hybrid) (Invited)

4. S. Kasai , "Amoeba-inspired analog electronic computer ", JKCCS 2023, Jan. 4-6, 2023, Gyeongju , Korea (KEYNOTE)

2021

Research Articles

3. S. Mizuno, R. Lu, K. Shimizu, Y. Ueba, M. Ishikawa, M. Kitamura, M. Hoga and S. Kasai, “Fabrication and characterization of a nano-convex-embedded Si MOSFET for nano-scale electrical discrimination”, Jpn. J. Appl. Phys. 60, pp.SCCE10.1-6 (2021).

Books

1. M. Lis, S. Onuma, D. Przyczyna, P. Zawal, T. Mazur, K. Pilarczyk, P. L. Gentili, S. Kasai and K. Szaciłowski, Chapter 1: “From Oscillatory Reactions to Robotics: A Serendipitous Journey Through Chemistry, Physics and Computation”, WSPC Book Series in Unconventional Computing, Handbook of Unconventional Computing, pp. 1-79 (2021).

International Conference Papers

5. S. Saito and S. Kasai, “Nonlinear Node Using Tunnel Diode and Its Connection for Physical Reservoir Computing System”, 2021 Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD 2021), Aug. 26 - 27, 2021, Online. 

6. Y. J. Yan, H. Amano, M. Aono, K. Ohkoda, S. Fukuda, K. Saito, and S. Kasai, “Resource-saving FPGA Implementation of the Satisfiability Problem Solver: AmoebaSATslim”, 2021 International Conference on Field-Programmable Technology (ICFPT), Dec. 6-10, 2021, Auckland, New Zealand.

2020

Research Articles

1. K. Sasaki, S. Saito, and S. Kasai, “Current timer switch in a GaAs-based nanowire coupled with polyoxometalate nanoparticle and conductive AFM tip”, Jpn. J. Appl. Phys. 59 (Oct. 2020) pp.105005.1-7 (doi:10.35848/1347-4065/abb9c9).

2. K. Saito, M. Aono, and S. Kasai, “Amoeba-inspired analog electronic computing system integrating resistance crossbar for solving the travelling salesman problem”, Scientific Reports 10 (Nov. 2020) pp. 20772.1-9 (doi: 10.1038/s41598-020-77617-7).

3. K. Saito and S. Kasai, “Effect of feedback delays on solution quality in amoeba-inspired computing system that solves traveling salesman problem”, Appl. Phys. Express 13 (Oct. 2020) pp.114501.1-5 (doi: 10.35848/1882-0786/abbfe1).

4. K. Saito, N. Suefuji, and S. Kasai, “Effect of asymmetric deformation dynamics in amoeboid organism on its search ability”, Bioinspiration & Biomimetics 16 (Mar. 2021) pp.036003.1-8 (doi:10.1088/1748-3190/abe6f9).

International Conference Papers

1. S. Mizuno, R. Lu, Y. Ueba, M. Ishikawa, M. Kitamura, M. Hoga, and S. Kasai, “Fabrication and Characterization of Nano-Convex-Embedded Si MOSFET toward Electrical Nanostructure Discrimination”, 33rd International Microprocesses and Nanotechnology Conference (MNC 2020), Nov. 9-12, 2020 (online).

2. K. Saito, S. Kasai, and M. Aono, “Evaluation of Solution Search Performance of Amoeba-Inspired Electronic Computing System for Solving Maximum Cut Problem”, 2020 International Symposium on Nonlinear Theory and Its Applications (NOLTA 2020), Nov. 16-19, 2020 (online).

3. S. Kasai, “Electronic implementation of nature-inspired functionalities dealing with fluctuations”, MJIIT-UTM Nanotech: Materials and Devices 2021 Prominent Lecture Series, Feb. 16, 2021 (online) (invited).

4. S. Kasai, “Stochastic resonance in electronics”, Krakow Condensed Matter (UPeL) Seminar, March 10, 2021 (online) (invited).

2019

Research Articles

1. K. Sasaki, S. Okamoto, S. Tashiro, T. Asai, and S. Kasai, “Formation and characterization of charge coupled structure of polyoxometalate particles and a GaAs-based nanowire for readout of molecular charge states”, Jpn. J. Appl. Phys. 58, pp.SDDE13.1-6 (2019).

2. X. Zeng, D. Zhang, Y. Zhu, M. Chen, H. Chen, S. Kasai, H. Meng, and O. Goto, “Insight into in-plane isotropic transport in anthracene-based organic semiconductors”, Journal of Materials Chemistry C 7, pp.14275-14283 (2019).

International Conference Papers

1. R. Lu, K. Shimizu, X. Yin, Y. Ueba, M. Ishikawa, M. Kitamura, S. Kasai, “Formation and Characterization of 2D Random Si Nano-Pattern Using Resist Collapse for Nano-Artifact Metrics”, 2019 Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD2019), July 1-3, 2020, Busan, Korea.

2. X. Yin and S. Kasai, “Atomic Scale Gap in Ni-Graphene Interface and Its Effect on Contact Resistance”, The 21st International Conference on Electron Dynamics in Semiconductors, Optoelectronics and Nanostructures (EDISON21), July 14-19, 2019, Nara, Japan.

3. S. Saito, K. Sasaki, and S. Kasai, “Observation of Synchronized Charge Behavior in a Polyoxometalate Nanoparticle Using a GaAs-Based Nanowire Charge Detector”, 32nd International Microprocesses and Nanotechnology Conference (MNC2019), Oct. 28-31, 2019, Hiroshima, Japan.

4. S. Kasai, “Amoeba-inspired electronic computer solving optimization problem”, International Symposium for Neuromorphic Hardware Research Center, Dec. 11-12, 2019, Kitakyushu, Fukuoka, Japan.

2018

Research Articles

1. T. Yamada, H. Fukuda, T. Fujiwara, P. Liu, K. Nakamura, S. Kasai, A. L. Vazquez de Parga, and H. Tanaka, "Energy gap opening by crossing drop cast single-layer graphene nanoribbons", Nanotechnology 29, pp.315705.1-10, 2018.

2. K. Saito, N. Suefuji, S. Kasai, and M. Aono, "Amoeba-inspired electronic computing system and its application to autonomous walking of a multi-legged robot", Journal of Applied Logics 5, pp.1799-1814, 2018.

International Conference Papers

1. S. Kasai, "Electronic Representation of Nature-inspired Functions for Nano-scale Electronic Systems", Nanotech Malaysia 2018, May 7-8, 2018, Kuala Lumpur, Malaysia. (invited)

2. S. Kasai, “Stochastic resonance in electron devices and its application”, ACSIN 2018 Informal Satellite Workshop Material Intelligence -Unconventional Computing by Network-based Materials-, Oct. 25-26, 2019, Iwanuma, Japan. (invited)

3. K. Saito, N. Suefuji, S. Kasai, and M. Aono, "Amoeba-inspired electronic solution-searching system and its application to finding walking maneuver of a multi-legged robot", 2018 IEEE 48th International Symposium on Multiple-Valued Logic, Linz, Austria, May 16-18, 2018.

4. K. Inada, K. Tajima, and S. Kasai, "User-adaptive Surface Myoelectric Signal Detection System Using Nonlinear Device Network", 2018 International Symposium on Nonlinear Theory and Its Applications (NOLTA 2018), Tarragona, Spain, September 2-6, 2018.

5. K. Sasaki, S. Okamoto, S. Tashiro, T. Asai, and S. Kasai, "Charge Coupling between Polyoxometalate Molecule and a GaAs-Based Nanowire for Readout of Molecular Multiple Charge State", 31st International Microprocesses and Nanotechnology Conference (MNC2018), Nov. 13-16, 2018, Sapporo Japan.

6. K. Shimizu, Y. Ueba, M. Kitamura, Y. Ohyagi, M. Hoga, N. Tate, M. Naruse, T. Matsumoto, and S. Kasai, "Study on Electrical Discrimination of 2D Random Nanostructures Embedded in a Si MOSFET", 31st International Microprocesses and Nanotechnology Conference (MNC2018), Nov. 13-16, 2018, Sapporo Japan.

2017

Research Articles

1. S. Kasai, A. Ichiki, and Y. Tadokoro, "Divergence of relative difference in Gaussian distribution function and stochastic resonance in a bistable system with frictionless state transition", Appl. Phys. Express 11, pp.037301.1-4 (2018).

2. Z. Yatabe, S. Inoue, J. T. Asubar, and S. Kasai, "Analytical derivation of charge relaxation time distribution in a transistor from current noise spectrum using inverse integral transformation method", Appl. Phys. Express 11, pp.031201.1-4 (2018)

3.  M. Chen, Y. Zhu, C. Yao, D. Zhang, Xi. Zeng, I. Murtaza, H. Chen, S. Kasai, H. Meng, O. Goto, "Intrinsic charge carrier mobility in single-crystal OFET by "fast trapping vs. slow detrapping" model", Organic Electronics 54, pp.237-244 (2018).

4.  A. Setiadi, H. Fujii, S. Kasai, K. Yamashita, T. Ogawa, T. Ikuta, Y. Kanai, K. Matsumoto, Y. Kuwahara, and M. Akai-Kasaya, "Room-temperature discrete-charge-fluctuation dynamics of a single molecule adsorbed on a carbon nanotube", Nanoscale 30, pp.10674-10683 (2017).

5.  S. Okamoto, M. Sato, K. Sasaki, and S. Kasai, "Detection of charge dynamics of a tetraphenylporphyrin particle using GaAs-based nanowire enhanced by particle-metal tip capacitive coupling", Jpn. J. Appl. Phys. 56, pp.06GK02.1-6 (2017).

Books

1.  S. Kasai, S. Inoue, S. Okamoto, K. Sasaki, X. Yin, R. Kuroda, M. Sato, R. Wakamiya, and K. Saito, "Detection and Control of Charge State in Single Molecules Toward Informatics in Molecular Networks", Molecular Architectonics -The Third Stage of Single Molecule Electronics-, Ed. T. Ogawa, Springer, Switzerland (2017), pp.69-94.

International Conference Papers

1.  S. Kasai, "Amoeba-inspired electronic computing system: Fluctuation and solution searching capability", Workshop on Molecular Architectonics - Toward Realization of Neuromorphic Computing by Nanomatrials, June 29-30, 2017, Toyonaka, Osaka, Japan (invited).

2. K. Saitoh and S. Kasai, "Impact of External Fluctuation on Solution Search in Amoeba-inspired Electronic Computing System", Workshop on Molecular Architectonics - Toward Realization of Neuromorphic Computing by Nanomatrials, June 29-30, 2017, Toyonaka, Osaka, Japan.

3. K. Inada, Y. Inden, and S. Kasai, "Development of Robust Surface Myoelectric Detection Technique Using a Nonlinear Device Network with Auto Parameter Tuning Mechanism", 2017 Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD2017), July 3-5, 2017, Gyeongju, Korea.

4.  K. Shimizu, X. Yin, K. Sasaki, and S. Kasai, "Electrical Nanostructure Discrimination Technique for Nano-artifact Metrics", 2017 Asia-Pacific Workshop on Fundamentals and Applications of Advanced Semiconductor Devices (AWAD2017), July 3-5, 2017, Gyeongju, Korea.

5. X. Yin and S. Kasai, " Reduction of EB resist residues on graphene surface in terms of resist adhesion and solubility in developer solution", 12nd Topical Workshop on Heterostructure Microelectronics (TWHM2017), August 28-31, 2017, Kirishima, Japan. 

6. X. Yin and S. Kasai, "Impact of Small Amount of Ni Atoms on Contact Resistance in Metal-Graphene System", 30th International Microprocesses and Nanotechnology Conference (MNC2017), November 6-9, 2017, Jeju, Korea.

7. K. Sasaki, S. Okamoto, S. Tashiro, T. Asai, and S. Kasai, "Characterization of stochastic charge dynamics of polyoxometalate dispersed on a GaAs-based nanowire FET", International Workshop on Molecular Architectonics 2018, March 2-3, 2018, Toyonaka, Osaka, Japan.

Contact:

Seiya KASAI   Dr. (Eng.)

Professor 

Research Center for Integrated Quantum Electronics (RCIQE)

Hokkaido University

North 13, West 8, 060-0813 Sapporo

JAPAN 

E-mail: kasai(at)rciqe.hokudai.ac.jp   (replace (at) by @）

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