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Silicon single-electron random number generator based on random telegraph signals at room temperature

Silicon single-electron random number generator based on random telegraph signals at room temperature
Silicon single-electron random number generator based on random telegraph signals at room temperature
The need for hardware random number generators (HRNGs) that can be integrated in a Silicon (Si) complementary-metal-oxide-semiconductor (CMOS) platform has become increasingly important in the era of the Internet-of-Things(IoT). Si MOSFETs exhibiting random telegraph signals (RTSs) have been considered as such a candidate for HRNG,though its application has been hindered by RTS’s variability and uncontrollable, unpredictable characteristics. In this paper, we report the generation and randomness evaluation of random numbers from RTSs in a Si single electron pump (SEP) device at room temperatures. SEP devices are known to consistently produce RTSs, due to a quantum dot electrically defined by multi-layer polycrystalline Si gates. Using RTSs observed in our devices, random numbers were extracted by a classifier supported by supervised learning, where part of data was used to train the classifier before it is applied to the rest to generate random numbers. The random numbers generated from RTSs were used as inputs forthe Monte Carlo method to calculate the values of π, and the distribution was compared against the result obtained from Mersenne twister, a representative pseudo random number generator (PRNG), under the same condition.πwasestimated more than 80000 times, and the distribution of the estimated values has a central value at 3.14 with a variance of 0.273, which is only twice larger than the result from PRNG. Our result paves a way to fully electronic CMOS compatible HRNG that can be integrated in a modern System-on-a-Chip in IoT devices.
2158-3226
Ibukuro, Kouta
b863054f-39db-4e0e-a2cb-981a86820dda
Liu, Fayong
beec7ff8-5835-4793-981b-fafd99b52549
Husain, Muhammad K
92db1f76-6760-4cf2-8e30-5d4a602fe15b
Sotto, Moise Sala Henri
2e7797fc-4433-4513-bd08-03ab7839452c
Hillier, Joseph William
3621050b-74de-4fb7-b1ee-968965966336
Li, Zuo
05f14f5e-fc6e-446e-ac52-64be640b5e42
Tomita, Isao
e4a78ed2-f525-4fb0-9711-86e2b2dd5587
Tsuchiya, Yoshishige
5a5178c6-b3a9-4e07-b9b2-9a28e49f1dc2
Rutt, Harvey
e09fa327-0c01-467a-9898-4e7f0cd715fc
Saito, Shinichi
14a5d20b-055e-4f48-9dda-267e88bd3fdc
Ibukuro, Kouta
b863054f-39db-4e0e-a2cb-981a86820dda
Liu, Fayong
beec7ff8-5835-4793-981b-fafd99b52549
Husain, Muhammad K
92db1f76-6760-4cf2-8e30-5d4a602fe15b
Sotto, Moise Sala Henri
2e7797fc-4433-4513-bd08-03ab7839452c
Hillier, Joseph William
3621050b-74de-4fb7-b1ee-968965966336
Li, Zuo
05f14f5e-fc6e-446e-ac52-64be640b5e42
Tomita, Isao
e4a78ed2-f525-4fb0-9711-86e2b2dd5587
Tsuchiya, Yoshishige
5a5178c6-b3a9-4e07-b9b2-9a28e49f1dc2
Rutt, Harvey
e09fa327-0c01-467a-9898-4e7f0cd715fc
Saito, Shinichi
14a5d20b-055e-4f48-9dda-267e88bd3fdc

Ibukuro, Kouta, Liu, Fayong, Husain, Muhammad K, Sotto, Moise Sala Henri, Hillier, Joseph William, Li, Zuo, Tomita, Isao, Tsuchiya, Yoshishige, Rutt, Harvey and Saito, Shinichi (2020) Silicon single-electron random number generator based on random telegraph signals at room temperature. AIP Advances, 10 (11), [115101]. (doi:10.1063/5.0023647).

Record type: Article

Abstract

The need for hardware random number generators (HRNGs) that can be integrated in a Silicon (Si) complementary-metal-oxide-semiconductor (CMOS) platform has become increasingly important in the era of the Internet-of-Things(IoT). Si MOSFETs exhibiting random telegraph signals (RTSs) have been considered as such a candidate for HRNG,though its application has been hindered by RTS’s variability and uncontrollable, unpredictable characteristics. In this paper, we report the generation and randomness evaluation of random numbers from RTSs in a Si single electron pump (SEP) device at room temperatures. SEP devices are known to consistently produce RTSs, due to a quantum dot electrically defined by multi-layer polycrystalline Si gates. Using RTSs observed in our devices, random numbers were extracted by a classifier supported by supervised learning, where part of data was used to train the classifier before it is applied to the rest to generate random numbers. The random numbers generated from RTSs were used as inputs forthe Monte Carlo method to calculate the values of π, and the distribution was compared against the result obtained from Mersenne twister, a representative pseudo random number generator (PRNG), under the same condition.πwasestimated more than 80000 times, and the distribution of the estimated values has a central value at 3.14 with a variance of 0.273, which is only twice larger than the result from PRNG. Our result paves a way to fully electronic CMOS compatible HRNG that can be integrated in a modern System-on-a-Chip in IoT devices.

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More information

Submitted date: 12 September 2020
Accepted/In Press date: 12 October 2020
Published date: 2 November 2020

Identifiers

Local EPrints ID: 444748
URI: http://eprints.soton.ac.uk/id/eprint/444748
ISSN: 2158-3226
PURE UUID: 6d26b6cf-4b77-4944-a419-2c1c17a7b7dd
ORCID for Kouta Ibukuro: ORCID iD orcid.org/0000-0002-6546-8873
ORCID for Fayong Liu: ORCID iD orcid.org/0000-0003-4443-9720
ORCID for Shinichi Saito: ORCID iD orcid.org/0000-0003-1539-1182

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Date deposited: 03 Nov 2020 17:30
Last modified: 18 Feb 2021 17:31

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Contributors

Author: Kouta Ibukuro ORCID iD
Author: Fayong Liu ORCID iD
Author: Muhammad K Husain
Author: Moise Sala Henri Sotto
Author: Joseph William Hillier
Author: Zuo Li
Author: Isao Tomita
Author: Yoshishige Tsuchiya
Author: Harvey Rutt
Author: Shinichi Saito ORCID iD

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