Self-correcting random number generator
Abstract
A system and method for generating random numbers. The system may include a random number generator (RNG), such as a quantum random number generator (QRNG) configured to self-correct or adapt in order to substantially achieve randomness from the output of the RNG. By adapting, the RNG may generate a random number that may be considered random regardless of whether the random number itself is tested as such. As an example, the RNG may include components to monitor one or more characteristics of the RNG during operation, and may use the monitored characteristics as a basis for adapting, or self-correcting, to provide a random number according to one or more performance criteria.
- Inventors:
- Issue Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1320887
- Patent Number(s):
- 9436436
- Application Number:
- 14/178,863
- Assignee:
- UT-Battelle, LLC (Oak Ridge, TN)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 2014 Feb 12
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
Citation Formats
Humble, Travis S., and Pooser, Raphael C. Self-correcting random number generator. United States: N. p., 2016.
Web.
Humble, Travis S., & Pooser, Raphael C. Self-correcting random number generator. United States.
Humble, Travis S., and Pooser, Raphael C. Tue .
"Self-correcting random number generator". United States. https://www.osti.gov/servlets/purl/1320887.
@article{osti_1320887,
title = {Self-correcting random number generator},
author = {Humble, Travis S. and Pooser, Raphael C.},
abstractNote = {A system and method for generating random numbers. The system may include a random number generator (RNG), such as a quantum random number generator (QRNG) configured to self-correct or adapt in order to substantially achieve randomness from the output of the RNG. By adapting, the RNG may generate a random number that may be considered random regardless of whether the random number itself is tested as such. As an example, the RNG may include components to monitor one or more characteristics of the RNG during operation, and may use the monitored characteristics as a basis for adapting, or self-correcting, to provide a random number according to one or more performance criteria.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Sep 06 00:00:00 EDT 2016},
month = {Tue Sep 06 00:00:00 EDT 2016}
}
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