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Title: Quantum Noise in the Flow of Time: A Temporal Study of the Noise in Quantum Computers
Award ID(s):
2217021
NSF-PAR ID:
10422695
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
EEE 28th International Symposium on On-Line Testing and Robust System Design (IOLTS)
Page Range / eLocation ID:
1 to 5
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  1. Arai, Kohei (Ed.)
    Quantum noise is seen by many researchers as a problem to be resolved. Current solutions increase quantum computing system costs significantly by requiring numerous hardware qubits to represent a logical qubit to average the noise away. However, despite its deleterious effects on system performance and the increased costs it creates, it may have some potential uses. This paper evaluates those. Specifically, it considers how quantum noise could be used to support the fuzzing cybersecurity and testing technique and AI techniques such as certain swarm artificial intelligence algorithms. Fuzzing is used to identify vulnerabilities in software by generating massive amounts of input cases for a program. Quantum noise provides an effective built-in fuzzing capability that is centered around the actual answer to a computation. These same phenomena, of clustered and centered fuzz-noise around the answer of an operation, could be similarly useful to AI techniques that can make effective use of lots of point values for optimization. Effectively, by concurrently considering the ‘multiverse’ of possible results to an operation, created by compounding noise, more beneficial solutions that are proximal to the actual result of an operation can be identified via testing quantum noise points with an effectiveness algorithm. Both of these potential uses for quantum noise are considered herein. 
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