Approximating Stochastic Quantum Noise through Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7810
- @InProceedings{Muqeet:2024:SSBSE,
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author = "Asmar Muqeet and Shaukat Ali and Paolo Arcaini",
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title = "Approximating Stochastic Quantum Noise through Genetic
Programming",
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booktitle = "SSBSE Challenge Track",
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year = "2024",
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editor = "Gunel Jahangirova and Foutse Khomh",
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volume = "14767",
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series = "Lecture Notes in Computer Science",
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pages = "56--62",
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address = "Porto de Galinhas, Brazil",
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month = "15 " # jul,
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publisher = "Springer Nature",
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keywords = "genetic algorithms, genetic programming, STGP, DEAP",
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isbn13 = "978-3-031-64573-0",
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URL = "
https://2024.esec-fse.org/profile/asmarmuqeet",
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DOI = "
doi:10.1007/978-3-031-64573-0_5",
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code_url = "
https://zenodo.org/records/11198788",
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abstract = "Quantum computing potential for exponential speedups
over classical computing has recently sparked
considerable interest. However, quantum noise presents
a significant obstacle to realizing this potential,
compromising computational reliability. Accurate
estimation and mitigation of noise are crucial for
achieving fault-tolerant quantum computation. While
current efforts focus on developing noise models
tailored to specific quantum computers, these models
often fail to fully capture the complexity of real
quantum noise. To this end, we propose an approach that
uses genetic programming (GP) to develop
expression-based noise models for quantum computers. We
represent the quantum noise model as a computational
expression, with each function corresponding to a
specific aspect of the noise behavior. By function
nesting, we create a chain of operations that
collectively capture the intricate nature of quantum
noise. Through GP, we explore the search space of
possible noise model expressions, gradually improving
the quality of the solution. We evaluated the approach
on five artificial noise models of varying complexity
and a real quantum computer. Results show that our
approach achieved an error difference of less than
2percent in approximating artificial noise models and
15percent for a real quantum computer.",
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notes = "Simula Research Laboratory",
- }
Genetic Programming entries for
Asmar Muqeet
Shaukat Ali
Paolo Arcaini
Citations