Applications of Quantum Field Theory to Problems in Machine Learning

Language: English

Published by Taylor and Francis Ltd, GB, 2026

1041281250 / 9781041281252

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This book examines quantum neural networks through renormalization techniques, supersymmetric field theory, and noisy harmonic oscillator systems. The book's analysis covers adaptive beamforming applications, brain modeling, gravitational control mechanisms, and mixed-state dynamics in superstring theory, and also includes:Comprehensive analysis of quantum neural networks through renormalization techniques and supersymmetric field theory applications in computational modelingInvestigation of quantum field dynamics with noise integration, filtering mechanisms, and scattering processes in curved spacetime environmentsStudy of adaptive beamforming methodologies combined with quantum neural networks for brain modeling and evolving field system applicationsExamination of mixed-state dynamics in superstring theory frameworks with emphasis on quantum noisy fields and supersymmetric effectsAnalysis of extended Kalman filter integration with quantum neural networks for transmission line control and field estimation optimizationThe work explores extended Kalman filter methodologies for transmission line control, field estimation, and symmetry-broken dynamics in signal processing systems for advanced computational modeling applications.This title has been co-published with Manakin Press. TandF does not sell or distribute the print editions in Bangladesh, Bhutan, India, Nepal, Pakistan, and Sri lanka.…

Seller Inventory # LU-9781041281252

Title
Applications of Quantum Field Theory to Problems in Machine Learning
Author
Harish Parthasarathy
Publisher
Taylor and Francis Ltd, GB
Publication year
2026
Condition
New
Binding
Hardback
Language
English
ISBN 10
1041281250
ISBN 13
9781041281252
Item weight
890 grams

Rarewaves.com UK

London, United Kingdom

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