Quantum-Inspired Statistical Frameworks: Enhancing Traditional Methods with Quantum Principles

Encyclopedia, Journal Year: 2025, Volume and Issue: 5(2), P. 48 - 48

Published: April 4, 2025

This manuscript introduces a comprehensive framework for augmenting classical statistical methodologies through the targeted integration of core quantum mechanical principles—specifically superposition, entanglement, measurement, wavefunctions, and density matrices. By concentrating on these foundational concepts instead whole expanse theory, we propose “quantum-inspired” models that address persistent shortcomings in conventional approaches. In particular, five pivotal distributions (normal, binomial, Poisson, Student’s t, chi-square) are reformulated to incorporate interference terms, phase factors, operator-based transformations, thereby facilitating representation multimodal data, phase-sensitive dependencies, correlated event patterns—characteristics frequently underrepresented purely real-valued, frameworks. Furthermore, ten quantum-inspired principles delineated guide practitioners systematically adapting mechanics traditional inferential tasks. These illustrated domain-specific applications finance, cryptography (distinct from direct applications), healthcare, climate modeling, demonstrating how amplitude-based confidence measures, matrices, measurement analogies can enrich standard by capturing more nuanced correlation structures enhancing predictive performance. unifying constructs with established this work underscores potential interdisciplinary collaboration paves way advanced data analysis tools capable addressing high-dimensional, complex, dynamically evolving datasets. Complete R code ensures reproducibility further exploration.

Language: Английский

Quantum-inspired metaheuristic algorithms for Industry 4.0: A scientometric analysis

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 139, P. 109635 - 109635

Published: Nov. 20, 2024

Language: Английский