Integrating Complex Adaptive Systems Theory with Whole-Systems Quantum Computing Approaches

This paper explores the intersection of Complex Adaptive Systems (CAS) and whole-systems quantum computing, focusing on how CAS principles can enhance quantum computing methods and vice versa. CAS, characterized by complexity, adaptability, self-organization, and emergence, amongst other properties, are prevalent in various domains, including ecology, economics, and social systems. Whole-systems quantum computing, particularly through quantum annealing, manipulates the global quantum state of a system, utilizing entanglement and superposition to solve optimization problems. The paper outlines a methodology for modeling complex adaptive problems using quantum annealing, alongside case studies illustrating CAS theory’s application in quantum computation. By examining representative quantum computing companies the paper investigates their management of entropy-a key summary metric in CAS-and correlations with quantum supremacy. The integration of CAS dynamics into quantum computing is posited to aid in designing more advanced Hamiltonians and quantum algorithms, enhancing the capability to tackle complex, real-world problems more efficiently. The paper calls for further research into several promising avenues, such as the development of sophisticated Hamiltonians that encode complex interdependencies, the validation of CAS models on quantum hardware, and the potential for systematizing quantum supremacy through a virtuous cycle of CAS-informed quantum algorithm development.

Authors

Publication Details

Published
2024-10-24
DOI
https://doi.org/10.1109/iemcon62851.2024.11093529
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Complex Adaptive Systems Theory with Whole-Systems Quantum Computing Approaches

Pravir Malik
Distributed and Parallel Computing Systems
article

Integrating Complex Adaptive Systems Theory with Whole-Systems Quantum Computing Approaches

Pravir Malik
article en

Abstract

This paper explores the intersection of Complex Adaptive Systems (CAS) and whole-systems quantum computing, focusing on how CAS principles can enhance quantum computing methods and vice versa. CAS, characterized by complexity, adaptability, self-organization, and emergence, amongst other properties, are prevalent in various domains, including ecology, economics, and social systems. Whole-systems quantum computing, particularly through quantum annealing, manipulates the global quantum state of a system, utilizing entanglement and superposition to solve optimization problems. The paper outlines a methodology for modeling complex adaptive problems using quantum annealing, alongside case studies illustrating CAS theory’s application in quantum computation. By examining representative quantum computing companies the paper investigates their management of entropy-a key summary metric in CAS-and correlations with quantum supremacy. The integration of CAS dynamics into quantum computing is posited to aid in designing more advanced Hamiltonians and quantum algorithms, enhancing the capability to tackle complex, real-world problems more efficiently. The paper calls for further research into several promising avenues, such as the development of sophisticated Hamiltonians that encode complex interdependencies, the validation of CAS models on quantum hardware, and the potential for systematizing quantum supremacy through a virtuous cycle of CAS-informed quantum algorithm development.

Openalex Percentile: Top 63%
Distributed and Parallel Computing Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.