| Issue |
E3S Web Conf.
Volume 498, 2024
III International Conference on Actual Problems of the Energy Complex: Mining, Production, Transmission, Processing and Environmental Protection (ICAPE2024)
|
|
|---|---|---|
| Article Number | 02007 | |
| Number of page(s) | 7 | |
| Section | Ecology and Environmental Protection Issues | |
| DOI | https://doi.org/10.1051/e3sconf/202449802007 | |
| Published online | 06 March 2024 | |
Model of biodiversity and plant sustainability based on quantum variational optimization
1 Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, 39, Kari Niyazov ave., Tashkent, 100000, Uzbekistan
2 Chirchik State Pedagogical University, 104, str. Amir Temur, Tashkent, 100000, Uzbekistan
* Corresponding author: dilnoz134@rambler.ru
Plant biodiversity plays an important role in the sustainability of ecosystems and human societies. The resilience of plants in the context of biodiversity relates to their ability to adapt to changing environmental conditions, provide ecosystem services and meet human needs. This article examines the influence of quantum variational optimization on the solution of a system of differential equations for a model of plant biodiversity and sustainability, taking into account the interaction between two populations. The system of equations models the dynamics of changes in the density of plant populations of types and over time, consider the influence of interaction, growth coefficients and the intensity of the impact of diseases and pests. The numerical integration method is used to solve the system of equations, and quantum variational optimization is also introduced. Quantum variational optimization is performed with the goal of minimizing the error obtained from a quantum computational experiment. An analysis is made of the optimal parameters found using quantum optimization and their impact on population dynamics. The article provides a comprehensive approach to studying the influence of quantum variational optimization on the solution of differential equations, and discusses the potential prospects for using this method in environmental and biological models.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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