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A quantum-hybrid ecological model for managing plant cultivation in saline and desert regions

D.T. Muhamediyeva, Narzillo Mamatov, A. N. Samijonov, Absametov Bayram Bekbosinovich, M. S. Qudaynazarov

Published Apr 9, 2026• 0 citations
Publisher

Abstract

The article considers the issue of scientifically based formation and management of the population of plants that restore the natural landscape, such as saxaul, yulgin, kandim and cherkes, in saline and severely degraded desert areas. These plants make a significant contribution to reducing wind erosion in the region, reducing soil salinity, restoring ecological stability and strengthening the feed base for livestock. The study proposes a hybrid mathematical model that describes their biomass growth, spatial distribution, competition and response to management influences. A computational approach based on a variational quantum algorithm is used to determine the central control parameter of the model. In this case, the optimal control value is found by minimizing the smallest value of the Hamiltonian energy. The spatial-temporal dynamics of plants is assessed through surface distribution maps of biomass, ecological stress indices, competition indicators, management costs and Hamiltonian evolution. The results have important practical significance in planning desert plant plantings, creating ecologically sustainable landscapes, and establishing sustainable agroecological systems in saline areas.

DOI
10.1051/e3sconf/202670301006/pdf

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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.
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