Numerical Methods for Linear PDEs and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "C1: Difference and Differential Equations".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 68
Special Issue Editors
Interests: applied PDEs; inverse problems; differential geometry
Special Issue Information
Dear Colleagues,
Applied partial differential equations (PDEs) are employed in modeling real-world phenomena across several disciplines, including fluid dynamics, thermodynamics, and electromagnetic fields. In the realm of quantum mechanics, these PDEs describe the evolution of a physical system's quantum state over time, which is essential for understanding atomic and molecular interactions. Given their complexity, numerically solving applied PDEs often involves the Method of Characteristics and Spectral methods. In practical applications, leveraging a combination of these techniques, alongside careful attention to stability, convergence, and accuracy, is critical for obtaining reliable solutions to real-world problems modeled by PDEs. In this Special Issue, we aim to broaden the scope of this research area and enhance understanding of this domain for researchers and scholars alike.
This Special Issue, "Numerical Methods for Linear PDEs and Applications", aims to publish original and significant contributions on the following topics:
- Model real-world phenomena across various disciplines, including fluid dynamics, thermodynamics, and electromagnetic fields.
- Qualitative theory applied to solutions for partial differential equations.
- Any application from image processing and data science to quantum computing, quantum simulation, and numerical solutions allows for simulating complex quantum systems, and these topics will be well-represented in this Special Issue.
Dr. Mozhgan Nora Entekhabi
Prof. Dr. Hugo Leiva
Guest Editors
Manuscript Submission Information
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Keywords
- partial differential equations
- numerical methods
- fluid dynamics
- stability and convergence
- quantum computing
- image processing
- applied mathematics
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