← Back to Publications List

COMPUTATIONAL AND STATISTICAL MODELING OF PHYSICAL SYSTEMS USING PROBABILISTIC METHODS

Students & Supervisors

Student Authors
Tahia Hasan Mim
Bachelor of Science in Computer Science & Engineering, FST
Afiyah Abida Ayesha
Bachelor of Science in Electrical & Electronic Engineering, FE
Labiba Chowdhury
Bachelor of Science in Industrial & Production Engineering, FE
Koushik Biswas Arko
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

In nature, innumerable physical systems show great complexity and stochasticity, that makes proper analytical solutions that makes proper analytical solutions illogical or unfeasible. Traditional ways to understand that how a specific system behaves under unpredictability aren’t always enough. To precisely understand how a physical system behaves under diffidence needs methods that go beyond the traditional ways. This study put forward an acceptable analysis of stochastic physical systems in a clear and approachable technique by using Probabilistic and Computational Framework. The preferred procedures or methodology for presenting the behavior of small-scale particles that isn’t fixed but totally unpredictable fully depends on Monte Carlo Simulations and Random Sampling Method. Conducting many simulations, key measurable quantities like probability distributions, variance, and exception values are achieved. The impact of microscopic randomness on global system behavior was inspected by the acquired quantities. To verify and ensure the stability of numerical results, both stability analysis and convergence were conducted. The analysis reveals that probabilistic modeling, along with computational simulations, can propitiously encapsulate stochastic or randomly influenced behavior that can not be obtained by analytical analysis. The findings illustrate even the random movements at the microscopic level can merge to construct clear and bigger scale patterns. In closing, the study apotheosis the significance of statistical methods and probabilistic in the research field of modern Theoretical and Computational Physics. The proposed framework is not just scalable and adaptable but also it can be applicable to broad spectrum of stochastic physical systems.

Keywords

Computational Physics Probabilistic Modeling Monte Carlo Simulation Stochastic Systems Statistical Physics

Publication Details

  • Type of Publication:
  • Conference Name: International Conference on Physics 2026
  • Date of Conference: 04/09/2026 - 04/09/2026
  • Venue: Physics department, Dhaka University
  • Organizer: Bangladesh Physical Society
View on Publisher