The Theoretical and Computational Physics research group is part of the academic development and educational research under the Department of Physics, Faculty of Mathematics and Natural Sciences (FMIPA), Syiah Kuala University. We advance fundamental understanding of physical phenomena through analytical theory and large-scale computations, bridging scales from quantum to cosmological and linking models with experiment and data. Amid rapid growth in computing power and data availability, theory and simulation are essential to design materials, interpret complex measurements, and predict emergent behavior. Our group provides a scientific platform for curriculum development, research training, and collaborative projects that cultivate rigorous reasoning, creativity, and reproducible computational practice.
Our Focus
The group explores core questions in quantum, many-body, and condensed matter physics, along with statistical and classical physics. They apply theoretical methods to explain phenomena like band structure, excitations, topology, non-equilibrium behaviors, and phase transitions, validating their ideas using targeted simulations. Their numerical experiments include molecular dynamics (MD), Monte Carlo, finite-difference, finite-element, and spectral methods. They also utilize electronic-structure tools such as density functional theory (DFT), tight-binding, and atomistic models to forecast material properties. Their research incorporates physics-informed machine learning, reduced-order models, and Bayesian inference with rigorous uncertainty quantification. All work is supported by scalable parallel/GPU computing, strong software practices, and effective visualizations.
Activities and programmes:
Community and practice shape our calendar. Our weekly Theory & Methods Seminar highlights current issues, introduces techniques and reviews notable literature. Often, a conceptual talk is paired with a live notebook or code demonstration. Code sprints and hackathons are held periodically to bring students and faculty together to prototype solvers, analysis tools and visualisations, with concrete milestones and open-source releases. Many of our initiatives are run in partnership with neighbouring disciplines, such as materials science, chemistry, Earth science and biomedical engineering, reflecting the field’s natural interdisciplinarity.
Research and Innovation Roadmap.
In the longer term, multiscale modelling pipelines are being constructed to connect ab initio predictions to mesoscale and continuum descriptions with explicit error control. The company is currently allocating financial resources to the development of AI-augmented simulation, physics-informed neural networks, differentiable physics, and emulator models. The objective of these investments is to facilitate the delivery of real-time or near-real-time predictions, while maintaining physical fidelity. The overarching objective of this research is to develop a methodology for materials and device optimisation through the utilisation of Bayesian strategies that balance exploration and robustness. This methodology is informed by the concept of uncertainty-aware design, which is predicated on the premise that uncertainty is an inherent aspect of any scientific endeavour. Algorithmically speaking, the organisation is preparing for exascale by developing portable, heterogeneous solvers that exploit CPUs and GPUs efficiently. It is evident that the institution is committed to the principles of open science. This commitment is reflected in the integration of code and data from the first day of instruction, the sharing of datasets with provenance, and the utilisation of modular teaching codes. These codes facilitate the transformation of lecture topics into living, testable artefacts.
Gallery Activities
Our Staff
Research Topics
| Year | Research Title | Research Leader |
|---|---|---|
| 2021 | Development of an IoT (Internet of Things)-Based Remote Instrumentation System as an Alternative for Conducting Physics Laboratory Sessions During the COVID-19 Pandemic | Irwandi, S.Si,M.Si., Ph.D |
| 2021 | The Impact of Work Placement (KKP) on Enhancing Students’ Understanding and Skills in STEM Fields in Preparing for the 4th Industrial Revolution (A Case Study of Physics Students at the Faculty of Mathematics and Natural Sciences, Unsyiah) | Rajibussalim |
| 2022 | Development of an Interdisciplinary STEMC Module Using Electromagnetic Key Concepts to Support the 2022 Curriculum for the Success of the Merdeka Belajar Program | Irwandi, S.Si, M.Si., Ph.D |
| 2023 | DEVELOPMENT OF A PARALLEL STEWART MANIPULATOR PLATFORM FOR ROBOTICS LEARNING BASED ON THE STEMC APPROACH | Irwandi, S.Si,M.Si., Ph.D |
| 2023 | ENHANCING ICT LITERACY THROUGH A REMOTE STEM LABORATORY PLATFORM IN SUPPORT OF THE SDGs TO ACHIEVE QUALITY EDUCATION | Irwandi, S.Si,M.Si., Ph.D |