CEQT Center of Excellence in Quantum Technology

Research › Simulation

Pillar 2 · Research

Simulation

Quantum many-body dynamics, agent-based and complex-systems simulation, computational chemistry and materials modelling, and digital twins.

Modelling systems that are too entangled, too many-bodied or too adaptive to solve directly.

Simulation is the part of the field with the clearest near-term payoff, because there are systems we genuinely cannot solve any other way. A molecule of modest size already has a state space beyond classical enumeration; a market, a power grid or an epidemic is not analytically tractable at all, for different reasons.

This pillar covers both. On the quantum side we work on many-body dynamics — the behaviour of strongly interacting systems, and the numerical methods that make them tractable. On the complex-systems side we build agent-based models, where the interesting behaviour is emergent rather than derived, and we are interested in what quantum and quantum-inspired methods add to them.

Computational chemistry sits between the two, and is where simulation most often meets an experimentalist with a question.

Information has a speed limitExact diagonalisation of a 9-spin transverse-field Ising chain, J = 1, h = 0.6
How a disturbance spreads along a 9-spin quantum chain Exact time evolution of a transverse-field Ising chain. One spin at the centre is flipped at time zero; the shading shows how far the disturbance has reached at each later time. It spreads in a widening cone rather than instantly — correlations have a speed limit. 1234567890246 Effect of flipping one spin, site by site, as time runs down site along the chain

Methods we use

  • Quantum many-body dynamics — strongly correlated systems, lattice models, time evolution.
  • Agent-based and complex-systems simulation — emergent behaviour, high-dimensional parameter spaces, calibration against data.
  • Computational chemistry and quantum simulation — electronic structure, medicinal chemistry applications.
  • Materials modelling — electronic and structural properties of functional materials.
  • Digital twins and hybrid simulation — physical models coupled to live data.

Problems we apply them to

  • Drug candidate screening and medicinal chemistry.
  • Functional and energy materials.
  • Market and macroeconomic dynamics as complex adaptive systems.
  • Smart-grid behaviour under distributed generation.
  • Fundamental questions in many-body quantum physics.

Active in: Finance & econometrics · Chemistry & materials · Energy & smart grids · Complex systems

Current work

  • On-going

    Neutral-atom quantum computing

    Simulation and control for neutral-atom architectures, jointly with RCQT.

  • On-going

    Atom arrangement for large-scale cold-atom quantum computers

    Defect-free array assembly and the optimisation problem underneath it.

People in this pillar

Dr. Parinya Udommai

Quantum many-body dynamics

parinya.udommai@cmu.ac.th

Assoc. Prof. Dr. Piyarat Nimmanpipug

Computational simulation and modelling (CSML) · medicinal chemistry

piyarat.n@cmu.ac.th

Asst. Prof. Dr. Waranont Anukool

Quantum-inspired agent-based simulation · Director

waranont.a@cmu.ac.th

Selected publications

  • “Monotonic manipulation of atomic density in an isovolumetric focused-beam trap for quantum atom experiments.” ScienceAsia 51S (2025). doi
  • “DFT insights into crystal plane effects of molybdenum phosphide (MoP) on the catalytic performance in deoxygenation of palmitic acid.” Catalysis Science & Technology 14, 190–201 (2024). doi
  • “Controllable terahertz intersubband absorptions in ZnO/(Sb,N) co-doped ZnO quantum wells: first-principles study.” J. Phys. Chem. Solids 185, 111765 (2024). doi

Browse all 215 publications →

See also

Algorithms that make these simulations tractable sit in Algorithm design; the compute they run on is described under Software & platforms. The physical cold-atom experiments are RCQT’s — see RCQT.

Last updated 14 September 2026.