Research › Foundations
Pillar 4 · Research
Foundations
Quantum information theory, computability and complexity, fractal and fractional methods, and quantum approaches in econometrics, finance and the social sciences.
The mathematics that decides what is computable at all.
This pillar asks what is computable at all, and under what cost. It is the slowest-moving of the four and the one that most often turns out to matter later: a complexity result constrains every algorithm anyone will ever write for that problem.
Two strands run through it. The first is conventional quantum information and complexity theory. The second is a body of work on fractal geometry and fractional calculus — non-integer dimensions, memory-dependent dynamics, non-local operators — applied to quantum systems, to networks, and to models in finance and physics where ordinary derivatives are the wrong tool. That work has produced results ranging from nonlinear Schrödinger equations to graph expanders with applications in quantum cryptography.
The econometrics and quantitative analysis group sits here too, because quantum finance and quantum econometrics are, at bottom, questions about representation: whether a quantum formalism describes a market better than a classical stochastic one.
Methods we use
- Quantum information theory — entanglement measures, entropy, information flow.
- Computability and complexity — problem classification and the limits of speed-up.
- Fractional calculus and fractal geometry — memory-dependent dynamics, non-local operators, non-integer dimension.
- Quantum econometrics, finance and social sciences — quantum and quantum-inspired formalisms for economic systems.
- Mathematical physics — the analytical backbone shared with the other pillars.
Problems we apply them to
- Option pricing and financial modelling under non-standard dynamics.
- Network and graph problems with cryptographic consequences.
- Memory effects in physical and engineered systems.
- Economic forecasting and macroeconomic modelling.
- Foundational questions raised by the other three pillars.
Active in: Finance & econometrics · Machine learning · Complex systems
Current work
- On-going
Development of deep knowledge in quantum technology for economic forecasting
- Continuing
Fractional and fractal methods in quantum systems
A sustained programme; a substantial share of the centre’s 2025–2026 publication record comes from it.
- Continuing
Quantum econometrics, finance and social sciences
People in this pillar
Prof. Dr. Rami Ahmad El-Nabulsi
Fractal quantum computing · fractional methods
Prof. Dr. Songsak Sriboonchitta
Econometrics and quantitative analysis
Assoc. Prof. Dr. Roengchai Tansuchat
Quantum finance and econometrics
Asst. Prof. Dr. Chukiat Chaiboonsri
Quantum econometrics
Selected publications
- “Black–Scholes equation in quantitative finance with variable parameters: a path to a generalized Schrödinger equation.” Financial Innovation (2026). doi
- “Fractional graph expanders and network dynamics: spectral properties and diffusion with applications to quantum cryptography.” Quantum Information Processing 25, 178 (2026). doi
- “Qualitative financial modelling in fractal dimensions.” Financial Innovation 11, 42 (2025). doi
- “Impact of Lagrangian deformations on photon entanglement and von Neumann entropy in multi-photon states.” Quantum Information Processing 25, 56 (2026). doi
See also
Results here feed directly into Algorithm design and the finance applications.
Last updated 14 September 2026.