About
PhyAnalytics
PhyAnalytics combines physical modelling, numerical computation, data and uncertainty to analyse complex physical systems and support better decisions.
Mission
To produce analysis of physical systems whose confidence is stated as clearly as its result. Many decisions about energy, infrastructure, industry and research rest on numbers that come without any indication of how far they can be trusted. PhyAnalytics exists to supply both.
Scientific foundation
The work sits at the intersection of physics, numerical methods, scientific computing, statistics and uncertainty quantification. Physics constrains what a model may do; numerical analysis guarantees that it is solved correctly; data determine its parameters; uncertainty quantification states what remains unknown.
That combination is the difference between physics-informed analytics and generic data analysis: the models extrapolate sensibly, their parameters mean something, and their failures can be diagnosed.
Approach
- 01 /
Problem
State the question in terms of a decision or a quantity, and what accuracy is needed.
- 02 /
Model
Formulate the physics and mathematics, with assumptions written down.
- 03 /
Computation
Solve the model numerically and verify the accuracy of the solution.
- 04 /
Data
Confront the model with measurements; calibrate its parameters.
- 05 /
Uncertainty
Propagate what is not known to the result; identify the dominant sources.
- 06 /
Interpretation
Explain what the result means, what it does not show, and what would change it.
Founder
Hope Donglo, PhD
Founder · Physicist
A physicist working on the theory and simulation of nuclear reactions, in particular the formation of superheavy nuclei in heavy-ion collisions. The work involves building and maintaining research simulation software, calibrating reaction models against experimental data, and quantifying the uncertainty of their predictions. PhyAnalytics applies the same methods to physical systems beyond nuclear physics.