He used a discrete Fick’s model of diffusion to model the railway network of Greater Manila, Philippines, showing left-skewed distributions of equilibrium times for various initial conditions. The paper is co-authored by Dr. Rene Batac, Enrico Miguel Posadas and Ramon Sarigumba.
Dr. Jude Maria V. Antenorcruz, a research faculty of the Complex Systems Group, was awarded the best oral presentation during the parallel sessions of the 2026 16th International Conference on Applied Physics and Mathematics (ICAPM) held on April 10-12, 2025 in Osaka, Japan.
Prof. Masaki Ogura from the @hu_oguralab Hiroshima University visited the DLSU on March 9, 2026. He gave a talk "From Local Interventions to Scalable System-Level Effects" to the faculty and students of the Complex Systems Group (CSG).
The preliminary work highlights the need for encouraging stronger collaborations among the researchers, not only from academia but from other sectors, to align with the targets outlined in the national science and technology agenda.
We studied the co-authorship network of a pioneer community of Philippine physics researchers:
K.M.A. Aguana and R.C. Batac, Emergence of power-law statistics in the co-authorship networks of Philippine physics researchers, Scientometrics, https://t.co/oLBRRv0qpa (2026).
Using data from Scopus limited to researchers from 5 universities offering doctoral degrees in physics, we observe faster-than-linear trends in productivity from 1985-2024. The distribution of co-author and co-authorship counts follow robust power-laws over the last two decades.
Our results recover power-law distributions of neuronal avalanches, with critical scaling exponents close to 3/2. The resulting rewired network also exhibits the log-normal distributions of node degrees, and the power-law distributions of edge weights with exponents close to 3.
We model brain network structures using sandpiles with learning on hierarchical modular networks:
M.T. Cirunay, R.C. Batac, and G. Ódor, Learning and criticality in a self-organizing model of connectome growth, Sci Rep 15, 31890 (2025). https://t.co/vNLBSWEHLp
In our model, the sandpile model of self-organized criticality is imposed on hierarchical modular networks. Hebbian learning is imposed during avalanche events, as toppled sites are rewired to have stronger connections. Random prunings are also introduced during stasis times.
We also observe the hierarchical scaling of Philippine cities based on population, which is a consequence of the Zipfian statistics. On the other hand, Gibrat's law is not observed, as the growth rates of the cities are found to be not independent of their populations.
Our new paper examines the power-law signatures in the statistics of populations of Philippine cities and municipalities:
D.M.T. Ordoñez and R.C. Batac, Testing the validity of Zipf and Pareto laws: A multi-method approach, Physica A, https://t.co/Q1IbD3PI0x
Census data from the last 20 years manifest power-law statistics for the top 30% of cities/municipalities that hold 70% of the population. Population distributions follow the Pareto law with exponents close to 2.5, and rank-size trends follow Zipf's law with exponents of 0.7.
Ordoñez has just received his Master of Science in Applied Physics degree from the De La Salle University. His research works in the Complex Systems Group involve statistical analyses of economic variables and urban complexity, with a focus on Philippine metropolitan regions.
Dylan Marcus Ordoñez, a member of the Complex Systems Group, presented his research work during the 43rd Physics Conference of the Physics Society of the Philippines held on June 25-28, 2025 in the University of the Philippines Diliman, Quezon City, Philippines.
The work identified the positive and negative factors affecting the deviations of individual Philippine local government units from the expected Zipf's law of population distribution using the 2020 census data and the Cities and Municipalities Competitiveness Index (CMCI).
These works appear to indicate that the atmosphere, while heavily affected by anthropogenic factors (primarily, urbanization) that cause pollution, is a complex system manifesting self-organized criticality (SOC).
This cross-sectional (i.e. across various cities) analysis complements the previous longitudinal (i.e. within-city data over extended periods of time) analyses that also show power-law regimes.