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On critical dynamics and thermodynamic efficiency of urban transformations

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  • Emanuele Crosato
  • Ramil Nigmatullin
  • Mikhail Prokopenko

Abstract

Urban transformations within large and growing metropolitan areas often generate critical dynamics affecting social interactions, transport connectivity and income flow distribution. We develop a statistical-mechanical model of urban transformations, exemplified for Greater Sydney, and derive a thermodynamic description highlighting critical regimes. We consider urban dynamics at two time scales: fast dynamics for the distribution of population and income, modelled via the maximum entropy principle, and slower dynamics evolving the urban structure under spatially distributed competition. We identify phase transitions between dispersed and polycentric phases, induced by varying the social disposition---a factor balancing the suburbs' attractiveness---in contrast with the travel impedance. Using the Fisher information we identify critical thresholds and quantify the thermodynamic cost of urban transformation, as the minimal work required to vary the underlying parameter. Finally, we introduce the notion of thermodynamic efficiency of urban transformation, as the ratio of the order gained during a change to the amount of required work, showing that this measure is maximised at criticality.

Suggested Citation

  • Emanuele Crosato & Ramil Nigmatullin & Mikhail Prokopenko, 2018. "On critical dynamics and thermodynamic efficiency of urban transformations," Papers 1806.03758, arXiv.org.
  • Handle: RePEc:arx:papers:1806.03758
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    References listed on IDEAS

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    1. Minoru Osawa & Takashi Akamatsu & Yuki Takayama, 2017. "Harris And Wilson (1978) Model Revisited: The Spatial Period‐Doubling Cascade In An Urban Retail Model," Journal of Regional Science, Wiley Blackwell, vol. 57(3), pages 442-466, June.
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    Cited by:

    1. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
    2. Benjamin Patrick Evans & Mikhail Prokopenko, 2021. "A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback," Papers 2102.09180, arXiv.org, revised May 2021.
    3. Slavko, Bohdan & Glavatskiy, Kirill S. & Prokopenko, Mikhail, 2021. "Revealing configurational attractors in the evolution of modern Australian and US cities," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    4. Benjamin Patrick Evans & Kirill Glavatskiy & Michael S. Harré & Mikhail Prokopenko, 2023. "The impact of social influence in Australian real estate: market forecasting with a spatial agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(1), pages 5-57, January.
    5. Minoru Osawa & Takashi Akamatsu & Yosuke Kogure, 2020. "Stochastic stability of agglomeration patterns in an urban retail model," Papers 2011.06778, arXiv.org.

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