Zipf's Law from Scale-free Geometry
January 05, 2015 Β· Declared Dead Β· π Physical Review E
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Henry W. Lin, Abraham Loeb
arXiv ID
1501.00738
Category
physics.soc-ph
Cross-listed
astro-ph.CO,
cond-mat.stat-mech,
cs.SI,
stat.AP
Citations
4
Venue
Physical Review E
Last Checked
4 months ago
Abstract
The spatial distribution of people exhibits clustering across a wide range of scales, from household ($\sim 10^{-2}$ km) to continental ($\sim 10^4$ km) scales. Empirical data indicates simple power-law scalings for the size distribution of cities (known as Zipf's law) and the population density fluctuations as a function of scale. Using techniques from random field theory and statistical physics, we show that these power laws are fundamentally a consequence of the scale-free spatial clustering of human populations and the fact that humans inhabit a two-dimensional surface. In this sense, the symmetries of scale invariance in two spatial dimensions are intimately connected to urban sociology. We test our theory by empirically measuring the power spectrum of population density fluctuations and show that the logarithmic slope $Ξ±= 2.04 \pm 0.09$, in excellent agreement with our theoretical prediction $Ξ±= 2$. The model enables the analytic computation of many new predictions by importing the mathematical formalism of random fields.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.soc-ph
π
π
The Cartographer
R.I.P.
π»
Ghosted
Networks beyond pairwise interactions: structure and dynamics
R.I.P.
π»
Ghosted
Statistical physics of human cooperation
R.I.P.
π»
Ghosted
Vital nodes identification in complex networks
R.I.P.
π»
Ghosted
Influence maximization in complex networks through optimal percolation
R.I.P.
π»
Ghosted
Scale-free networks are rare
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted