Related Experiment Video
Updated: Jul 8, 2025
13:44
Sealable Femtoliter Chamber Arrays for Cell-free Biology
Published on: March 11, 2015
9.5K
Partisan voter model: Stochastic description and noise-induced transitions
Jaume Llabrés1, Maxi San Miguel1, Raúl Toral1
1Institute for Cross-Disciplinary Physics and Complex Systems IFISC (CSIC-UIB), Campus UIB, 07122 Palma de Mallorca, Spain.
Physical Review. E
|December 20, 2023
Summary
We analyzed the partisan voter model (PVM) and its noisy version (NPVM). The NPVM introduces agent preferences and spontaneous state changes, revealing new intermediate phases and transition types.
Area of Science:
- Statistical Physics
- Social Dynamics
- Computational Social Science
Background:
- The partisan voter model (PVM) is a key framework for understanding opinion dynamics.
- Previous studies on the noisy voter model (NVM) have shown noise-induced transitions.
- Limited understanding exists regarding the impact of agent-specific preferences and spontaneous state changes on PVM dynamics.
Purpose of the Study:
- To conduct a comprehensive mean-field analysis of the partisan voter model (PVM).
- To introduce and analyze a noisy version of the PVM (NPVM), incorporating agent preferences and spontaneous state changes.
- To investigate the impact of noise on phase transitions and emergent behaviors in social opinion models.
Main Methods:
- Mean-field analysis of the PVM.
- Introduction and mathematical modeling of the noisy partisan voter model (NPVM).
- Analytical calculation of exit probabilities, fixation times, and quasistationary distributions.
- Investigation of finite-size effects and phase transitions.
Main Results:
- Analytical results for exit probabilities, fixation times, and quasistationary distribution of the PVM.
- The NPVM exhibits modified noise-induced transitions compared to the NVM.
- Emergence of intermediate phases and both continuous and discontinuous transitions in the NPVM.
Conclusions:
- The NPVM offers a more nuanced model of opinion dynamics by including agent-specific factors.
- Noise plays a crucial role in shaping the emergent phases and transition behaviors in social opinion models.
- This study advances the understanding of complex dynamics in voter models and their extensions.
Related Concept Videos
01:09Random Variables
12.1K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
12.1K
01:10Entropy Change in Reversible Processes
2.6K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.6K
01:13Randomized Experiments
7.0K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
7.0K
00:59Propagation of Uncertainty from Random Error
698
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
698
01:34Woodward–Hoffmann Selection Rules and Microscopic Reversibility
3.1K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.1K
01:14Probability in Statistics
13.1K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
13.1K