Related Experiment Video
Updated: Jul 13, 2025
11:52
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
Published on: February 9, 2017
6.0K
Inference of time-ordered multibody interactions
Unai Alvarez-Rodriguez1,2, Luka V Petrović2, Ingo Scholtes2,3
1University of Deusto, 48007 Bilbao, Spain.
Physical Review. E
|October 18, 2023
Summary
We developed time-ordered multibody interactions to analyze complex systems with temporal and many-body dependencies. Our method efficiently extracts these interactions from data, robustly handling statistical errors.
Area of Science:
- Complex Systems Science
- Statistical Physics
- Network Science
Background:
- Complex systems often exhibit both temporal dynamics and intricate many-body interactions.
- Understanding these coupled dependencies is crucial for modeling and prediction.
- Existing methods may struggle to capture the full complexity of such systems.
Purpose of the Study:
- To introduce a novel framework for describing complex systems using time-ordered multibody interactions.
- To develop an algorithm for extracting these interactions from observational data.
- To provide a measure for characterizing the complexity of interaction ensembles.
Main Methods:
- Decomposition of multivariate Markov chain dynamics into time-ordered multibody interactions.
- Development of a data-driven algorithm for interaction extraction.
- Introduction of a complexity measure for interaction ensembles.
- Experimental validation of algorithm robustness and efficiency.
Main Results:
- Demonstrated decomposition of Markov chain dynamics into time-ordered multibody interactions.
- Presented a robust and efficient algorithm for extracting these interactions from system dynamics.
- Showcased the ability to infer parsimonious interaction ensembles.
Conclusions:
- Time-ordered multibody interactions provide a powerful framework for complex systems.
- The developed algorithm offers a reliable method for analyzing temporal and many-body dependencies.
- This approach enhances our ability to model and understand complex system behaviors.
Related Concept Videos
01:06Virtual Work for a System of Connected Rigid Bodies
390
Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
Next,...
390
01:18Kinematic Equations - III
7.7K
The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
Using the kinematic equations,...
Using the kinematic equations,...
7.7K
01:17Kinematic Equations - II
9.6K
The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
9.6K
01:15Kinematic Equations: Problem Solving
12.5K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
12.5K
01:14Multicompartment Models: Overview
151
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
151
01:05Collisions in Multiple Dimensions: Introduction
5.4K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.4K