Complexity in physics refers to systems with many components that interact in multiple ways, leading to emergent behavior that is not easily predictable. It often involves studying how small changes can lead to significant impacts on the overall system.
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Complex systems are sensitive to initial conditions, meaning small differences can lead to vastly different outcomes.
Complexity often involves non-linear interactions where outputs are not directly proportional to inputs.
Emergent properties are characteristics of a system that arise from the interactions of its parts and cannot be predicted just by analyzing individual components.
Examples of complex systems include weather patterns, ecosystems, and even financial markets.
In physics, studying complexity often requires computational models and simulations due to the intricate interdependencies within the system.
Review Questions
What does it mean for a system to exhibit emergent properties?
How do non-linear interactions affect the predictability of complex systems?
Give an example of a complex system and explain why it is considered complex.
Geometric shapes that can be split into parts, each of which is a reduced-scale copy of the whole. They are often used to describe naturally occurring phenomena in complex systems.
Non-linearity: A relationship in which change in output is not proportional to change in input, common in complex systems where small changes can have large effects.