How Can I Approach Modeling Physical Phenomena in Physics and Computer Science?

  • Thread starter Necross
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In summary, the speaker is a second year engineering student who is switching to physics with a minor in computer sciences. They have some programming experience and are looking for resources to help them model physical phenomena, such as planet/solar system formation. The other speaker suggests that they need a good understanding of differential equations and recommends some books. The original speaker expresses gratitude for the advice.
  • #1
Necross
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Hello All. I am a second year engineering student switching over from Mechatronics engineering to physics with a minor in computer sciences. While I have done some programming in C, C++, Java, TCL and Assembler, I would like to know how I would approach modeling physical phenomena...e.g basic models of planet/solar system formation etc...I've had a Data Structures and Algorithms course and have a rough understanding of trees and various other data structures...Are there any texts that can help me out with this?

- Thanks
- Necross
 
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  • #2
You need a good understanding of Differential equations, both ODE and PDE, along with numerical methods. Your CS background is a good starting place but you must have the math in order to understand and create workable models.
 
  • #3
Can you please recommend some good books? I've touched upon ODE's and have some PDE's in theory in some of my current physics courses. I will be learning ODE's and PDE's soon enough but I can't wait that long. It's going to hold me back from doing this and having a complete understanding of the theory itself. Thanks for the reply. :)
 

1. What is learning modelling?

Learning modelling is the process of creating a simplified representation of a complex system or concept in order to understand and make predictions about its behavior. It involves using various techniques and tools, such as mathematical equations, computer simulations, and statistical models, to analyze and interpret data.

2. Why is learning modelling important?

Learning modelling allows us to gain a deeper understanding of complex systems and phenomena, and can help us make informed decisions and predictions. It is widely used in various fields such as science, engineering, economics, and social sciences.

3. What are the steps involved in learning modelling?

The steps involved in learning modelling may vary depending on the specific system or concept being studied, but generally include: defining the problem, collecting and organizing data, selecting and developing a suitable model, testing and validating the model, and interpreting and communicating the results.

4. What skills are needed to be successful in learning modelling?

Successful learning modelling requires a combination of technical skills, such as proficiency in mathematics, statistics, and programming, as well as critical thinking and problem-solving abilities. Effective communication and collaboration skills are also important, as modelling often involves working with a team.

5. How can I improve my learning modelling skills?

Improving learning modelling skills requires practice and continuous learning. It is important to stay updated on new techniques and tools, and to actively seek out opportunities to apply modelling in different contexts. Seeking feedback and collaborating with others can also help improve skills and expand knowledge in this field.

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