Can Calculus Perfectly Model Nature?

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In summary: Scientists use calculus to create models because it provides a useful tool for understanding and predicting the behavior of natural phenomena. Calculus can be used to approximate the behavior of complex systems, and even with its limitations, it is still more accurate and precise than simpler methods like the difference quotient and sigma summation. In summary, calculus is a valuable tool for modeling nature, even though it is not perfect and may require assumptions and averages to create equations. It is used because it provides a more accurate and precise understanding of complex systems compared to simpler methods.
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I have taken what is equivalent to 1 semester of college calculus in high school. I differentiated and integrated functions like the volume of a sphere V=(4/3)pi(r^3). However, as I understand it this is a function of a geometrical object that doesn't exist in nature. In fact, most of the equations from the textbook we used were "perfect" equations, instantaneous rates or exact functions that the didn't match their real life counterparts, which I assumed was for the sake of making it easier on the author and student. My first question is how are scientists derive equations modeling natural objects, like the surface area of a meteorite, using calculus to describe them perfectly? If enumerating all of the irregularities is impossible, which I would assume is so, then why is calculus used at all if you have to make assumptions and averages and can't create a definitive equation to model nature perfectly? Why would calculus be used instead of difference quotient for derivative and sigma summation for integral? Calculus seems so definitive (existing in a perfect reality) as opposed to physics (assumptions, averages and approximations based on empirical data from nature) and I don't understand how the two mesh so well. Also, aren't there limits to exactness in nature (Planck length and time) and shouldn't these prevent calculus from creating equations exactly modeling nature?

I think my confusion can be blamed on one of two problems:
1. I don't have a firm foundation on physics (just equations and things like harmonic motion and acceleration from calculus)
2. The course was AP Calculus AB and was geared toward passing the AP test, instead of thoroughly covering each topic, so I think I may have missed some key concepts.

Feel free to make any corrections in my understandings or assumptions. Thank you.
 
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A word that comes to mind is approximation.
 
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No mathematical model describes a physical situation perfectly. No one has ever claimed that calculus modeled nature perfectly! But that doesn't really matter. Any physical problem is going to have values based on measurement- and the measurement is not perfect.
 

FAQ: Can Calculus Perfectly Model Nature?

What is the difference between instantaneous and average values?

Instantaneous values refer to a specific point in time, while average values represent the overall trend or average of a set of values over a period of time.

Which type of value is more accurate?

It depends on the situation. Instantaneous values are more accurate for measuring changes or variability over a short period of time, while average values are more accurate for representing long-term trends or overall patterns.

How are instantaneous and average values calculated?

Instantaneous values are calculated at a specific point in time, often using precise measurements or observations. Average values are calculated by taking the sum of all values in a set and dividing by the number of values.

Can instantaneous and average values be used interchangeably?

No, they represent different aspects of a set of values. Using one in place of the other can lead to inaccurate conclusions or interpretations.

In what situations would it be more appropriate to use instantaneous or average values?

Instantaneous values are useful for measuring changes or fluctuations over time, such as in scientific experiments or weather forecasting. Average values are more suitable for representing long-term trends or patterns, such as in economic or population data.

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