Mathematicians & Big O, Big Omega: Usage & Context

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In summary, mathematicians and computer scientists commonly use concepts such as Big O, Big Omega, Little O, and asymptotic analysis to analyze the behavior of functions as their input approaches certain values. These concepts are especially useful in asymptotic analysis, where they can be used to represent the truncation of a polynomial, such as the Taylor series for the sine function. While these concepts may not be used in all cases, they are helpful in understanding the asymptotic behavior of functions as their input approaches certain values.
  • #1
Swapnil
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Hi, I was wondering, do mathematicians (like computer scientists) use things like Big O, Big Omega, Little O, etc. a lot? If so, in what context?
 
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In asymptotic analysis.
 
  • #3
Yep, asymptotic analysis accounts for most of it. It's also used to show the truncation of a (Taylor series) polynomial:

[tex]\sin(x)=x-\frac{x^3}{6}+O(x^5)[/tex]
 
  • #4
And isn't that, really, an expression for sin(x)'s asymptotic behaviour as x ambles peacefully off towards the origin?:wink:

(If you write sin(x) with an explicit remainder term, say, by utilization of the mean-value theorem for integrals, then it is of course something different, but we wouldn't use O's in that case).
 
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  • #5
arildno said:
And isn't that, really, an expression for sin(x)'s asymptotic behaviour as x ambles peacefully off towards the origin?:wink:

Oh yes absolutely. It's just a different way of thinking about it.
 

1. What are "Big O" and "Big Omega" in mathematics?

"Big O" and "Big Omega" are two notations used in mathematics to describe the asymptotic behavior of a function. Big O notation, denoted as O(), represents the upper bound or worst-case scenario of the growth rate of a function. Big Omega notation, denoted as Ω(), represents the lower bound or best-case scenario of the growth rate of a function.

2. How are "Big O" and "Big Omega" used in mathematics?

Big O and Big Omega are used to analyze the efficiency or complexity of algorithms. They help in understanding how the time or space required by an algorithm changes with the input size. By using these notations, mathematicians can compare different algorithms and choose the most efficient one for a given problem.

3. What is the difference between "Big O" and "Big Omega"?

The main difference between Big O and Big Omega is that Big O represents the upper bound while Big Omega represents the lower bound. This means that Big O notation gives an upper limit on the growth rate of a function, while Big Omega notation gives a lower limit on the growth rate of a function.

4. What is the significance of "Big O" and "Big Omega" in computer science?

In computer science, "Big O" and "Big Omega" are used to analyze the time and space complexity of algorithms. This helps in understanding the performance of an algorithm and predicting how it will scale with larger input sizes. It also helps in designing and optimizing algorithms for better efficiency.

5. Can "Big O" and "Big Omega" be used interchangeably?

No, "Big O" and "Big Omega" cannot be used interchangeably. While they both describe the growth rate of a function, they represent different aspects of it. Big O gives an upper bound, while Big Omega gives a lower bound. In some cases, they may be equal, but in most cases, they are not interchangeable.

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