Difference between revisions of "Prime Number Theorem"

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The Prime Number Theorem is one of the most famous theorem in mathematics.  It states that the number of primes not exceeding n is asymptotic to <math>\frac{n}{\log(n)}</math>, where log(n) is the logarithm of (n) to the base e.   
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The '''Prime Number Theorem''' is one of the most famous theorems in mathematics.  It states that the number of primes not exceeding n is asymptotic to <math>\frac{n}{\log(n)}</math>, where log(n) is the logarithm of (n) to the base e.   
  
 
The number of primes not exceeding n is commonly written as <math>\pi(n)</math>, and an asymptotic relationship between a(n) and b(n) is commonly designated as a(n)~b(n).  (This does not mean that a(n)-b(n) is small as n increases.  It means the ratio of a(n) to b(n) approaches one as n increases.)
 
The number of primes not exceeding n is commonly written as <math>\pi(n)</math>, and an asymptotic relationship between a(n) and b(n) is commonly designated as a(n)~b(n).  (This does not mean that a(n)-b(n) is small as n increases.  It means the ratio of a(n) to b(n) approaches one as n increases.)

Revision as of 19:40, October 4, 2007

The Prime Number Theorem is one of the most famous theorems in mathematics. It states that the number of primes not exceeding n is asymptotic to , where log(n) is the logarithm of (n) to the base e.

The number of primes not exceeding n is commonly written as , and an asymptotic relationship between a(n) and b(n) is commonly designated as a(n)~b(n). (This does not mean that a(n)-b(n) is small as n increases. It means the ratio of a(n) to b(n) approaches one as n increases.)

The Prime Number Theorem thus states that ~ .

In other words, the limit (as n approaches infinity) of the ratio of pi(n) to n/log(n) is one. Put a third way, n/log(n) is a good approximation for .

Equivalent Statements

Carl Friedrich Gauss conjectured the equivalent statement that was asymptotic to defined as:

.

In fact, for large x this turns out to be a better approximation than . The size of the error is closely related to the behavior of the Riemann Zeta function