Discover an Original Identity with Merten's Function

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In summary, The conversation discusses the discovery of a potential new identity involving Merten's function and its application in Lehman's work. The participant also mentions accessing the graphic version of the function through LaTeX format.
  • #1
MathNerd
I don't know if this identity has been found before but I have never seen it before in my study of Merten's function, so I believe this to be original. I derived the following interesting identity involving Merten's function

[tex] \sum_{ 1 \leq n \leq p - 1 } M( \frac {p}{n} ) = 0, \ \forall \ p \ \epsilon \ \Re[/tex]

where M(x) is Merten's function.

Tell me your thoughs ... :smile:
 
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geraldmcgarvey, you enclose it in [ tex] [ /tex] tags (no spaces though). You can also click on any LaTeX graphic to see the code that generated it.
 

FAQ: Discover an Original Identity with Merten's Function

What is Merten's Function and how is it used?

Merten's Function is a mathematical function that is used to discover an original identity. It is primarily used in number theory and can help identify patterns and relationships between numbers.

How does Merten's Function work?

Merten's Function takes in a positive integer as its input and outputs a value that indicates the sum of the logarithms of all the prime numbers up to that input number.

What is the significance of discovering an original identity with Merten's Function?

Discovering an original identity with Merten's Function can provide insights into the distribution of prime numbers and help identify patterns and relationships between them. It can also be used in cryptography and other areas of mathematics.

Are there any limitations to using Merten's Function?

Yes, there are some limitations to using Merten's Function. It can only be used for positive integers and it is not an efficient method for large numbers.

How can Merten's Function be applied in real-life situations?

Merten's Function has various applications in number theory, cryptography, and computer science. It can also be used in analyzing data sets and identifying patterns in data. Additionally, it has potential uses in finance and economics for predicting stock market trends.

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