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Post Closed as "Not suitable for this site" by Alexey Ustinov, Myshkin, Jeremy Rouse, Felipe Voloch, Wolfgang
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I am not sure if I should ask this question here or somewhere else.

Background: I was searching through random mathematics paper that are related to cryptography and I came across this paper (page 3). I just read the abstract and algorithm itself, I don't understand Chinese. It offers new method to find a Modular inverses. It has some interesting properties that I observed:

  1. during each step iteration of the loop: $x_{11} * x_{22} + x_{12} * x_{21} = m$ which is good to validate the result during each iteration
  2. algorithm terminates in even number of steps for some unknown reason

In abstract section, author says this method was invented by this mathematicians.

I have two unrelated questions:

  1. why this algorithm always terminates in even number of steps (or number of iterations of the loop is always even)
  2. was this algorithm invented before extended-euclidean algorithm that we use today

Algorithm: Python and SageMath implementations.

enter image description here

I am not sure if I should ask this question here or somewhere else.

Background: I was searching through random mathematics paper that are related to cryptography and I came across this paper (page 3). I just read the abstract and algorithm itself, I don't understand Chinese. It offers new method to find a Modular inverses. It has some interesting properties that I observed:

  1. during each step iteration of the loop: $x_{11} * x_{22} + x_{12} * x_{21} = m$ which is good to validate the result during each iteration
  2. algorithm terminates in even number of steps for some unknown reason

In abstract section, author says this method was invented by this mathematicians.

I have two unrelated questions:

  1. why this algorithm always terminates in even number of steps
  2. was this algorithm invented before extended-euclidean algorithm that we use today

Algorithm: Python and SageMath implementations.

enter image description here

I am not sure if I should ask this question here or somewhere else.

Background: I was searching through random mathematics paper that are related to cryptography and I came across this paper (page 3). I just read the abstract and algorithm itself, I don't understand Chinese. It offers new method to find a Modular inverses. It has some interesting properties that I observed:

  1. during each step iteration of the loop: $x_{11} * x_{22} + x_{12} * x_{21} = m$ which is good to validate the result during each iteration
  2. algorithm terminates in even number of steps for some unknown reason

In abstract section, author says this method was invented by this mathematicians.

I have two unrelated questions:

  1. why this algorithm always terminates in even number of steps (or number of iterations of the loop is always even)
  2. was this algorithm invented before extended-euclidean algorithm that we use today

Algorithm: Python and SageMath implementations.

enter image description here

Source Link
Node.JS
  • 133
  • 6

Curious about an old algorithm which calculates modular inverse

I am not sure if I should ask this question here or somewhere else.

Background: I was searching through random mathematics paper that are related to cryptography and I came across this paper (page 3). I just read the abstract and algorithm itself, I don't understand Chinese. It offers new method to find a Modular inverses. It has some interesting properties that I observed:

  1. during each step iteration of the loop: $x_{11} * x_{22} + x_{12} * x_{21} = m$ which is good to validate the result during each iteration
  2. algorithm terminates in even number of steps for some unknown reason

In abstract section, author says this method was invented by this mathematicians.

I have two unrelated questions:

  1. why this algorithm always terminates in even number of steps
  2. was this algorithm invented before extended-euclidean algorithm that we use today

Algorithm: Python and SageMath implementations.

enter image description here