Exploring Ulam's Spiral Theory with a Double Spiral Twist

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In summary, the conversation discussed Ulam's theory of plotting real integers in a spiral pattern and the idea of using a double spiral with negative integers. The speaker is interested in finding a pattern in prime numbers, but acknowledges the possibility of imaginary primes. They also mention attempting to write a program to load the integers into an array in this spiral pattern for comparison.
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qwantum_phlux
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To begin i am by no means a machine for converting coffee into theoroms (a mathematician) by do like to dabble. i was lookin over ulam's theory of plotting real integers in a spiral fom:

7 6 5
8 1 4
9 2 3
10 11 ...

in an attempt to find a pattern in prim numbers...
i know my idea may be invalid on the account of imaginary primes... but i was wondering if anyone had tried the same but with a double spiral starting with 0 in the center and negative integers:
-8 -7 -6 -5
-9 2 1 -4
... 3 0 -3 ...
4 -1 -2 9
5 6 7 8
my formatting isn't the greatest, but you get the idea. if the idea is invalid feel free to shoot me down, and if not could one suggest an algorithm to load the integers into and array in a this spiral pattern so i can load a large plot to compare...(im attempting to write a program).
 
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  • #2
-8 -7-6 -5
-9 2 1 -4
3 0 -3
4 -1 -2 9
5 6 7 8
(format fix)
 
  • #3
-7-6-5
2 1 -4
3 0 -3
4-1-2
5 6 7
{final attempt}
 

Related to Exploring Ulam's Spiral Theory with a Double Spiral Twist

1. What is Ulam's theory reborn?

Ulam's theory reborn is a mathematical concept proposed by the American mathematician Stanislaw Ulam in the 1960s. It is an extension of his earlier work on the "Monte Carlo" method of numerical integration, which is used to approximate the value of complex integrals.

2. What are the main ideas behind Ulam's theory reborn?

The main ideas behind Ulam's theory reborn include the use of "quasi-random" sequences, which are more evenly distributed than purely random numbers, and the concept of "discrepancy," which measures how well a sequence fills a given space. These ideas are used in various applications, such as low-discrepancy sampling and numerical integration.

3. How is Ulam's theory reborn different from traditional Monte Carlo methods?

Unlike traditional Monte Carlo methods, which use purely random numbers, Ulam's theory reborn incorporates the use of quasi-random sequences. This results in more accurate approximations and faster convergence rates, making it a more efficient method for certain applications.

4. What are some real-world applications of Ulam's theory reborn?

Ulam's theory reborn has been applied in various fields such as finance, computer graphics, and scientific computing. It has been used to improve the accuracy and speed of Monte Carlo simulations, as well as in the design of low-discrepancy sampling techniques for computer graphics and optimization problems.

5. Are there any limitations to Ulam's theory reborn?

While Ulam's theory reborn has proven to be a powerful tool in various applications, it is not a universal solution and has its limitations. It is most effective for problems with a high-dimensional space and smooth integrands. In some cases, traditional Monte Carlo methods may still be more suitable.

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