Top person sorted by score

The Prover-Account Top 20
Persons by: number score normalized score
Programs by: number score normalized score
Projects by: number score normalized score

At this site we keep several lists of primes, most notably the list of the 5,000 largest known primes. Who found the most of these record primes? We keep separate counts for persons, projects and programs. To see these lists click on 'number' to the right.

Clearly one 100,000,000 digit prime is much harder to discover than quite a few 100,000 digit primes. Based on the usual estimates we score the top persons, provers and projects by adding ‎(log n)3 log log n‎ for each of their primes n. Click on 'score' to see these lists.

Finally, to make sense of the score values, we normalize them by dividing by the current score of the 5000th prime. See these by clicking on 'normalized score' in the table on the right.

rankpersonprimesscore
561 Luigi Morelli 2 46.9890
562 Matthias Baur 8 46.9854
563 Jeffrey Mangio 2 46.9810
564 Tim Rickard 1 46.9695
565 Dr. Karsten Steffens 1 46.9676
566 Nikolay Yurgandzhiev 2 46.9670
567 William Dean 1 46.9669
568 Florian Gnann 1 46.9668
569 Jay Zhao 1 46.9665
570 Alexey Utebaev 1 46.9643
571 Vitor Amorim 1 46.9637
572 Konrad Sliwicki 1 46.9605
573 Dusan Vykouril 1 46.9599
574 Ossi Mauno 2 46.9595
575 Toni Keskitalo 1 46.9591
576 Jave Ivanovski 1 46.9579
577 Sam Black 1 46.9538
578 Mario Lein 1 46.9537
579 Sebastien Deram 1 46.9500
580 Don Wellck 1 46.9485

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Notes:


Score for Primes

To find the score for a person, program or project's primes, we give each prime n the score (log n)3 log log n; and then find the sum of the scores of their primes. For persons (and for projects), if three go together to find the prime, each gets one-third of the score. Finally we take the log of the resulting sum to narrow the range of the resulting scores. (Throughout this page log is the natural logarithm.)

How did we settle on (log n)3 log log n? For most of the primes on the list the primality testing algorithms take roughly O(log(n)) steps where the steps each take a set number of multiplications. FFT multiplications take about

O( log n . log log n . log log log n )

operations. However, for practical purposes the O(log log log n) is a constant for this range number (it is the precision of numbers used during the FFT, 64 bits suffices for numbers under about 2,000,000 digits).

Next, by the prime number theorem, the number of integers we must test before finding a prime the size of n is O(log n) (only the constant is effected by prescreening using trial division).  So to get a rough estimate of the amount of time to find a prime the size of n, we just multiply these together and we get

O( (log n)3 log log n ).

Finally, for convenience when we add these scores, we take the log of the result.  This is because log n is roughly 2.3 times the number of digits in the prime n, so (log n)3 is quite large for many of the primes on the list. (The number of decimal digits in n is floor((log n)/(log 10)+1)).

Printed from the PrimePages <t5k.org> © Reginald McLean.