How to resolve the algorithm Distribution of 0 digits in factorial series step by step in the Nim programming language

Published on 12 May 2024 09:40 PM

How to resolve the algorithm Distribution of 0 digits in factorial series step by step in the Nim programming language

Table of Contents

Problem Statement

Large Factorials and the Distribution of '0' in base 10 digits. We can see that some features of factorial numbers (the series of numbers 1!, 2!, 3!, ...) come about because such numbers are the product of a series of counting numbers, and so those products have predictable factors. For example, all factorials above 1! are even numbers, since they have 2 as a factor. Similarly, all factorials from 5! up end in a 0, because they have 5 and 2 as factors, and thus have 10 as a factor. In fact, the factorial integers add another 0 at the end of the factorial for every step of 5 upward: 5! = 120, 10! = 3628800, 15! = 1307674368000, 16! = 20922789888000 and so on. Because factorial numbers, which quickly become quite large, continue to have another terminal 0 on the right hand side of the number for every factor of 5 added to the factorial product, one might think that the proportion of zeros in a base 10 factorial number might be close to 1/5. However, though the factorial products add another terminating 0 every factor of 5 multiplied into the product, as the numbers become quite large, the number of digits in the factorial product expands exponentially, and so the number above the terminating zeros tends toward 10% of each digit from 0 to 1 as the factorial becomes larger. Thus, as the factorials become larger, the proportion of 0 digits in the factorial products shifts slowly from around 1/5 toward 1/10, since the number of terminating zeros in n! increases only in proportion to n, whereas the number of digits of n! in base 10 increases exponentially. Create a function to calculate the mean of the proportions of 0 digits out of the total digits found in each factorial product from 1! to N!. This proportion of 0 digits in base 10 should be calculated using the number as printed as a base 10 integer. Example: for 1 to 6 we have 1!, 2!, 3!, 4!, 5!, 6!, or (1, 2, 6, 24, 120, 720), so we need the mean of (0/1, 0/1, 0/1, 0/2, 1/3, 1/3) = (2/3) (totals of each proportion) / 6 (= N), or 0.1111111... Example: for 1 to 25 the mean of the proportions of 0 digits in the factorial products series of N! with N from 1 to 25 is 0.26787. Do this task for 1 to N where N is in (100, 1000, and 10000), so, compute the mean of the proportion of 0 digits for each product in the series of each of the factorials from 1 to 100, 1 to 1000, and 1 to 10000. Find the N in 10000 < N < 50000 where the mean of the proportions of 0 digits in the factorial products from 1 to N permanently falls below 0.16. This task took many hours in the Python example, though I wonder if there is a faster algorithm out there.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm Distribution of 0 digits in factorial series step by step in the Nim programming language

Source code in the nim programming language

import strutils, std/monotimes
import bignum

let t0 = getMonoTime()
var sum = 0.0
var f = newInt(1)
var lim = 100
for n in 1..10_000:
  f *= n
  let str = $f
  sum += str.count('0') / str.len
  if n == lim:
    echo n, ":\t", sum / float(n)
    lim *= 10
echo()
echo getMonoTime() - t0


import strutils, std/monotimes
import bignum

let t0 = getMonoTime()
var sum = 0.0
var first = 0
var f = newInt(1)
var count0 = 0
for n in 1..<50_000:
  f *= n
  while f mod 10 == 0:    # Reduce the length of "f".
    f = f div 10
    inc count0
  let str = $f
  sum += (str.count('0') + count0) / (str.len + count0)
  if sum / float(n) < 0.16:
    if first == 0: first = n
  else:
    first = 0

echo "Permanently below 0.16 at n = ", first
echo "Execution time: ", getMonoTime() - t0


  

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