The following equation is almost true.

And by almost true, I mean correct to well over 200 decimal places. This sum comes from [1]. Here I will show why the two sides are very nearly equal and why they’re not exactly equal.

Let’s explore the numerator of the sum with a little code.

    >>> from math import tanh, pi
    >>> for n in range(1, 11): print(n*tanh(pi))
                               
    0.99627207622075
    1.9925441524415
    2.98881622866225
    3.985088304883 
    ....  
    10.95899283842825 

When we take the floor (the integer part [2]) of the numbers above, the pattern seems to be

⌊n tanh π⌋ = n – 1

If the pattern continues, our sum would be 1/81. To see this, multiply the series by 100, evaluate the equation below at x = 1/10, and divide by 100.

Our sum is close to 1/81, but not exactly equal to it, because

⌊n tanh π⌋ = n – 1

holds for a lot of n‘s but not for all n.

Note that

tanh π = 0.996… = 1 – 0.00372…

and so

⌊n tanh π⌋ = n – 1

will hold as long as n < 1/0.00372… = 268.2…

Now

⌊268 tanh π⌋ = 268-1

but

⌊269 tanh π⌋ = 269-2.

So the 269th term on the left side

is less than the 269th term of the sum

10^-2 + 2×10^-3 + 3×10^-4 + … = 1/81

for the right side.

We can compare the decimal expansions of both sides by using the Mathematica command

    N[Sum[Floor[n Tanh[Pi]]/10^n, {n, 1, 300}], 300]

This shows the following:

Related posts

• Almost prime generators and almost integers
• Putting a brace under something in LaTeX

[1] J. M. Borwein and P. B. Borwein. Strange Series and High Precision Fraud. The American Mathematical Monthly, Vol. 99, No. 7, pp. 622-640

[2] The floor of a real number x is the greatest integer ≤ x. For positive x, this is the integer part of x, but not for negative x.

Here is a general approach to determining whether a number is divisible by a prime. I’ll start with a couple examples before I state the general rule. This method is documented in [1].

First example: Is 2759 divisible by 31?

Yes, because

and 0 is divisible by 31.

Is 75273 divisible by 61? No, because

and 33 is not divisible by 61.

What in the world is going on?

Let p be an odd prime and n a number we want to test for divisibility by p. Write n as 10a + b where b is a single digit. Then there is a number k, depending on p, such that n is divisible by p if and only if

is divisible by p.

So how do we find k?

• If p ends in 1, we can take k = ⌊p / 10⌋.
• If p ends in 3, we can take k = ⌊7p / 10⌋.
• If p ends in 7, we can take k = ⌊3p / 10⌋.
• If p ends in 9, we can take k = ⌊9p / 10⌋.

Here ⌊x⌋ means the floor of x, the largest integer no greater than x. Divisibility by even primes and primes ending in 5 is left as an exercise for the reader. The rule takes more effort to carry out when k is larger, but this rule generally takes less time than long division by p.

One final example. Suppose we want to test divisibility by 37. Since 37*3 = 111, k = 11.

Let’s test whether 3293 is divisible by 37.

329 – 11×3 = 296

29 – 11×6 = -37

and so yes, 3293 is divisible by 37.

[1] R. A. Watson. Tests for Divisibility. The Mathematical Gazette, Vol. 87, No. 510 (Nov., 2003), pp. 493-494

The sum of the reciprocals of consecutive integers is never an integer. That is, for all positive integers m and n with n > m, the sum

is never an integer. This was proved by József Kürschák in 1908.

This means that the harmonic numbers defined by

are never integers for n > 1. The harmonic series diverges, so the sequence of harmonic numbers goes off to infinity, but it does so carefully avoiding all integers along the way.

Kürschák’s theorem says that not only are the harmonic numbers never integers, the difference of two distinct harmonic numbers is never an integer. That is, H_n – H_m is never an integer unless m = n.

Related posts

• Computing harmonic numbers
• Numerators of harmonic numbers
• Summing floating point numbers
• Special numbers

The smaller the base you write numbers in, the smaller their digits sums will be on average.

This need not be true of any given number, only for numbers on average. For example, let n = 2021. In base 10, the sum of the digits is 5, but in base 2 the sum of the digits is 8 because n is written as 11111100101 in binary. So for our particular example, a smaller base lead to a larger digit sum. In fact, all smaller bases than 10 lead to a larger digit sum for 2021. But on average, numbers have smaller digit sums when written in binary than when written in base 10.

Let’s explore this with a little Python code, then look at a theoretical result.

First, we need some code to express numbers in different bases, and here’s a simple function for that.

    # From https://stackoverflow.com/a/28666223
    def numberToBase(n, b):
        if n == 0:
            return [0]
        digits = []
        while n:
            digits.append(int(n % b))
            n //= b
        return digits[::-1]

Using the code above, our digit sum function is trivial:

    def digitSum(n, b):
        return sum(numberToBase(n, b))

Now for our simulation.

    import numpy as np
    np.random.seed(20200103)

    upper_bound = 1000000000
    sample_size = 1000
    bases = np.arange(2, 17)

    sample = np.random.randint(0, upper_bound, size = sample_size)
    out = [sum(digitSum(n, b) for n in sample)/sample_size for b in bases]

A theorem in [1] says that

where S(b, N) is the sum of the number of digits of all numbers from 1 to N when written in base b. This value is asymptotically equal to the expression on the right.

We can compute the average number of digits we’d expect in our simulation using the asymptotic result as an approximation.

    asymp = [0.5*(b-1)*np.log(upper_bound) / np.log(b) for b in bases]

The table below compares the simulation results to theory.

    |------+------------+------------|
    | base | simulation | asymptotic |
    |------+------------+------------|
    |    2 |     14.899 |     14.949 |
    |    3 |     18.660 |     18.863 |
    |    4 |     22.317 |     22.423 |
    |    5 |     25.398 |     25.752 |
    |    6 |     28.345 |     28.915 |
    |    7 |     30.996 |     31.949 |
    |    8 |     34.839 |     34.880 |
    |    9 |     36.422 |     37.726 |
    |   10 |     40.275 |     40.500 |
    |   11 |     41.480 |     43.211 |
    |   12 |     44.353 |     45.868 |
    |   13 |     47.454 |     48.476 |
    |   14 |     49.949 |     51.041 |
    |   15 |     51.772 |     53.567 |
    |   16 |     53.610 |     56.058 |
    |------+------------+------------|

[1] L. E. Bush. An Asymptotic Formula for the Average Sum of the Digits of Integers. The American Mathematical Monthly , Mar., 1940, Vol. 47, pp. 154-156.

Pick a positive integer k and take the product of k consecutive integers greater than k. Then the result is divisible by a prime number greater than k. This theorem was first proved 128 years ago [1].

For example, suppose we pick k = 5. If we take the product

20*21*22*23*24

then it’s obviously divisible by a prime larger than 5 because 23 is one of the factors. But we could also take, for example,

32*33*34*35*36.

Although the sequence {32, 33, 34, 35, 36} doesn’t contain any primes, it contains a couple numbers with prime factors larger than 5, namely 33 = 3*11 and 34 = 2*17. Sylvester’s theorem guarantees that there will always be one number out of 5 consecutive integers that is divisible by a prime greater than 5, provided the first number is itself greater than 5.

For one more example, we can pick k = 8 and look at

140*141*142*…*147.

One of the numbers between 140 and 147 (inclusive) must be divisible by a prime greater than 8, and in fact five of them are, starting with 141 = 3*47.

In both of our examples there were multiple numbers that had a prime factor large enough to satisfy Sylvester’s theorem. Are there examples where only one number has a factor large enough? Yes, but not many.

For example, {8, 9} is a pair of consecutive integers, only one of which has a prime factor bigger than 2. And {8, 9, 10} is an example of 3 consecutive integers, only one of which has a prime factor larger than 3. I wrote a program to search for examples with k = 4 and didn’t find any.

In any case, a theorem dating back to 1897 [2] proves that there could only be finitely many examples for k > 2. Lehmer extends the results [2] in his paper [3].

***

[1] J. J. Sylvester, On arithmetical series, Messenger Math., 21 (1892) 1-19, and 87-120; Collected Mathematical Papers, 4 (1912) 687-731.

[2] G. St0rmer, Quelques theoremes sur l’equation de Pell x² – Dy² = ± 1 et leurs applications,
Skr. Norske Vid. Akad. Oslo, I no. 2 (1897).

[3] D. H. Lehmer, The Prime Factors of Consecutive Integers, The American Mathematical Monthly , Feb., 1965, Vol. 72, No. 2, Part 2, pp. 19-20.

The largest known primes are Mersenne primes, in part because the Lucas-Lehmer algorithm makes it more efficient to test Mersenne numbers for primality than to test arbitrary numbers. These numbers have the form 2ⁿ – 1.

The Great Internet Mersenne Prime Search (GIMPS) announced today that they have tested whether 2ⁿ – 1 is prime for all values of n less than 100,000,000 [1]. More specifically, they’ve tested each exponent at least once, though they’d like to test each exponent twice before giving up on it.

If we assume all of their initial calculations are correct, we can say, for example, that 2^82,589,933 – 1 is the 51st Mersenne prime. Before we had to say that it was the 51st known Mersenne prime because there could be a smaller, undiscovered Mersenne prime, in which case 2^82,589,933 – 1 might be the 52nd Mersenne prime. Mersenne primes have not always been discovered in order. For example, the 29th Mersenne prime was discovered after the 30th and 31st such numbers.

So for now, again assuming all the GIMPS calculations have been correct, we know all Mersenne primes less than 2^100,000,000, and there are 51 of them.

Related posts

• Five things about Mersenne primes
• Even perfect numbers
• Fermat primes

[1] There’s no need to test every value of n. We know that if 2ⁿ – 1 is prime, then n is prime. So we only need to check prime values of n.

An integer n is said to be square-free if no perfect square (other than 1) divides n. Similarly, n is said to be cube-free if no perfect cube (other than 1) divides n.

In general, n is said to be k-free if it has no divisor d > 1 where d is a kth power [1].

As x gets larger, the proportion of numbers less than x that are k-free approaches 1/ζ(k). That is

where Q_k(x) is the number of k-free positive integers less than or equal to x and ζ is the Riemann zeta function.

The values of ζ at even integers are known in closed form. So, for example, the proportion of square-free numbers less than x approaches 6/π² since ζ(2) = π²/6. For odd integers the values of ζ must be calculated numerically.

Once you have a theorem that says one thing converges to another, it’s natural to ask next is how fast it converges. How well does the limit work as an approximation of the finite terms? Are there any bounds on the errors?

In [2] the authors give new estimates the remainder term

Python code

Let’s play with this using Python. The code below is meant to be clear rather than efficient.

    from sympy import factorint

    def kfree(n, k):
        exponents = factorint(n).values()
        return max(exponents) < k

    def Q(k, x):
        q = 1 # because 1 is not k-free
        for n in range(2, x+1):
            if kfree(n, k):
                q += 1
        return q

    print(Q(4, 1000000))

This says Q₄(1,000,000) = 923,939.

So Q₄(10⁶)/10⁶ = 0.923939. Now ζ(4) = π⁴/90, so 1/ζ(4) = 0.9239384….

We have R₄(10⁶) = 0.597 and so in this case R is quite small.

(If we didn’t know ζ in closed form, we could calculate it in python with scipy.special.zeta.)

More posts involving Riemann zeta

• • Near zeros of zeta
  • Distribution of zeta zeros
  • Multivariate zeta
  • Probability of coprime sets
  • Estimating power law exponents

[1] It would be clearer if we said kth power-free, but people shorten this to k-free.

In my opinion the term “k-free” is misleading. The term ought to mean a number not divisible by k, or maybe a number that has no digit k when written in some base. But the terminology is what it is.

[2] Michael Mossinghoff, Tomás Oliviera e Sliva, and Timothy Trudgian. The distribution of k-free numbers. Mathematics of Computation. Posted November 24, 2020. https://doi.org/10.1090/mcom/3581

A digitally delicate prime is a prime number such that if any of its digits are changed by any amount, the result is not prime. The smallest such number is 294001. This means that variations on this number such as 394001 or 291001 or 294081 are all composite.

A paper [1] posted last week gives several new results concerning digitally delicate primes. Here I’ll just mention a few things that are known.

First, there are infinitely many digitally delicate primes. They are uncommon, but they have positive density. That is, as x goes to infinity, the ratio of the number of digitally delicate primes less than x to the total number of primes less than x converges to a small positive number.

This result has been extended to bases other than base 10. In [1] the authors extend the result to widely digitally delicate primes, meaning that the result holds even if you consider the “digits” of a number to include leading zeros.

The following Python code tests whether a number is a digitally delicate prime. It then takes the first six digitally delicate primes and verifies that they are indeed digitally delicate.

from sympy import isprime
from math import floor, log10

def num_digits(n):
    return floor(log10(n))+1

def digit_in_pos(n, pos):
    return (n // 10**pos) % 10

def set_digit(n, pos, new):
    "change digit in given position to new value"
    old = digit_in_pos(n, pos)
    return n + (new - old)*10**pos

def is_digitally_delicate_prime(n):
    if not isprime(n):
        return False
    nd = num_digits(n)
    for pos in range(nd):
        for newdigit in range(10):
            if digit_in_pos(n, pos) == newdigit:
                continue
            m = set_digit(n, pos, newdigit)
            if isprime(m):
                print("m = ", m)
                return False
    return True

for p in [294001, 505447, 584141, 604171, 971767, 1062599]:
    print(is_digitally_delicate_prime(p))

[1] Michael Filaseta and Jeremiah Southwick. Primes that become composite after changing an arbitrary digit. Mathematics of Computation. Article electronically published on November 24, 2020. https://doi.org/10.1090/mcom/3593

Let π(x) be the number of primes less than x. The simplest form of the prime number theorem says that π(x) is asymptotically equal to x/log(x), where log means natural logarithm. That is,

This means that in the limit as x goes to infinity, the relative error in approximating π(x) with x/log(x) goes to 0. However, there is room for improvement. The relative approximation error goes to 0 faster if we replace x/log(x) with li(x) where

The prime number theorem says that for large x, the error in approximating π(x) by li(x) is small relative to π(x) itself. It would appear that li(x) is not only an approximation for π(x), but it is also an upper bound. That is, it seems that li(x) > π(x). However, that’s not true for all x.

Littlewood proved in 1914 that there is some x for which π(x) > li(x). We still don’t know a specific number x for which this holds, though we know such numbers exist. The smallest such x is the definition of Skewes’ number. The number of digits in Skewes’ number is known to be between 20 and 317, and is believed to be close to the latter.

Littlewood not only proved that li(x) – π(x) is sometimes negative, he proved that it changes sign infinitely often. So naturally there is interest in estimating li(x) – π(x) for very large values of x.

A new result was published a few days ago [1] refining previous bounds to prove that

for all x > exp(2000).

When x = exp(2000), the right side is roughly 10⁸⁵⁷ and π(x) is roughly 10⁸⁶⁵, and so the relative error is roughly 10^-8. That is, the li(x) approximation to π(x) is accurate to 8 significant figures, and the accuracy increases as x gets larger.

***

[1] Platt and Trudgian. The error term in the prime number theorem. Mathematics of Computation. November 16, 2020. https://doi.org/10.1090/mcom/3583