A weird but an interesting question I thought of ...

Consider this random 100-digit integer that I generated using random.org


This number will most likely have $1,2,3..$ upto $9$ in them. But when we further look into we can also find $10$, (i.e $1$ then $0$ right after) and also $11$. But there's no $12$ in them (i.e no $1$ then a $2$ right after).

So what I want to find out is what will be the approximation of $n$, such that there will be $1,2,3,...,(n-2),(n-1),n$ integers that can be seen inside a random x-digit. Also note that $(n+1)$ can never be found in a random x-digit.

If you say that the 'n' value will change randomly and there cannot be any asymptotic or approximations of that. You're kind of wrong. See, I did this with 9 other random 100-digit numbers and also the 100 decimal places of the famous constants $\pi,e$ and $\phi$. The results are pretty close to $11$. Here are them; (scroll right to see the corresponding $n-values$)

$$\begin{array} {|r|r|}\hline Sl. No. & 100-Digit Integer & n-value \\ \hline 1 & 9771602964370316251552537368279107346523948777589513994616004391156991741564023185294939440725424639 & 11 \\ \hline 2 & 5933798531736924945959336111487355483181228762319970946972332473586986158448822614193445434946714049 & 9 \\ \hline 3 & 0748006010018385701305255708540275105163777493821503992289412752198434315022707697359036044788900096 & 10 \\ \hline 4 & 8895177092192596874320826762636449513223106780359367744719402357085023730983517329137267473940940810 & 10 \\ \hline 5 & 4921918080733246056200145588743524919616898465382373461652822273753544023393089458416653653351525383 & 9 \\ \hline 6 & 6386614054105909456194325500596228770058096441918965347422338768650600045406879715848359336828536144 & 10 \\ \hline 7 & 8599263737601951772329677396723688342052445287633091648167742178784189581850841772769226465303321562 & 9 \\ \hline 8 & 0660623044515625611084768937485195387862394776640249639087054616789402273433078233077669093361145164 & 11 \\ \hline 9 & 8747230800762985911116404157733707704590034002122077023051291424897238915375434573976156208269944527 & 9 \\ \hline 10 & 1177720655605689615530670722522895831819411456667323162088720568188745848931083487687853204730731860 & 11 \\ \hline π & 1415926535897932384626433832795028841971693993751058209749445923078164062862089986280348253421170679 & 11 \\ \hline e & 7182818284590452353602874713526624977572470936999595749669676277240766303535475945713821785251664274 & 9 \\ \hline φ & 6180339887498948482045868343656381177203091798057628621354486227052604628189024497072072041893911374 & 9 \\ \hline \end{array}$$

Now take the average of all the n-values and you'll get

$n ≈ 9.8$, for $x=100$

I'm starting to work on $x=1000$ and for a hint $n ≈ 99$ or $100$ and this is just like approximate value of an approximate value, I'll find a good approximate value soon. So what are your thoughts on this? What will be a good expression that could take in the $x$ value and give a good approximate?

I'm got a formula, a crude, anecdotal that could give a value close to what is got. I'll post it soon after a few modifications.


Some observations that I did.

$$n ≈ \frac{x}{10}\tag{1}\label{1}$$

Or I can say that for a $x$, the $n$ value is; (Big thanks to @glowstonetrees for an inspiration.) $$n≈9*10^{m−3}\tag{2}\label{2}$$ Where $m$ is the no. of digits of $x$. But we know $x$ is the no. of digits of the given $x$-digit value. So $m$ is like no. of digits of the no. of digits of $x$-digit integer

Now for my own anecdotal estimate of this;


The reason I chose log is that it is a "slow-moving" function so it doesn't change rapidly. And don't ask me why $\pi$ is there, I don't know I kinda like it. But I also edited it and made it more efficient; so it is;


The reason I chose $\sin(79.4)$ is that $$\sin(79.4)=0.9829353491$$ So I didn't want an exact $1$ as in Eq.3 but a rather a number close to 0.98. And I believe this is an irrational number and $sin(79.8)$ is just an estimate for this.


Now to test all these expressions with $x=10000$, from data I got that $n≈999$

$$n≈\frac{10000}{10}=1000\tag{By Eq.1}\label{5}$$ $$n≈9*10^{5−3}\tag{By Eq.2}\label{6}=900$$ $$n≈\pi^{2\left(\log\left(10000\right)-1\right)}≈961.38\tag{By Eq.3}\label{7}$$ $$n≈\pi^{2\left(\log\left(10000\right)-\sin\left(79.4\right)\right)}≈999.6\tag{By Eq.4}\label{8}$$

So yeah even know my equation, i.e Eq 4 did well; I have to say Eq 1 of $n≈\frac{x}{10}$ is really the best bet for simplicity and accuracy.

  • $\begingroup$ To be clear, if $n=\operatorname{digit}(m)$ where $m$ contains integers from $1$ to $(n-1)$ but not $(n-2)$, then you are asking for $\lim_{m\to\infty}\frac1m\operatorname{digit}(m)$? $\endgroup$ – Simply Beautiful Art Sep 8 '19 at 13:06
  • $\begingroup$ I honestly really don't get what you're saying. I don't really know a lot you see, Sorry. what does "digit(m)" signify?. And also take it this way; Consider a 10-digit number $$7270421235$$ We can see it has 1,2,3,4,5, but not 6. hence the streak ends there and we can say $n=5$ in this case. But for larger number with larger digits, we can get like $1,2,3,4,5,6...,7,8,9,10,11$ but not $12$. So we say for that large-digit value, $n=11$ $\endgroup$ – Rayreware Sep 8 '19 at 13:10
  • $\begingroup$ Sorry my previous comment made a mistake, it ought to be "...contains integers from $1$ to $n$ but not $n+1$..." e.g. $5=\operatorname{digit}(7270421235)$. And are you asking for the average value of this for increasingly large values? $\endgroup$ – Simply Beautiful Art Sep 8 '19 at 13:15
  • $\begingroup$ Wait a function like that already exists? Then if so I can build up from that. And yes, I'm asking for the average/approximate value of n for a m-digit integer $\endgroup$ – Rayreware Sep 8 '19 at 13:18
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    $\begingroup$ It is an average taken over all $x$-digit numbers $\endgroup$ – glowstonetrees Sep 8 '19 at 13:26

These are just some thoughts, not a complete answer. But since the comment section is getting kinda long, I decided to post this here.

There are $9 \cdot 10^{x-1}$ $x$-digit integers.

The integers with $n$-value $=0$ are those that do not contain the digit $1$. There are $8\cdot 9^{x-1}$ such integers.

The integers with $n$-value $=1$ are those that have the digit $1$, but do not contain a single $2$. There are $8 \cdot 9^{x-1} - 7 \cdot 8^{x-1}$ such integers (those with no $2$'s minus those with no $2$'s and no $1$'s).

Similarly, the integers with $n$-value $=2$ are those that have $1$ and $2$ but no $3$. There are $8 \cdot 9^{x-1} - 2 \cdot 7 \cdot 8^{x-1} + 6 \cdot 7^{x-1}$.

And so on...

\begin{array} {|r|r|}\hline n\text{-value} & \text{Number of $x$-digit integers with this $n$-value} \\ \hline 0 & 8\cdot 9^{x-1} \\ \hline 1 & 8\cdot 9^{x-1} - 7 \cdot 8^{x-1} \\ \hline 2 & 8\cdot 9^{x-1} - 2\cdot 7 \cdot 8^{x-1} + 6 \cdot 7^{x-1} \\ \hline 3 & 8\cdot 9^{x-1} - 3\cdot 7 \cdot 8^{x-1} + 3\cdot 6 \cdot 7^{x-1} - 5 \cdot 6^{x-1} \\ \hline 4 & \sum_{k=0}^4 C^4_k\cdot (8-k) \cdot (9-k)^{x-1} \\ \hline 5 & \sum_{k=0}^5 C^5_k\cdot (8-k) \cdot (9-k)^{x-1} \\ \hline 6 & \sum_{k=0}^6 C^6_k\cdot (8-k) \cdot (9-k)^{x-1} \\ \hline 7 & \sum_{k=0}^7 C^7_k\cdot (8-k) \cdot (9-k)^{x-1} \\ \hline 8 & \sum_{k=0}^8 C^8_k\cdot (8-k) \cdot (9-k)^{x-1} \\ \hline \end{array}

For convenience, I shall call the numbers on the right column of the table $n_0, n_1, n_2, \dots, n_8$.

The remaining $9\cdot 10^{x-1} - (n_0 + \cdots + n_8)$ integers have all the digits $1$ through $9$, so their $n$-values are $\geq 9$.

It follows that a lower bound for $n$ is

$$\frac{0n_0 + 1n_1 + 2n_2 + \cdots + 8n_8 + 9\big[9\cdot 10^{x-1} - (n_0 + \cdots + n_8)\big]}{9\cdot 10^{x-1}}$$

Note that this is a pretty tight lower bound, since $\frac{n_0}{9\cdot 10^{x-1}} = 0.8$ so that $80\%$ of the integers have already been accounted for in the first item.

  • $\begingroup$ A nice start, +1. However, this is not necessarily "a pretty tight lower bound"; by your argument, you could stop the sum at the first term and conclude that 0 was a pretty tight lower bound. $\endgroup$ – Rahul Sep 8 '19 at 15:00

Given a random sequence of $x$ digits in base $b$, the probability that a given $m$-digit string does not appear is $$S(m) := \left(1 - \frac{1}{b^m}\right)^x \approx \exp\left(-\frac{x}{b^m}\right),$$ and the approximation is good even for modest $m$. Whether a given $m$-digit string appears is close to independent from whether another given $m$-digit string appears, so the probability that all $(b - 1) \cdot b^{m - 1}$ strings of length $2$ (not starting with $0$) appear is approximately $$P(m) := \left[1 - \exp\left(-\frac{x}{b^m}\right) \right]^{(b - 1) \cdot b^{m - 1}} \approx \exp \left[-(b - 1) \cdot b^{m - 1} \exp \left(-\frac{x}{b^m}\right)\right] .$$

For small $m$ this probability is close to $1$ and for large $m$ this probability is close to $0$. To find the $m$ values at which the critical behavior occurs---that is, for which the probability is not extremely close to $0$ or $1$, we find where the probability is about $e^{-1}$. Solving, we find that $$m \approx \log_b x - \log_b W \left( x \left(1 - \frac{1}{b}\right) \right) = \log_b x + O(\log \log x), $$ where $W$ is the Lambert $W$-function. Informally (when this quantity is nonintegral) we expect most of the interest behavior to occur when $m$ is the integer $a$ preceding $m$ and the integer $a + 1$ succeeding $m$, and so expect the expected value $m$ will be within an order of magnitude of this quantity.

The probability of exactly $k$ strings of length $a$ being missing is about $P (1 - P)^k$, where $P := P(a)$, and the expected value of the minimum of $k$ positive integers with $a$ or fewer digits is $\frac{1}{k + 1} \cdot (b^a - 1)$, so the expected value of the first missing number, contingent on that that number having $a$ or fewer digits is $$(b^a - 1)\sum_{k = 0}^\infty \frac{P (1 - P)^k}{k + 1} = (b^a - 1) \frac{P \log P}{P - 1} = (b^a - 1) \log P + O\left(\frac{\log P}{P}\right) .$$

Now, consider the case in which no strings of length $a$ are missing. The probability that any given string of length $a + 1$ occurs is about $1 - S$, $S := S(a + 1)$, so the probability that exactly the first $r$ strings of length $a + 1$ all occur is $S (1 - S)^r$, and so (unless $S$ is really close to $1$) the expected value of the number of strings $10\ldots00, 10\ldots01, \ldots$ that occurs is about $$\sum_{k = 0}^{\infty} k S (1 - S)^k = \frac{1}{S} - 1.$$

This gives for the expected value of $n$ the approximation $$\Bbb E[n] \approx (b^a - 1) \frac{P \log P}{P - 1} + \frac{1}{S} - 1 = (b^a - 1) \log P + \frac{1}{S} + O(1) .$$

For the example in the comments, where $x = 10^5$ and $b = 10$, we find $a = 4$, then $P = 0.664\!\ldots$ (so all strings of length $4$ in a string of length $10^5$ about $2 / 3$ of the time), $S = e^{-1}$, and an expected value of $$8.1 \cdot 10^3 .$$ A Monte Carlo simulation with $2 \cdot 10^5$ trials gives an average value of $\approx 8383$, so the relative error at least in this case is modest.

For $b = 10$, the estimates using this method for the expected value of $n$ are (to $2$ significant figures)

$$\begin{array}{rrr} x & \Bbb E[n] \\ \hline 10^{2\phantom{.5}} & 11 \\ 10^{2.5} & 32 \\ 10^{3\phantom{.5}} & 100 \\ 10^{3.5} & 120 \\ 10^{4\phantom{.5}} & 980 \\ 10^{4.5} & 1020 \\ 10^{5\phantom{.5}} & 8100 \\ 10^{5.5} & 10000 \\ 10^{6\phantom{.5}} & 32000 \\ \end{array}$$

Remark If we take $x$ to be some constant multiple $\lambda \cdot b^m$ of $b^m$, this approximation simplifies some to $$\exp\left(-(b - 1) \cdot b^{m - 1} e^{-\lambda}\right) ,$$ but this quantity approaches $0$ as $m \to \infty$, so for large $m$ the probability that all strings of length $m$ occur among $\lambda \cdot b^m$ digits approaches $0$. So, as $x \to \infty$ the expected number $n$ of numbers that occur in a string of length $x$ grows more slowly than any constant multiple of $x$, and in particular (for $b = 10$) the approximation $\Bbb E[n] \approx \frac{x}{10}$ cannot be valid for large $m$. We can already see this in the table above, where for $x = 10^6$ we have $\Bbb E[n] \approx \frac{x}{100}$.

  • $\begingroup$ In defense for $n=\frac{x}{10}$. I did some manual observation on a random $x=100,000$-digit numbers. And here is what I've found; we know then by my estimate; $$n=10,000$$. And this is pretty accurate. When I searched for the numbers below this like 9999, 9998... so on. they are all present in it. And this estimate is so accurate that, after 10,000 maybe 10,001 will be present but 10,003 or 10,004 or such may not be present. The $n$-value is also accurate for $x=100$, we get $n=10$ which is really close to what we got. $\endgroup$ – Rayreware Sep 9 '19 at 2:03
  • $\begingroup$ It's not surprising that for some ranges of $x$ you find that all numbers through $9999$ are present but one of the first $5$-digit numbers is not. But that's not because the "estimate is so accurate"---it's because the expected number of occurrences of any given $4$-digit number is $10$ times that of any given $5$-digit number, so as soon as you cross the threshold into $5$-digit numbers, the chance that any particular number does not occur as a substring increases dramatically. $\endgroup$ – Travis Willse Sep 9 '19 at 3:18
  • $\begingroup$ To illustrate this point, consider a random $200\,000$-digit number. Using the estimates in my answer, the probability that all $4$-digit numbers occur is $\exp \left(-\frac{9000}{e^{20}}\right) \approx 0.99998\!\ldots$, a near certainty. But the odds that any given $5$-digit number occurs is only $1 - e^{-2} \approx 0.86466\!\ldots$, so we should expect failure quickly, on average after checking $e^2 \approx 7.38905\!\ldots$. Indeed, this gives a good estimate for the expected value of $n$, namely $9999 + e^2$, which is between $10\,006$ and $10\,007$. $\endgroup$ – Travis Willse Sep 9 '19 at 3:25
  • $\begingroup$ But in this case $x = 200\,000$, so the estimate $\frac{x}{10}$ gives $20\,000$, which is off by a factor of $\approx 2$. The guess $n = \frac{x}{10}$ is tempting if you only check $x$ close to integer powers of $10$ and not too large (say, $x \leq 100\,000$), but this illustrates the need to test conjectures over more than a handful of (especially atypical) cases. $\endgroup$ – Travis Willse Sep 9 '19 at 3:30
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    $\begingroup$ @Rayreware: To explain it another way, Travis's argument implies that if you pick a random 100,000-digit number, 66% of the time $n$ will indeed be a little over 10,000. But the other 34% of the time it will be much smaller -- anywhere between 1,000 and 10,000, I expect. Since you only checked one random 100,000-digit number, it seems you just got lucky (but not that lucky, it was a 2 in 3 chance). I've run some of my own tests and can verify that about 1 out of 3 times I get a much smaller $n$. $\endgroup$ – Rahul Sep 9 '19 at 3:36

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