Tag Archives: recreational maths

Self-Raising Power

by in √2, Irrational numbers, Mathematics, Powers, Square root of 2 and tagged , , , , , , , , , , , , , , , , , , | Leave a comment

The square root of 2 is the number that, raised to the power of 2, equals 2. That is, if r^2 = r * r = 2, then r = √2. The cube root of 2 is the number that, raised to the power of 3, equals 2. That is, if r^3 = r * r * r = 2, then r = [3]√2.

But what do you call the number that, raised to the power of itself, equals 2? I suggest “the auto-root of 2”. Here, if r^r = 2, then r = [r]√2. I don’t know a quick way to calculate the auto-root, but you can adapt a well-known algorithm for approximating the square root of a number. The square-root algorithm looks like this:

n = 2
r = 1
for c = 1 to 20
    r = (r + n/r) / 2
next c
print r

r = 1.414213562…

Note the fourth line of the algorithm: r = (r + n/r) / 2. When r is an over-estimate of √2, then 2/r will be an under-estimate (and vice versa). (r + 2/r) / 2 splits the difference and refines the estimate. Using the lines above as the model, the auto-root algorithm looks like this:

n = 2
r = 1
for c = 1 to 20
    r = (r + [r]√n) / 2[*]
next c
print r

r = 1.559610469…

*This is equivalent to r = (r + n^(1/r)) / 2

Here are the first 100 digits of [r]√2 = r in base 10:

1, 5, 5, 9, 6, 1, 0, 4, 6, 9, 4, 6, 2, 3, 6, 9, 3, 4, 9, 9, 7, 0, 3, 8, 8, 7, 6, 8, 7, 6, 5, 0, 0, 2, 9, 9, 3, 2, 8, 4, 8, 8, 3, 5, 1, 1, 8, 4, 3, 0, 9, 1, 4, 2, 4, 7, 1, 9, 5, 9, 4, 5, 6, 9, 4, 1, 3, 9, 7, 3, 0, 3, 4, 5, 4, 9, 5, 9, 0, 5, 8, 7, 1, 0, 5, 4, 1, 3, 4, 4, 4, 6, 9, 1, 2, 8, 3, 9, 7, 3…

And here is [r]√n = r for n = 2..20:

autopower(2) = 1.5596104694623693499703887…
autopower(3) = 1.8254550229248300400414692…
autopower(4) = 2
autopower(5) = 2.1293724827601566963803119…
autopower(6) = 2.2318286244090093673920215…
autopower(7) = 2.3164549587856123013255030…
autopower(8) = 2.3884234844993385564187215…
autopower(9) = 2.4509539280155796306228059…
autopower(10) = 2.5061841455887692562929409…
autopower(11) = 2.5556046121008206152514542…
autopower(12) = 2.6002950000539155877172082…
autopower(13) = 2.6410619164843958084118390…
autopower(14) = 2.6785234858912995813011990…
autopower(15) = 2.7131636040042392095764012…
autopower(16) = 2.7453680235674634847098492…
autopower(17) = 2.7754491049442334313328329…
autopower(18) = 2.8036632456580215496843618…
autopower(19) = 2.8302234384970308956026277…
autopower(20) = 2.8553085030012414128332189…

I assume that the auto-root is always an irrational number, except when n is a perfect power of suitable form, i.e. n = p^p for some integer p. For example, autoroot(4) = 2, because 2^2 = 4, autoroot(27) = 3, because 3^3 = 27, and so on.

And here is the graph of autoroot(n) for n = 2..10000:
autoroot

Get Your Prox Off

by in Fractals, Geometry, Mathematics and tagged , , , , , , , , , , , , , | Leave a comment

Create a triangle. Find a point somewhere inside it. Choose a corner at random and move halfway towards it. Mark the new point. Repeat the procedure: choose, move, mark. Repeat again and again. In time, a fractal will appear:

siertri

However, if you try the same thing with a square – choose a corner at random, move halfway towards it, mark the new point, repeat – no fractal appears. Instead, the points fill the interior of the square:

sierquad

But what happens if you impose restrictions on the randomly chosen corner (or chorner)? Suppose you can’t choose the same corner twice in a row. If this rule is applied to the square, this fractal appears:

restrict4_T

restrict4_Tanim

Now apply the no-corner-twice-in-a-row rule to a square that contains a central chorner. This fractal appears:

restrict4_Tc

And if the rule is that you can choose a corner twice in a row but not thrice? This fractal appears:

restrict4FT

restrict4FTc

Here is the rule is that a corner can’t be chosen if it was chosen two moves ago:

restrict4_3F

But what if the restriction is based not on how often or when a corner is chosen, but on its proximity, i.e. how near it is to the marked point? If the nearest corner can’t be chosen, the result is the same as the no-corner-twice-in-a-row rule:

prox4_1

But if the second-nearest corner can’t be chosen, this fractal appears:

prox4_2

This is the fractal when the third-nearest corner can’t be chosen:

prox4_3

And this is the fractal when the fourth-nearest, or most distant, corner can’t be chosen:

prox4_4

Here are the same restrictions applied to a pentagon:

prox5_1

Nearest corner forbidden

prox5_2

Second-nearest corner forbidden

prox5_3

Third corner forbidden

prox5_4

Fourth corner forbidden

prox5_5

Fifth corner forbidden

prox5_5anim

Fifth corner forbidden (animated)

And a pentagon with a central chorner:

prox5_anim_c

Now try excluding more than one corner. Here are pentagons excluding the n-nearest and n+1-nearest corners (for example, the nearest and second-nearest corners; the second-nearest and third-nearest; and so on):

prox5n_n1_anim

But what if the moving point is set equal to the n-nearest corner before it moves again? If the corner is the second-nearest and the shape is a triangle with a central chorner, this is the fractal that appears:

prox3_set2c

prox3_set2c_anim

Animated version

And here is the same rule applied to various n-nearest corners in a pentagon:

prox5_set_anim

The Choice of the Circle

by in Geometry, Mathematics and tagged , , , , , , , , , , , , , , , , , , | Leave a comment

Here’s an elementary mathematical problem: how many ways are there to choose three numbers from a set of six numbers? If the set is (1, 2, 3, 4, 5, 6), these are the possible choices (or combinations):

(1, 2, 3), (1, 2, 4), (1, 2, 5), (1, 2, 6), (1, 3, 4), (1, 3, 5), (1, 3, 6), (1, 4, 5), (1, 4, 6), (1, 5, 6), (2, 3, 4), (2, 3, 5), (2, 3, 6), (2, 4, 5), (2, 4, 6), (2, 5, 6), (3, 4, 5), (3, 4, 6), (3, 5, 6), (4, 5, 6) (c = 20)

So 6C3 = 20 (C stands for “combination”). The general formula is nCr = (n! / (n-r)!) / r!, where n is the number to choose from, r is the number of choices and n! is factorial n, or n multiplied by all numbers less than itself. For example, 6! = 6 * 5 * 4 * 3 * 2 * 1 = 720. When n = 6 and c = 3, 6C3 = (6! / (6-3)!) / 3! = (720 / 6) / 6 = 20.

There isn’t much visual appeal in the choices above, but there’s a simple way to change that. Take the ways of choosing two numbers from a set of ten. They start like this:

(1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (1, 8), (1, 9), (1, 10), (2, 3), (2, 4), (2, 5), (2, 6), (2, 7), (2, 8), (2, 9), (2, 10), (3, 4), (3, 5), (3, 6)…

Suppose each choice represents the midpoint of two points chosen from a set of ten points around a pentagon, so that (1, 2) is half-way between points 1 and 2, (3, 5) is half-way between points 3 and 5, and so on:

pent_10_2

Now take the ways of choosing three numbers from a set of ten:

(1, 2, 3), (1, 2, 4), (1, 2, 5), (1, 2, 6), (1, 2, 7), (1, 2, 8), (1, 2, 9), (1, 2, 10), (1, 3, 4), (1, 3, 5), (1, 3, 6), (1, 3, 7), (1, 3, 8), (1, 3, 9), (1, 3, 10)…

Now the pentagon looks like this, with (1, 2, 3) representing the point midway between 1, 2 and 3, (1, 3, 9) representing the point midway between 1, 3 and 9, and so on:

pent_10_3

Now here are 10C4, 10C5 and 10C6 for the pentagon:

pent_10_4

pent_10_5

pent_10_6

You can also generate the points 5C4 = 5, then add them to the original five points and generate 10C4:

pent4_1

5C4

pent4_2

10C4

And here are 5C5, 6C5 and 12C5:

pent5

Here are 7C7 and 8C8, adding points as for 5C4:

hept7

octo8

And here is 12C6 using a dodecagon:

dodeca_6

And various nCr for dodecagons and other polygons:

various

This method can also be used to represent the partitions of n, or the number of sets whose members sum to n. The partitions of 5 are these:

(5), (4, 1), (3, 2), (3, 1, 1), (2, 2, 1), (2, 1, 1, 1), (1, 1, 1, 1, 1)

There are seven partitions, so p(5) = 7. Partitions start small and get very large, starting with p(1), p(2), p(3) and so on:

1, 2, 3, 5, 7, 11, 15, 22, 30, 42, 56, 77, 101, 135, 176, 231, 297, 385, 490, 627, 792, 1002, 1255, 1575, 1958, 2436, 3010, 3718, 4565, 5604, 6842, 8349, 10143, 12310, 14883, 17977, 21637, 26015, 31185, 37338, 44583, 53174, 63261, 75175, 89134, 105558, 124754, 147273, 173525, 204226, 239943, 281589, 329931, 386155, 451276, 526823, 614154, 715220, 831820, 966467, 1121505, 1300156…

Suppose the partitions of n are treated as sets of points around a polygon with n vertices. Each set is then used to generate the point midway between its members. For example, (5, 4, 4, 2) is one partition of 15 and would represent the point midway between 5, 4, 4 and 2 of a pentadecagon. Here is a graphical representation of p(30):

partition30

Here are graphical representations for the partitions 5 to 15, then 15 to 60 in increments of 5 (15, 20, 25, etc):

partitions5_60

And here are some close-ups for the partitions of 35 and 40:

partitions40

Power Trip

by in Integer Sequences, Mathematics, Powers and tagged , , , , , , , , , , , , , , , , , , | Leave a comment

Here are the first few powers of 2:

2 = 1 * 2
4 = 2 * 2
8 = 4 * 2
16 = 8 * 2
32 = 16 * 2
64 = 32 * 2
128 = 64 * 2
256 = 128 * 2
512 = 256 * 2
1024 = 512 * 2
2048 = 1024 * 2
4096 = 2048 * 2
8192 = 4096 * 2
16384 = 8192 * 2
32768 = 16384 * 2
65536 = 32768 * 2
131072 = 65536 * 2
262144 = 131072 * 2
524288 = 262144 * 2
1048576 = 524288 * 2
2097152 = 1048576 * 2
4194304 = 2097152 * 2
8388608 = 4194304 * 2
16777216 = 8388608 * 2
33554432 = 16777216 * 2
67108864 = 33554432 * 2…

As you can see, it’s a one-way power-trip: the numbers simply get larger. But what happens if you delete the digit 0 whenever it appears in a result? For example, 512 * 2 = 1024, which becomes 124. If you apply this rule, the sequence looks like this:

2 * 2 = 4
4 * 2 = 8
8 * 2 = 16
16 * 2 = 32
32 * 2 = 64
64 * 2 = 128
128 * 2 = 256
256 * 2 = 512
512 * 2 = 1024 → 124
124 * 2 = 248
248 * 2 = 496
496 * 2 = 992
992 * 2 = 1984
1984 * 2 = 3968
3968 * 2 = 7936
7936 * 2 = 15872
15872 * 2 = 31744
31744 * 2 = 63488
63488 * 2 = 126976
126976 * 2 = 253952
253952 * 2 = 507904 → 5794
5794 * 2 = 11588
11588 * 2 = 23176
23176 * 2 = 46352
46352 * 2 = 92704 → 9274…

Is this a power-trip? Not quite: it’s a return trip, because the numbers can never grow beyond a certain size and the sequence falls into a loop. If the result 2n contains a zero, then zerodelete(2n) < n, so the sequence has an upper limit and a number will eventually occur twice. This happens at step 526 with 366784, which matches 366784 at step 490.

The rate at which we delete zeros can obviously be varied. Call it 1:z. The sequence above sets z = 1, so 1:z = 1:1. But what if z = 2, so that 1:z = 1:2? In other words, the procedure deletes every second zero. The first zero occurs when 1024 = 2 * 512, so 1024 is left as it is. The second zero occurs when 2 * 1024 = 2048, so 2048 becomes 248. When z = 2 and every second zero is deleted, the sequence begins like this:

1 * 2 = 2
2 * 2 = 4
4 * 2 = 8
8 * 2 = 16
16 * 2 = 32
32 * 2 = 64
64 * 2 = 128
128 * 2 = 256
256 * 2 = 512
512 * 2 = 1024 → 1024
1024 * 2 = 2048 → 248
248 * 2 = 496
496 * 2 = 992
992 * 2 = 1984
1984 * 2 = 3968
3968 * 2 = 7936
7936 * 2 = 15872
15872 * 2 = 31744
31744 * 2 = 63488
63488 * 2 = 126976
126976 * 2 = 253952
253952 * 2 = 507904 → 50794
50794 * 2 = 101588 → 101588
101588 * 2 = 203176 → 23176
23176 * 2 = 46352
46352 * 2 = 92704 → 92704
92704 * 2 = 185408 → 18548

This sequence also has a ceiling and repeats at step 9134 with 5458864, which matches 5458864 at step 4166. And what about the sequence in which z = 3 and every third zero is deleted? Does this have a ceiling or does the act of multiplying by 2 compensate for the slower removal of zeros?

In fact, it can’t do so. The larger 2n becomes, the more zeros it will tend to contain. If 2n is large enough to contain 3 zeros on average, the deletion of zeros will overpower multiplication by 2 and the sequence will not rise any higher. Therefore the sequence that deletes every third zero will eventually repeat, although I haven’t been able to discover the relevant number.

But this reasoning applies to any rate, 1:z, of zero-deletion. If z = 100 and every hundredth zero is deleted, numbers in the sequence will rise to the point at which 2n contains sufficient zeros on average to counteract multiplication by 2. The sequence will have a ceiling and will eventually repeat. If z = 10^100 or z = 10^(10^100) and every googolth or googolplexth zero is deleted, the same is true. For any rate, 1:z, at which zeros are deleted, the sequence n = zerodelete(2n,z) has an upper limit and will eventually repeat.

Update (30×21)

Six years later, I’ve found the answer for z = 3. And uncovered a serious error in this article. See:

• Power Trap

Block n Rule

by in Base Behavior, Binary numbers, Integer Sequences, Mathematics and tagged , , , , , , , , , , , , , , , , , | Leave a comment

One of my favourite integer sequences uses the formula n(i) = n(i-1) + digsum(n(i-1)), where digsum(n) sums the digits of n. In base 10, it goes like this:

1, 2, 4, 8, 16, 23, 28, 38, 49, 62, 70, 77, 91, 101, 103, 107, 115, 122, 127, 137, 148, 161, 169, 185, 199, 218, 229, 242, 250, 257, 271, 281, 292, 305, 313, 320, 325, 335, 346, 359, 376, 392, 406, 416, 427, 440, 448, 464, 478, 497, 517, 530, 538, 554, 568, 587, 607, 620, 628, 644, 658, 677, 697, 719, 736, 752, 766, 785, 805, 818, 835, 851, 865, 884, 904, 917, 934, 950, 964, 983, 1003…

Another interesting sequence uses the formula n(i) = n(i-1) + digprod(n(i-1)), where digprod(n) multiplies the digits of n (excluding 0). In base 10, it goes like this:

1, 2, 4, 8, 16, 22, 26, 38, 62, 74, 102, 104, 108, 116, 122, 126, 138, 162, 174, 202, 206, 218, 234, 258, 338, 410, 414, 430, 442, 474, 586, 826, 922, 958, 1318, 1342, 1366, 1474, 1586, 1826, 1922, 1958, 2318, 2366, 2582, 2742, 2854, 3174, 3258, 3498, 4362, 4506, 4626, 4914, 5058, 5258, 5658, 6858, 8778, 11914, 11950, 11995…

You can apply these formulae in other bases and it’s trivially obvious that the sequences rise most slowly in base 2, because you’re never summing or multiplying anything but the digit 1. However, there is a sequence for which base 2 is by far the best performer. It has the formula n(i) = n(i-1) + blockmult(n(i-1)), where blockmult(n) counts the lengths of distinct blocks of the same digit, including 0, then multiplies those lengths together. For example:

blockmult(3,b=2) = blockmult(11) = 2
blockmult(28,b=2) = blockmult(11100) = 3 * 2 = 6
blockmult(51,b=2) = blockmult(110011) = 2 * 2 * 2 = 8
blockmult(140,b=2) = blockmult(10001100) = 1 * 3 * 2 * 2 = 12
blockmult(202867,b=2) = blockmult(110001100001110011) = 2 * 3 * 2 * 4 * 3 * 2 * 2 = 576

The full sequence begins like this (numbers are represented in base 10, but the formula is being applied to their representations in binary):

1, 2, 3, 5, 6, 8, 11, 13, 15, 19, 23, 26, 28, 34, 37, 39, 45, 47, 51, 59, 65, 70, 76, 84, 86, 88, 94, 98, 104, 110, 116, 122, 126, 132, 140, 152, 164, 168, 171, 173, 175, 179, 187, 193, 203, 211, 219, 227, 245, 249, 259, 271, 287, 302, 308, 316, 332, 340, 342, 344, 350, 354, 360, 366, 372, 378, 382, 388, 404, 412, 436, 444, 460, 484, 500, 510, 518, 530, 538, 546, 555, 561, 579, 595, 603, 611, 635, 651, 657, 663, 669, 675, 681…

In higher bases, it rises much more slowly. This is base 3:

1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 14, 16, 17, 19, 20, 21, 22, 24, 26, 29, 31, 33, 34, 35, 37, 39, 42, 44, 48, 49, 51, 53, 56, 58, 60, 61, 62, 64, 65, 66, 68, 70, 71, 73, 75, 77, 79, 82, 85, 89, 93, 95, 97, 98, 100, 101, 102, 103, 105, 107, 110, 114, 116, 120, 124, 127, 129, 131, 133, 137, 139, 141, 142, 143, 145, 146, 147, 149, 151, 152, 154, 156, 158, 160, 163…

And this is base 10:

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 90…

Note how, in bases 3 and 10, blockmult(n) often equals 1. In base 3, the sequence contains [141, 142, 143, 145]:

blockmult(141,b=3) = blockmult(12020) = 1 * 1 * 1 * 1 = 1
blockmult(142,b=3) = blockmult(12021) = 1 * 1 * 1 * 1 = 1
blockmult(143,b=3) = blockmult(12022) = 1 * 1 * 1 * 2 = 2

The formula also returns 1 much further along the sequence in base 3. For example, the 573809th number in the sequence, or n(573809), is 5775037 and blockmult(5775037) = blockmult(101212101212021) = 1^15 = 1. But in base 2, blockmult(n) = 1 is very rare. It happens three times at the beginning of the sequence:

1, 2, 3, 5, 6, 8, 11…

After that, I haven’t found any more examples of blockmult(n) = 1, although blockmult(n) = 2 occurs regularly. For example,

blockmult(n(100723)) = blockmult(44739241) = blockmult(10101010101010101010101001) = 2
blockmult(n(100724)) = blockmult(44739243) = blockmult(10101010101010101010101011) = 2
blockmult(n(100725)) = blockmult(44739245) = blockmult(10101010101010101010101101) = 2

Does the sequence in base 2 return another example of blockmult(n) = 1? The odds seem against it. For any given number of digits in base 2, there is only one number for which blockmult(n) = 1. For example: 1, 10, 101, 1010, 10101, 101010, 1010101… As the sequence increases, the percentage of these numbers becomes smaller and smaller. But the sequence is infinite, so who knows what happens in the end? Perhaps blockmult(n) = 1 occurs infinitely often.

Over Again

by in Fractals, Geometry, Mathematics and tagged , , , , , , , , , , | 1 Comment

In Boldly Breaking the Boundaries, I looked at the use of squares in what I called over-fractals, or fractals whose sub-divisions reproduce the original shape but appear beyond its boundaries. Now I want to look at over-fractals using triangles. They’re less varied than those involving squares, but still include some interesting shapes. This is the space in which sub-triangles can appear, with the central seeding triangle coloured gray: triangle
Here are some over-fractals based on the pattern above: overtri1
overtri1_static

overtri2
overtri2_static

overtri3

overtri3_static

overtri4
overtri4_static

overtri5
overtri5_static

overtri6
overtri6_static

overtri7
overtri7_static

overtri8
overtri8_static

overtri9
overtri9_static

overtri10
overtri10_static

overtri11
overtri11_static

overtri12
overtri12_static

overtri13

overtri13_static

Boldly Breaking the Boundaries

by in Fractals, Geometry, Mathematics, Rep-Tiles and tagged , , , , , , , , , , , , , , , , , | Leave a comment

In “M.I.P. Trip”, I looked at fractals like this, in which a square is divided repeatedly into a pattern of smaller squares:
2x2inner

2x2inner_static

3x3innera

3x3innera_static

3x3innerb

3x3innerb_static

As you can see, the sub-squares appear within the bounds of the original square. But what if some of the sub-squares appear beyond the bounds of the original square? Then a new family of fractals is born, the over-fractals:

fractal2x2a

fractal2x2a_static

fractal2x2b

fractal2x2b_static

fractal2x2c

fractal2x2c_static

fractal2x2d

fractal2x2d_static

fractal2x2e

fractal2x2e_static

fractal3x3a

fractal3x3a_static

fractal3x3b

fractal3x3b_static

fractal3x3c

fractal3x3c_static

fractal3x3d

fractal3x3e

fractal3x3f

fractal3x3g

fractal3x3h

fractal3x3i

fractal3x3j

fractal3x3k

fractal3x3l

fractal3x3m

fractal3x3n

fractal4x4a

fractal4x4c

fractal4x4b

Lette’s Roll

by in Geometry, π, Mathematics, Pi and tagged , , , , , , , , , , , , , , , , , , , | Leave a comment

A roulette is a little wheel or little roller, but it’s much more than a game in a casino. It can also be one of a family of curves created by tracing the path of a point on a rotating circle. Suppose a circle rolls around another circle of the same size. This is the resultant roulette:
roulette1

roulette1static
The shape is called a cardioid, because it looks like a heart (kardia in Greek). Now here’s a circle with radius r rolling around a circle with radius 2r:
roulette2

roulette2static

That shape is a nephroid, because it looks like a kidney (nephros in Greek).

This is a circle with radius r rolling around a circle with radius 3r:
roulette3

roulette3static
And this is r and 4r:
roulette4

roulette4static
The shapes above might be called outer roulettes. But what if a circle rolls inside another circle? Here’s an inner roulette whose radius is three-fifths (0.6) x the radius of its rollee:
roulette5

roulette5static
The same roulette appears inverted when the inner circle has a radius two-fifths (0.4) x the radius of the rollee:
roulette5a
But what happens when the circle rolling “inside” is larger than the rollee? That is, when the rolling circle is effectively swinging around the rollee, like a bunch of keys being twirled on an index finger? If the rolling radius is 1.5 times larger, the roulette looks like this:
roulette6
If the rolling radius is 2 times larger, the roulette looks like this:
roulette2over

Here are more outer, inner and over-sized roulettes:

roulette_outer

roulette_inner

roulette_over

And you can have circles rolling inside circles inside circles:

roulette7

roulette0616

roulette0616all

And here’s another circle-in-a-circle in a circle:

roulette07c015c

Playing the Double Base

by in Base Behavior, Binary numbers, Mathematics and tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Here’s some mathematical nonsense:

10 > 12
100 > 122
1000 > 1222

How can 1000 > 1222? Well, it makes perfect sense in what you might call a double base. In this base, every number is identified by a unique string of digits, but the strings don’t behave as they do in a standard base.

To see how this double base works, first look at 9 in standard base 2. To generate the binary digits from right to left, you follow the procedure x mod 2 and x = x div 2, where (x mod 2) returns the remainder when x is divided by 2 and (x div 2) divides x by 2 and discards the remainder:

9 mod 2 = 1 → ...1
9 div 2 = 4
4 mod 2 = 0 → ..01
4 div 2 = 2
2 mod 2 = 0 → .001
2 div 2 = 1
1 mod 2 = 1 → 1001

So 9[b=10] = 1001[b=2]. To adapt the procedure to base 3, simply use x mod 3 and x = x div 3:

32 mod 3 = 2 → ...2
32 div 3 = 10
10 mod 3 = 1 → ..12
10 div 3 = 3
3 mod 3 = 0 → .012
3 div 3 = 1
1 mod 3 = 1 → 1012

So 32[b=10] = 1012[b=3].

But what happens if you mix bases and use (x mod 3) and (x div 2), like this?:

2 mod 3 = 2 → .2
2 div 2 = 1
1 mod 3 = 1 → 12

3 mod 3 = 0 → .0
3 div 2 = 1
1 mod 3 = 1 → 10

So 10 > 12, i.e. 10[b=3,2] > 12[b=3,2].

5 mod 3 = 2 → ..2
5 div 2 = 2
2 mod 3 = 2 → .22
2 div 2 = 1
1 mod 3 = 1 → 122

6 mod 3 = 0 → ..0
6 div 2 = 3
3 mod 3 = 0 → .00
3 div 2 = 1
1 mod 3 = 1 → 100

So 100 > 122.

11 mod 3 = 2 → ...2
11 div 2 = 5
5 mod 3 = 2 → ..22
5 div 2 = 2
2 mod 3 = 2 → .222
2 div 2 = 1
1 mod 3 = 1 → 1222

12 mod 3 = 0 → …0
12 div 2 = 6
6 mod 3 = 0 → ..00
6 div 2 = 3
3 mod 3 = 0 → .000
3 div 2 = 1
1 mod 3 = 1 → 1000

And 1000 > 1222. Here are numbers 1 to 32 in this double base:

1 = 1
12 = 2
10 = 3
121 = 4
122 = 5
100 = 6
101 = 7
1212 = 8
1210 = 9
1221 = 10
1222 = 11
1000 = 12
1001 = 13
1012 = 14
1010 = 15
12121 = 16
12122 = 17
12100 = 18
12101 = 19
12212 = 20
12210 = 21
12221 = 22
12222 = 23
10000 = 24
10001 = 25
10012 = 26
10010 = 27
10121 = 28
10122 = 29
10100 = 30
10101 = 31
121212 = 32

Given a number represented in this mixed base, how do you extract the underlying n? Suppose the number takes the form n = (digit[1]..digit[di]), where digit[1] is the first and leftmost digit and digit[di] the final and rightmost digit. Then this algorithm will extract n:

n = 1
for i = 2 to di
..n = n * 2
..while n mod 3 ≠ digit[i]
....n = n + 1
..endwhile
next i
print n

For example, suppose n = 12212[b=3,2]. Then di = 5 and the algorithm will work like this:

n = 1
n = n * 2 = 2.
2 mod 3 = 2 = digit[2]
2 * 2 = 4
4 mod 3 = 1 ≠ digit[3]
5 mod 3 = 2 = digit[3]
5 * 2 = 10
10 mod 3 = 1 = digit[4]
10 * 2 = 20
20 mod 3 = 2 = digit[5]

Therefore 12212[b=3,2] = 20[b=10].

Now try some more mathematical nonsense:

21 > 100
111 > 1,000
1,001 > 10,000
10,001 > 100,000

How can numbers with d digits be greater than numbers with d+1 digits? Easily. In this incremental base, the base adjusts itself as the digits are generated, like this:

5 mod 2 = 1 → .1
5 div 2 = 2
2 mod (2 + 1) = 2 mod 3 = 2 → 21

The first digit generated is 1, so the base increases to (2 + 1) = 3 for the second digit. Compare the procedure when n = 4:

4 mod 2 = 0 → ..0
4 div 2 = 2
2 mod 2 = 0 → .00
2 div 2 = 1
1 mod 2 = 1 → 100

So 21 > 100, because 4 is a power of 2 and all the digits generated by (x mod 2) are 0 except the final and leftmost. 2 + 0 = 2. Now try n = 33:

33 mod 2 = 1 → ...1
33 div 2 = 16
16 mod (2+1) = 16 mod 3 = 1 → ..11
16 div 3 = 5
5 mod (3+1) = 5 mod 4 = 1 → .111
5 div 4 = 1
1 mod (4+1) = 1 mod 5 = 1.

33[b=10] = 1111[b=2,3,4,5].

Here are numbers 1 to 60 in this incremental base (note how 21 > 100, 111 > 1000, 1001 > 10000 and 10001 > 100000):

1 = 1
10 = 2
11 = 3
100 = 4*
21 = 5*
110 = 6
101 = 7
1000 = 8*
111 = 9*
210 = 10
121 = 11
1100 = 12
201 = 13
1010 = 14
211 = 15
10000 = 16*
221 = 17
1110 = 18
1001 = 19*
2100 = 20
311 = 21
1210 = 22
321 = 23
11000 = 24
1101 = 25
2010 = 26
1011 = 27
10100 = 28
421 = 29
2110 = 30
1201 = 31
100000 = 32*
1111 = 33
2210 = 34
1021 = 35
11100 = 36
2001 = 37
10010 = 38
1211 = 39
21000 = 40
1121 = 41
3110 = 42
2101 = 43
12100 = 44
1311 = 45
3210 = 46
1221 = 47
110000 = 48
2201 = 49
11010 = 50
2011 = 51
20100 = 52
1321 = 53
10110 = 54
10001 = 55*
101000 = 56
2111 = 57
4210 = 58
1421 = 59
21100 = 60

And here are numbers 256 to 270 (Note how 8,421 > 202,100 > 100,000,000):

100000000 = 256*
11221 = 257
101110 = 258
32101 = 259
202100 = 260*
13311 = 261
41210 = 262
10321 = 263
1111000 = 264
24201 = 265
131010 = 266
23011 = 267
320100 = 268
8421 = 269*
52110 = 270

Extracting n from a number represented in this incremental base is trickier than for the double base using (x mod 3) and (x div 2). To see how to do it, examine 11221[b=incremental]. The fifth and rightmost digit is 1, so the base increases to (2 + 1) = 3 for the fourth digit, which is 2. The base increases to (3 + 2) = 5 for the third digit, which is 2 again. The base increases to (5 + 2) = 7 for the second digit, 1. But the first and rightmost digit, 1, represents (x div 7) mod (7 + 1 = 8). So n can be extracted like this:

digit[1] * 7 = 1 * 7 = 7
7 mod 7 = 0 ≠ digit[2]
8 mod 7 = 1 = digit[2]
8 * 5 = 40
40 mod 5 = 0 ≠ digit[3]
41 mod 5 = 1 ≠ digit[3]
42 mod 5 = 2 = digit[3]
42 * 3 = 126
126 mod 3 = 0 ≠ digit[4]
127 mod 3 = 1 ≠ digit[4]
128 mod 3 = 2 = digit[4]
128 * 2 = 256
256 mod 2 = 0 ≠ digit[5]
257 mod 2 = 1 = digit[5]

So 11221[b=8,7,5,3,2] = 257[b=10].

Now try 8421[b=incremental]. The fourth and rightmost digit is 1, so the base increases to (2 + 1) = 3 for the third digit, which is 2. The base increases to (3 + 2) = 5 for the second digit, 4. But the first and rightmost digit, 8, represents (x div 5) mod (5 + 4 = 9). So n can be extracted like this:

digit[1] * 5 = 8 * 5 = 40
40 mod 5 = 0 ≠ digit[2]
41 mod 5 = 1 ≠ digit[2]
42 mod 5 = 2 ≠ digit[2]
43 mod 5 = 3 ≠ digit[2]
44 mod 5 = 4 = digit[2]
44 * 3 = 132
132 mod 3 = 0 ≠ digit[3]
133 mod 3 = 1 ≠ digit[3]
134 mod 3 = 2 = digit[3]
134 * 2 = 268
268 mod 2 = 0 ≠ digit[4]
269 mod 2 = 1 = digit[4]

So 8421[b=9,5,3,2] = 269[b=10].

Narcischism

by in Binary numbers, Mathematics, Narcissistic numbers and tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

What have bits to do with splits? A lot. Suppose you take the digits 12345, split them in all possible ways, then sum the results, like this:

12345 → (1234 + 5) + (123 + 45) + (123 + 4 + 5) + (12 + 345) + (12 + 34 + 5) + (12 + 3 + 45) + (12 + 3 + 4 + 5) + (1 + 2345) + (1 + 234 + 5) + (1 + 23 + 45) + (1 + 23 + 4 + 5) + (1 + 2 + 345) + (1 + 2 + 34 + 5) + (1 + 2 + 3 + 45) + (1 + 2 + 3 + 4 + 5) = 5175.

That’s a sum in base 10, but base 2 is at work below the surface, because each set of numbers is the answer to a series of binary questions: split or not? There are four possible places to split the digits 12345: after the 1, after the 2, after the 3 and after the 4. In (1 + 2 + 3 + 4 + 5), the binary question “Split or not?” is answered SPLIT every time. In (1234 + 5) and (1 + 2345) it’s answered SPLIT only once.

So the splits are governed by a four-digit binary number ranging from 0001 to 1111. When the binary digit is 1, split; when the binary digit is 0, don’t split. In binary, 0001 to 1111 = 01 to 15 in base 10 = 2^4-1. That’s for a five-digit number, so the four-digit 1234 will have 2^3-1 = 7 sets of sums:

1234 → (123 + 4) + (12 + 34) + (12 + 3 + 4) + (1 + 234) + (1 + 23 + 4) + 110 (1 + 2 + 34) + (1 + 2 + 3 + 4) = 502.

And the six-digit number 123456 will have 2^5-1 = 31 sets of sums. By now, an exciting question may have occurred to some readers. Does any number in base 10 equal the sum of all possible numbers formed by splitting its digits?

The exciting answer is: 0. In other words: No. To see why not, examine a quick way of summing the split-bits of 123,456,789, with nine digits. The long way is to find all possible sets of split-bits. There are 2^8-1 = 255 of them. The quick way is to sum these equations:

1 * 128 + 10 * 64 + 100 * 32 + 1000 * 16 + 10000 * 8 + 100000 * 4 + 1000000 * 2 + 10000000 * 1
2 * 128 + 20 * 64 + 200 * 32 + 2000 * 16 + 20000 * 8 + 200000 * 4 + 2000000 * 2 + 20000000 * 1
3 * 128 + 30 * 64 + 300 * 32 + 3000 * 16 + 30000 * 8 + 300000 * 4 + 3000000 * 3
4 * 128 + 40 * 64 + 400 * 32 + 4000 * 16 + 40000 * 8 + 400000 * 7
5 * 128 + 50 * 64 + 500 * 32 + 5000 * 16 + 50000 * 15
6 * 128 + 60 * 64 + 600 * 32 + 6000 * 31
7 * 128 + 70 * 64 + 700 * 63
8 * 128 + 80 * 127
9 * 255

Sum = 52,322,283.

52,322,283 has eight digits. If you use the same formula for the nine-digit number 999,999,999, the sum is 265,621,761, which has nine digits but is far smaller than 999,999,999. If you adapt the formula for the twenty-digit 19,999,999,999,999,999,999 (starting with 1), the split-bit sum is 16,562,499,999,987,400,705. In base 10, as far as I can see, numbers increase too fast and digit-lengths too slowly for the binary governing the split-sums to keep up. That’s also true in base 9 and base 8:

Num = 18,888,888,888,888,888,888 (b=9)
Sum = 16,714,201,578,038,328,760

Num = 17,777,777,777,777,777,777 (b=8)
Sum = 17,070,707,070,625,000,001

So what about base 7? Do the numbers increase slowly enough and the digit-lengths fast enough for the binary to keep up? The answer is: 1. In base 7, this twenty-digit number is actually smaller than its split-bit sum:

Num = 16,666,666,666,666,666,666 (b=7)
Sum = 20,363,036,303,404,141,363

And if you search below that, you can find a number that is equal to its split-bit sum:

166512 → (1 + 6 + 6 + 5 + 1 + 2) + (16 + 6 + 5 + 1 + 2) + (1 + 66 + 5 + 1 + 2) + (166 + 5 + 1 + 2) + (1 + 6 + 65 + 1 + 2) + (16 + 65 + 1 + 2) + (1 + 665 + 1 + 2) + (1665 + 1 + 2) + (1 + 6 + 6 + 51 + 2) + (16 + 6 + 51 + 2) + (1 + 66 + 51 + 2) + (166 + 51 + 2) + (1 + 6 + 651 + 2) + (16 + 651 + 2) + (1 + 6651 + 2) + (16651 + 2) + (1 + 6 + 6 + 5 + 12) + (16 + 6 + 5 + 12) + (1 + 66 + 5 + 12) + (166 + 5 + 12) + (1 + 6 + 65 + 12) + (16 + 65 + 12) + (1 + 665 + 12) + (1665 + 12) + (1 + 6 + 6 + 512) + (16 + 6 + 512) + (1 + 66 + 512) + (166 + 512) + (1 + 6 + 6512) + (16 + 6512) + (1 + 66512) = 166512[b=7] = 33525[b=10].

So 33525 in base 7 is what might be called a narcischist: it can gaze into the split-bits of its own digits and see itself gazing back. In base 6, 1940 is a narcischist:

12552 → (1 + 2 + 5 + 5 + 2) + (12 + 5 + 5 + 2) + (1 + 25 + 5 + 2) + (125 + 5 + 2) + (1 + 2 + 55 + 2) + (12 + 55 + 2) + (1 + 255 + 2) + (1255 + 2) + (1 + 2 + 5+ 52) + (12 + 5 + 52) + (1 + 25 + 52) + (125 + 52) + (1 + 2 + 552) + (12 + 552) + (1 + 2552) = 12552[b=6] = 1940[b=10].

In base 5, 4074 is a narcischist:

112244 → (1 + 1 + 2 + 2 + 4 + 4) + (11 + 2 + 2 + 4 + 4) + (1 + 12 + 2 + 4 + 4) + (112 + 2 + 4 + 4) + (1 + 1 + 22 + 4 + 4) + (11 + 22 + 4 + 4) + (1 + 122 + 4 + 4) + (1122 + 4 + 4) + (1 + 1 + 2 + 24 + 4) + (11 + 2 + 24 + 4) + (1 + 12 + 24 + 4) + (112 + 24 + 4) + (1 + 1 + 224 + 4) + (11 + 224 + 4) + (1 + 1224 + 4) + (11224 + 4) + (1 + 1 + 2 + 2 + 44) + (11 + 2 + 2 + 44) + (1 + 12 + 2 + 44) + (112 + 2 + 44) + (1 + 1 + 22 + 44) + (11 + 22 + 44) + (1 + 122 + 44) + (1122 + 44) + (1 + 1 + 2 + 244) + (11 + 2 + 244) + (1 + 12 + 244) + (112 + 244) + (1 + 1 + 2244) + (11 + 2244) + (1 + 12244) = 112244[b=5] = 4074.

And in base 4, 27 is:

123 → (1 + 2 + 3) + (12 + 3) + (1 + 23) = 123[b=4] = 27.

And in base 3, 13 and 26 are:

111 → (1 + 1 + 1) + (11 + 1) + (1 + 11) = 111[b=3] = 13.

222 → (2 + 2 + 2) + (22 + 2) + (2 + 22) = 222[b=3] = 26.

There are many more narcischists in all these bases, even if you exclude numbers with zeroes in them, like these in base 4:

1022 → (1 + 0 + 2 + 2) + (10 + 2 + 2) + (1 + 02 + 2) + (102 + 2) + (1 + 0 + 22) + (10 + 22) + (1 + 022) = 1022[b=4] = 74.

1030 → (1 + 0 + 3 + 0) + (10 + 3 + 0) + (1 + 03 + 0) + (103 + 0) + (1 + 0 + 30) + (10 + 30) + (1 + 030) = 1030[b=4] = 76.

1120 → (1 + 1 + 2 + 0) + (11 + 2 + 0) + (1 + 12 + 0) + (112 + 0) + (1 + 1 + 20) + (11 + 20) + (1 + 120) = 1120[b=4] = 88.