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| *<math display="inline">M_g(n)=\min\{k\in\mathbb{N}:g^{k}(n)\equiv0\ (\operatorname{mod}3)\}</math> (the amount of times <math>g(n)</math> must be applied to reach a multiple of 3) | | *<math display="inline">M_g(n)=\min\{k\in\mathbb{N}:g^{k}(n)\equiv0\ (\operatorname{mod}3)\}</math> (the amount of times <math>g(n)</math> must be applied to reach a multiple of 3) |
| *<math>q(n)=f^{M_f(n)}(8)</math> | | *<math>q(n)=f^{M_f(n)}(8)</math> |
| The sequence the values for which as long as Lucy's Moonlight does not halt, we get configurations of the form <math>C(k,8)</math>, denoted <math>c_n</math>, can be written as: | | The sequence of values for which as long as Lucy's Moonlight does not halt, we get configurations of the form <math>C(k,8)</math>, denoted <math>c_n</math>, can be written as: |
| <math display="block">\textstyle c_0=0,\qquad c_{n+1}=(c_n-S(M_f(c_n)-1))\times\frac{2q(c_n)+8}{3}+(1-c_n+S(M_f(c_n)-1))\times\frac{2}{3}g^{M_g(q(c_n))}(q(c_n)).</math> | | <math display="block">\textstyle c_0=0,\qquad c_{n+1}=(c_n-S(M_f(c_n)-1))\times\frac{2q(c_n)+8}{3}+(1-c_n+S(M_f(c_n)-1))\times\frac{2}{3}g^{M_g(q(c_n))}(q(c_n)).</math> |
| Lucy's Moonlight halts if and only if there exists a <math>c\in c_n</math> such that <math>c-S(M_f(c)-1)=1</math> and <math>q(c_n)\equiv1\ (\operatorname{mod}3)</math>. | | Lucy's Moonlight halts if and only if there exists a <math>c\in c_n</math> such that <math>c-S(M_f(c)-1)=1</math> and <math>q(c_n)\equiv1\ (\operatorname{mod}3)</math>. |
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| #If <math>n=1</math>, then <math>n</math> will decrease to 0, the game is won, or a new round begins, each with probability <math display="inline>\frac{1}{3}</math>. | | #If <math>n=1</math>, then <math>n</math> will decrease to 0, the game is won, or a new round begins, each with probability <math display="inline>\frac{1}{3}</math>. |
| #If <math>n=0</math>, then a new round begins. | | #If <math>n=0</math>, then a new round begins. |
| If <math>P(n)</math> is the probability of winning a round with starting value <math>n</math>, then <math display="inline">P(n)=\frac{1}{3}P(n-1)+\frac{2}{3}P(n-2)</math> if <math>n\ge2</math>. This is a recurrence relation whose general solution is <math display="inline">P(n)=c_0+c_1{\Big({-\frac{2}{3}}\Big)}^n</math>. The boundary conditions <math>P(0)=0</math> and <math display="inline">P(1)=\frac{1}{3}</math> enable us to obtain <math display="inline">c_0=\frac{1}{5}</math> and <math display="inline">c_1=-\frac{1}{5}</math>. Since <math display="inline">\left\vert {-\frac{2}{3}}\right\vert <1</math>, <math display="inline">P(n)\approx\frac{1}{5}</math> for large <math>n</math>, so the probability of winning the game in <math>r</math> rounds is approximately <math display="inline">1-\Big(\frac{4}{5}\Big)^r</math>. Because we have an unlimited number of rounds available, the game will almost surely be won eventually, so Lucy's Moonlight will almost surely halt. | | If <math>P(n)</math> is the probability of winning a round with starting value <math>n</math>, then <math display="inline">P(n)=\frac{1}{3}P(n-1)+\frac{2}{3}P(n-2)</math> if <math>n\ge2</math>. This is a recurrence relation whose general solution is <math display="inline">P(n)=c_0+c_1{\Big({-\frac{2}{3}}\Big)}^n</math>. The boundary conditions <math>P(0)=0</math> and <math display="inline">P(1)=\frac{1}{3}</math> enable us to obtain <math display="inline">c_0=\frac{1}{5}</math> and <math display="inline">c_1=-\frac{1}{5}</math>. Since <math display="inline">\left\vert {-\frac{2}{3}}\right\vert <1</math>, <math display="inline">P(n)\approx\frac{1}{5}</math> for large <math>n</math>, so the probability of winning the game in <math>r</math> rounds is approximately <math display="inline">1-\Big(\frac{4}{5}\Big)^r</math>. Because there is an unlimited number of rounds available, the game will almost surely be won eventually, so Lucy's Moonlight will almost surely halt. |
| [[Category:Cryptids]] | | [[Category:Cryptids]] |
Revision as of 00:22, 13 April 2025
1RB0RD_0RC1RE_1RD0LA_1LE1LC_1RF0LD_---0RA
(bbch)
Lucy's Moonlight is a BB(6) Cryptid. This Turing machine was first mentioned on Discord by Racheline on 1 Mar 2025, who afterward found a set of high-level rules describing it. Shawn Ligocki later discovered and shared a more refined set of rules, displayed below.
|
0 |
1
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A
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1RB
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0RD
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B
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0RC
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1RE
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C
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1RD
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0LA
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D
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1LE
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1LC
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E
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1RF
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0LD
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F
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---
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0RA
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The transition table of Lucy's Moonlight.
Analysis
Let
. Then,

Proof
Consider the partial configuration
, which after three steps is
. To advance, this shift rule is required:

This means we have

after

steps, with

after three further steps. From here, we can use the fact that

becomes

in four steps if

to get this rule:

Using this rule produces

in

steps. With five more steps, we get

, which is also

. To summarize:

With

we have

and are able to apply this rule

times, with three possible scenarios:
- If
, then in
steps we arrive at
. The matching complete configuration is
. In
steps we have
, followed by
after three steps. We note that if
, then
becomes
in 8 steps, giving this transition rule:
In this instance, the result is
, equal to
, after
steps. This gives a total of
steps.
- We can rewrite
as
if
. Given this, we have
, and if
, then in
steps we arrive at
, which in
steps becomes
, and then
after three more steps. We end with
steps to get
, equal to
. This gives a total of
steps.
- If
and we reuse the technique of rewriting
, then in
steps we arrive at
, which in
steps becomes
, and then in five steps,
. Adding
steps gives us
, and another eight gives us
. After
steps, the configuration is
and after three more,
. We conclude with
, equal to
, after
steps, for a total of
steps.
The behaviour of Lucy's Moonlight changes at the boundary conditions:
or
. These changes are addressed below:
- If
and
, then starting from
, we take three steps to get
. It is here that another shift rule must come into use:
Upon using this shift rule, we get
in
steps. This configuration is the same as
. With 40 more steps, we end at
, equal to
, for a total of
steps.
- If
and
, then in
steps we arrive at
. With
more steps we now have
. Given five steps, the result is
, which turns into
, equal to
in
steps for a total of
steps.
- If
and
, then starting from
, we get
in three steps. Since
and
are the same, what follows is
in
steps before finally reaching
, and therefore the undefined F0
transition, in three steps. This gives a total of
steps.
- If
and
, then in
steps we arrive at
. It takes a further
steps to reach
, and adding three more gives us
. With
more steps we end up with
, equal to
. This gives a total of
steps.
- If
and
, then starting from
, we take three steps to get
, and taking
more steps produces
. After 40 steps, we reach
, which is
, for a total of
steps.
The information above can be summarized as

Substituting

, where

is the remainder of

modulo 3, yields the final result.
We can define these functions:
(the movement of
according to the first three rules)
(which imitates
decreasing, with
representing function iteration)
(the number of iterations of
needed to reach a boundary condition)
(representing rules 5 and 7)
(the amount of times
must be applied to reach a multiple of 3)

The sequence of values for which as long as Lucy's Moonlight does not halt, we get configurations of the form
, denoted
, can be written as:

Lucy's Moonlight halts if and only if there exists a

such that

and

.
Trajectory
Starting with
after two steps, Lucy's Moonlight repeatedly applies the Collatz-like rules. The first few steps are shown below:

From

, it takes 11 rule steps to get

and 6811 more to get

, where

. Because

grows tetrationally, analysis of

and

is critical to understanding the nature of any additional terms of this sequence. Despite this, Lucy's Moonlight can be argued to
probviously halt if one considers each instance of

as the beginning of an independent round of a luck-based game, detailed below:
- A random large number
is generated.
- At each time unit,
will decrease by 1 with probability
or decrease by 2 with probability
. This step repeats as long as
.
- If
, then
will decrease to 0, the game is won, or a new round begins, each with probability
.
- If
, then a new round begins.
If
is the probability of winning a round with starting value
, then
if
. This is a recurrence relation whose general solution is
. The boundary conditions
and
enable us to obtain
and
. Since
,
for large
, so the probability of winning the game in
rounds is approximately
. Because there is an unlimited number of rounds available, the game will almost surely be won eventually, so Lucy's Moonlight will almost surely halt.