Probability of Outcomes in Merge Shuffle

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In summary, the conversation discusses Merge Sort and Merge Shuffle, two algorithms used for sorting a list of elements. Merge Sort splits the list into halves and repeatedly combines them until the list is sorted, while Merge Shuffle randomly selects elements from the two lists during the combining stage. The question being explored is the probability of producing a given result when performing Merge Shuffle on a list of unique elements. The conversation also mentions the difficulty of analyzing this probability when the length of the list is not a power of 2.
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ardentra
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So I've been banging my head on this problem for a few days and haven't gotten very far, hoping someone has some insights. I know this sort of reads like a homework problem, but this problem is the result of personal investigations and does not come from an assignment.

So for those of you who don't know, Merge Sort is an algorithm that works by taking a list of elements to be sorted, L, and splitting L into halves L1 and L2, then splitting those halves, repeatedly until reaching a set of lists of length 1. Then the lists are recombined with correct ordering until once again arriving at one list, which is now sorted. Lists are not sets: order matters, and in this case you can only add items onto the front of lists.

So say you had the list of numbers 3,9,8,0,2,1,5,7,4,6. Performing Merge Sort would look like this(I removed commas for convenience):

3980215746

39802 15746

39 802 15 746

3 9 8 02 1 5 7 46

3 9 8 0 2 1 5 7 4 6

39 8 02 15 7 46

39 028 15 467

02389 14567

0123456789

During the merge steps, items are selected one at a time from the left side of both L1 and L2, compared to one another, and the item with the smaller value is added to the new list. This step is repeated until the lists have been combined.
So a single merge step would operate like this for lists L1 = 2,3 and L2 = 1,4:

Compare 1 and 2
Add 1 to the recombined list
Compare 2 and 4
Add 2 to the recombined list
Compare 3 and 4
Add 3 to the recombined list
Add 4 to the recombined list


So that is Merge Sort. Merge Shuffle works the same way, except that during the recombining stage, there is a 50% chance of a number being taken from L1 and a 50% chance of a number being taken from L2 for addition to the recombined list.
So combining lists L1 = 1,2 and L2 = 3,4 might operate like this:

Select 1 or 3
Add 3 to the recombined list
Select 1 or 4
Add 1 to the recombined list
Select 2 or 4
Add 4 to the recombined list
Add 2 to the recombined list

Which would create the newly shuffled list L = 3142.

I am fairly sure that at a single add step during a merge, the probability of an element at position e in list E = E1... ...En of length n ending up in position t of the target list T = T1, T2... where x positions in T have already been filled and d = t - x is equal to:

if e > d then probability = 0
if e + o < d then probability = 0
otherwise probability = .5d

Where o is the number of items remaining in the other list being merged.

So this is the question I want to solve: Given input list I of length n, and I containing no repeated items, what is the probability that performing Merge Shuffle on I produces I as the result?

And more generally, given input list I of length n, and I containing no repeated items, what is the probability of producing the given result LI?
 
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If n is a power of 2, this looks easy to analyze.
If n is not, that looks ugly - you have to keep track of all combinations of k with k+1 elements somewhere. Let f(I) be the result of a merge shuffle. I think f(I)=I can be studied with some casework (look at n=2, n=3, n=4, n=5, ..., try to find a recursion formula), but I don't know how to get the more general result.
 

1. What is the "Probability of Outcomes in Merge Shuffle"?

The "Probability of Outcomes in Merge Shuffle" refers to the likelihood or chance of a particular sequence of elements occurring when two sets of data are combined using a merge shuffle algorithm. This algorithm involves taking two sets of data and randomly combining them to create a new set with elements from both sets.

2. How is the probability of outcomes calculated in a merge shuffle?

The probability of outcomes in a merge shuffle is calculated by taking into account the total number of elements in the two sets being merged, and then determining the number of ways in which those elements can be combined. This can be done using combinatorics and probability theory.

3. What factors influence the probability of outcomes in a merge shuffle?

The main factors that influence the probability of outcomes in a merge shuffle are the size of the two sets being merged and the randomness of the algorithm used to combine them. A larger set size and a more random shuffle algorithm can result in a higher number of possible outcomes and therefore a lower probability of any specific outcome.

4. Is the probability of outcomes in a merge shuffle affected by the order of elements in the original sets?

No, the probability of outcomes in a merge shuffle is not affected by the order of elements in the original sets. This is because the shuffle algorithm randomly combines the elements from the two sets, regardless of their original order, resulting in an equally likely chance for all possible outcomes.

5. How can the probability of outcomes in a merge shuffle be used in practical applications?

The probability of outcomes in a merge shuffle can be used in various practical applications, such as data science, gambling, and cryptography. In data science, it can help in analyzing and predicting outcomes when merging different datasets. In gambling, it can be used to determine the chances of winning in certain games that involve shuffling. In cryptography, it can be used to generate secure and random sequences of data.

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