Can the determinant of a combinatorial matrix be proven to always equal 1?

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In summary, the conversation discusses the problem of finding the determinant of a given n x n matrix A, with entries a_ij defined as the binomial coefficient of m_j + i - 1 and j - 1. The determinant is found to be 1, but the group is interested in finding a proof for this result. Suggestions are given, such as exploring the transposition of matrices and using cofactors, but it is ultimately suggested to first check for the case where m_j=1 and then use induction over n. The use of formulas for diagonals is also mentioned as a potential helpful tool.
  • #1
rbzima
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Let [itex]A\Large[/itex] be the [itex]n \times n[/itex] matrix [itex] (a_{ij}) [/itex] given by
[tex]a_{ij} = \binom{m_j + i - 1}{j - 1} [/tex]
where [itex]i,j = 1, 2, ..., n[/itex] and [itex]n[/itex] and [itex]m_j[/itex] are natural numbers. Find the determinant of [itex]A\Large[/itex].

So, I've been looking at this problem for the past couple days and it is a really interesting problem. I discovered that the determinant is actually 1, however I'm wondering how to show this result in terms of a proof. If anyone has any suggestions, they would be greatly welcomed! ;)

I personally was thinking that when you transpose the matrices, something interesting happens with the nested matrices in the upper left corner moving outward, but I'm not entirely sure this is a right approach to be taking. Also, finding determinants by cofactors is really only helpful in smaller matrices, so I was wondering if it might also need to be expanded using the Big Formula, which in this case would consist of n! different terms.
 
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  • #2
I would first check whether it is still true for all ##m_j =1##. Then an induction over ##n## should be the way to prove it. Also formulas for the various diagonals might help a lot.
 

1. What is a Combinatorial Matrix problem?

A Combinatorial Matrix problem is a mathematical problem that involves finding the optimal arrangement of elements in a matrix based on a set of rules or constraints. It is a subfield of combinatorial optimization that has applications in various fields such as operations research, computer science, and engineering.

2. What are some common examples of Combinatorial Matrix problems?

Some common examples of Combinatorial Matrix problems include the assignment problem, the traveling salesman problem, and the knapsack problem. These problems all involve finding the most efficient way to allocate resources or arrange elements based on a given set of constraints.

3. What techniques are used to solve Combinatorial Matrix problems?

Various techniques can be used to solve Combinatorial Matrix problems, including dynamic programming, branch and bound, and greedy algorithms. These techniques involve breaking down the problem into smaller subproblems and finding the optimal solution for each subproblem, which can then be combined to find the overall optimal solution.

4. What are some real-life applications of Combinatorial Matrix problems?

Combinatorial Matrix problems have many real-life applications, such as in supply chain management, scheduling and timetabling, and network routing. For example, a company may use Combinatorial Matrix techniques to optimize their production schedule or a transportation company may use them to determine the most efficient routes for their vehicles.

5. What are the challenges in solving Combinatorial Matrix problems?

One of the main challenges in solving Combinatorial Matrix problems is the exponential growth in the number of possible solutions as the size of the problem increases. This makes it difficult to find the optimal solution in a reasonable amount of time. Additionally, the complexity of the problem may increase if there are multiple constraints or if the problem involves a large number of elements.

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