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Why row replacement in a system of linear equations doesn't alter the solution set. The author demonstrates that every solution of the original system is also a solution of the row-replaced system, and vice versa, by using the fact that one row replacement operation can be undone. This concept is essential for understanding the properties of matrices and solving systems of linear equations.
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A couple of you have asked about a rigorous explanation of why this is true. Here’s how I would explain it.
Suppose we are given a system of linear equations in n variables and m equations, a 11 x 1 +... + a 1 nxn = b 1 a 21 x 1 +... + a 2 nxn = b 2
... am 1 x 1 +... + amnxn = bm
For shorthand, lets call this system of equations S. We want to show that it has the same solution as the system obtained by adding c times the ith row of S to the jth row of S. (i and j are arbitrary integers between 1 and m). We call this new, row-replaced system S′. There are two things to show. Every solution of S is a solution of S′^ AND every solution of S′^ is a solution of S. To start with, let t = (t 1 ,... , tn) be a solution of S. We want to show it is also a solution of S′. Note that
(1) ak 1 t 1 +... + akntn = bk
holds for every value of k, and so it is easy to see that t is a solution for every equation of S′^ (except possibly the jth one, ie. the modified one). The jth equation of S′^ is
c(ai 1 x 1 +... + ainxn) + aj 1 x 1 +... + ajnxn = cbi + bj.
However, if we substitute the t’s into the x’s, using (1), we get that
cbi + bj = cbi + bj ,
which is certainly true. Therefore, every solution of S is also a solution of S′. To show the converse (that is, to show that every solution of S′^ is a solution of S) we note the following fact. One can do a single row replacement operation to S′^ to re-obtain S (add −c times row i to row j). Thus we can perform the same argument as above (with the roles of S and S′^ reversed) and see that every solution of S′^ is also a solution of S.
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