triangle matrices regularly pop increase in straight algebra and also in the theory of straight systems. Therefore, that is worthwhile to examine their nature in detail, which we do below.

You are watching: Inverse of upper triangular matrix is upper triangular proof Definition A procession is reduced triangular if and also only if at any time i\$" style="background-position:0px -1295px;vertical-align:-5px"/>.

Remember the the main diagonal the a square matrix is the set of all the entries such the their row and column indices coincide, the is, the set" style="background-position:0px -388px;"/>

Therefore, in a reduced triangular matrix all the elements above the key diagonal (i.e., those whose pillar index is higher than the heat index ) are zero.

Definition A procession is upper triangular if and only if at any time

Thus, in an top triangular matrix all the aspects below the key diagonal (i.e., those whose obelisk index is much less than the heat index ) are zero.

## Examples

Some examples of triangle matrices follow.

Example take into consideration the matrix" style="background-position:0px -208px;"/>The entries on the main diagonal room " />The entries above the key diagonal are all zero: " />Therefore, the procession is lower triangular.

Example define the matrix" style="background-position:0px -39px;"/>The entries ~ above the main diagonal are " />The entries listed below the key diagonal space all zero: " />Therefore, the matrix is top triangular.

The complying with sections report a variety of properties satisfied by triangle matrices.

## The transpose of a triangular matrix is triangular

Suppose that is lower triangular, so the whenever i\$" style="background-position:0px -1295px;vertical-align:-5px"/>. By definition, the entries that the transpose satisfy" style="background-position:0px -426px;"/>Therefore, " style="background-position:0px -707px;vertical-align:-8px"/> anytime i\$" style="background-position:0px -1295px;vertical-align:-5px"/>. Hence, is top triangular.

Suppose that and are two reduced triangular matrices. We have to prove that" style="background-position:0px -492px;"/>whenever i\$" style="background-position:0px -1295px;vertical-align:-5px"/>. But, as soon as i\$" style="background-position:0px -1295px;vertical-align:-5px"/>, we have actually that " />where: in action we have actually used the truth that due to the fact that Proposition A triangular procession (upper or lower) is invertible if and only if all the entries top top its key diagonal space non-zero.

Let us first prove the "only if" part. Suppose a reduced triangular procession has a zero entry on the key diagonal on heat , that is," style="background-position:0px -736px;"/>Consider the sub-matrix created by the an initial rows that . The -th pillar of is zero due to the fact that , and all the columns to its right are zero since is reduced triangular. Then, contends most non-zero columns. As a consequence, it contends most linearly independent columns. Thus, its column rank is at most . Due to the fact that row rank and also column location coincide, this means that has at most linearly live independence rows. Together a consequence, the rows that are not linearly independent. Yet the rows of are additionally rows of . Therefore, the rows the room not linearly independent, is no full-rank and it is not invertible. To sum up, we have proved the if over there is a zero entry on the main diagonal the , then is not invertible. As a consequence, is invertible only if there room no zero entries top top the key diagonal. We now must prove the "if part" (if there space no zero entries on the key diagonal, then is invertible). We space going to prove that by contradiction. If is no invertible, then its rows space not linearly independent and one of them (suppose it is the -th row) can be created as a linear combination of the other rows: " />If there are various other rows listed below , through indices , then your coefficients in the linear mix must be zero. In particular, should be zero due to the fact that the -th row is the just one having a non-zero entry in the -th column and has actually a zero entrance in the -th column. Therefore, " />By the same token, need to be zero due to the fact that the -th heat is the only one in the linear combination having a non-zero entry in the -th column and also has actually a zero entry in the -th column. Thus, " />We repeat this reasoning until we deduce the " style="background-position:0px -170px;"/>As a consequence," style="background-position:0px -1px;"/>But this is impossible due to the fact that has a non-zero entry in the -th column and also " style="background-position:0px -466px;vertical-align:-5px"/> all have zero entries in that column. Thus, we have actually proved by contradiction the if every the diagonal entries that room non-zero, then no row of have the right to be written as a linear mix of the others. Together a consequence, the rows room linearly independent and is invertible. We have now showed the proposition for lower triangular matrices. The proof for top triangular matrices is comparable (replace columns with rows).

Proposition If a lower (upper) triangular matrix is invertible, climate its station is lower (upper) triangular. Furthermore, every entry on the key diagonal that is same to the mutual of the matching entry ~ above the main diagonal of , the is," style="background-position:0px -313px;"/>for .

Let be a lower triangular matrix. Signify by " style="background-position:0px -682px;vertical-align:-5px"/> the columns of . Through definition, the train station satisfies" style="background-position:0px -644px;"/>where is the identity matrix. The columns the space the vectors " style="background-position:0px -774px;vertical-align:-5px"/> of the standard basis. The -th vector that the standard basis has all entries equal to zero other than the -th, which is same to . By the outcomes presented in the lecture on matrix products and also linear combinations, the columns that satisfy" style="background-position:0px -557px;"/>for . This is a mechanism of equations that have the right to be composed as " />Note the the constants on the right-hand side are zero in all equations yet the -th. Since is invertible, the diagonal aspects (" style="background-position:0px -364px;vertical-align:-5px"/>) room non-zero. Because , the very first equation has solution . By plugging this solution right into the second equation, we acquire (because ). Then, we deal with the third equation, and so on, till we with the -th equation, whereby for the an initial time we discover a non-zero equipment . Thus, the entries that the column vector over the -th row room all zero. But is the -th tower of and the statement hold true for all . Together a consequence, every the entries that whose row index is less than the shaft index are zero. In various other words, is reduced triangular. The evidence for upper triangular matrices is analogous.

## Triangular matrices and also echelon form

This ar explores the connection in between triangular matrices and matrices in echelon form.

Remember the a matrix is claimed to be in heat echelon form if and only if 1) all its non-zero rows have a pivot (i.e., a non-zero entry such that all the entries come its left and below it room equal to zero) and also 2) every its zero rows are located listed below the non-zero rows. Intend is an invertible upper triangular matrix. Then, has actually no zero rows because all its diagonal line entries space non-zero. Furthermore, each heat of includes a diagonal line entry, which is a pivot because it is non-zero and also it has only zeros below it and also to that left. Therefore, is in heat echelon form.

This is a straightforward consequence of the vault proposition. We simply need to usage the truth that: 1) the transpose of an top triangular matrix is lower triangular; 2) the transpose of a procession in heat echelon form is in column echelon form.

Let it is in a square procession in heat echelon form. Scan the rows of from peak to bottom in search of pivots. You will uncover a pivot on each row till you gain to the zero rows. Each pivot you discover is below and also to the appropriate of the previous one. Therefore, the pivots are constantly to the appropriate of the key diagonal. Entries to the left of the pivots need to be zero. Therefore, a fortiori, entries to the left of the main diagonal space zero. Hence, is upper triangular.

This is an immediate an effect of the previous proposition. We just need to use the facts that the transpose the a matrix in heat echelon form is in shaft echelon form and the transpose the an top triangular procession is reduced triangular.