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Matrix Calculator

Created by Anna Szczepanek, PhD
Reviewed by Rijk de Wet
Last updated: May 09, 2024


Welcome to Omni's matrix calculator! This humongous matrix solver serves as a hub to connect and coordinate all of Omni's calculators that involve various matrix operations in math. Here, you can get a bird's eye view of the wide matrix landscape:

  • Learn (or recall) what a matrix is in math;
  • What the most important matrix types are, and
  • Find a large collection of links to (almost) all of our matrix calculators.

Enjoy!

What is a matrix in math?

A matrix is a fancy name for an array of numbers. An example of a matrix would be

A=[1234]\small A = \begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix}

Matrices have rows and columns. In matrix AA above, the 1st row is [1 2][1\ 2] and the 2nd row is [3 4][3\ 4]. Its 1st column and 2nd columns read respectively

[13] and [24].\small \begin{bmatrix}1 \\ 3 \end{bmatrix} \text{ \scriptsize and } \begin{bmatrix}2 \\ 4 \end{bmatrix}.

The number of rows and columns gives the dimensions of the matrix. In our example, AA is a 2×22 \times 2 matrix with two rows by two columns.

Based on this dimension, we distinguish several types of matrices:

  • For a square matrix, the number of rows equals the number of columns.
  • A row matrix has only one row (hence the name) and several columns.
  • A column matrix has only one column and several rows.

❓ What type of matrix is AA which we defined above?

Moreover, we say that a matrix has cells in which we write the elements of our array. For example, the cell in the 2nd row and the 1st column of AA contains the value 33: the coordinates of this cell is (2,1)(2,1) and we would notate it as a2,1=3a_{2,1} = 3.

Matrices are a convenient way to store and manipulate more data than just an individual number. And so now the question arises: what operations can we perform on matrices? Can we for instance add or multiply them like ordinary numbers?

Well, almost. Since lots of numbers are involved simultaneously, calculations with matrices are more tricky than with individual numbers. For instance, if we want to add them, we first have to make sure that we can — only matrices with the same dimensions can be added. And for multiplication, the dimension requirement is even trickier.

How to use this matrix calculator?

This matrix calculator is very straightforward to use. Here's how:

  1. The first few fields at the top of our matrix calculator help you pick the matrix operation you need. They are sorted logically, but don't worry — the whole list is next in the following section.
  2. Choose the matrix size. In this matrix solver only the dimensions 2×22\times2 and 3×33\times3 are available. More sizes are available in the calculators dedicated to the selected matrix operation — the specific link is displayed at the bottom.
  3. Enter the coefficients of your matrix and enjoy the result that appears immediately.
  4. For more info on the matrix operation you've just performed, visit the dedicated tool.

Matrix operations in math

Here we list all the matrix math operations available in our matrix solver. To discover more about them, follow the links to the dedicated calculators.

Math operations that act on one matrix (unary matrix operations)

Math operations that act on two matrices (binary matrix operations)

What are the types of matrices in math?

The most popular special types of matrices are the following:

  • Diagonal;
  • Identity;
  • Triangular (upper or lower);
  • Symmetric;
  • Skew-symmetric;
  • Invertible;
  • Orthogonal;
  • Positive/negative definite; and
  • Positive/negative semi-definite.

Let's briefly define each of the matrix types that we mentioned above.

  • Diagonal matrix

    Square matrices that have non-zero coefficients only in the diagonal cells. It's very easy to compute its powers.

  • Identity matrix

    This is a diagonal matrix that has only ones on its diagonal and zeroes everywhere else. It's everyone's favorite matrix when it comes to matrix multiplication, because it leaves the other matrix unchanged — much like multiplying a number with 11!

  • Triangular matrix (upper or lower)

    A square matrix with non-zero coefficients on the diagonal and above the diagonal (if it's upper triangular) or below the diagonal (if lower triangular).

    Its determinant coincides with the product of the diagonal values. Often appears in matrix decompositions and numerical methods.

  • Symmetric matrix

    A square matrix that is symmetric with respect to its diagonal, i.e., aj,i=ai,ja_{j,i}=a_{i,j} for all i,j=1,,ni,j=1, \ldots, n. In words: the coefficient in ii-th row and jj-th column equals the coefficient of jj-th row and ii-th column. Such a matrix has real eigenvalues and an orthonormal eigenbasis.

  • Skew-symmetric (antisymmetric) matrix

    A square matrix whose entries satisfy aji=aija_{ji}=-a_{ij}. It follows that the diagonal elements are all equal to zero, because only ai,i=0a_{i,i}=0 can satisfy ai,i=ai,ia_{i,i} = -a_{i,i}. The trace of an antisymmetric matrix is therefore always equals zero.

  • Invertible matrix

    A square matrix that has an inverse, i.e., AA is invertible if there exists BB such that AB=BA=IAB = BA = I, where II is the identity matrix. The determinant of an invertible matrix is always non-zero.

  • Orthogonal matrix

    This is a square matrix whose columns constitute a set of orthonormal vectors (and its vectors form such a set as well). Equivalently we can say that a matrix is orthogonal if its transpose coincides with its inverse. The determinant of an orthogonal matrix is equal to 11 or 1-1.

  • Definite matrices

    All the matrices we consider below are symmetric (or Hermitian). xTx^{T} denotes the (Hermitian) transpose of xx (whether xx is a vector or a matrix).

    • Positive semi-definite matrix
      A matrix AA is positive semi-definite if xTAx0x^{{T}}Ax\geq 0 for every vector xx.

      Only positive semi-definite matrices have real and non-negative eigenvalues, and all positive semi-definite matrices have such eigenvalues.

    • Positive definite matrix
      A matrix AA is positive definite if xTAx>0x^{ {T}}Ax > 0 for every non-zero vector xx.

      Only positive definite matrices have real and positive eigenvalues, and all positive definite matrices have such eigenvalues.

    • Negative semi-definite matrix
      A matrix AA is negative semi-definite if xTAx0x^{ {T}}Ax\leq 0 for every vector xx.

      Negative semi-definite matrices are exactly those matrices whose eigenvalues are all real and non-positive.

    • Negative-definite matrix
      A matrix AA is negative definite if xTAx<0x^{ {T}}Ax < 0 for every non-zero vector xx.

      Negative definite matrices are exactly those matrices whose eigenvalues are all real and negative.

🙋 As we can see in the definitions above, a matrix cannot be simultaneously positive and negative definite, but it can be positive and negative semi-definite: it happens exactly when it's the zero matrix.

FAQ

How do I determine the type of matrix in math?

Certain types of matrices in maths are easy to detect, while other types are more intricate. Here are a few tips on how to detect matrix type:

  1. Start by just looking at the matrix structure: Is it diagonal? Symmetric? Triangular?
  2. Other types depend on deeper properties — check the eigenvalues, inverse, transpose, product of transpose and the initial matrix, etc.
  3. Use advanced math software, e.g., Omni's matrix solver, to help you detect the type of your matrix.

How many matrix operations are there in math?

No one really knows, but there's a lot of them. Scientists come up with new matrix operations which help them deal with different problems related to matrices and their applications in real life. Remember that matrix operations can act on one or more matrices, and they can return another matrix, multiple matrices, or a single number/vector, or a set of numbers/vectors or a polynomial, etc. The possibilities are endless!

What are the real life applications of a matrix?

Because matrices are a perfect way to deal with lots of numbers simultaneously, they are extremely useful in many domains of our modern, data-laden life. Real-life matrix applications include:

  • 3D graphics, e.g. in games;
  • Cryptography and data science;
  • Economics and econometrics;
  • Engineering and construction;
  • Electronics, and
  • Physics in general.
Anna Szczepanek, PhD
Select a matrix operation
Takes
One matrix
Returns
A number
Operation
Determinant
Select the matrix size
2 × 2
a₁a₂
b₁b₂
Matrix entries
a₁
a₂
b₁
b₂
Result
Enter the coefficients in the fields above.
Precision: 6 decimal places.
Learn more! 🎓
Visit our dedicated determinant calculator for a detailed explanation of this matrix operation.
More matrix sizes available there!
Check out 35 similar linear algebra calculators 🔢
Adjoint matrixCharacteristic polynomialCholesky decomposition… 32 more
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