Matrix Trace Calculator
The trace of a square matrix — the sum of its main-diagonal entries.
Related tools
All Matrices & vectors tools →Open Matrix Trace Calculator and you get an answer straight away, with no account to create. Its place is under Matrices & vectors; Matrix Calculator and Matrix Power Calculator (Aⁿ, n from −10 to 20) answer the questions closest to this one.
How to use it
- Open the tool — no signup or install needed.
- Enter your input or adjust the available options.
- Get your result instantly, then copy or download it.
Frequently asked questions
What is Matrix Trace Calculator?
The trace of a square matrix — the sum of its main-diagonal entries.
When would I actually use this?
Checking a decomposition done by hand, solving a linear system, and finding the eigenvalues that describe how a transformation stretches space.
What is the most common mistake?
Inverting a matrix to solve a system. Elimination or a factorisation is both faster and far more stable numerically; an explicit inverse amplifies rounding error, especially when the matrix is close to singular.
How is Matrix Trace Calculator different from Matrix Calculator?
They sit next to each other but answer different questions: Matrix Calculator is the one to open when you need it to add, subtract and multiply matrices, scale, transpose, and find the determinant and inverse of A. Pick whichever matches what you're starting from — both are free.
Is there a tool for the next step?
Matrix Power Calculator (Aⁿ, n from −10 to 20) is the closest one after this: Raise a 1×1 to 5×5 matrix to any power from −10 to 20 in exact fractions: A⁰ = I, binary exponentiation for positive n, the exact inverse for negative n, and an honest det(A) = 0 when no inverse exists.
What else is worth having open alongside it?
Matrix Rank Calculator and Adjacency matrix calculator — they come up in the same task often enough to be worth a second tab.
Where do the figures come from?
The decompositions follow their textbook definitions with partial pivoting where it applies. Results are exact for small integer matrices and subject to floating-point rounding otherwise.