
Are all matrices Diagonalizable?
Answer
217.8k+ views
Hint: In this question, we have to check whether all matrices are diagonalizable or not. So, a square matrix \[A\] is diagonalizable if it is similar to a diagonal matrix that is if there exists an invertible matrix \[P\] such that \[{P^{ - 1}}AP\] is a diagonal matrix.
Complete step-by-step solution: Matrices are the form of rows and columns that are arranged in a rectangular form. There are a lot of operations that can be performed in the matrices. For example, addition, subtraction, and multiplication. There are different types of matrices that are present. For example,
1) Row matrices.
2) Column matrices.
3) Singular matrices.
4) Symmetric and non-symmetric matrices.
Diagonalization matrices are square matrices that are having \[n \times n\] the form and it is written as,
\[A = PD{P^{ - 1}}\]
Or equivalently say that
\[D = {P^{ - 1}}AP\]
Here, P is a singular matrix, D is the diagonal matrix and \[{P^{ - 1}}\] is the inverse singular matrix.
Now, here we can see that the result is coming in the form of \[n \times n\] matrix which means that it is in the form of square matrices because the row and column are equal but as we can see that the matrices are of different types as well, for example, row-matrices which is the form of \[m \times n\] where \[m\] is the row and \[n\] is the column.
Hence, all matrices are not diagonalizable.
Note : The matrices are square as well as non-square matrices. There are some main properties that are followed by the matrices. The properties are commutative, associative, identity and inverse.
Complete step-by-step solution: Matrices are the form of rows and columns that are arranged in a rectangular form. There are a lot of operations that can be performed in the matrices. For example, addition, subtraction, and multiplication. There are different types of matrices that are present. For example,
1) Row matrices.
2) Column matrices.
3) Singular matrices.
4) Symmetric and non-symmetric matrices.
Diagonalization matrices are square matrices that are having \[n \times n\] the form and it is written as,
\[A = PD{P^{ - 1}}\]
Or equivalently say that
\[D = {P^{ - 1}}AP\]
Here, P is a singular matrix, D is the diagonal matrix and \[{P^{ - 1}}\] is the inverse singular matrix.
Now, here we can see that the result is coming in the form of \[n \times n\] matrix which means that it is in the form of square matrices because the row and column are equal but as we can see that the matrices are of different types as well, for example, row-matrices which is the form of \[m \times n\] where \[m\] is the row and \[n\] is the column.
Hence, all matrices are not diagonalizable.
Note : The matrices are square as well as non-square matrices. There are some main properties that are followed by the matrices. The properties are commutative, associative, identity and inverse.
Recently Updated Pages
Elastic Collision in Two Dimensions Explained Simply

Elastic Collisions in One Dimension Explained

Electric Field of Infinite Line Charge and Cylinders Explained

Electric Flux and Area Vector Explained Simply

Electric Field of a Charged Spherical Shell Explained

Electricity and Magnetism Explained: Key Concepts & Applications

Trending doubts
JEE Main 2026: Application Form Open, Exam Dates, Syllabus, Eligibility & Question Papers

Derivation of Equation of Trajectory Explained for Students

Hybridisation in Chemistry – Concept, Types & Applications

Understanding the Angle of Deviation in a Prism

Understanding Collisions: Types and Examples for Students

How to Convert a Galvanometer into an Ammeter or Voltmeter

Other Pages
JEE Advanced Marks vs Ranks 2025: Understanding Category-wise Qualifying Marks and Previous Year Cut-offs

Understanding Atomic Structure for Beginners

Ideal and Non-Ideal Solutions Explained for Class 12 Chemistry

Degree of Dissociation: Meaning, Formula, Calculation & Uses

Understanding Electromagnetic Waves and Their Importance

Understanding the Electric Field of a Uniformly Charged Ring

