How can a rank 1 complex matrix be written as a product of two matrices?

  • Context: Undergrad 
  • Thread starter Thread starter Euge
  • Start date Start date
Click For Summary
SUMMARY

A complex matrix \( M \) of rank 1 can be expressed as the outer product of two vectors, specifically \( M = \mathbf{uv}^T \), where \( \mathbf{u} \) is an \( m \times 1 \) column vector and \( \mathbf{v} \) is an \( n \times 1 \) column vector. This representation is fundamental in linear algebra, illustrating how low-rank matrices can be decomposed into simpler components. The discussion highlights the importance of understanding matrix rank and the properties of outer products in matrix theory.

PREREQUISITES
  • Understanding of matrix rank and its implications
  • Familiarity with outer products in linear algebra
  • Basic knowledge of complex matrices
  • Proficiency in matrix notation and operations
NEXT STEPS
  • Study the properties of matrix rank in detail
  • Explore the concept of outer products and their applications
  • Learn about matrix decompositions, specifically Singular Value Decomposition (SVD)
  • Investigate the role of rank in linear transformations and their geometric interpretations
USEFUL FOR

Mathematicians, students studying linear algebra, and anyone interested in matrix theory and its applications in various fields such as data science and machine learning.

Euge
Gold Member
MHB
POTW Director
Messages
2,072
Reaction score
245
Here is this week's POTW:

-----
If $M$ is a complex $m \times n$ matrix of rank $1$, show that $M$ can be written as $\bf{uv^T}$ where $\bf{u}$ is an $m\times 1$ matrix and $\bf{v}$ is an $n\times 1$ matrix.

-----

Remember to read the https://mathhelpboards.com/showthread.php?772-Problem-of-the-Week-%28POTW%29-Procedure-and-Guidelines to find out how to https://mathhelpboards.com/forms.php?do=form&fid=2!
 
Physics news on Phys.org
Congratulations to Opalg and castor28 for their correct solutions. Here is castor28's solution.
As the column space of $M$ has dimension $1$, it is spanned by a single vector $\mathbf{u}$. Therefore, for all $i$, the column $i$ of $M$ can be written as $\mathbf{u}v_i$ for some scalar $v_i$.

This shows that $M=\mathbf{uv^T}$, where $\mathbf{v^T}$ is the column vector $(v_i)$.
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
5K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
1
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
Replies
1
Views
4K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K