Dim null ST <= dim null S + dim null T

  • Thread starter Thread starter fishturtle1
  • Start date Start date
Click For Summary

Homework Help Overview

The discussion revolves around the relationship between the dimensions of the null spaces of two linear transformations, specifically examining the inequality involving the null space of the composition of these transformations. The subject area is linear algebra, focusing on concepts such as null spaces, linear transformations, and the rank-nullity theorem.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants explore the idea of finding a spanning set for the null space of the composition of two transformations. Questions arise regarding the inclusion of certain bases and the implications of the rank-nullity theorem. Some participants suggest alternative bases for the intersection of ranges and null spaces.

Discussion Status

The discussion includes various approaches to proving the relationship between the dimensions of the null spaces. Some participants have offered hints and insights that guide the exploration of the problem, while others are questioning assumptions and considering different interpretations of the problem setup.

Contextual Notes

There are indications of uncertainty regarding the mappings and the conditions under which certain bases can be used. Participants express the need for clarification on whether specific transformations map onto certain null spaces.

fishturtle1
Messages
393
Reaction score
82
Homework Statement
Suppose ##U## and ##V## are finite dimensional vector spaces and ##S \in \mathcal{L}(V, W)## and ##T \in \mathcal{L}(U, V)##. Prove that ##\dim \operatorname{null} ST \le \dim \operatorname{null} S + \dim \operatorname{null} T##.
Relevant Equations
------
For a linear map ##T \in \mathcal{L}(U, V)##, ##\text{null} T = \lbrace u \in U : Tu = 0 \rbrace##

Fundamental theorem of linear maps: ##\dim U = \dim \text{null} T + \dim T(U)##
--------
Proof: Since ##U, V## are finite dimensional, we have that ##\operatorname{null} S, \operatorname{null} T## are finite dimensional. Let ##v_1, \dots v_m## be a basis of ##\operatorname{null}S## and ##u_1, \dots, u_n## be a basis of ##\operatorname{null} T##. It is enough to show there are ##m + n## vectors that span ##\operatorname{null} ST##. Let ##x \in \operatorname{null}ST##. Then ##x \in \operatorname{null}T## or ##Tx \in \operatorname{null}S##. So ##u_1, \dots, u_n## is in our list of ##m+n## vectors.

If ##T## maps onto ##\operatorname{null}S##, then for each ##v_i## there is ##y_i \in U## such that ##Ty_i = v_i##. So ##Ty_1, \dots, Ty_m## spans ##\operatorname{null}S##. This implies ##\operatorname{span} \lbrace y_1, \dots, y_m, u_1, \dots, u_n \rbrace\supseteq \operatorname{null}ST##. But I don't think I can say ##T## maps onto ##\operatorname{null}S##. Can I have a hint, please?
 
Physics news on Phys.org
The approach of finding a spanning set of at most ##m+n## should work, and the ##u_i## should be included. Instead of taking these vectors ##y_i##, how about taking a basis for ##\text{Range}(T)\cap\text{Nul}(S)##?

Edit: To clarify, if ##Tx_1,\ldots, Tx_n## is such a basis, I mean to use the vectors ##x_1,\ldots, x_n.##
 
Last edited:
  • Like
Likes   Reactions: fishturtle1
Hint: ##\operatorname{null}(ST) = T^{-1}(\operatorname{null}(S))## and rank-nullity theorem.
 
  • Like
Likes   Reactions: fishturtle1
Thank you, I think I got it using what you said:

Proof: Since ##U, V## are finite dimensional, we have ##\operatorname{null} S## and ##\operatorname{null}T## are finite dimensional. Let ##u_1, \dots, u_n## be a basis for ##\operatorname{null} T## and ##Tx_1, \dots, Tx_k## be a basis for ##\operatorname{Range}(T) \cap \operatorname{null} S##. We note that ##k \le \dim \operatorname{null} S##. We'll show the statement ##\operatorname{span} \lbrace u_1, \dots, u_n, x_1, \dots, x_k \rbrace = \operatorname{null} ST## is true.

##(\subseteq)## Let ##a_1u_1 + \dots a_nu_n + b_1x_1 + \dots + b_kx_k \in \operatorname{span} \lbrace u_1, \dots, u_n, x_1, \dots, x_k \rbrace##. Then

##
\begin{align*}
ST(a_1u_1 + \dots a_nu_n + b_1x_1 + \dots + b_kx_k) &= S(a_1T(u_1) + \dots + a_n T(u_n) + b_1T(x_1) + \dots + b_kT(x_k)) \\
& = S(0 + \dots + 0 + b_1T(x_1) + \dots + b_kT(x_k)) \\
&= S(b_1T(x_1) + \dots + b_kT(x_k)) \\
&= 0
\end{align*}##
This shows ##\operatorname{span} \lbrace u_1, \dots, u_n, x_1, \dots, x_k \rbrace \subseteq \operatorname{null} ST##.

##(\supseteq)## If ##x \in \operatorname{null}ST##, then ##x \in \operatorname{null}T## or ##Tx \in \operatorname{null} S##. I.e., ##x \in \operatorname{span} \lbrace u_1, \dots, u_n \rbrace##. Otherwise, ##Tx \in \operatorname{Range}(T) \cap \operatorname{null}S## and since ##x_1, \dots, x_k## is linearly independent, we have ##x \in \operatorname{span} \lbrace x_1, \dots, x_k \rbrace##. This shows ##\operatorname{span} \lbrace u_1, \dots, u_n, x_1, \dots, x_k \rbrace \supseteq \operatorname{null} ST##.

We can conclude ##\dim \operatorname{null}ST \le n + k \le n + m = \dim \operatorname{null}T + \dim \operatorname{null}S##. []
 
  • Like
Likes   Reactions: Infrared
I see using post #3:

Proof: First we show ##\operatorname{null}(ST) = T^{-1}(\operatorname{null}(S))##.

##(\subseteq)## Let ##x \in \operatorname{null}(ST)##. Then ##S(Tx) = 0## which means ##Tx \in \operatorname{null}(S)## i.e. ##x \in T^{-1}(\operatorname{null}(S))##.

##(\supseteq)## Let ##x \in T^{-1}(\operatorname{null}(S))##. Then ##Tx \in \operatorname{null}(S)## so ##S(Tx) = 0## i.e. ##x \in \operatorname{null}(ST)##.

We can conclude ##\operatorname{null}(ST) = T^{-1}(\operatorname{null}(S))##.

By rank nullity theorem: ##\dim \operatorname{null}(ST) = \dim T^{-1}(\operatorname{null}(S)) = \dim \operatorname{null}(T) + \dim T(T^{-1}(\operatorname{null}(S))) \le \operatorname{null}(T) + \operatorname{null}(S)##. []
 
  • Like
Likes   Reactions: member 587159
Or you can consider that ##KerT \subset KerST##. How much larger can it be?
 

Similar threads

Replies
8
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 1 ·
Replies
1
Views
3K
Replies
34
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K
Replies
10
Views
3K
  • · Replies 23 ·
Replies
23
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 3 ·
Replies
3
Views
4K