Aren't all linear operators one-to-one and onto?

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Discussion Overview

The discussion centers around the properties of linear operators, specifically whether all linear operators are one-to-one (injective) and onto (surjective). Participants explore various examples and counterexamples, including differentiation and projection operators, and consider the implications of finite versus infinite dimensional vector spaces.

Discussion Character

  • Debate/contested
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant asserts that for any linear operator A from a vector space W to itself, the kernel is the zero vector and the range is all of W, suggesting it should be one-to-one due to linearity.
  • Another participant questions this by providing the example of the differentiation operator A = d/dx, arguing that it is not one-to-one when applied to certain functions like ln(x), as the outputs have different domains.
  • Some participants suggest that the properties of linear operators depend on the choice of the vector space W, particularly noting that if W includes all real functions, the operator may not be one-to-one.
  • Projection operators are cited as counterexamples to the claim that all linear operators are one-to-one, with participants discussing how they can map different inputs to the same output.
  • It is noted that a linear operator from a finite-dimensional space is one-to-one if and only if it is onto, with some participants acknowledging they had forgotten this condition.
  • One participant emphasizes that the finite dimensionality of W is crucial to the discussion, indicating that the properties may not hold in infinite-dimensional spaces.
  • The differentiation operator is highlighted as an important example, with a participant noting that it is not one-to-one since it maps constant functions to zero, although it is onto when considering smooth functions.
  • Integration is discussed as a related operator, with conditions that can make it one-to-one but not onto, further complicating the discussion of linear operators.
  • A later reply elaborates on the relationship between differentiation and integration, describing how they interact with subspaces of smooth functions.

Areas of Agreement / Disagreement

Participants express disagreement regarding the properties of linear operators, particularly in relation to finite versus infinite dimensions and specific examples like differentiation and projection operators. There is no consensus on whether all linear operators are one-to-one and onto.

Contextual Notes

The discussion highlights limitations related to the dimensionality of vector spaces and the specific definitions of linear operators. The examples provided illustrate the complexity of the topic and the need for careful consideration of conditions and assumptions.

pellman
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Let W be a vector space and let A be a linear operator W --> W. Isn't it the case that for any such A, the kernel of A is the zero vector and the range is all of W? And that it is one-to-one from linearity? I ask because an author I am reading goes through a lot of steps to show that a certain operator is one-to-one and onto yet I thought it was a given for any linear operator.
 
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What if ##A = \frac{d}{dx}##? One to One is bijective, right?
I don't believe that that operator is one to one, if you consider it acting on ln(x) in W. If you differentiate, you get 1/x, and the domain of those two functions are different (assuming no absolute value sign on ln(x)). ln(x): (0, inf) and 1/x: (-inf,0) U (0,inf). This is an injective mapping, which is not 1 to 1.
 
So I think it depends on W, is what I'm gathering. If W is a vector space that includes all real functions, then no, it's not 1 to 1. I'm not 100% sure, though. Someone will likely step in and correct me on this =/
 
pellman said:
Let W be a vector space and let A be a linear operator W --> W. Isn't it the case that for any such A, the kernel of A is the zero vector and the range is all of W? And that it is one-to-one from linearity? I ask because an author I am reading goes through a lot of steps to show that a certain operator is one-to-one and onto yet I thought it was a given for any linear operator.
T(a):=0 is linear: T(a+b)=0=T(a)+T(b); T(ca)=0=cT(a). Projection operators are not 1-1: P(a,b,c)=P(a,b,d) ; ## c \neq d ## For P(x,y,z):=P(x,y,0). Or, take a matrix with linearly-dependent rows/columns. EDITIt is not injective (independently of the choice of basis).
 
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Projection operators! Yes. thank you for that counter example.
 
pellman said:
Projection operators! Yes. thank you for that counter example.

A linear operator (from finite dimensional W to W) is 1-1 iff it is onto. That may be what you were thinking.
 
PeroK said:
A linear operator (from finite dimensional W to W) is 1-1 iff it is onto. That may be what you were thinking.
Yes. I just didn't remember that not all linear operators are one-to-one.
 
"finite dimensional W" is important here. It is not true if you drop that requirement.
 
the most important linear operator is D = differentiation, on the (infinite dimensional) linear space W of smooth functions. Then notice that D of a constant function is zero, so it is not 1-1. (it is onto however.)
 
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  • #10
Add integration with the requirement f(0)=0 and you have the example for 1-1 but not onto.
 
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  • #11
nice remark.

here we have the subspace Z of those smooth functions that equal zero at 0, and the complementary (real) line R of constant functions. then the space of all smooth functions is a direct product of Z and R, and D is 1-1 on Z and onto all smooth functions. the inverse of this restriction therefore, i.e. integration with f(0) = 0, is an injection from all smooth functions onto the subspace Z.

So differentiation D is essentially projection of all smooth functions onto the subspace Z, followed by an isomorphism from Z to all smooth functions. And the special integration above is essentially the inverse isomorphism of all smooth functions onto Z, followed by inclusion of Z into all smooth functions.

In general any linear surjection which has a kernel, restricts to an isomorphism on any subspace complementary to that kernel. Then the inmverse isomorphism is injective and not surjective.
 

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