Proving a fact about inner product spaces

In summary, proving a fact about inner product spaces involves demonstrating that certain properties hold for the inner product, such as symmetry, linearity, and positive definiteness. This can be done through rigorous mathematical proofs and examples, showcasing the usefulness and versatility of inner product spaces in various areas of mathematics, including linear algebra, functional analysis, and optimization. Additionally, understanding and utilizing the properties of inner product spaces is crucial in many applications, such as signal processing, data compression, and quantum mechanics.
  • #1
Mr Davis 97
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Homework Statement


Let ##V## be a vector space equipped with an inner product ##\langle \cdot, \cdot \rangle##. If ##\langle x,y \rangle = \langle x, z\rangle## for all ##x \in V##, then ##y=z##.

Homework Equations

The Attempt at a Solution


Here is my attempt. ##\langle x,y \rangle = \langle x, z\rangle## means that ##\langle x,y \rangle - \langle x, z\rangle = 0##, and so ##\langle x, y - z\rangle = 0##. This is as far as I've gotten. I don't see how to deduce that ##y - z = 0##.
 
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  • #2
Mr Davis 97 said:

Homework Statement


Let ##V## be a vector space equipped with an inner product ##\langle \cdot, \cdot \rangle##. If ##\langle x,y \rangle = \langle x, z\rangle## for all ##x \in V##, then ##y=z##.

Homework Equations

The Attempt at a Solution


Here is my attempt. ##\langle x,y \rangle = \langle x, z\rangle## means that ##\langle x,y \rangle - \langle x, z\rangle = 0##, and so ##\langle x, y - z\rangle = 0##. This is as far as I've gotten. I don't see how to deduce that ##y - z = 0##.
It's hidden in the term "inner product". In the sense used here, it is non-degenerated, which means exactly this: ##\langle x,y \rangle=0 \; \forall \; x \in V \Longrightarrow y=0##. This is true for the usual dot product like in real vector spaces. It is not automatically true for an arbitrary bilinear form. So in concrete cases, one has to check the properties of the "inner product" used.
 
  • #3
fresh_42 said:
It's hidden in the term "inner product". In the sense used here, it is non-degenerated, which means exactly this: ##\langle x,y \rangle=0 \; \forall \; x \in V \Longrightarrow y=0##. This is true for the usual dot product like in real vector spaces. It is not automatically true for an arbitrary bilinear form. So in concrete cases, one has to check the properties of the "inner product" used.
So are you saying that ##\langle x,y \rangle=0 \; \forall \; x \in V \Longrightarrow y=0## is a property of inner product spaces in general?
 
  • #4
Mr Davis 97 said:
So are you saying that ##\langle x,y \rangle=0 \; \forall \; x \in V \Longrightarrow y=0## is a property of inner product spaces in general?
No, I'm not saying this, because I'm used to deal with bilinear forms, that do not obey this rule and I don't see why they shouldn't be called inner product, too. So I am saying: look at your definition. This is even more important in the complex case, in which the product isn't symmetric anymore. (See https://en.wikipedia.org/wiki/Inner_product_space#Alternative_definitions.2C_notations_and_remarks.)

The convention however is, that inner products have to be positive definite, that is ##\langle x,y \rangle \geq 0## and ##\langle x,x \rangle=0 \Longleftrightarrow x=0##. With this convention we get in your case ##\forall_{x}\; \langle x,y-z \rangle=0 \Longrightarrow \langle y-z,y-z \rangle=0 \Longrightarrow y-z=0##.
 
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  • #5
fresh_42 said:
No, I'm not saying this, because I'm used to deal with bilinear forms, that do not obey this rule and I don't see why they shouldn't be called inner product, too. So I am saying: look at your definition. This is even more important in the complex case, in which the product isn't symmetric anymore. (See https://en.wikipedia.org/wiki/Inner_product_space#Alternative_definitions.2C_notations_and_remarks.)

The convention however is, that inner products have to be positive definite, that is ##\langle x,y \rangle \geq 0## and ##\langle x,x \rangle=0 \Longleftrightarrow x=0##. With this convention we get in your case ##\forall_{x}\; \langle x,y-z \rangle=0 \Longrightarrow \langle y-z,y-z \rangle=0 \Longrightarrow y-z=0##.
Could you explain the implication ##\forall_{x}\; \langle x,y-z \rangle=0 \Longrightarrow \langle y-z,y-z \rangle=0##?
 
  • #6
Mr Davis 97 said:
Could you explain the implication ##\forall_{x}\; \langle x,y-z \rangle=0 \Longrightarrow \langle y-z,y-z \rangle=0##?
Yes.
Mr Davis 97 said:
If ##\langle x,y \rangle = \langle x, z\rangle## for all ##x\in V##
Mr Davis 97 said:
... so ##\langle x, y - z\rangle = 0##.
... still for all ##x\in V##, so especially for ##x:=y-z##.
 
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  • #7
As fresh_42 said, it holds for all ## x## including ## x:=y-z##. There is an axiom of scalar product, that gives you the answer of what ##y-z## can be if its length is zero.
 
  • #8
fresh_42 said:
No, I'm not saying this, because I'm used to deal with bilinear forms, that do not obey this rule and I don't see why they shouldn't be called inner product, too. So I am saying: look at your definition. This is even more important in the complex case, in which the product isn't symmetric anymore. (See https://en.wikipedia.org/wiki/Inner_product_space#Alternative_definitions.2C_notations_and_remarks.)

The convention however is, that inner products have to be positive definite, that is ##\langle x,y \rangle \geq 0## and ##\langle x,x \rangle=0 \Longleftrightarrow x=0##. With this convention we get in your case ##\forall_{x}\; \langle x,y-z \rangle=0 \Longrightarrow \langle y-z,y-z \rangle=0 \Longrightarrow y-z=0##.

Don't you mean ##<x,x> \geq 0##?
 
  • #9
Math_QED said:
Don't you mean ##<x,x> \geq 0##?
Yes, of course. Copy and paste error.
 

1. What is an inner product space?

An inner product space is a mathematical concept used in linear algebra to define a notion of length and angle for vectors. It is a vector space equipped with an inner product, which is a mathematical operation that takes two vectors as inputs and produces a scalar as an output. The inner product satisfies certain properties, such as symmetry, linearity, and positive definiteness.

2. How do you prove a fact about inner product spaces?

To prove a fact about inner product spaces, you must use the properties of inner products and vector spaces. This involves using the definition of the inner product, as well as any relevant theorems or properties. You may also need to use techniques such as induction or contradiction to prove the fact. It is important to carefully follow the logic and steps of the proof to ensure its validity.

3. What are some common facts that can be proven about inner product spaces?

Some common facts that can be proven about inner product spaces include the Cauchy-Schwarz inequality, the Pythagorean theorem, and the Gram-Schmidt process. Other facts may involve properties of orthogonal or orthonormal vectors, projections, and distances between vectors. The specific facts that can be proven about inner product spaces will depend on the context and the properties of the vector space in question.

4. Can a fact about inner product spaces be proven using different methods?

Yes, a fact about inner product spaces can be proven using different methods. Some facts may have multiple proofs, each using a different approach or technique. This can provide a deeper understanding of the concept and its implications. Additionally, different methods may be more suitable for different contexts or may be more efficient in terms of time and complexity.

5. How are inner product spaces used in real-world applications?

Inner product spaces have various applications in fields such as physics, engineering, and computer science. They are used to model physical phenomena, analyze data, and solve optimization problems. For example, inner product spaces are used in signal processing to analyze and process signals, in quantum mechanics to model physical systems, and in machine learning to classify data.

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