Are all finite dimensional hilbert spaces isomorphic to spaces with Euclidean norms? ...
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Are all finite dimensional hilbert spaces isomorphic to spaces with Euclidean norms?
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Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)What is the difference between a Hilbert space and Euclidean space?Are two Hilbert spaces with the same algebraic dimension (their Hamel bases have the same cardinality) isomorphic?Any finite-dimensional subspace of a Hilbert space is closed: easier proof?Can Hilbert spaces generalize non-Euclidean geometry by having the sum of the angles of a triangle not be equal to pi?A basis of $V$ is linearly independent in $H$ where $V subset H$ are Hilbert spaces?Can we have infinite-dimensional separable Hilbert spaces?Hermitian and self-adjoint operators on infinite-dimensional Hilbert spacesInequivalent norms (given by different inner products) on infinite dimensional Hilbert space.Are Isomorphic Hilbert Spaces Still SolutionsWhat is the difference between a Hilbert space and Euclidean space?Hilbert Space: infinite or finite? - All real inner product spaces are Hilbert spaces?
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I have read that Hilbert spaces generalize Euclidean spaces to infinite dimensions.
This suggests to me that any finite dimensional Hilbert space is isomorphic to a space with the norm $||v||=sqrt {v_1^2 +...+v_n^2}$. Is this true? If not, then it seems it is wrong to say that Hilbert spaces generalize Euclidean spaces to infinite dimensions (i.e. they would be more general than that).
euclidean-geometry hilbert-spaces
$endgroup$
add a comment |
$begingroup$
I have read that Hilbert spaces generalize Euclidean spaces to infinite dimensions.
This suggests to me that any finite dimensional Hilbert space is isomorphic to a space with the norm $||v||=sqrt {v_1^2 +...+v_n^2}$. Is this true? If not, then it seems it is wrong to say that Hilbert spaces generalize Euclidean spaces to infinite dimensions (i.e. they would be more general than that).
euclidean-geometry hilbert-spaces
$endgroup$
$begingroup$
Are you familiar with Gram-Schmidt orthonormalization? Given an arbitrary basis of a finite dimensional inner product space, the procedure generates an orthonormal basis, i.e. one with respect to which the inner product is the usual Euclidean one (the dot product). Given such a basis, it should be clear how to get an isometry (the natural notion of isomorphism for inner product spaces) from any finite dimensional inner product space to $mathbb{R}^n$ equipped with the dot product.
$endgroup$
– jawheele
4 hours ago
add a comment |
$begingroup$
I have read that Hilbert spaces generalize Euclidean spaces to infinite dimensions.
This suggests to me that any finite dimensional Hilbert space is isomorphic to a space with the norm $||v||=sqrt {v_1^2 +...+v_n^2}$. Is this true? If not, then it seems it is wrong to say that Hilbert spaces generalize Euclidean spaces to infinite dimensions (i.e. they would be more general than that).
euclidean-geometry hilbert-spaces
$endgroup$
I have read that Hilbert spaces generalize Euclidean spaces to infinite dimensions.
This suggests to me that any finite dimensional Hilbert space is isomorphic to a space with the norm $||v||=sqrt {v_1^2 +...+v_n^2}$. Is this true? If not, then it seems it is wrong to say that Hilbert spaces generalize Euclidean spaces to infinite dimensions (i.e. they would be more general than that).
euclidean-geometry hilbert-spaces
euclidean-geometry hilbert-spaces
edited 1 hour ago
user56834
asked 5 hours ago
user56834user56834
3,36321253
3,36321253
$begingroup$
Are you familiar with Gram-Schmidt orthonormalization? Given an arbitrary basis of a finite dimensional inner product space, the procedure generates an orthonormal basis, i.e. one with respect to which the inner product is the usual Euclidean one (the dot product). Given such a basis, it should be clear how to get an isometry (the natural notion of isomorphism for inner product spaces) from any finite dimensional inner product space to $mathbb{R}^n$ equipped with the dot product.
$endgroup$
– jawheele
4 hours ago
add a comment |
$begingroup$
Are you familiar with Gram-Schmidt orthonormalization? Given an arbitrary basis of a finite dimensional inner product space, the procedure generates an orthonormal basis, i.e. one with respect to which the inner product is the usual Euclidean one (the dot product). Given such a basis, it should be clear how to get an isometry (the natural notion of isomorphism for inner product spaces) from any finite dimensional inner product space to $mathbb{R}^n$ equipped with the dot product.
$endgroup$
– jawheele
4 hours ago
$begingroup$
Are you familiar with Gram-Schmidt orthonormalization? Given an arbitrary basis of a finite dimensional inner product space, the procedure generates an orthonormal basis, i.e. one with respect to which the inner product is the usual Euclidean one (the dot product). Given such a basis, it should be clear how to get an isometry (the natural notion of isomorphism for inner product spaces) from any finite dimensional inner product space to $mathbb{R}^n$ equipped with the dot product.
$endgroup$
– jawheele
4 hours ago
$begingroup$
Are you familiar with Gram-Schmidt orthonormalization? Given an arbitrary basis of a finite dimensional inner product space, the procedure generates an orthonormal basis, i.e. one with respect to which the inner product is the usual Euclidean one (the dot product). Given such a basis, it should be clear how to get an isometry (the natural notion of isomorphism for inner product spaces) from any finite dimensional inner product space to $mathbb{R}^n$ equipped with the dot product.
$endgroup$
– jawheele
4 hours ago
add a comment |
3 Answers
3
active
oldest
votes
$begingroup$
If we are given an inner product on a finite dimensional space, there will always be a change of basis that turns the given inner product into the Euclidean one.
By definition the product $(cdot,cdot)$ can be represented as a symmetric positive-definite matrix $A$ such that $(x,y) = x^T A y$. Now by the spectral theorem (which you probably learnt in Linear Algebra) the matrix $A$ has an orthogonal basis of eigenvectors. In other words there is an orthogonal matrix $M$ such that $J = M^TAM$ is diagonal. That means $(x,y) = x^T M^TJ My = (Mx)^TJ(My)$.
Exercise: Use positive-definiteness to prove $J$ has only positive diagonal entries $lambda_1,lambda_2,ldots,lambda_n$.
It follows there is a further diagonal matrix $L$ such that $J=LIL = L^TIL$. That gives $$(x,y) = (Mx)^TL^TIL(My)= (LMx)^T(LMy)$$
Put another way, for each $x,y$ we have
$$big(,(LM)^{-1}x,(LM)^{-1}y, big) = x^T y$$
That means the given product is the Euclidean product with respect to the basis with transition matrix $LM$.
$endgroup$
add a comment |
$begingroup$
It is true in multiple ways. You have to distinguish between algebraic and tological isomorphy.
Let us consider vector spaces over $mathbb{R}$, the case for $mathbb{C}$ is analogous. First, realize, that any real vector space $V$ of dimension $n$ is (algebraically) isomorphic to $mathbb{R}^n$. To see the isomorphism, one can choose an arbitrary base
$$ b_1, ..., b_n in V$$
of $V$ and then define the mapping
$$ V ni v mapsto (text{coordinates of v with respect to $b_1,...,b_n$}) in mathbb{R}^n quad (dagger).$$
It is not hard to show, that this is a bijection as well as a vector space homomorphism.
So every finite dimensional real vector space V is algebraically isomorphic to $mathbb{R}^n$.
Morever, every Hilbert space of dimension $n$ is topologically isomorphic to $mathbb{R}^n$ (where the topology on $H$ is induced by the scalar product of $H$). To see this, realize that $(dagger)$ is a continuous bijection with continuous inverse and therefore a topological isomorphism.
$endgroup$
add a comment |
$begingroup$
Any Euclidean space is Hilbert space, so Hilbert spaces generalize Euclidean. But Euclidean space isn't just a finite dimensional linear space, it's a finite dimensional linear space with additional structure - either inner product, or norm that satisfies parallelogram law.
Such structure can be introduced on any finite dimensional space, so any finite dimensional space is isomorphic to some Euclidean as linear space.
$endgroup$
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
add a comment |
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3 Answers
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active
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3 Answers
3
active
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active
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active
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$begingroup$
If we are given an inner product on a finite dimensional space, there will always be a change of basis that turns the given inner product into the Euclidean one.
By definition the product $(cdot,cdot)$ can be represented as a symmetric positive-definite matrix $A$ such that $(x,y) = x^T A y$. Now by the spectral theorem (which you probably learnt in Linear Algebra) the matrix $A$ has an orthogonal basis of eigenvectors. In other words there is an orthogonal matrix $M$ such that $J = M^TAM$ is diagonal. That means $(x,y) = x^T M^TJ My = (Mx)^TJ(My)$.
Exercise: Use positive-definiteness to prove $J$ has only positive diagonal entries $lambda_1,lambda_2,ldots,lambda_n$.
It follows there is a further diagonal matrix $L$ such that $J=LIL = L^TIL$. That gives $$(x,y) = (Mx)^TL^TIL(My)= (LMx)^T(LMy)$$
Put another way, for each $x,y$ we have
$$big(,(LM)^{-1}x,(LM)^{-1}y, big) = x^T y$$
That means the given product is the Euclidean product with respect to the basis with transition matrix $LM$.
$endgroup$
add a comment |
$begingroup$
If we are given an inner product on a finite dimensional space, there will always be a change of basis that turns the given inner product into the Euclidean one.
By definition the product $(cdot,cdot)$ can be represented as a symmetric positive-definite matrix $A$ such that $(x,y) = x^T A y$. Now by the spectral theorem (which you probably learnt in Linear Algebra) the matrix $A$ has an orthogonal basis of eigenvectors. In other words there is an orthogonal matrix $M$ such that $J = M^TAM$ is diagonal. That means $(x,y) = x^T M^TJ My = (Mx)^TJ(My)$.
Exercise: Use positive-definiteness to prove $J$ has only positive diagonal entries $lambda_1,lambda_2,ldots,lambda_n$.
It follows there is a further diagonal matrix $L$ such that $J=LIL = L^TIL$. That gives $$(x,y) = (Mx)^TL^TIL(My)= (LMx)^T(LMy)$$
Put another way, for each $x,y$ we have
$$big(,(LM)^{-1}x,(LM)^{-1}y, big) = x^T y$$
That means the given product is the Euclidean product with respect to the basis with transition matrix $LM$.
$endgroup$
add a comment |
$begingroup$
If we are given an inner product on a finite dimensional space, there will always be a change of basis that turns the given inner product into the Euclidean one.
By definition the product $(cdot,cdot)$ can be represented as a symmetric positive-definite matrix $A$ such that $(x,y) = x^T A y$. Now by the spectral theorem (which you probably learnt in Linear Algebra) the matrix $A$ has an orthogonal basis of eigenvectors. In other words there is an orthogonal matrix $M$ such that $J = M^TAM$ is diagonal. That means $(x,y) = x^T M^TJ My = (Mx)^TJ(My)$.
Exercise: Use positive-definiteness to prove $J$ has only positive diagonal entries $lambda_1,lambda_2,ldots,lambda_n$.
It follows there is a further diagonal matrix $L$ such that $J=LIL = L^TIL$. That gives $$(x,y) = (Mx)^TL^TIL(My)= (LMx)^T(LMy)$$
Put another way, for each $x,y$ we have
$$big(,(LM)^{-1}x,(LM)^{-1}y, big) = x^T y$$
That means the given product is the Euclidean product with respect to the basis with transition matrix $LM$.
$endgroup$
If we are given an inner product on a finite dimensional space, there will always be a change of basis that turns the given inner product into the Euclidean one.
By definition the product $(cdot,cdot)$ can be represented as a symmetric positive-definite matrix $A$ such that $(x,y) = x^T A y$. Now by the spectral theorem (which you probably learnt in Linear Algebra) the matrix $A$ has an orthogonal basis of eigenvectors. In other words there is an orthogonal matrix $M$ such that $J = M^TAM$ is diagonal. That means $(x,y) = x^T M^TJ My = (Mx)^TJ(My)$.
Exercise: Use positive-definiteness to prove $J$ has only positive diagonal entries $lambda_1,lambda_2,ldots,lambda_n$.
It follows there is a further diagonal matrix $L$ such that $J=LIL = L^TIL$. That gives $$(x,y) = (Mx)^TL^TIL(My)= (LMx)^T(LMy)$$
Put another way, for each $x,y$ we have
$$big(,(LM)^{-1}x,(LM)^{-1}y, big) = x^T y$$
That means the given product is the Euclidean product with respect to the basis with transition matrix $LM$.
answered 5 hours ago
DaronDaron
5,20111126
5,20111126
add a comment |
add a comment |
$begingroup$
It is true in multiple ways. You have to distinguish between algebraic and tological isomorphy.
Let us consider vector spaces over $mathbb{R}$, the case for $mathbb{C}$ is analogous. First, realize, that any real vector space $V$ of dimension $n$ is (algebraically) isomorphic to $mathbb{R}^n$. To see the isomorphism, one can choose an arbitrary base
$$ b_1, ..., b_n in V$$
of $V$ and then define the mapping
$$ V ni v mapsto (text{coordinates of v with respect to $b_1,...,b_n$}) in mathbb{R}^n quad (dagger).$$
It is not hard to show, that this is a bijection as well as a vector space homomorphism.
So every finite dimensional real vector space V is algebraically isomorphic to $mathbb{R}^n$.
Morever, every Hilbert space of dimension $n$ is topologically isomorphic to $mathbb{R}^n$ (where the topology on $H$ is induced by the scalar product of $H$). To see this, realize that $(dagger)$ is a continuous bijection with continuous inverse and therefore a topological isomorphism.
$endgroup$
add a comment |
$begingroup$
It is true in multiple ways. You have to distinguish between algebraic and tological isomorphy.
Let us consider vector spaces over $mathbb{R}$, the case for $mathbb{C}$ is analogous. First, realize, that any real vector space $V$ of dimension $n$ is (algebraically) isomorphic to $mathbb{R}^n$. To see the isomorphism, one can choose an arbitrary base
$$ b_1, ..., b_n in V$$
of $V$ and then define the mapping
$$ V ni v mapsto (text{coordinates of v with respect to $b_1,...,b_n$}) in mathbb{R}^n quad (dagger).$$
It is not hard to show, that this is a bijection as well as a vector space homomorphism.
So every finite dimensional real vector space V is algebraically isomorphic to $mathbb{R}^n$.
Morever, every Hilbert space of dimension $n$ is topologically isomorphic to $mathbb{R}^n$ (where the topology on $H$ is induced by the scalar product of $H$). To see this, realize that $(dagger)$ is a continuous bijection with continuous inverse and therefore a topological isomorphism.
$endgroup$
add a comment |
$begingroup$
It is true in multiple ways. You have to distinguish between algebraic and tological isomorphy.
Let us consider vector spaces over $mathbb{R}$, the case for $mathbb{C}$ is analogous. First, realize, that any real vector space $V$ of dimension $n$ is (algebraically) isomorphic to $mathbb{R}^n$. To see the isomorphism, one can choose an arbitrary base
$$ b_1, ..., b_n in V$$
of $V$ and then define the mapping
$$ V ni v mapsto (text{coordinates of v with respect to $b_1,...,b_n$}) in mathbb{R}^n quad (dagger).$$
It is not hard to show, that this is a bijection as well as a vector space homomorphism.
So every finite dimensional real vector space V is algebraically isomorphic to $mathbb{R}^n$.
Morever, every Hilbert space of dimension $n$ is topologically isomorphic to $mathbb{R}^n$ (where the topology on $H$ is induced by the scalar product of $H$). To see this, realize that $(dagger)$ is a continuous bijection with continuous inverse and therefore a topological isomorphism.
$endgroup$
It is true in multiple ways. You have to distinguish between algebraic and tological isomorphy.
Let us consider vector spaces over $mathbb{R}$, the case for $mathbb{C}$ is analogous. First, realize, that any real vector space $V$ of dimension $n$ is (algebraically) isomorphic to $mathbb{R}^n$. To see the isomorphism, one can choose an arbitrary base
$$ b_1, ..., b_n in V$$
of $V$ and then define the mapping
$$ V ni v mapsto (text{coordinates of v with respect to $b_1,...,b_n$}) in mathbb{R}^n quad (dagger).$$
It is not hard to show, that this is a bijection as well as a vector space homomorphism.
So every finite dimensional real vector space V is algebraically isomorphic to $mathbb{R}^n$.
Morever, every Hilbert space of dimension $n$ is topologically isomorphic to $mathbb{R}^n$ (where the topology on $H$ is induced by the scalar product of $H$). To see this, realize that $(dagger)$ is a continuous bijection with continuous inverse and therefore a topological isomorphism.
answered 5 hours ago
Joker123Joker123
736313
736313
add a comment |
add a comment |
$begingroup$
Any Euclidean space is Hilbert space, so Hilbert spaces generalize Euclidean. But Euclidean space isn't just a finite dimensional linear space, it's a finite dimensional linear space with additional structure - either inner product, or norm that satisfies parallelogram law.
Such structure can be introduced on any finite dimensional space, so any finite dimensional space is isomorphic to some Euclidean as linear space.
$endgroup$
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
add a comment |
$begingroup$
Any Euclidean space is Hilbert space, so Hilbert spaces generalize Euclidean. But Euclidean space isn't just a finite dimensional linear space, it's a finite dimensional linear space with additional structure - either inner product, or norm that satisfies parallelogram law.
Such structure can be introduced on any finite dimensional space, so any finite dimensional space is isomorphic to some Euclidean as linear space.
$endgroup$
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
add a comment |
$begingroup$
Any Euclidean space is Hilbert space, so Hilbert spaces generalize Euclidean. But Euclidean space isn't just a finite dimensional linear space, it's a finite dimensional linear space with additional structure - either inner product, or norm that satisfies parallelogram law.
Such structure can be introduced on any finite dimensional space, so any finite dimensional space is isomorphic to some Euclidean as linear space.
$endgroup$
Any Euclidean space is Hilbert space, so Hilbert spaces generalize Euclidean. But Euclidean space isn't just a finite dimensional linear space, it's a finite dimensional linear space with additional structure - either inner product, or norm that satisfies parallelogram law.
Such structure can be introduced on any finite dimensional space, so any finite dimensional space is isomorphic to some Euclidean as linear space.
answered 5 hours ago
mihaildmihaild
1,30413
1,30413
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
add a comment |
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I'm not sure what linear spaces have to do with this? Do you mean this: en.wikipedia.org/wiki/Linear_space_(geometry)? It seems like a very different formalization than norm/metric/inner product based formalizations.
$endgroup$
– user56834
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
I meant usual vector spaces (they are also called linear spaces sometime). Did you mean something different in question text? ("any finite dimensional linear spaces")
$endgroup$
– mihaild
3 hours ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
$begingroup$
whoops that should have been "hilbert space". Typo, sorry!
$endgroup$
– user56834
1 hour ago
add a comment |
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$begingroup$
Are you familiar with Gram-Schmidt orthonormalization? Given an arbitrary basis of a finite dimensional inner product space, the procedure generates an orthonormal basis, i.e. one with respect to which the inner product is the usual Euclidean one (the dot product). Given such a basis, it should be clear how to get an isometry (the natural notion of isomorphism for inner product spaces) from any finite dimensional inner product space to $mathbb{R}^n$ equipped with the dot product.
$endgroup$
– jawheele
4 hours ago