Projection-valued measure

Mathematical operator-value measure of interest in quantum mechanics and functional analysis

In mathematics, particularly in functional analysis, a projection-valued measure (or spectral measure) is a function defined on certain subsets of a fixed set and whose values are self-adjoint projections on a fixed Hilbert space.[1] A projection-valued measure (PVM) is formally similar to a real-valued measure, except that its values are self-adjoint projections rather than real numbers. As in the case of ordinary measures, it is possible to integrate complex-valued functions with respect to a PVM; the result of such an integration is a linear operator on the given Hilbert space.

Projection-valued measures are used to express results in spectral theory, such as the important spectral theorem for self-adjoint operators, in which case the PVM is sometimes referred to as the spectral measure. The Borel functional calculus for self-adjoint operators is constructed using integrals with respect to PVMs. In quantum mechanics, PVMs are the mathematical description of projective measurements.[clarification needed] They are generalized by positive operator valued measures (POVMs) in the same sense that a mixed state or density matrix generalizes the notion of a pure state.

Definition

Let H {\displaystyle H} denote a separable complex Hilbert space and ( X , M ) {\displaystyle (X,M)} a measurable space consisting of a set X {\displaystyle X} and a Borel σ-algebra M {\displaystyle M} on X {\displaystyle X} . A projection-valued measure π {\displaystyle \pi } is a map from M {\displaystyle M} to the set of bounded self-adjoint operators on H {\displaystyle H} satisfying the following properties:[2][3]

  • π ( E ) {\displaystyle \pi (E)} is an orthogonal projection for all E M . {\displaystyle E\in M.}
  • π ( ) = 0 {\displaystyle \pi (\emptyset )=0} and π ( X ) = I {\displaystyle \pi (X)=I} , where {\displaystyle \emptyset } is the empty set and I {\displaystyle I} the identity operator.
  • If E 1 , E 2 , E 3 , {\displaystyle E_{1},E_{2},E_{3},\dotsc } in M {\displaystyle M} are disjoint, then for all v H {\displaystyle v\in H} ,
π ( j = 1 E j ) v = j = 1 π ( E j ) v . {\displaystyle \pi \left(\bigcup _{j=1}^{\infty }E_{j}\right)v=\sum _{j=1}^{\infty }\pi (E_{j})v.}
  • π ( E 1 E 2 ) = π ( E 1 ) π ( E 2 ) {\displaystyle \pi (E_{1}\cap E_{2})=\pi (E_{1})\pi (E_{2})} for all E 1 , E 2 M . {\displaystyle E_{1},E_{2}\in M.}

The second and fourth property show that if E 1 {\displaystyle E_{1}} and E 2 {\displaystyle E_{2}} are disjoint, i.e., E 1 E 2 = {\displaystyle E_{1}\cap E_{2}=\emptyset } , the images π ( E 1 ) {\displaystyle \pi (E_{1})} and π ( E 2 ) {\displaystyle \pi (E_{2})} are orthogonal to each other.

Let V E = im ( π ( E ) ) {\displaystyle V_{E}=\operatorname {im} (\pi (E))} and its orthogonal complement V E = ker ( π ( E ) ) {\displaystyle V_{E}^{\perp }=\ker(\pi (E))} denote the image and kernel, respectively, of π ( E ) {\displaystyle \pi (E)} . If V E {\displaystyle V_{E}} is a closed subspace of H {\displaystyle H} then H {\displaystyle H} can be wrtitten as the orthogonal decomposition H = V E V E {\displaystyle H=V_{E}\oplus V_{E}^{\perp }} and π ( E ) = I E {\displaystyle \pi (E)=I_{E}} is the unique identity operator on V E {\displaystyle V_{E}} satisfying all four properties.[4][5]

For every ξ , η H {\displaystyle \xi ,\eta \in H} and E M {\displaystyle E\in M} the projection-valued measure forms a complex-valued measure on H {\displaystyle H} defined as

μ ξ , η ( E ) := π ( E ) ξ η {\displaystyle \mu _{\xi ,\eta }(E):=\langle \pi (E)\xi \mid \eta \rangle }

with total variation at most ξ η {\displaystyle \|\xi \|\|\eta \|} .[6] It reduces to a real-valued measure when

μ ξ ( E ) := π ( E ) ξ ξ {\displaystyle \mu _{\xi }(E):=\langle \pi (E)\xi \mid \xi \rangle }

and a probability measure when ξ {\displaystyle \xi } is a unit vector.

Example Let ( X , M , μ ) {\displaystyle (X,M,\mu )} be a σ-finite measure space and, for all E M {\displaystyle E\in M} , let

π ( E ) : L 2 ( X ) L 2 ( X ) {\displaystyle \pi (E):L^{2}(X)\to L^{2}(X)}

be defined as

ψ π ( E ) ψ = 1 E ψ , {\displaystyle \psi \mapsto \pi (E)\psi =1_{E}\psi ,}

i.e., as multiplication by the indicator function 1 E {\displaystyle 1_{E}} on L2(X). Then π ( E ) = 1 E {\displaystyle \pi (E)=1_{E}} defines a projection-valued measure.[6] For example, if X = R {\displaystyle X=\mathbb {R} } , E = ( 0 , 1 ) {\displaystyle E=(0,1)} , and ϕ , ψ L 2 ( R ) {\displaystyle \phi ,\psi \in L^{2}(\mathbb {R} )} there is then the associated complex measure μ ϕ , ψ {\displaystyle \mu _{\phi ,\psi }} which takes a measurable function f : R R {\displaystyle f:\mathbb {R} \to \mathbb {R} } and gives the integral

E f d μ ϕ , ψ = 0 1 f ( x ) ψ ( x ) ϕ ¯ ( x ) d x {\displaystyle \int _{E}f\,d\mu _{\phi ,\psi }=\int _{0}^{1}f(x)\psi (x){\overline {\phi }}(x)\,dx}

Extensions of projection-valued measures

If π is a projection-valued measure on a measurable space (X, M), then the map

χ E π ( E ) {\displaystyle \chi _{E}\mapsto \pi (E)}

extends to a linear map on the vector space of step functions on X. In fact, it is easy to check that this map is a ring homomorphism. This map extends in a canonical way to all bounded complex-valued measurable functions on X, and we have the following.

Theorem — For any bounded Borel function f {\displaystyle f} on X {\displaystyle X} , there exists a unique bounded operator T : H H {\displaystyle T:H\to H} such that [7][8]

T ξ ξ = X f ( λ ) d μ ξ ( λ ) , ξ H . {\displaystyle \langle T\xi \mid \xi \rangle =\int _{X}f(\lambda )\,d\mu _{\xi }(\lambda ),\quad \forall \xi \in H.}

where μ ξ {\displaystyle \mu _{\xi }} is a finite Borel measure given by

μ ξ ( E ) := π ( E ) ξ ξ , E M . {\displaystyle \mu _{\xi }(E):=\langle \pi (E)\xi \mid \xi \rangle ,\quad \forall E\in M.}

Hence, ( X , M , μ ) {\displaystyle (X,M,\mu )} is a finite measure space.

The theorem is also correct for unbounded measurable functions f {\displaystyle f} but then T {\displaystyle T} will be an unbounded linear operator on the Hilbert space H {\displaystyle H} .

This allows to define the Borel functional calculus for such operators and then pass to measurable functions via the Riesz–Markov–Kakutani representation theorem. That is, if g : R C {\displaystyle g:\mathbb {R} \to \mathbb {C} } is a measurable function, then a unique measure exists such that

g ( T ) := R g ( x ) d π ( x ) . {\displaystyle g(T):=\int _{\mathbb {R} }g(x)\,d\pi (x).}

Spectral theorem

Let H {\displaystyle H} be a separable complex Hilbert space, A : H H {\displaystyle A:H\to H} be a bounded self-adjoint operator and σ ( A ) {\displaystyle \sigma (A)} the spectrum of A {\displaystyle A} . Then the spectral theorem says that there exists a unique projection-valued measure π A {\displaystyle \pi ^{A}} , defined on a Borel subset E σ ( A ) {\displaystyle E\subset \sigma (A)} , such that[9]

A = σ ( A ) λ d π A ( λ ) , {\displaystyle A=\int _{\sigma (A)}\lambda \,d\pi ^{A}(\lambda ),}

where the integral extends to an unbounded function λ {\displaystyle \lambda } when the spectrum of A {\displaystyle A} is unbounded.[10]

Direct integrals

First we provide a general example of projection-valued measure based on direct integrals. Suppose (X, M, μ) is a measure space and let {Hx}xX be a μ-measurable family of separable Hilbert spaces. For every EM, let π(E) be the operator of multiplication by 1E on the Hilbert space

X H x   d μ ( x ) . {\displaystyle \int _{X}^{\oplus }H_{x}\ d\mu (x).}

Then π is a projection-valued measure on (X, M).

Suppose π, ρ are projection-valued measures on (X, M) with values in the projections of H, K. π, ρ are unitarily equivalent if and only if there is a unitary operator U:HK such that

π ( E ) = U ρ ( E ) U {\displaystyle \pi (E)=U^{*}\rho (E)U\quad }

for every EM.

Theorem. If (X, M) is a standard Borel space, then for every projection-valued measure π on (X, M) taking values in the projections of a separable Hilbert space, there is a Borel measure μ and a μ-measurable family of Hilbert spaces {Hx}xX , such that π is unitarily equivalent to multiplication by 1E on the Hilbert space

X H x   d μ ( x ) . {\displaystyle \int _{X}^{\oplus }H_{x}\ d\mu (x).}

The measure class[clarification needed] of μ and the measure equivalence class of the multiplicity function x → dim Hx completely characterize the projection-valued measure up to unitary equivalence.

A projection-valued measure π is homogeneous of multiplicity n if and only if the multiplicity function has constant value n. Clearly,

Theorem. Any projection-valued measure π taking values in the projections of a separable Hilbert space is an orthogonal direct sum of homogeneous projection-valued measures:

π = 1 n ω ( π H n ) {\displaystyle \pi =\bigoplus _{1\leq n\leq \omega }(\pi \mid H_{n})}

where

H n = X n H x   d ( μ X n ) ( x ) {\displaystyle H_{n}=\int _{X_{n}}^{\oplus }H_{x}\ d(\mu \mid X_{n})(x)}

and

X n = { x X : dim H x = n } . {\displaystyle X_{n}=\{x\in X:\dim H_{x}=n\}.}

Application in quantum mechanics

In quantum mechanics, given a projection valued measure of a measurable space X to the space of continuous endomorphisms upon a Hilbert space H,

  • the projective space of the Hilbert space H is interpreted as the set of possible states Φ of a quantum system,
  • the measurable space X is the value space for some quantum property of the system (an "observable"),
  • the projection-valued measure π expresses the probability that the observable takes on various values.

A common choice for X is the real line, but it may also be

  • R3 (for position or momentum in three dimensions ),
  • a discrete set (for angular momentum, energy of a bound state, etc.),
  • the 2-point set "true" and "false" for the truth-value of an arbitrary proposition about Φ.

Let E be a measurable subset of the measurable space X and Φ a normalized vector-state in H, so that its Hilbert norm is unitary, ||Φ|| = 1. The probability that the observable takes its value in the subset E, given the system in state Φ, is

P π ( φ ) ( E ) = φ π ( E ) ( φ ) = φ | π ( E ) | φ , {\displaystyle P_{\pi }(\varphi )(E)=\langle \varphi \mid \pi (E)(\varphi )\rangle =\langle \varphi |\pi (E)|\varphi \rangle ,}

where the latter notation is preferred in physics.

We can parse this in two ways.

First, for each fixed E, the projection π(E) is a self-adjoint operator on H whose 1-eigenspace is the states Φ for which the value of the observable always lies in E, and whose 0-eigenspace is the states Φ for which the value of the observable never lies in E.

Second, for each fixed normalized vector state ψ {\displaystyle \psi } , the association

P π ( ψ ) : E ψ π ( E ) ψ {\displaystyle P_{\pi }(\psi ):E\mapsto \langle \psi \mid \pi (E)\psi \rangle }

is a probability measure on X making the values of the observable into a random variable.

A measurement that can be performed by a projection-valued measure π is called a projective measurement.

If X is the real number line, there exists, associated to π, a Hermitian operator A defined on H by

A ( φ ) = R λ d π ( λ ) ( φ ) , {\displaystyle A(\varphi )=\int _{\mathbf {R} }\lambda \,d\pi (\lambda )(\varphi ),}

which takes the more readable form

A ( φ ) = i λ i π ( λ i ) ( φ ) {\displaystyle A(\varphi )=\sum _{i}\lambda _{i}\pi ({\lambda _{i}})(\varphi )}

if the support of π is a discrete subset of R.

The above operator A is called the observable associated with the spectral measure.

Generalizations

The idea of a projection-valued measure is generalized by the positive operator-valued measure (POVM), where the need for the orthogonality implied by projection operators is replaced by the idea of a set of operators that are a non-orthogonal partition of unity[clarification needed]. This generalization is motivated by applications to quantum information theory.

See also

Notes

  1. ^ Conway 2000, p. 41.
  2. ^ Hall 2013, p. 138.
  3. ^ Reed & Simon 1980, p. 234.
  4. ^ Rudin 1991, p. 308.
  5. ^ Hall 2013, p. 541.
  6. ^ a b Conway 2000, p. 42.
  7. ^ Kowalski, Emmanuel (2009), Spectral theory in Hilbert spaces (PDF), ETH Zürich lecture notes, p. 50
  8. ^ Reed & Simon 1980, p. 227,235.
  9. ^ Reed & Simon 1980, p. 235.
  10. ^ Hall 2013, p. 205.

References

  • Conway, John B. (2000). A course in operator theory. Providence (R.I.): American mathematical society. ISBN 978-0-8218-2065-0.
  • Hall, Brian C. (2013). Quantum Theory for Mathematicians. New York: Springer Science & Business Media. ISBN 978-1-4614-7116-5.
  • Mackey, G. W., The Theory of Unitary Group Representations, The University of Chicago Press, 1976
  • Moretti, V. (2017), Spectral Theory and Quantum Mechanics Mathematical Foundations of Quantum Theories, Symmetries and Introduction to the Algebraic Formulation, vol. 110, Springer, Bibcode:2017stqm.book.....M, ISBN 978-3-319-70705-1
  • Narici, Lawrence; Beckenstein, Edward (2011). Topological Vector Spaces. Pure and applied mathematics (Second ed.). Boca Raton, FL: CRC Press. ISBN 978-1584888666. OCLC 144216834.
  • Reed, M.; Simon, B. (1980). Methods of Modern Mathematical Physics: Vol 1: Functional analysis. Academic Press. ISBN 978-0-12-585050-6.
  • Rudin, Walter (1991). Functional Analysis. Boston, Mass.: McGraw-Hill Science, Engineering & Mathematics. ISBN 978-0-07-054236-5.
  • Schaefer, Helmut H.; Wolff, Manfred P. (1999). Topological Vector Spaces. GTM. Vol. 8 (Second ed.). New York, NY: Springer New York Imprint Springer. ISBN 978-1-4612-7155-0. OCLC 840278135.
  • G. Teschl, Mathematical Methods in Quantum Mechanics with Applications to Schrödinger Operators, https://www.mat.univie.ac.at/~gerald/ftp/book-schroe/, American Mathematical Society, 2009.
  • Trèves, François (2006) [1967]. Topological Vector Spaces, Distributions and Kernels. Mineola, N.Y.: Dover Publications. ISBN 978-0-486-45352-1. OCLC 853623322.
  • Varadarajan, V. S., Geometry of Quantum Theory V2, Springer Verlag, 1970.
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