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Preparation variance and spread of an assigned sharp observable
The reading of preparation variance and preparation spread for an assigned sharp observable of the framework: the variance and standard deviation of the outcome law of a preparation, their units, their existence hypotheses through the moment theorem, the centered-vector form for pure preparations of domain vectors, and the resulting definition of the product of two spreads. The item fixes terminology and readings of P1 and P2 only; it asserts no apparatus resolution, no measurement error, no disturbance, no joint measurement, no dynamics and no empirical result, and it does not claim that any preparation has finite moments automatically.
Definition
(a) Setting. Adopt the state and composition postulate P1 and the observable and probability postulate P2 in the readings of The state space of the framework: preparations, pure rays and density operators and Assigned sharp observables and the outcome law of the framework (State and composition postulate P1: Hilbert spaces, preparations and composite systems, Observable and probability postulate P2: self-adjoint observables, spectral probability and finite unsharp outcomes), and assume the Axiom of Countable Choice and the Axiom of Choice (The Axiom of Countable Choice (), The Axiom of Choice). Let be an assigned sharp observable with declared unit and outcome law in a preparation , in the sense of Assigned sharp observables and the outcome law of the framework clause (b).
(b) Preparation variance. When the mean and the second moment of the outcome law are finite, the preparation variance of in is read in the square of the declared unit, and the preparation spread is , read in the unit . When either quantity is not finite the variance and the spread of the pair in are not defined; the definition does not extend them by .
(c) Values and hypotheses. The variance and its hypotheses are exactly those of the moment theorem: for a pure preparation of a unit vector the spread is , equal to when ; for a preparation the identities and existence criteria are those of Mean, second moment and variance of an assigned observable in a preparation and Mean, second moment and variance of the scalar spectral law. In particular, for an orthonormal density expansion , the mean is finite exactly when by Mean, second moment and variance of the scalar spectral law clause (d); zero-weight indices are omitted before evaluating their component integrals. For a pure unit vector the corresponding criterion is membership in by clause (b). Componentwise domain membership alone does not imply convergence of the weighted sum, and finite moments are not automatic.
(d) Products of spreads. For two assigned sharp observables and in a common preparation in which both spreads are defined, the product is a nonnegative real number read in the product unit ; for a pure preparation of a unit vector in it is with the real means and .
(e) Reading and scope. The spread is a property of the pair (preparation, assigned observable): it is the standard deviation of the outcome law that P2 assigns. It is not an apparatus resolution, not a measurement error and not a disturbance of the preparation; those are further objects that require a declared instrument or apparatus model and are not introduced here. Clause (b) makes no claim that a preparation realizes a specific laboratory state, that a laboratory procedure measures with resolution , or that the spread is observed in any experiment; the identification of an apparatus with the pair is a tested identification under the preparation and apparatus postulate P7. Dimensions, SI unit conventions and quantity types of the framework fixes the units in which the displays are read.
Remarks
- Vanishing spread and eigenstates. For a pure preparation of a unit vector , clause (c) shows exactly when , that is exactly when is an eigenvector of ; this is the framework's reading of the textbook statement that the uncertainty of an observable vanishes in an eigenstate. The identification of a laboratory state with such a preparation is again a tested identification, not a consequence of the definition.
- The product is not a joint distribution. Clause (d) forms a product of two spreads of the same preparation; it does not introduce a joint outcome law of and , and the product can be defined even when no joint sharp observable of the pair exists. Joint sharp observables are a separate notion with its own criterion.
Depends on
The Axiom of Choice
The Axiom of Countable Choice ()
Dimensions, SI unit conventions and quantity types of the framework
Assigned sharp observables and the outcome law of the framework
The state space of the framework: preparations, pure rays and density operators
The state space: density operators, pure and mixed states, and purity
Mean, second moment and variance of the scalar spectral law
Observable and probability postulate P2: self-adjoint observables, spectral probability and finite unsharp outcomes
State and composition postulate P1: Hilbert spaces, preparations and composite systems
Mean, second moment and variance of an assigned observable in a preparation
Dependency tree · 2 levels
Sources
- D. Tong, Quantum Mechanics (author-hosted lecture set), Section 3.4.1, printed pages 84-85 (PDF pages 87-88): the variance of an observable in a state defined as the uncertainty, the eigenstate case and the position-momentum example
- B. Zwiebach, MIT 8.05 Quantum Physics II (Fall 2013), Chapter 5 'Uncertainty Principle and Compatible Observables', Section 1, printed pages 1-3: the uncertainty defined as the norm of the centered vector and the identity (Delta A)^2 = <A^2> - <A>^2
- G. Teschl, Mathematical Methods in Quantum Mechanics, 1st edition 2009, Section 3.1, printed pages 88-95 (PDF pages 100-107): expectation values and moments of a self-adjoint operator in a state