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The Gaussian family attains the position-momentum bound in the massive model
An exact model computation for the spin-0 massive particle model of the framework: the normalized Gaussian preparation, its position and momentum outcome densities, the spreads sigma/sqrt(2) and hbar/(sigma sqrt(2)) and the product hbar/2, and the linear dependence of its centered position and momentum vectors that realizes the equality case of the position-momentum preparation relation. The example uses the model's own sharp outcome laws and the cited mathematics; it computes no dynamics, models no measurement, records no empirical value and claims no characterization of all equality states.
Example
Adopt the state and composition postulate P1, which assigns the ray of a unit vector as a pure preparation, the observable and probability postulate P2, and the massive-particle model postulate P5 read through The massive spin-s particle model of the framework: state space, operators, units and frame readings for a spinless particle (, ) of mass parameter . Assume the Axiom of Choice and the Axiom of Countable Choice (The Axiom of Choice, The Axiom of Countable Choice ()), as required by the spectral probability and moment suppliers used below. Fix a width and define with momentum width and momentum representative under the model's momentum transform . Then:
(i) is a unit vector, so P1 assigns its ray as a pure preparation; for all , and ;
(ii) the position outcome law of has density in the coordinate , with mean and variance , so ;
(iii) , that is the momentum outcome law of has density , with mean and variance , so ;
(iv) for every , and the centered vectors are linearly dependent with vanishing real part of their pairing: so the equality case of The position-momentum preparation relation of the massive spin-s model clause (c) is realized.
The computation is one family of preparations in the model; it is not a characterization of all preparations attaining , involves no dynamics, no detection model and no empirical value.
Facts & Assumptions
Given: The postulates P1 and P2 and the model P5 read through The massive spin-s particle model of the framework: state space, operators, units and frame readings with ; the Axiom of Choice and the Axiom of Countable Choice; a width ; the action constant ; the vector ; the momentum transform ; a coordinate or .
Heat kernel. For the function on is in , satisfies (The heat kernel on and its causal extension, Normalisation, parabolic scaling, heat equation and derivative bounds for the heat kernel), and has absolutely integrable first and second moments with and (First and second Gaussian heat-kernel moments).
Gaussian Fourier transform and momentum transform. With the -normalized unitary Plancherel transform one has for (Euclidean Gaussian transform with the 2π normalization); the model's momentum transform satisfies with and for (Momentum Fourier Jacobian: the unitary momentum representation clauses (a),(c), The momentum representation of the componentwise kinematics clause (a)).
Outcome laws of the model. For a unit class the position law of is and the momentum law of is (Position and momentum outcome laws of the massive spin-s model clauses (a) and (c), Assigned sharp observables and the outcome law of the framework clause (b)).
Moments and spreads. For a unit vector in the domain of the operator the mean and variance of the outcome law exist and equal the quadratic-form mean and the squared norm of the centered vector (Mean, second moment and variance of an assigned observable in a preparation clauses (a) and (b), Preparation variance and spread of an assigned sharp observable clauses (b) and (c)).
Position-momentum relation. For every unit one has , with equality if and only if the centered vectors are linearly dependent and their pairing has vanishing real part (The position-momentum preparation relation of the massive spin-s model clauses (a) and (c)).
Schwartz functions and weak derivatives. A smooth function lies in exactly when all seminorms are finite (Schwartz space and its seminorms). A function has its classical partial derivatives as locally integrable weak derivatives (Classical derivatives agree with weak derivatives). When those derivatives are in , their classes give the model's momentum-domain membership. We distinguish a smooth function from its almost-everywhere class, using the same symbol when passing to that class.
Product integration. Integrals of nonnegative measurable functions on product spaces may be iterated (Tonelli's theorem for nonnegative measurable functions on a sigma-finite product), and (The Gaussian integral ).
Choice in the spectral laws and moments. The Axiom of Choice is the spectral theorem's stated hypothesis for constructing the spectral projection-valued measures of the self-adjoint operators; the moment suppliers also state the Axiom of Choice and Countable Choice. Thus the Born-law and moment steps below are conditional on these assumptions. The integrations and Gaussian Fourier calculation use the separate measure and Fourier suppliers [F1], [F2] and [F7].
Verification
Given: The data of the example and [F1]-[F8].
[The preparation] With one has , so [F1] gives . Repeated differentiation gives with a polynomial : start with and use . Each monomial of has modulus at most for some nonnegative integer . For , is bounded on : for it is at most , and for its maximum occurs at . Thus all Schwartz seminorms are finite, proving by [F6]. Moreover [F1] gives . The classical derivative is consequently in and is the weak derivative by [F6]. The model's maximal domains therefore contain this class in every and , and . This proves (i).
[Position law and spread] By [F3], [F7] and step 1.1, the law of has density By [F1] the first moment of this density vanishes and its second moment equals the one-dimensional heat-kernel second moment , so by [F4] the mean is and the variance is ; hence . This is (ii).
[Momentum representative] Write with . By [F2], , and substituting and gives . By [F2], ; its coefficient is and its exponent is with . This is the displayed Gaussian .
[Momentum law and spread] The momentum law density of is, by [F3] and step 2.2, the -th marginal of ; by the same heat-kernel moment computation as in step 2.1 with replaced by , its mean is and its variance is , so . This is (iii).
[Saturation and equality case] Multiplying the two spreads of steps 2.1 and 3.1 gives , the lower bound of [F5]. The centered vectors are and because both means vanish, and step 1.1 gives , a linear dependence. With the inner product linear in its first argument and , the pairing is , so its real part vanishes. By the equality clause of [F5] these properties are exactly the equality case of the position-momentum relation. This is (iv).
Remarks
- No converse is claimed. The verification shows that the Gaussian family attains the bound and satisfies the equality conditions of The position-momentum preparation relation of the massive spin-s model; it does not claim that every preparation with is Gaussian, and no classification of the equality set is recorded here.
- One family, three coordinates. The computation is uniform in the coordinate and in the width ; different widths give different preparations, and the momentum width is a property of this family in the model, not a measured resolution.
Depends on
The Axiom of Choice
The Axiom of Countable Choice ()
The heat kernel on and its causal extension
The massive spin-s particle model of the framework: state space, operators, units and frame readings
Assigned sharp observables and the outcome law of the framework
Preparation variance and spread of an assigned sharp observable
Schwartz space and its seminorms
Classical derivatives agree with weak derivatives
Euclidean Gaussian transform with the 2π normalization
First and second Gaussian heat-kernel moments
Normalisation, parabolic scaling, heat equation and derivative bounds for the heat kernel
Momentum Fourier Jacobian: the unitary momentum representation
The momentum representation of the componentwise kinematics
State and composition postulate P1: Hilbert spaces, preparations and composite systems
Position and momentum outcome laws of the massive spin-s model
Mean, second moment and variance of an assigned observable in a preparation
The position-momentum preparation relation of the massive spin-s model
The Gaussian integral
Tonelli's theorem for nonnegative measurable functions on a sigma-finite product
Dependency tree · 2 levels
Sources
- D. Tong, Quantum Mechanics (author-hosted lecture set), Section 3.4.1, printed pages 86-88 (PDF pages 89-91): the Gaussian wavepacket, its position and momentum variances and the saturation Delta x Delta p = hbar/2
- J. Binney and D. Skinner, The Physics of Quantum Mechanics, Sections 2.3.2-2.3.3 and Box 2.3, printed pages 27-31 (PDF pages 35-39): the Gaussian packet's momentum-space amplitude, the dispersion product sigma_p sigma = hbar/2 and the Gaussian integral
- B. Zwiebach, MIT 8.05 Quantum Physics II (Fall 2013), Chapter 5 'Uncertainty Principle and Compatible Observables', Section 2, printed pages 3-6: the saturation conditions of the uncertainty inequality