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University Quantum Mechanics I · topic UQMI-10.04

Orthogonality, normalisation, and <m|n> = delta_mn

Connect the ideas, make your working visible, and test the result. Use the hints when you need a starting point; open the full solution after your attempt.

Further practice

Work through a fresh case before tackling the extension.

Further practice · 01

Orthogonality, normalisation, and ⟨m|n⟩ = δₘₙ: predict a finite change

Kets |m⟩ and |n⟩ are orthogonal when ⟨m|n⟩ = 0, and a ket is normalised when ⟨n|n⟩ = 1; a set obeying ⟨m|n⟩ = δₘₙ is orthonormal, and the eigenkets of a Hermitian operator with a discrete spectrum can always be chosen that way. Use the supplied topic model Y_out = c*sind(theta), where Y_out is REMAINDER LENGTH √⟨w|w⟩ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sind/cosd/tand use degrees. theta is Angle from |e₁⟩ to |b⟩, measured in °. Keep phi (Direction of the first pick |e₁⟩) = 20 °; c (Length of |b⟩, √⟨b|b⟩) = 1.2 fixed. For this exercise use only 34.875 ° ≤ theta ≤ 86.325 ° on this continuous branch. A grid of test settings is an input restriction for this exercise, not by itself a claim of physical quantisation. This calculation retains the topic model's stated assumptions; it does not extend them to a different physical setup. Calculate Y_out at theta = 46.194 ° and 53.397 °. Find the signed output change ΔY_out and the average sensitivity ΔY_out/Δtheta across this interval. State whether the response increases or decreases; distinguish this interval average from a derivative at one point.

Explore the question data

REMAINDER LENGTH √⟨w|w⟩ against theta

Predictions from the supplied Orthogonality, normalisation, and ⟨m|n⟩ = δₘₙ model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): REMAINDER LENGTH √⟨w|w⟩

REMAINDER LENGTH √⟨w|w⟩ against thetaPredictions from the supplied Orthogonality, normalisation, and ⟨m|n⟩ = δₘₙ model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: theta: Angle from |e₁⟩ to |b⟩ / °. Vertical axis: REMAINDER LENGTH √⟨w|w⟩. Exact values are available in the data table below.0.66570.80380.94181.081.21832.8246.7160.674.4988.38xy

Horizontal axis (x): theta: Angle from |e₁⟩ to |b⟩ / °

Axes show the supplied calibration interval; the origin may lie outside the plot.

Reading 1theta: Angle from |e₁⟩ to |b⟩ / °: 34.88REMAINDER LENGTH √⟨w|w⟩: 0.6861
Read the exact data as a table
REMAINDER LENGTH √⟨w|w⟩ against theta — supplied values
theta: Angle from |e₁⟩ to |b⟩ / °REMAINDER LENGTH √⟨w|w⟩
34.8750.6861455522731347
47.73750.8880857066279694
60.61.0454565733442271
73.46251.1503603702909018
86.3251.197532416969702

These are the supplied values, not a worked answer. No fitted trend is drawn.

Show a hint

Substitute each value of theta separately while keeping every other input fixed, then subtract in the same order.

Reveal the worked solution
  1. At theta = 46.194 °, substitute into Y_out = c*sind(theta): Y₀ = 0.866025.
  2. At theta = 53.397 °, the same fixed-parameter model gives Y₁ = 0.963344.
  3. Signed change: ΔY_out = Y₁ − Y₀ = 0.0973182; the input change is Δtheta = 7.203 °.
  4. Average sensitivity is ΔY_out/Δtheta = 0.0135108 1 per °. Its positive sign means that this response increases over the specified interval.
  5. This is a secant slope between two settings. It equals a point derivative only for a locally linear relation or in a justified small-interval limit.

Answer Y₀ = 0.866025, Y₁ = 0.963344; ΔY_out = 0.0973182; average sensitivity = 0.0135108 1 per °.

Compare the assumptions, method and units with your attempt. Explain any correction before trying another question.

Extra challenging questions

Work through the linked stages and explain what each result means.

Extra challenging · 01

Orthogonality, normalisation, and ⟨m|n⟩ = δₘₙ: infer an input with uncertainty

Kets |m⟩ and |n⟩ are orthogonal when ⟨m|n⟩ = 0, and a ket is normalised when ⟨n|n⟩ = 1; a set obeying ⟨m|n⟩ = δₘₙ is orthonormal, and the eigenkets of a Hermitian operator with a discrete spectrum can always be chosen that way. Use the supplied topic model Y_out = c*sind(theta), where Y_out is REMAINDER LENGTH √⟨w|w⟩ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sind/cosd/tand use degrees. theta is Angle from |e₁⟩ to |b⟩, measured in °. Keep phi (Direction of the first pick |e₁⟩) = 20 °; c (Length of |b⟩, √⟨b|b⟩) = 1.2 fixed. For this exercise use only 34.875 ° ≤ theta ≤ 86.325 ° on this continuous branch. A grid of test settings is an input restriction for this exercise, not by itself a claim of physical quantisation. This calculation retains the topic model's stated assumptions; it does not extend them to a different physical setup. A reading gives Y_out = 1.0984539, with a bounded reading uncertainty ±0.014862. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown theta by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.005145 °, using a numerical bracket if required. Find the full input interval consistent with the bounded reading uncertainty and compare it with a symmetric input-error assumption. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

REMAINDER LENGTH √⟨w|w⟩ against theta

Predictions from the supplied Orthogonality, normalisation, and ⟨m|n⟩ = δₘₙ model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): REMAINDER LENGTH √⟨w|w⟩

REMAINDER LENGTH √⟨w|w⟩ against thetaPredictions from the supplied Orthogonality, normalisation, and ⟨m|n⟩ = δₘₙ model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: theta: Angle from |e₁⟩ to |b⟩ / °. Vertical axis: REMAINDER LENGTH √⟨w|w⟩. Exact values are available in the data table below.0.66570.80380.94181.081.21832.8246.7160.674.4988.38xy

Horizontal axis (x): theta: Angle from |e₁⟩ to |b⟩ / °

Axes show the supplied calibration interval; the origin may lie outside the plot.

Reading 1theta: Angle from |e₁⟩ to |b⟩ / °: 34.88REMAINDER LENGTH √⟨w|w⟩: 0.6861
Read the exact data as a table
REMAINDER LENGTH √⟨w|w⟩ against theta — supplied values
theta: Angle from |e₁⟩ to |b⟩ / °REMAINDER LENGTH √⟨w|w⟩
34.8750.6861455522731347
47.73750.8880857066279694
60.61.0454565733442271
73.46251.1503603702909018
86.3251.197532416969702

These are the supplied values, not a worked answer. No fitted trend is drawn.

Show a hint

The model's endpoint predictions bracket the reading. Solve Y_out(theta) = Y_measured and then solve again at Y_measured − u and Y_measured + u; a nonlinear inverse can give unequal input deviations.

Reveal the worked solution
  1. Endpoint predictions are Y_out(34.875) = 0.686146 and Y_out(86.325) = 1.19753. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives theta_line = 34.875 + (1.09845 − 0.686146)(86.325 − 34.875)/(1.19753 − 0.686146) = 76.3568 °. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Use the actual equation, not the chord, and bracket its root. Evaluating the midpoint and retaining the sign-changing half-interval gives theta = 66.2595 °; substituting back gives Y_out = 1.0984539.
  4. The interpolation error in the input is |theta_line − theta| = 10.0973 °. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 1.0835919 and 1.1133159. Sort the roots even if the response decreases: 64.5543 ° ≤ theta ≤ 68.0888 °.
  6. The lower and upper input deviations are 1.70515 ° and 1.82929 °. They differ because the inverse response is nonlinear; a symmetric error bar would only be a local approximation. This interval includes reading uncertainty only, not model error or uncertainty in fixed inputs.

Answer theta ≈ 66.2595 °; compatible interval [64.5543, 68.0888] °. Endpoint interpolation gives 76.3568 °.

Compare the assumptions, method and units with your attempt. Explain any correction before trying another question.