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University Physics V · unit UPV-09

Angular Momentum in Quantum Mechanics

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.

Extra challenging questions

A selection from this pathway. Open a topic below for its complete practice and challenge set.

Extra challenging · 01

Angular momentum as a rotation generator: infer an input with uncertainty

Classical angular momentum L = r × p is the conserved charge of rotational symmetry and, equivalently, the generator of rotations in phase space: bracketing any function with n̂⋅L rotates it about n̂. Use the supplied topic model Y_out = 2*sind(beta)*sind(alpha/2)/max((alpha*pi/180)*(beta*pi/180),0.0001), where Y_out is GAP ÷ αβ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; max(a,b) selects the larger value; sind/cosd/tand use degrees. alpha is Turn about x, α, measured in °. Keep beta (Turn about y, β) = 30 ° fixed. For this exercise use only 14.0313 ° ≤ alpha ≤ 80.9688 ° 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 = 0.91886373, with a bounded reading uncertainty ±0.0050522. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown alpha by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.00669375 °, 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

GAP ÷ αβ against alpha

Predictions from the supplied Angular momentum as a rotation generator 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): GAP ÷ αβ

GAP ÷ αβ against alphaPredictions from the supplied Angular momentum as a rotation generator 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: alpha: Turn about x, α / °. Vertical axis: GAP ÷ αβ. Exact values are available in the data table below.0.874420.894710.914990.935270.9555511.3529.4347.565.5783.65xy

Horizontal axis (x): alpha: Turn about x, α / °

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

Reading 1alpha: Turn about x, α / °: 14.03GAP ÷ αβ: 0.9525
Read the exact data as a table
GAP ÷ αβ against alpha — supplied values
alpha: Turn about x, α / °GAP ÷ αβ
14.031250.9525452425535038
30.7656250.9434987437681529
47.50.9278171164312091
64.2343750.9057002962490946
80.968750.8774296037957648

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(alpha) = 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(14.0313) = 0.952545 and Y_out(80.9688) = 0.87743. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives alpha_line = 14.0313 + (0.918864 − 0.952545)(80.9688 − 14.0313)/(0.87743 − 0.952545) = 44.0457 °. 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 alpha = 54.8631 °; substituting back gives Y_out = 0.91886373.
  4. The interpolation error in the input is |alpha_line − alpha| = 10.8174 °. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 0.91381153 and 0.92391593. Sort the roots even if the response decreases: 50.8343 ° ≤ alpha ≤ 58.6276 °.
  6. The lower and upper input deviations are 4.02884 ° and 3.76447 °. 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 alpha ≈ 54.8631 °; compatible interval [50.8343, 58.6276] °. Endpoint interpolation gives 44.0457 °.

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

Extra challenging · 02

Angular momentum operators and the rotation algebra: infer an input with uncertainty

The angular momentum operators are the three Hermitian generators L̂_i = ε_ijk x̂_j p̂_k, defined about a chosen origin, whose commutators close on themselves as [L̂_i, L̂_j] = iħ ε_ijk L̂_k, making exp(−iθ n̂⋅L̂/ħ) the unitary that rotates a state by θ about n̂. Use the supplied topic model Y_out = sind(be)*cosd(be)*(1-cosd(al)), where Y_out is OUT-OF-PLANE z (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sind/cosd/tand use degrees. be is Rotation about y, angle b, measured in °. Keep al (Rotation about x, angle a) = 30 ° fixed. For this exercise use only 6.375 ° ≤ be ≤ 44.175 ° 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 = 0.057338476, with a bounded reading uncertainty ±0.0014432. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown be by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.00378 °, 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

OUT-OF-PLANE z against be

Predictions from the supplied Angular momentum operators and the rotation algebra 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): OUT-OF-PLANE z

OUT-OF-PLANE z against bePredictions from the supplied Angular momentum operators and the rotation algebra 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: be: Rotation about y, angle b / °. Vertical axis: OUT-OF-PLANE z. Exact values are available in the data table below.0.01270.026780.040870.054960.069054.86315.0725.2735.4845.69xy

Horizontal axis (x): be: Rotation about y, angle b / °

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

Reading 1be: Rotation about y, angle b / °: 6.375OUT-OF-PLANE z: 0.01478
Read the exact data as a table
OUT-OF-PLANE z against be — supplied values
be: Rotation about y, angle b / °OUT-OF-PLANE z
6.3750.01478392487140784
15.8250.035150176496723695
25.2750.05172620981610092
34.7249999999999940.0627246430525858
44.1750.06695952304336973

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(be) = 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(6.375) = 0.0147839 and Y_out(44.175) = 0.0669595. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives be_line = 6.375 + (0.0573385 − 0.0147839)(44.175 − 6.375)/(0.0669595 − 0.0147839) = 37.2048 °. 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 be = 29.433 °; substituting back gives Y_out = 0.057338476.
  4. The interpolation error in the input is |be_line − be| = 7.77178 °. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 0.055895276 and 0.058781676. Sort the roots even if the response decreases: 28.2775 ° ≤ be ≤ 30.6714 °.
  6. The lower and upper input deviations are 1.15546 ° and 1.23841 °. 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 be ≈ 29.433 °; compatible interval [28.2775, 30.6714] °. Endpoint interpolation gives 37.2048 °.

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

Extra challenging · 03

Ladder operators and the quantisation of j and m: infer an input with uncertainty

The ladder operators J± = J_x ± iJ_y raise or lower the J_z eigenvalue by ħ without changing J², and the requirement that their output have a non-negative norm forces J² = ħ²j(j+1) with j = 0, ½, 1, … and J_z = mħ with m running from −j to j in unit steps. Use the supplied topic model Y_out = sqrt((j-min(k-j,j))*(j+min(k-j,j)+1)), where Y_out is ‖J₊|j,m⟩‖ (ħ). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sqrt(x) means √x; min(a,b) selects the smaller value. k is Rungs climbed k (m = k − j, capped at j), dimensionless. Keep j (Angular momentum j) = 1.5 fixed. For this exercise use only 1 ≤ k ≤ 3, at the specified test settings separated by 1. 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 = 1.7320508 ħ, with a bounded reading uncertainty ±0.16 ħ. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. Determine every allowed value of k consistent with that bound. Compare with a straight-line interpolation between the two endpoint predictions, and explain why a fractional setting may be inadmissible. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

‖J₊|j,m⟩‖ against k

Predictions from the supplied Ladder operators and the quantisation of j and m model, with all other inputs fixed as stated in the question. 3 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): ‖J₊|j,m⟩‖ / ħ

‖J₊|j,m⟩‖ against kPredictions from the supplied Ladder operators and the quantisation of j and m model, with all other inputs fixed as stated in the question. 3 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: k: Rungs climbed k (m = k − j, capped at j). Vertical axis: ‖J₊|j,m⟩‖ / ħ. Exact values are available in the data table below.-0.080.4611.542.080.921.4622.543.08xy

Horizontal axis (x): k: Rungs climbed k (m = k − j, capped at j)

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

Reading 1k: Rungs climbed k (m = k − j, capped at j): 1‖J₊|j,m⟩‖ / ħ: 2
Read the exact data as a table
‖J₊|j,m⟩‖ against k — supplied values
k: Rungs climbed k (m = k − j, capped at j)‖J₊|j,m⟩‖ / ħ
12
21.7320508075688772
30

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

Show a hint

Enumerate the permitted settings in the stated range, evaluate Y_out at each, and retain every setting satisfying |Y_out − Y_measured| ≤ u. The plotted predictions are supplied calibration evidence.

Reveal the worked solution
  1. Endpoint predictions are Y_out(1) = 2 ħ and Y_out(3) = 0 ħ. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives k_line = 1 + (1.73205 − 2)(3 − 1)/(0 − 2) = 1.26795. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Evaluate the model at each permitted setting. The central reading corresponds to k = 2; only the allowed settings 2 lie inside the stated reading bound.
  4. The interpolation error in the input is |k_line − k| = 0.732051.
  5. The compatible allowed values span 2 to 2. Values between specified test settings are outside this exercise's input domain even if an interpolation passes through them.
  6. The quoted output bound restricts which specified settings remain compatible. It does not change physical restrictions on quantum numbers or counts, and the chosen grid alone does not establish physical quantisation.

Answer Compatible k: 2. Endpoint interpolation predicts 1.26795; check admissibility against the discrete settings.

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

Extra challenging · 04

Angular momentum matrices and the uncertainty bound: infer an input with uncertainty

The matrix representation of angular momentum writes J_x, J_y and J_z as (2j+1)×(2j+1) Hermitian matrices whose entries are ⟨j, m′|J_i|j, m⟩ in the eigenbasis of J² and J_z, so operator identities become checks on matrix products. Use the supplied topic model Y_out = sqrt(max(j*(j+1)-(j-min(k,2*j))^2,0)/2), where Y_out is ΔJx = ΔJy (ħ). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sqrt(x) means √x; min(a,b) selects the smaller value; max(a,b) selects the larger value. j is Angular momentum j, dimensionless. Keep k (Steps k below the top state) = 0 fixed. For this exercise use only 0.5 ≤ j ≤ 3, at the specified test settings separated by 0.5. 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 ħ, with a bounded reading uncertainty ±0.05798 ħ. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. Determine every allowed value of j consistent with that bound. Compare with a straight-line interpolation between the two endpoint predictions, and explain why a fractional setting may be inadmissible. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

ΔJx = ΔJy against j

Predictions from the supplied Angular momentum matrices and the uncertainty bound 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): ΔJx = ΔJy / ħ

ΔJx = ΔJy against jPredictions from the supplied Angular momentum matrices and the uncertainty bound 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: j: Angular momentum j. Vertical axis: ΔJx = ΔJy / ħ. Exact values are available in the data table below.0.4710.66670.86241.0581.2540.41.0751.752.4253.1xy

Horizontal axis (x): j: Angular momentum j

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

Reading 1j: Angular momentum j: 0.5ΔJx = ΔJy / ħ: 0.5
Read the exact data as a table
ΔJx = ΔJy against j — supplied values
j: Angular momentum jΔJx = ΔJy / ħ
0.50.5
10.7071067811865476
21
2.51.118033988749895
31.224744871391589

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

Show a hint

Enumerate the permitted settings in the stated range, evaluate Y_out at each, and retain every setting satisfying |Y_out − Y_measured| ≤ u. The plotted predictions are supplied calibration evidence.

Reveal the worked solution
  1. Endpoint predictions are Y_out(0.5) = 0.5 ħ and Y_out(3) = 1.22474 ħ. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives j_line = 0.5 + (1 − 0.5)(3 − 0.5)/(1.22474 − 0.5) = 2.22474. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Evaluate the model at each permitted setting. The central reading corresponds to j = 2; only the allowed settings 2 lie inside the stated reading bound.
  4. The interpolation error in the input is |j_line − j| = 0.224745.
  5. The compatible allowed values span 2 to 2. Values between specified test settings are outside this exercise's input domain even if an interpolation passes through them.
  6. The quoted output bound restricts which specified settings remain compatible. It does not change physical restrictions on quantum numbers or counts, and the chosen grid alone does not establish physical quantisation.

Answer Compatible j: 2. Endpoint interpolation predicts 2.22474; check admissibility against the discrete settings.

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

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