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University Quantum Mechanics II · unit UQMII-13

Emission and Absorption of Radiation

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

The electric-dipole Hamiltonian and its validity: infer an input with uncertainty

The electric-dipole Hamiltonian H′ = −d⋅E(t), with d = qr, is the coupling of an atom to a light wave whose field is treated as uniform across the atom: the leading term of an expansion in k a, the atom's size times the wave number, which is of order α. Use the supplied topic model Y_out = 10^lg, where Y_out is WAVELENGTH λ (nm). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793. lg is Wavelength, log₁₀(λ / 1 nm), dimensionless. Keep wt (Phase of the wave ωt) = 60 ° fixed. For this exercise use only -0.575 ≤ lg ≤ 2.575 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 = 22.207517 nm, with a bounded reading uncertainty ±3.2912 nm. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown lg by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.000315, 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

WAVELENGTH λ against lg

Predictions from the supplied The electric-dipole Hamiltonian and its validity 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): WAVELENGTH λ / nm

WAVELENGTH λ against lgPredictions from the supplied The electric-dipole Hamiltonian and its validity 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: lg: Wavelength, log₁₀(λ / 1 nm). Vertical axis: WAVELENGTH λ / nm. Exact values are available in the data table below.-14.7686.65188.1289.5390.9-0.7010.149511.852.701xy

Horizontal axis (x): lg: Wavelength, log₁₀(λ / 1 nm)

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

Reading 1lg: Wavelength, log₁₀(λ / 1 nm): -0.575WAVELENGTH λ / nm: 0.2661
Read the exact data as a table
WAVELENGTH λ against lg — supplied values
lg: Wavelength, log₁₀(λ / 1 nm)WAVELENGTH λ / nm
-0.5750.26607250597988097
0.21249999999999991.631172909227838
0.99999999999999989.999999999999995
1.787499999999999961.30557921498205
2.5749999999999993375.83740428844357

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(lg) = 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(-0.575) = 0.266073 nm and Y_out(2.575) = 375.837 nm. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives lg_line = -0.575 + (22.2075 − 0.266073)(2.575 − -0.575)/(375.837 − 0.266073) = -0.390972. 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 lg = 1.3465; substituting back gives Y_out = 22.207517 nm.
  4. The interpolation error in the input is |lg_line − lg| = 1.73747. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 18.916317 nm and 25.498717 nm. Sort the roots even if the response decreases: 1.27684 ≤ lg ≤ 1.40652.
  6. The lower and upper input deviations are 0.0696634 and 0.0600183. 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 lg ≈ 1.3465; compatible interval [1.27684, 1.40652]. Endpoint interpolation gives -0.390972.

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

Extra challenging · 02

Absorption and stimulated emission of incoherent light: infer an input with uncertainty

In incoherent light, absorption and stimulated emission are constant rates, each proportional to the squared transition dipole and to the light's spectral energy density at the transition frequency, and equal to each other for non-degenerate levels. Use the supplied topic model Y_out = 1/(2*w), where Y_out is INCOHERENT RATE R = ω₁²/(2γ) (ω₁). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793. w is Band half-width γ, measured in ω₁. Keep tm (Time marker ω₁t) = 3 fixed. For this exercise use only 1.50937 ω₁ ≤ w ≤ 8.99062 ω₁ 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 = 0.082332479 ω₁, with a bounded reading uncertainty ±0.0040078 ω₁. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown w by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.000748125 ω₁, 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

INCOHERENT RATE R = ω₁²/(2γ) against w

Predictions from the supplied Absorption and stimulated emission of incoherent light 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): INCOHERENT RATE R = ω₁²/(2γ) / ω₁

INCOHERENT RATE R = ω₁²/(2γ) against wPredictions from the supplied Absorption and stimulated emission of incoherent light 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: w: Band half-width γ / ω₁. Vertical axis: INCOHERENT RATE R = ω₁²/(2γ) / ω₁. Exact values are available in the data table below.0.044590.1190.19340.26790.34231.213.235.257.279.29xy

Horizontal axis (x): w: Band half-width γ / ω₁

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

Reading 1w: Band half-width γ / ω₁: 1.509INCOHERENT RATE R = ω₁²/(2γ) / ω₁: 0.3313
Read the exact data as a table
INCOHERENT RATE R = ω₁²/(2γ) against w — supplied values
w: Band half-width γ / ω₁INCOHERENT RATE R = ω₁²/(2γ) / ω₁
1.5093750.33126293995859213
3.37968749999999970.14794267221451687
5.250.09523809523809523
7.1203124999999990.07022163704191355
8.9906250.05561348627042058

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(w) = 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(1.50937) = 0.331263 ω₁ and Y_out(8.99062) = 0.0556135 ω₁. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives w_line = 1.50937 + (0.0823325 − 0.331263)(8.99062 − 1.50937)/(0.0556135 − 0.331263) = 8.26546 ω₁. 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 w = 6.07294 ω₁; substituting back gives Y_out = 0.082332479 ω₁.
  4. The interpolation error in the input is |w_line − w| = 2.19252 ω₁. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 0.078324679 ω₁ and 0.086340279 ω₁. Sort the roots even if the response decreases: 5.79104 ω₁ ≤ w ≤ 6.38368 ω₁.
  6. The lower and upper input deviations are 0.281898 ω₁ and 0.310746 ω₁. 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 w ≈ 6.07294 ω₁; compatible interval [5.79104, 6.38368] ω₁. Endpoint interpolation gives 8.26546 ω₁.

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

Extra challenging · 03

Einstein's A and B coefficients and spontaneous emission: infer an input with uncertainty

Einstein's A coefficient is the rate at which an excited atom decays with no light present; the B coefficients turn the spectral energy density at the transition frequency into absorption and stimulated-emission rates. Use the supplied topic model Y_out = 1/(exp(0.0143878*10^(-lg-lt))-1), where Y_out is PHOTONS PER MODE n̄ = B_baρ/A (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; exp(x) means eˣ. lg is Wavelength, log₁₀(λ / 1 m), dimensionless. Keep lt (Temperature, log₁₀(T / 1 K)) = 3.8; gr (Degeneracy ratio g_b/g_a) = 2 fixed. For this exercise use only -5.8625 ≤ lg ≤ -1.1375 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 = 458.43986, with a bounded reading uncertainty ±68.731. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown lg by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.0004725, 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

PHOTONS PER MODE n̄ = B_baρ/A against lg

Predictions from the supplied Einstein's A and B coefficients and spontaneous emission 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): PHOTONS PER MODE n̄ = B_baρ/A

PHOTONS PER MODE n̄ = B_baρ/A against lgPredictions from the supplied Einstein's A and B coefficients and spontaneous emission 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: lg: Wavelength, log₁₀(λ / 1 m). Vertical axis: PHOTONS PER MODE n̄ = B_baρ/A. Exact values are available in the data table below.-127873491.60e42.46e43.32e4-6.051-4.776-3.5-2.224-0.9485xy

Horizontal axis (x): lg: Wavelength, log₁₀(λ / 1 m)

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

Reading 1lg: Wavelength, log₁₀(λ / 1 m): -5.862PHOTONS PER MODE n̄ = B_baρ/A: 0.2344
Read the exact data as a table
PHOTONS PER MODE n̄ = B_baρ/A against lg — supplied values
lg: Wavelength, log₁₀(λ / 1 m)PHOTONS PER MODE n̄ = B_baρ/A
-5.86250.23435198047322944
-4.681258.645109450836868
-3.5138.17797445114795
-2.318752104.5170408971458
-1.137500000000000231952.05623285961

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(lg) = 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(-5.8625) = 0.234352 and Y_out(-1.1375) = 31952.1. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives lg_line = -5.8625 + (458.44 − 0.234352)(-1.1375 − -5.8625)/(31952.1 − 0.234352) = -5.79474. 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 lg = -2.98025; substituting back gives Y_out = 458.43986.
  4. The interpolation error in the input is |lg_line − lg| = 2.81449. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 389.70886 and 527.17086. Sort the roots even if the response decreases: -3.05071 ≤ lg ≤ -2.91964.
  6. The lower and upper input deviations are 0.0704587 and 0.0606074. 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 lg ≈ -2.98025; compatible interval [-3.05071, -2.91964]. Endpoint interpolation gives -5.79474.

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

Extra challenging · 04

The 2p lifetime of hydrogen computed: infer an input with uncertainty

The 2p lifetime is τ = 1/A, the inverse of the spontaneous-emission rate to 1s, which is fixed by the cube of the Lyman-α frequency and by the squared dipole matrix element e²|⟨100|r|21m⟩|², the same for all three m. Use the supplied topic model Y_out = 1.29027*(1-exp(-1.5*z*r)*(1+z*r*(1.5+z*r*(1.125+z*r*(0.5625+0.2109375*z*r)))))/z, where Y_out is RADIAL INTEGRAL FROM 0 TO R (a₀). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; exp(x) means eˣ. r is Upper limit R of the radial integral, measured in a₀. Keep z (Nuclear charge Z (hydrogen-like ion)) = 1 fixed. For this exercise use only 1.72188 a₀ ≤ r ≤ 10.7781 a₀ 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 = 1.2689892 a₀, with a bounded reading uncertainty ±0.003124 a₀. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown r by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.000905625 a₀, 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

RADIAL INTEGRAL FROM 0 TO R against r

Predictions from the supplied The 2p lifetime of hydrogen computed 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): RADIAL INTEGRAL FROM 0 TO R / a₀

RADIAL INTEGRAL FROM 0 TO R against rPredictions from the supplied The 2p lifetime of hydrogen computed 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: r: Upper limit R of the radial integral / a₀. Vertical axis: RADIAL INTEGRAL FROM 0 TO R / a₀. Exact values are available in the data table below.0.10960.4160.72241.0291.3351.363.8056.258.69511.14xy

Horizontal axis (x): r: Upper limit R of the radial integral / a₀

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

Reading 1r: Upper limit R of the radial integral / a₀: 1.722RADIAL INTEGRAL FROM 0 TO R / a₀: 0.155
Read the exact data as a table
RADIAL INTEGRAL FROM 0 TO R against r — supplied values
r: Upper limit R of the radial integral / a₀RADIAL INTEGRAL FROM 0 TO R / a₀
1.7218750.15503511029679815
3.98593749999999950.9188143244691869
6.2499999999999991.2340717826720429
8.51406251.2845834649366372
10.7781251.2898156243003407

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(r) = 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(1.72188) = 0.155035 a₀ and Y_out(10.7781) = 1.28982 a₀. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives r_line = 1.72188 + (1.26899 − 0.155035)(10.7781 − 1.72188)/(1.28982 − 0.155035) = 10.6119 a₀. 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 r = 7.24619 a₀; substituting back gives Y_out = 1.2689892 a₀.
  4. The interpolation error in the input is |r_line − r| = 3.36573 a₀. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 1.2658652 a₀ and 1.2721132 a₀. Sort the roots even if the response decreases: 7.10957 a₀ ≤ r ≤ 7.40317 a₀.
  6. The lower and upper input deviations are 0.136615 a₀ and 0.156986 a₀. 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 r ≈ 7.24619 a₀; compatible interval [7.10957, 7.40317] a₀. Endpoint interpolation gives 10.6119 a₀.

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

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