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University Advanced Quantum Mechanics · topic UAQM-14.03

The Born-Markov master equation for an atom in the vacuum field

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

The Born-Markov master equation for an atom in vacuum: predict a finite change

The Born-Markov master equation is the closed equation of motion for an atom's density matrix once the vacuum field has been traced out: unitary motion at the observed frequency, plus a dissipator that empties |e⟩ into |g⟩ at the rate Γ. Use the supplied topic model Y_out = p*exp(-t), where Y_out is EXCITED POPULATION ρₑₑ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; exp(x) means eˣ. t is Time Γt, dimensionless. Keep p (Initial excited population ρₑₑ(0)) = 0.75; f (Coherence, fraction of its maximum) = 1 fixed. For this exercise use only 0.53125 ≤ t ≤ 4.46875 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 t = 1.3975 and 1.94875. Find the signed output change ΔY_out and the average sensitivity ΔY_out/Δt across this interval. State whether the response increases or decreases; distinguish this interval average from a derivative at one point.

Explore the question data

EXCITED POPULATION ρₑₑ against t

Predictions from the supplied The Born-Markov master equation for an atom in vacuum 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): EXCITED POPULATION ρₑₑ

EXCITED POPULATION ρₑₑ against tPredictions from the supplied The Born-Markov master equation for an atom in vacuum 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: t: Time Γt. Vertical axis: EXCITED POPULATION ρₑₑ. Exact values are available in the data table below.-0.0086960.1080.22470.34150.45820.37381.4372.53.5634.626xy

Horizontal axis (x): t: Time Γt

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

Reading 1t: Time Γt: 0.5313EXCITED POPULATION ρₑₑ: 0.4409
Read the exact data as a table
EXCITED POPULATION ρₑₑ against t — supplied values
t: Time ΓtEXCITED POPULATION ρₑₑ
0.531250.4409022548417599
1.5156250.1647531357409315
2.50.0615637489679241
3.4843750.023004692262400192
4.468750.00859622545669639

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

Show a hint

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

Reveal the worked solution
  1. At t = 1.3975, substitute into Y_out = p*exp(-t): Y₀ = 0.185411.
  2. At t = 1.94875, the same fixed-parameter model gives Y₁ = 0.106839.
  3. Signed change: ΔY_out = Y₁ − Y₀ = -0.0785717; the input change is Δt = 0.55125.
  4. Average sensitivity is ΔY_out/Δt = -0.142534 1 per unit input. Its negative sign means that this response decreases 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 = 0.185411, Y₁ = 0.106839; ΔY_out = -0.0785717; average sensitivity = -0.142534 1 per unit input.

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

The Born-Markov master equation for an atom in vacuum: infer an input with uncertainty

The Born-Markov master equation is the closed equation of motion for an atom's density matrix once the vacuum field has been traced out: unitary motion at the observed frequency, plus a dissipator that empties |e⟩ into |g⟩ at the rate Γ. Use the supplied topic model Y_out = p*exp(-t), where Y_out is EXCITED POPULATION ρₑₑ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; exp(x) means eˣ. t is Time Γt, dimensionless. Keep p (Initial excited population ρₑₑ(0)) = 0.75; f (Coherence, fraction of its maximum) = 1 fixed. For this exercise use only 0.53125 ≤ t ≤ 4.46875 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 = 0.039922825, with a bounded reading uncertainty ±0.004699. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown t by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.00039375, 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

EXCITED POPULATION ρₑₑ against t

Predictions from the supplied The Born-Markov master equation for an atom in vacuum 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): EXCITED POPULATION ρₑₑ

EXCITED POPULATION ρₑₑ against tPredictions from the supplied The Born-Markov master equation for an atom in vacuum 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: t: Time Γt. Vertical axis: EXCITED POPULATION ρₑₑ. Exact values are available in the data table below.-0.0086960.1080.22470.34150.45820.37381.4372.53.5634.626xy

Horizontal axis (x): t: Time Γt

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

Reading 1t: Time Γt: 0.5313EXCITED POPULATION ρₑₑ: 0.4409
Read the exact data as a table
EXCITED POPULATION ρₑₑ against t — supplied values
t: Time ΓtEXCITED POPULATION ρₑₑ
0.531250.4409022548417599
1.5156250.1647531357409315
2.50.0615637489679241
3.4843750.023004692262400192
4.468750.00859622545669639

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(t) = 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(0.53125) = 0.440902 and Y_out(4.46875) = 0.00859623. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives t_line = 0.53125 + (0.0399228 − 0.440902)(4.46875 − 0.53125)/(0.00859623 − 0.440902) = 4.18342. 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 t = 2.93312; substituting back gives Y_out = 0.039922825.
  4. The interpolation error in the input is |t_line − t| = 1.2503. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 0.035223825 and 0.044621825. Sort the roots even if the response decreases: 2.82185 ≤ t ≤ 3.05835.
  6. The lower and upper input deviations are 0.111275 and 0.125226. 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 t ≈ 2.93312; compatible interval [2.82185, 3.05835]. Endpoint interpolation gives 4.18342.

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