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University Physics V · topic UPV-02.01

Four quantitative failures of the classical account

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

Four quantitative failures of the classical account: predict a finite change

The classical failure inventory is the list of sharp wrong predictions — atomic collapse in picoseconds, harmonic spectra, temperature-blind heat capacities, an undefined entropy constant — that classical mechanics, electrodynamics and statistical mechanics make about ordinary matter. Use the supplied topic model Y_out = 1.5+(tr/t)^2*exp(-tr/t)/max((1-exp(-tr/t))^2,0.000000001)+(tv/t)^2*exp(-tv/t)/max((1-exp(-tv/t))^2,0.000000001), where Y_out is C_V AT T (R). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; exp(x) means eˣ; max(a,b) selects the larger value. tv is Vibration quantum θ_vib, measured in K. Keep tr (Rotation quantum θ_rot) = 85 K; t (Gas temperature T) = 300 K fixed. For this exercise use only 1384.38 K ≤ tv ≤ 5715.63 K 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 tv = 2337.25 K and 2943.63 K. Find the signed output change ΔY_out and the average sensitivity ΔY_out/Δtv across this interval. State whether the response increases or decreases; distinguish this interval average from a derivative at one point.

Explore the question data

C_V AT T against tv

Predictions from the supplied Four quantitative failures of the classical account 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): C_V AT T / R

C_V AT T against tvPredictions from the supplied Four quantitative failures of the classical account 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: tv: Vibration quantum θ_vib / K. Vertical axis: C_V AT T / R. Exact values are available in the data table below.2.48472.54282.60092.6592.717112112381355047195889xy

Horizontal axis (x): tv: Vibration quantum θ_vib / K

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

Reading 1tv: Vibration quantum θ_vib / K: 1384C_V AT T / R: 2.709
Read the exact data as a table
C_V AT T against tv — supplied values
tv: Vibration quantum θ_vib / KC_V AT T / R
1384.3752.7085280607810933
2467.18752.511482706259243
35502.49435336253227
4632.81252.4933838079367443
5715.6252.4933388825594234

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

Show a hint

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

Reveal the worked solution
  1. At tv = 2337.25 K, substitute into Y_out = 1.5+(tr/t)^2*exp(-tr/t)/max((1-exp(-tr/t))^2,0.000000001)+(tv/t)^2*exp(-tv/t)/max((1-exp(-tv/t))^2,0.000000001): Y₀ = 2.51846 R.
  2. At tv = 2943.63 K, the same fixed-parameter model gives Y₁ = 2.49861 R.
  3. Signed change: ΔY_out = Y₁ − Y₀ = -0.0198443 R; the input change is Δtv = 606.375 K.
  4. Average sensitivity is ΔY_out/Δtv = -0.0000327262 R per K. 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 = 2.51846 R, Y₁ = 2.49861 R; ΔY_out = -0.0198443 R; average sensitivity = -0.0000327262 R per K.

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

Four quantitative failures of the classical account: infer an input with uncertainty

The classical failure inventory is the list of sharp wrong predictions — atomic collapse in picoseconds, harmonic spectra, temperature-blind heat capacities, an undefined entropy constant — that classical mechanics, electrodynamics and statistical mechanics make about ordinary matter. Use the supplied topic model Y_out = 1.5+(tr/t)^2*exp(-tr/t)/max((1-exp(-tr/t))^2,0.000000001)+(tv/t)^2*exp(-tv/t)/max((1-exp(-tv/t))^2,0.000000001), where Y_out is C_V AT T (R). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; exp(x) means eˣ; max(a,b) selects the larger value. tv is Vibration quantum θ_vib, measured in K. Keep tr (Rotation quantum θ_rot) = 85 K; t (Gas temperature T) = 300 K fixed. For this exercise use only 1384.38 K ≤ tv ≤ 5715.63 K 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 = 2.4936041 R, with a bounded reading uncertainty ±0.000039783 R. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown tv by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.433125 K, 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

C_V AT T against tv

Predictions from the supplied Four quantitative failures of the classical account 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): C_V AT T / R

C_V AT T against tvPredictions from the supplied Four quantitative failures of the classical account 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: tv: Vibration quantum θ_vib / K. Vertical axis: C_V AT T / R. Exact values are available in the data table below.2.48472.54282.60092.6592.717112112381355047195889xy

Horizontal axis (x): tv: Vibration quantum θ_vib / K

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

Reading 1tv: Vibration quantum θ_vib / K: 1384C_V AT T / R: 2.709
Read the exact data as a table
C_V AT T against tv — supplied values
tv: Vibration quantum θ_vib / KC_V AT T / R
1384.3752.7085280607810933
2467.18752.511482706259243
35502.49435336253227
4632.81252.4933838079367443
5715.6252.4933388825594234

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(tv) = 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(1384.38) = 2.70853 R and Y_out(5715.63) = 2.49334 R. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives tv_line = 1384.38 + (2.4936 − 2.70853)(5715.63 − 1384.38)/(2.49334 − 2.70853) = 5710.29 K. 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 tv = 4026.42 K; substituting back gives Y_out = 2.4936041 R.
  4. The interpolation error in the input is |tv_line − tv| = 1683.86 K. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 2.4935643 R and 2.4936439 R. Sort the roots even if the response decreases: 3977.43 K ≤ tv ≤ 4083.2 K.
  6. The lower and upper input deviations are 48.9911 K and 56.775 K. 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 tv ≈ 4026.42 K; compatible interval [3977.43, 4083.2] K. Endpoint interpolation gives 5710.29 K.

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