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University Physics III · topic UPIII-08.03

Time dilation, proper time, and length contraction

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

Time dilation, proper time & length contraction: predict a finite change

Proper time is the interval between two events read by one clock present at both; any inertial frame in which the events occur at different places measures the longer interval Δt = γΔτ, and an object moving at v in that frame is shorter along v by the same factor, L = L₀/γ. Use the supplied topic model Y_out = 1/sqrt(1-b*b), where Y_out is LORENTZ FACTOR γ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sqrt(x) means √x. b is Speed of the clock β = v/c, dimensionless. Keep no other adjustable input fixed. For this exercise use only 0.095625 ≤ b ≤ 0.804375 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 b = 0.25155 and 0.350775. Find the signed output change ΔY_out and the average sensitivity ΔY_out/Δb across this interval. State whether the response increases or decreases; distinguish this interval average from a derivative at one point.

Explore the question data

LORENTZ FACTOR γ against b

Predictions from the supplied Time dilation, proper time & length contraction 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): LORENTZ FACTOR γ

LORENTZ FACTOR γ against bPredictions from the supplied Time dilation, proper time & length contraction 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: b: Speed of the clock β = v/c. Vertical axis: LORENTZ FACTOR γ. Exact values are available in the data table below.0.97751.1611.3441.5271.710.067280.25860.450.64140.8327xy

Horizontal axis (x): b: Speed of the clock β = v/c

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

Reading 1b: Speed of the clock β = v/c: 0.09563LORENTZ FACTOR γ: 1.005
Read the exact data as a table
LORENTZ FACTOR γ against b — supplied values
b: Speed of the clock β = v/cLORENTZ FACTOR γ
0.0956251.0046036669149399
0.27281251.0394284068994142
0.451.1197850219117087
0.62718749999999991.2839140979959294
0.8043751.683156202973745

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

Show a hint

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

Reveal the worked solution
  1. At b = 0.25155, substitute into Y_out = 1/sqrt(1-b*b): Y₀ = 1.03322.
  2. At b = 0.350775, the same fixed-parameter model gives Y₁ = 1.06785.
  3. Signed change: ΔY_out = Y₁ − Y₀ = 0.0346275; the input change is Δb = 0.099225.
  4. Average sensitivity is ΔY_out/Δb = 0.34898 1 per unit input. 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 = 1.03322, Y₁ = 1.06785; ΔY_out = 0.0346275; average sensitivity = 0.34898 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

Time dilation, proper time & length contraction: infer an input with uncertainty

Proper time is the interval between two events read by one clock present at both; any inertial frame in which the events occur at different places measures the longer interval Δt = γΔτ, and an object moving at v in that frame is shorter along v by the same factor, L = L₀/γ. Use the supplied topic model Y_out = 1/sqrt(1-b*b), where Y_out is LORENTZ FACTOR γ (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sqrt(x) means √x. b is Speed of the clock β = v/c, dimensionless. Keep no other adjustable input fixed. For this exercise use only 0.095625 ≤ b ≤ 0.804375 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 = 1.177485, with a bounded reading uncertainty ±0.025932. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown b by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.000070875, 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

LORENTZ FACTOR γ against b

Predictions from the supplied Time dilation, proper time & length contraction 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): LORENTZ FACTOR γ

LORENTZ FACTOR γ against bPredictions from the supplied Time dilation, proper time & length contraction 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: b: Speed of the clock β = v/c. Vertical axis: LORENTZ FACTOR γ. Exact values are available in the data table below.0.97751.1611.3441.5271.710.067280.25860.450.64140.8327xy

Horizontal axis (x): b: Speed of the clock β = v/c

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

Reading 1b: Speed of the clock β = v/c: 0.09563LORENTZ FACTOR γ: 1.005
Read the exact data as a table
LORENTZ FACTOR γ against b — supplied values
b: Speed of the clock β = v/cLORENTZ FACTOR γ
0.0956251.0046036669149399
0.27281251.0394284068994142
0.451.1197850219117087
0.62718749999999991.2839140979959294
0.8043751.683156202973745

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(b) = 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(0.095625) = 1.0046 and Y_out(0.804375) = 1.68316. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives b_line = 0.095625 + (1.17748 − 1.0046)(0.804375 − 0.095625)/(1.68316 − 1.0046) = 0.2762. 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 b = 0.527962; substituting back gives Y_out = 1.177485.
  4. The interpolation error in the input is |b_line − b| = 0.251762. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 1.151553 and 1.203417. Sort the roots even if the response decreases: 0.495877 ≤ b ≤ 0.556321.
  6. The lower and upper input deviations are 0.032085 and 0.028359. 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 b ≈ 0.527962; compatible interval [0.495877, 0.556321]. Endpoint interpolation gives 0.2762.

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