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University Quantum Mechanics II · topic UQMII-04.02

Product states, entangled states and the Schmidt decomposition

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

Product and entangled states: the Schmidt decomposition: predict a finite change

The Schmidt decomposition writes a pure state of two systems as |ψ⟩ = Σₖ √pₖ |uₖ⟩|vₖ⟩, pairing orthonormal kets of A with orthonormal kets of B, with weights pₖ ≥ 0 that sum to 1; the state is a product exactly when a single weight equals 1. Use the supplied topic model Y_out = abs(sind(2*th)*sind(ph))/2, where Y_out is |det C| = AREA (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; abs(x) means |x|; sind/cosd/tand use degrees. th is Weight angle θ, measured in °. Keep ph (Angle φ from |b₁⟩ to |b₂⟩) = 60 °; rot (Turn β of spin B's kets) = 20 ° fixed. For this exercise use only 13.5 ° ≤ th ≤ 42.9 ° 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 th = 19.968 ° and 24.084 °. Find the signed output change ΔY_out and the average sensitivity ΔY_out/Δth across this interval. State whether the response increases or decreases; distinguish this interval average from a derivative at one point.

Explore the question data

|det C| = AREA against th

Predictions from the supplied Product and entangled states: the Schmidt decomposition 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): |det C| = AREA

|det C| = AREA against thPredictions from the supplied Product and entangled states: the Schmidt decomposition 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: th: Weight angle θ / °. Vertical axis: |det C| = AREA. Exact values are available in the data table below.0.18720.25070.31420.37770.441312.3220.2628.236.1444.08xy

Horizontal axis (x): th: Weight angle θ / °

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

Reading 1th: Weight angle θ / °: 13.5|det C| = AREA: 0.1966
Read the exact data as a table
|det C| = AREA against th — supplied values
th: Weight angle θ / °|det C| = AREA
13.50.19658365292562002
20.850.28805319324960416
28.20.36066547690329975
35.550.4096669774465852
42.90.4318498364191888

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

Show a hint

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

Reveal the worked solution
  1. At th = 19.968 °, substitute into Y_out = abs(sind(2*th)*sind(ph))/2: Y₀ = 0.277965.
  2. At th = 24.084 °, the same fixed-parameter model gives Y₁ = 0.322639.
  3. Signed change: ΔY_out = Y₁ − Y₀ = 0.0446748; the input change is Δth = 4.116 °.
  4. Average sensitivity is ΔY_out/Δth = 0.0108539 1 per °. 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 = 0.277965, Y₁ = 0.322639; ΔY_out = 0.0446748; average sensitivity = 0.0108539 1 per °.

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

Product and entangled states: the Schmidt decomposition: infer an input with uncertainty

The Schmidt decomposition writes a pure state of two systems as |ψ⟩ = Σₖ √pₖ |uₖ⟩|vₖ⟩, pairing orthonormal kets of A with orthonormal kets of B, with weights pₖ ≥ 0 that sum to 1; the state is a product exactly when a single weight equals 1. Use the supplied topic model Y_out = abs(sind(2*th)*sind(ph))/2, where Y_out is |det C| = AREA (dimensionless). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; abs(x) means |x|; sind/cosd/tand use degrees. th is Weight angle θ, measured in °. Keep ph (Angle φ from |b₁⟩ to |b₂⟩) = 60 °; rot (Turn β of spin B's kets) = 20 ° fixed. For this exercise use only 13.5 ° ≤ th ≤ 42.9 ° 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 = 0.38536322, with a bounded reading uncertainty ±0.006973. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown th by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.00294 °, 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

|det C| = AREA against th

Predictions from the supplied Product and entangled states: the Schmidt decomposition 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): |det C| = AREA

|det C| = AREA against thPredictions from the supplied Product and entangled states: the Schmidt decomposition 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: th: Weight angle θ / °. Vertical axis: |det C| = AREA. Exact values are available in the data table below.0.18720.25070.31420.37770.441312.3220.2628.236.1444.08xy

Horizontal axis (x): th: Weight angle θ / °

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

Reading 1th: Weight angle θ / °: 13.5|det C| = AREA: 0.1966
Read the exact data as a table
|det C| = AREA against th — supplied values
th: Weight angle θ / °|det C| = AREA
13.50.19658365292562002
20.850.28805319324960416
28.20.36066547690329975
35.550.4096669774465852
42.90.4318498364191888

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(th) = 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(13.5) = 0.196584 and Y_out(42.9) = 0.43185. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives th_line = 13.5 + (0.385363 − 0.196584)(42.9 − 13.5)/(0.43185 − 0.196584) = 37.0908 °. 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 th = 31.434 °; substituting back gives Y_out = 0.38536322.
  4. The interpolation error in the input is |th_line − th| = 5.65681 °. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 0.37839022 and 0.39233622. Sort the roots even if the response decreases: 30.4549 ° ≤ th ≤ 32.4833 °.
  6. The lower and upper input deviations are 0.979136 ° and 1.04933 °. 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 th ≈ 31.434 °; compatible interval [30.4549, 32.4833] °. Endpoint interpolation gives 37.0908 °.

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