Solving the Heat Equation — Question 9

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Question 9

For ut=uxxu_t=u_{xx} on (0,π)(0,\pi) with zero endpoint values, let ϕn(x)=2/πsin⁡(nx)\phi_n(x)=\sqrt{2/\pi}\sin(nx) be the orthonormal spatial modes. Write u(x,0)=∑cnϕn(x)u(x,0)=\sum c_n\phi_n(x) and u(x,T)=∑dnϕn(x)u(x,T)=\sum d_n\phi_n(x), where T>0T>0. All norms in this question are L2(0,π)L^2(0,\pi) norms.

Tasks

  1. Relate cnc_n and dnd_n. Prove that there is at most one L2L^2 initial field for given exact final data, and state the precise coefficient condition for such an initial field to exist.

  2. Use initial fields ϕn\phi_n to show that uniqueness of backward reconstruction does not imply continuous dependence on final data in these norms.

  3. Suppose measurement noise in the final field has norm at most δ\delta. Reconstruct only modes 1,…,N1,\ldots,N and prove that the reconstructed noise has norm at most eN2Tδe^{N^2T}\delta. Show that this bound is sharp.

  4. For T=0.1T=0.1, δ=10−6\delta=10^{-6}, choose the largest integer NN certified to keep reconstructed noise below 0.010.01. Plot log⁡10\log_{10} of modal amplification against integer mode number, and explain why controlling noise alone does not bound the omitted true initial modes.

Original worksheet page 1: question and worked solution for 9-5-009
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Question 9 – Solution

Strategy. Each forward-decaying mode becomes an exponentially amplified mode when time is reversed.

Step 1: Characterize exact inversion. Forward evolution gives dn=cne−n2Td_n=c_ne^{-n^2T}, so the only possible coefficients are cn=en2Tdn\boxed{c_n=e^{n^2T}d_n}. Completeness implies at most one initial field. It exists in L2L^2 exactly when ∑n≥1e2n2T|dn|2<∞.\boxed{\sum_{n\ge 1}e^{2n^2T}|d_n|^2<\infty.} Indeed this condition constructs an L2L^2 sine expansion whose forward solution has the given coefficients. Arbitrary L2L^2 final data need not satisfy this stronger condition.

Step 2: Disprove continuity despite uniqueness. Take fn=ϕnf_n=\phi_n, whose initial norm is one. Its final field has norm e−n2T→0e^{-n^2T}\to 0. Thus final data tend to zero while their uniquely determined initial fields do not. The backward map on its attainable-data domain is not continuous at zero in the stated norms. No contradiction arises with the stable forward problem, which damps these same modes.

Step 3: Bound noise after truncating the inverse. Let ηn\eta_n be the noise coefficients, so ∑|ηn|2≤δ2\sum|\eta_n|^2\le\delta^2. The retained reconstructed noise satisfies ∥∑n=1Nen2Tηnϕn∥22=∑n=1Ne2n2T|ηn|2≤e2N2Tδ2.\left\|\sum_{n=1}^N e^{n^2T}\eta_n\phi_n\right\|_2^2 =\sum_{n=1}^N e^{2n^2T}|\eta_n|^2\le e^{2N^2T}\delta^2. Taking square roots gives the bound, attained by noise δϕN\delta\phi_N.

Step 4: Choose a noise cutoff and state its limitation. The requirement is e0.1N210−6<10−2e^{0.1N^2}10^{-6}<10^{-2}, or N2<40log⁡10N^2<40\log 10. Thus N=9\boxed{N=9} is the largest certified integer: the bounds for 9,109,10 are approximately 0.0032950.003295 and 0.0220270.022027. The plot uses discrete stems, since nn is an integer; their heights are 0.1n2/log⁡100.1n^2/\log 10. The omitted initial tail has norm (∑n>N|cn|2)1/2(\sum_{n>N}|c_n|^2)^{1/2}, for which no numerical bound was supplied. A noise cutoff controls amplification but requires additional prior information to control that approximation error.

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Original worksheet page 2: question and worked solution for 9-5-009

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