Solutions

Solutions to exercises from Chapter 1

Solution to Exercise 1.1. Let us establish existence and uniqueness of the point of minimum.

  1. 1) Existence of the point of minimum follows from section 1.4, because the particular form of the kernel z(t, s) was never used in the proof.
  2. 2) Similarly, uniqueness can be obtained in the same way as it was done in section 1.6. However, we put a short proof of uniqueness here.

Note that f(a) ≥ 0 for all aL2([0,1]). Hence, the functionals f(a) and (f(a))2 reach their minima on the same set of points.

Suppose that f(a) reaches minimum at points a1 and a0 with essentially different functions a1 and a0, which means that ||a1a0|| > 0; here, all norms are in L2([0, 1]). Then, images and images (min f)2.

If is easy to show that f2(a) is a convex function of a, and images z(1, •)||2 is a strictly convex function of a. The convexity of f2(a) follows from the facts that square function is convex and increasing in the range of f(a) and the functional f(a) is convex due to Lemma 1.4. The strict convexity of images follows from Remark 1.8.

From the convexity and strong convexity, it follows that for any point at = ta1 + (1 — t)a0, t ∈ (0, 1), we have

images

whence

images

Thus, for every point at, t ∈ (0,1), the function f reaches its minimum at at while images. This is contrary to the assumption that for every function a where f(a) reaches minimum, ga(1) = f(a).

Solution to Exercise 1.2. We give the solution only for the second statement.

  1. 2) Note that the kernel of the Riemann–Liouville process is (β—1)-homogeneous, namely for any c > 0
images

Let us establish that our kernel satisfies the assumption of Exercise 1.1. Suppose that the functional f reaches minimum at some point aL2([0,1]). So, we need to check that ga(1) = f(a). Suppose the opposite is true, ga(1) < f(a), and try to obtain a contradiction. To this end, extend the function a from [0, 1] to [0, +∞), by adding it as follows:

images

This allows us to consider ga(t) for t > 1. Prove the following property of semicontinuity:

Indeed, for t > 0

images

Due to the mean-square continuity of the Riemann–Liouville process, images tends to 0 as t → 1. Hence

images

whence [S.1] follows.

Recall our assumption ga(1) < f(a). Since

images

which holds true due to [S.1], and

images

which is the definition of f(a), c > 1 exists such that

Define a function

images

Then

images

With [S.2], we have

images

However, the functional f reaches its minimal value at point a. Hence

Since f(a) ≥ 0 and c1−2β < 0, inequality [S.3] is possible only if f(a) = 0. However, as ga(1) ≥ 0, this contradicts to assumption ga(1) < f(a).

We have verified the assumption from item 2 of Exercise 1.1. Now, apply Exercise 1.1 to prove the desired uniqueness.

REMARK S.1.– In the solution above, the function ga(t) is in fact continuous on [0, +∞).

Solution to Exercise 1.3. First, let us prove the inequality

[s.4] images

Indeed, apply inequality [1.15]:

images

Now, for N = 3, create a matrix

and verify that the functional F reaches its minimum at multiple points. Hence, let us prove that

images

Indeed, for every images

images

Thus, 1 is a lower bound for F(a):

Now evaluate f(a) for a = (2,1,1) and for a = (2, 1, 2):

From [S.6] and [S.7], it follows that images. Finally,

images

and the minimum of F is reached at two different points.

REMARK S.2.– For the matrix K defined in [S.5], the set of all points, where the minimum of F is reached, is a line segment in images:

images

REMARK S.3.– The N × N matrix K for which the functional F reaches minimum at multiple points can be constructed for any N ≥ 3.

For N =1, the minimum of F is reached at the unique point a = (k11).

For N = 2, the minimum of F is reached at the unique point images

Solutions to exercises from Chapter 2

Solution to Exercise 2.6. We have obvious inequalities

images

On the left-hand side, the minimum is reached for images (see the proof of Theorem 2.7). The right-hand side is equal to images. Thus,

images

In section 2.1.6.2, we showed that if images images. In this case

images

and inequality [2.83] becomes

images

Solutions to exercises from Chapter 3

Solution to Exercise 3.3. By Stirling’s formula [3.51],

images

since images and images. Now the required result follows from the representation

images

see [A1.18].

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