Tag Archives: maps

On limit at infinity of functions and their derivatives

We consider continuously differentiable real functions defined on (0,) and the limits limxf(x) and limxf(x).

A map f such that limxf(x)= and limxf(x)=0

Consider the map f:xx. It is clear that limxf(x)=. As f(x)=12x, we have as announced limxf(x)=0

A bounded map g having no limit at infinity such that limxg(x)=0

One idea is to take an oscillating map whose wavelength is increasing to . Let’s take the map g:xcosx. g doesn’t have a limit at as for nN, we have g(n2π2)=cosnπ=(1)n. However, the derivative of g is g(x)=sinx2x, and as |g(x)|12x for all x(0,), we have limxg(x)=0.

Non linear map preserving Euclidean norm

Let V be a real vector space endowed with an Euclidean norm .

A bijective map T:VV that preserves inner product , is linear. Also, Mazur-Ulam theorem states that an onto map T:VV which is an isometry (T(x)T(y)=xy for all x,yV) and fixes the origin (T(0)=0) is linear.

What about an application that preserves the norm (T(x)=x for all xV)? T might not be linear as we show with following example:T:VVxxif x1xxif x=1

It is clear that T preserves the norm. However T is not linear as soon as V is not the zero vector space. In that case, consider x0 such that x0=1. We have:{T(2x0)=2x0 as 2x0=2whileT(x0)+T(x0)=x0+(x0)=2x0

Non linear map preserving orthogonality

Let V be a real vector space endowed with an inner product ,.

It is known that a bijective map T:VV that preserves the inner product , is linear.

That might not be the case if T is supposed to only preserve orthogonality. Let’s consider for V the real plane R2 and the map T:R2R2(x,y)(x,y)for xy0(x,0)(0,x)(0,y)(y,0)

The restriction of T to the plane less the x-axis and the y-axis is the identity and therefore is bijective on this set. Moreover T is a bijection from the x-axis onto the y-axis, and a bijection from the y-axis onto the x-axis. This proves that T is bijective on the real plane.

T preserves the orthogonality on the plane less x-axis and y-axis as it is the identity there. As T swaps the x-axis and the y-axis, it also preserves orthogonality of the coordinate axes. However, T is not linear as for non zero xy we have: {T[(x,0)+(0,y)]=T[(x,y)]=(x,y)whileT[(x,0)]+T[(0,y)]=(0,x)+(y,0)=(y,x)

A linear map having all numbers as eigenvalue

Consider a linear map φ:EE where E is a linear space over the field C of the complex numbers. When E is a finite dimensional vector space of dimension n1, the number of eigenvalues is finite. The eigenvalues are the roots of the characteristic polynomial χφ of φ. χφ is a complex polynomial of degree n1. Therefore the set of eigenvalues of φ is non-empty and its cardinal is less than n.

Things are different when E is an infinite dimensional space.

A linear map having all numbers as eigenvalue

Let’s consider the linear space E=C([0,1]) of smooth complex functions having derivatives of all orders and defined on the segment [0,1]. E is an infinite dimensional space: it contains all the polynomial maps.

On E, we define the linear map φ:C([0,1])C([0,1])ff

The set of eigenvalues of φ is all C. Indeed, for λC the map teλt is an eigenvector associated to the eigenvalue λ.

A linear map having no eigenvalue

On the same linear space E=C([0,1]), we now consider the linear map ψ:C([0,1])C([0,1])fxf

Suppose that λC is an eigenvalue of ψ and hE an eigenvector associated to λ. By hypothesis, there exists x0[0,1] such that h(x0)0. Even better, as h is continuous, h is non-vanishing on J[0,1] where J is an open interval containing x0. On J[0,1] we have the equality (ψ(h))(x)=xh(x)=λh(x) Hence x=λ for all xJ[0,1]. A contradiction proving that ψ has no eigenvalue.

A strictly increasing map that is not one-to-one

Consider two partially ordered sets (E,) and (F,) and a strictly increasing map f:EF. If the order (E,) is total, then f is one-to-one. Indeed for distinct elements x,yE, we have either x<y or y<x and consequently f(x)<f(y) or f(y)<f(x). Therefore f(x) and f(y) are different. This is not true anymore for a partial order (E,). We give a counterexample.

Consider a finite set E having at least two elements and partially ordered by the inclusion. Let f be the map defined on the powerset (E) that maps AE to its cardinal |A|. f is obviously strictly increasing. However f is not one-to-one as for distincts elements a,bE we have f({a})=1=f({b})

Radius of convergence of power series

We look here at the radius of convergence of the sum and product of power series.

Let’s recall that for a power series n=0anxn where 0 is not the only convergence point, the radius of convergence is the unique real 0<R such that the series converges whenever |x|<R and diverges whenever |x|>R.

Given two power series with radii of convergence R1 and R2, i.e.
f1(x)=n=0anxn, |x|<R1f2(x)=n=0bnxn, |x|<R2 The sum of the power series f1(x)+f2(x)=n=0anxn+n=0bnxn=n=0(an+bn)xn and its Cauchy product:
f1(x)f2(x)=(n=0anxn)(n=0bnxn)=n=0(nl=0albnl)xn
both have radii of convergence greater than or equal to min{R1,R2}.

The radii can indeed be greater than min{R1,R2}. Let’s give examples.
Continue reading Radius of convergence of power series

Isometric versus affine

Throughout this article we let E and F denote real normed vector spaces. A map f:EF is an isometry if f(x)f(y)=xy for all x,yE, and f is affine if f((1t)a+tb)=(1t)f(a)+tf(b) for all a,bE and t[0,1]. Equivalently, f is affine if the map T:EF, defined by T(x)=f(x)f(0) is linear.

First note that an isometry f is always one-to-one as f(x)=f(y) implies 0=f(x)f(y)=xy hence x=y.

There are two important cases when every isometry is affine:

  1. f is bijective (equivalently surjective). This is Mazur-Ulam theorem, which was proven in 1932.
  2. F is a strictly convex space. Recall that a normed vector space (S,) is strictly convex if and only if for all distinct x,yS, x=y=1 implies x+y2<1. For example, an inner product space is strictly convex. The sequence spaces p for 1<p< are also strictly convex.

Continue reading Isometric versus affine

A trigonometric series that is not a Fourier series (Lebesgue-integration)

We already provided here an example of a trigonometric series that is not the Fourier series of a Riemann-integrable function (namely the function xn=1sinnxn).

Applying an Abel-transformation (like mentioned in the link above), one can see that the function f(x)=n=2sinnxlnn is everywhere convergent. We now prove that f cannot be the Fourier series of a Lebesgue-integrable function. The proof is based on the fact that for a 2π-periodic function g, Lebesgue-integrable on [0,2π], the sum n=1cncnn is convergent where (cn)nZ are the complex Fourier coefficients of g: cn=12π2π0g(t)eikt dt. As the series n=21nlnn is divergent, we will be able to conclude that the sequence defined by γ0=γ1=γ1=0,γn=γn=1lnn (n2) cannot be the Fourier coefficients of a Lebesgue-integrable function, hence that f is not the Fourier series of any Lebesgue-integrable function. Continue reading A trigonometric series that is not a Fourier series (Lebesgue-integration)

A trigonometric series that is not a Fourier series (Riemann-integration)

We’re looking here at convergent trigonometric series like f(x)=a0+k=1(ancosnx+bnsinnx) which are convergent but are not Fourier series. Which means that the terms an and bn cannot be writtenan=1π2π0g(t)cosntdt(n=0,1,)bn=1π2π0g(t)sinntdt(n=1,2,) where g is any integrable function.

This raises the question of the type of integral used. We cover here an example based on Riemann integral. I’ll cover a Lebesgue integral example later on.

We prove here that the function f(x)=n=1sinnxn is a convergent trigonometric series but is not a Fourier series. Continue reading A trigonometric series that is not a Fourier series (Riemann-integration)

Counterexamples around Dini’s theorem

In this article we look at counterexamples around Dini’s theorem. Let’s recall:

Dini’s theorem: If K is a compact topological space, and (fn)nN is a monotonically decreasing sequence (meaning fn+1(x)fn(x) for all nN and xK) of continuous real-valued functions on K which converges pointwise to a continuous function f, then the convergence is uniform.

We look at what happens to the conclusion if we drop some of the hypothesis.

Cases if K is not compact

We take K=(0,1), which is not closed equipped with the common distance. The sequence fn(x)=xn of continuous functions decreases pointwise to the always vanishing function. But the convergence is not uniform because for all nN supx(0,1)xn=1

The set K=R is closed but unbounded, hence also not compact. The sequence defined by fn(x)={0for x<nxnnfor nx<2n1for x2n is continuous and monotonically decreasing. It converges to 0. However, the convergence is not uniform as for all nN: sup{fn(x):xR}=1. Continue reading Counterexamples around Dini’s theorem