All posts by Jean-Pierre Merx

A non-measurable set

We describe here a non-measurable subset of the segment I=[0,1]R.

Let’s define on I an equivalence relation by xy if and only if xyQ. The equivalence relation induces equivalence classes on I. For xI, it’s equivalence class [x] is [x]={yI : yxQ}. By the Axiom of Choice, we can form a set A by selecting a single point from each equivalence class.

We claim that the set A is not Lebesgue measurable.

For all qQ we denote Aq={q+x :xA}. Let’s take p,qQ. If it exists zApAq, it means that there exist u,vA such that
z=p+u=q+v hence uv=qp=0 as u,v are supposed to be unique representatives of the classes of the equivalence relation . Finally if p,q are distincts, ApAq=.

As Lebesgue measure μ is translation invariant, we have for qQ[0,1] : μ(A)=μ(Aq) and also Aq[0,2]. Hence if we denote
B=qQ[0,1]Aq we have B[0,2]. If we suppose that A is measurable, we get
μ(B)=qQ[0,1]μ(Aq)=qQ[0,1]μ(A)2 by countable additivity of Lebesgue measure (the set Q[0,1] being countable infinite). This implies μ(A)=0.

Let’s prove now that
[0,1]qQ[1,1]Aq For z[0,1], there exists uA such that z[u]. As A[0,1], we have q=zuQ and 1q1. And z=q+u means that zAq. This proves the inclusion. However the inclusion implies the contradiction
1=μ([0,1])qQ[1,1]μ(Aq)=qQ[1,1]μ(A)=0

Finally A is not Lebesgue measurable.

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

Counterexample around Morera’s theorem

Let’s recall Morera’s theorem.

Morera’s theorem
Suppose that f is a continuous complex-valued function in a connected open set ΩC such that
Δf(z) dz=0 for every closed triangle ΔΩ{p} where pΩ. Then f is holomorphic in Ω.

Does the conclusion of Morera’s theorem still hold if f is supposed to be continuous only in Ω{p}? The answer is negative and we provide a counterexample.

Let Ω be the entire complex plane, f defined as follows
f(z)={1z2if z00otherwise and p the origin.

For a,bΩ{0} we have
[a,b]f(z) dz=[a,b]dzz2=10ba[a+t(ba)]2 dt=[1a+t(ba)]10=1a1b

Hence for a triangle Δ with vertices at a,b,cΩ{0}:
Δf(z) dz=(1a1b)+(1b1c)+(1c1a)=0

However, f is not holomorphic in Ω as it is even not continuous at 0.

Continuity versus uniform continuity

We consider real-valued functions.

A real-valued function f:IR (where I is an interval) is continuous at x0I when: (ϵ>0)(δ>0)(xI)(|xx0|δ|f(x)f(x0)|ϵ). When f is continuous at all xI, we say that f is continuous on I.

f:IR is said to be uniform continuity on I if (ϵ>0)(δ>0)(x,yI)(|xy|δ|f(x)f(y)|ϵ).

Obviously, a function which is uniform continuous on I is continuous on I. Is the converse true? The answer is negative.

An (unbounded) continuous function which is not uniform continuous

The map f:RRxx2 is continuous. Let’s prove that it is not uniform continuous. For 0<x<y we have |f(x)f(y)|=y2x2=(yx)(y+x)2x(yx) Hence for yx=δ>0 and x=1δ we get
|f(x)f(y)|2x(yx)=2>1 which means that the definition of uniform continuity is not fulfilled for ϵ=1.

For this example, the function is unbounded as limxx2=. Continue reading Continuity versus uniform continuity

Around binary relations on sets

We are considering here binary relations on a set A. Let’s recall that a binary relation R on A is a subset of the cartesian product RA×A. The statement (x,y)R is read as x is R-related to y and also denoted by xRy.

Some importants properties of a binary relation R are:

reflexive
For all xA it holds xRy
irreflexive
For all xA it holds not xRy
symmetric
For all x,yA it holds that if xRy then yRx
antisymmetric
For all x,yA if xRy and yRx then x=y
transitive
For all x,y,zA it holds that if xRy and yRz then xRz

A relation that is reflexive, symmetric and transitive is called an equivalence relation. Let’s see that being reflexive, symmetric and transitive are independent properties.

Symmetric and transitive but not reflexive

We provide two examples of such relations. For the first one, we take for A the set of the real numbers R and the relation R={(x,y)R2|xy>0}. R is symmetric as the multiplication is also symmetric. R is also transitive as if xy>0 and yz>0 you get xy2z>0. And as y2>0, we have xz>0 which means that xRz. However, R is not reflexive as 0R0 doesn’t hold.

For our second example, we take A=N and R={(1,1)}. It is easy to verify that R is symmetric and transitive. However R is not reflexive as nRn doesn’t hold for n1. Continue reading Around binary relations on sets

A proper subspace without an orthogonal complement

We consider an inner product space V over the field of real numbers R. The inner product is denoted by ,.

When V is a finite dimensional space, every proper subspace FV has an orthogonal complement F with V=FF. This is no more true for infinite dimensional spaces and we present here an example.

Consider the space V=C([0,1],R) of the continuous real functions defined on the segment [0,1]. The bilinear map
,:V×VR(f,g)f,g=10f(t)g(t)dt is an inner product on V.

Let’s consider the proper subspace H={fV;f(0)=0}. H is an hyperplane of V as H is the kernel of the linear form φ:ff(0) defined on V. H is a proper subspace as φ is not always vanishing. Let’s prove that H={0}.

Take gH. By definition of H we have 10f(t)g(t)dt=0 for all fH. In particular the function h:ttg(t) belongs to H. Hence
0=h,g=10tg(t)g(t)dt The map ttg2(t) is continuous, non-negative on [0,1] and its integral on this segment vanishes. Hence tg2(t) is always vanishing on [0,1], and g is always vanishing on (0,1]. As g is continuous, we finally get that g=0.

H doesn’t have an orthogonal complement.

Moreover we have
(H)={0}=VH

A non-compact closed ball

Consider a normed vector space (X,). If X is finite-dimensional, then a subset YX is compact if and only if it is closed and bounded. In particular a closed ball Br[a]={xX;xar} is always compact if X is finite-dimensional.

What about infinite-dimensional spaces?

The space A=C([0,1],R)

Consider the space A=C([0,1],R) of the real continuous functions defined on the interval [0,1] endowed with the sup norm:
f=supx[0,1]|f(x)|
Is the closed unit ball B1[0] compact? The answer is negative and we provide two proofs.

The first one is based on open covers. For n1, we denote by fn the piecewise linear map defined by {fn(0)=fn(12n12n+2)=0fn(12n)=1fn(12n+12n+2)=fn(1)=0 All the fn belong to B1[0]. Moreover for 1n<m we have 12n+12n+2<12m12m+2. Hence the supports of the fn are disjoint and fnfm=1.

Now consider the open cover U={B12(x);xB1[0]}. For xB1[0]} and u,vB12(x), uv<1. Therefore, each B12(x) contains at most one fn and a finite subcover of U will contain only a finite number of fn proving that A is not compact.

Second proof based on convergent subsequence. As A is a metric space, it is enough to prove that A is not sequentially compact. Consider the sequence of functions gn:xxn. The sequence is bounded as for all nN, gn=1. If (gn) would have a convergent subsequence, the subsequence would converge pointwise to the function equal to 0 on [0,1) and to 1 at 1. As this function is not continuous, (gn) cannot have a subsequence converging to a map gA.

Riesz’s theorem

The non-compactness of A=C([0,1],R) is not so strange. Based on Riesz’s lemma one can show that the unit ball of an infinite-dimensional normed space X is never compact. This is sometimes known as the Riesz’s theorem.

The non-compactness of A=C([0,1],R) is just standard for infinite-dimensional normed vector spaces!

Continuity under the integral sign

We consider here a measure space (Ω,A,μ) and TR a topological subspace. For a map f:T×ΩR such that for all tT the map f(t,):ΩRωf(t,ω) is integrable, one can define the function F:TRtΩf(t,ω) dμ(ω)

Following theorem is well known (and can be proven using dominated convergence theorem):

THEOREM for an adherent point xT, if

  • ωΩlimtxf(t,ω)=φ(ω)
  • There exists a map g:ΩR such that tT,ωΩ, |f(t,ω)|g(ω)

then φ is integrable and limtxF(t)=Ωφ(ω) dμ(ω)
In other words, one can switch lim and signs.

We provide here a counterexample showing that the conclusion of the theorem might not hold if f is not bounded by a function g as supposed in the premises of the theorem. Continue reading Continuity under the integral sign

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)