# Topological Quasilinear Spaces

Authors: Yılmaz Yılmaz; Sümeyye Çakan; Şahika Aytekin
Journal: Abstract and Applied Analysis
 (2012)

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## Abstract

We introduce, in this work, the notion of topological quasilinear spaces as a generalization of the notion of normed quasilinear spaces defined by Aseev (1986). He introduced a kind of the concept of a quasilinear spaces both including a classical linear spaces and also nonlinear spaces of subsets and multivalued mappings. Further, Aseev presented some basic quasilinear counterpart of linear functional analysis by introducing the notions of norm and bounded quasilinear operators and functionals. Our investigations show that translation may destroy the property of being a neighborhood of a set in topological quasilinear spaces in contrast to the situation in topological vector spaces. Thus, we prove that any topological quasilinear space may not satisfy the localization principle of topological vector spaces.


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## Body

## 1. Introduction

In [1], Aseev introduced the concept of quasilinear spaces both including classical linear spaces and modelling nonlinear spaces of subsets and multivalued mappings. Then, he proceeds a similar way to linear functional analysis on quasilinear spaces by introducing notions of the norm and quasilinear operators and functionals. Further, he presented some results which are quasilinear counterparts of fundamental definitions and theorems in linear functional analysis and differential calculus in Banach spaces. This pioneering work has motivated a lot of authors to introduce new results on multivalued mappings, fuzzy quasilinear operators, and set-valued analysis [2–4].One of the most useful example of a quasilinear space is the setKC(E) of all convex compact subsets of a normed space E. The investigation of this class involves convex and interval analysis. Intervals are excellent tools for handling global optimization problems and for supplementing standard techniques. This is because an interval is an infinite set and is thus a carrier of an infinite amount of information which means global information. We refer the reader to [5] for detailed information about global optimization related to interval analysis. Further, the theory of set differential equations also needs the analysis of KC(E) [3].There are various ways introducing and handling quasilinear spaces. Another important treatment is those of Markow's approach (see [6, 7]). However, we think that Aseev's treatment provides the most suitable base and necessary tools to proceed a similar analysis on quasilinear spaces to those of classical linear functional analysis. Further, it reflects more aspects of set-valued algebra and analysis by the advantages of the ordering relation. After the introduction of normed quasilinear spaces and bounded quasilinear operators in [1], we think that the investigation of quasilinear topologies on a quasilinear spaces and the introduction of some new results may provide important contributions to the improvement of the quasilinear functional analysis.


## 2. Preliminaries and Some New Results on Quasilinear Spaces

Let us start this section by giving some notation and preliminary results. We mainly follow the terminology of [1, 8]. For some topological space X, the notation 𝒩x stands for the family of all neighborhoods of an x∈X. Let X be a topological vector space (TVS, for short), x∈X and G⊂X. Then G∈𝒩x if and only if G-x∈𝒩0 and x-G∈𝒩0. This is the localization principle of TVSs.A setX  is called a quasilinear space(QLS, for short), [1], if a partial ordering relation “≤”, an algebraic sum operation, and an operation of multiplication by real numbers are defined in it in such way that the following conditions hold for any elements x,y,z,u∈X, and any real scalars α,β:
(2.1)x≤x,x≤zifx≤y,y≤z,x=yifx≤y,y≤x,x+y=y+x,x+(y+z)=(x+y)+z,thereexistsanelement0∈Xsuchthatx+0=x,α⋅(β⋅x)=(α⋅β)⋅x,α⋅(x+y)=α⋅x+α⋅y,1⋅x=x,0⋅x=0,(α+β)⋅x≤α⋅x+β⋅x,x+z≤y+vifx≤y,z≤v,α⋅x≤α⋅yifx≤y.A linear space is a QLS with the partial ordering relation “x≤y if and only if x=y”.Perhaps the most popular example of nonlinear QLSs is the set of all closed intervals of real numbers with the inclusion relation “⊆” , algebraic sum operation
(2.2)A+B={a+b:a∈A,b∈B},
and the real-scalar multiplication
(2.3)λA={λa:a∈A}.
We denote this set by KC(ℝ). Another one is K(ℝ), the set of all compact subsets of real numbers. In general, K(E) and KC(E) stand for the space of all nonempty closed bounded and nonempty convex and closed bounded subsets of any normed linear space E, respectively. Both are QLSs with the inclusion relation and with a slight modification of addition as follows:
(2.4)A+B={a+b:a∈A,b∈B}¯,
and with the real-scalar multiplication above.Hence,KC(E)={A∈K(E):A convex}.Lemma 2.1 (see [1]).
In a QLSX the element 0 is minimal, that is, x=0 if x≤0.Definition 2.2.
An elementx′∈X is called an inverse of an x∈X if x+x′=0. If an inverse element exists, then it is unique. An element x having an inverse is called regular; otherwise, it is called singular.We show later that the minimality is not only a property of0 but also is shared by the other regular elements.Lemma 2.3 (see [1]).
Suppose that each elementx in the QLS X has an inverse element x′∈X. Then the partial ordering in X is determined by equality, the distributivity conditions hold, and, consequently, X is a linear space.Corollary 2.4 (see [1]).
In a real linear space, equality is the only way to define a partial ordering such that conditions (2.1) hold.It will be assumed in what follows that-x=(-1)x. An element x in a QLS is regular if and only if x-x=0 if and only if x′=-x.Definition 2.5.
Suppose thatX is a QLS and Y⊆X. Y is called a subspace of X whenever Y is a quasilinear space with the same partial ordering and the same operations on X.Theorem 2.6.
Y is a subspace of a QLS X if and only if for every x,y∈Y and α,β∈ℝ, αx+βy∈Y.Proof of this theorem is quite similar to its classical linear algebraic counterpart.LetX be a QLS and Y be a subspace of X. Suppose that each element x in Y has an inverse element x′∈Y; then by Lemma 2.3 the partial ordering on Y is determined by the equality. In this case the distributivity conditions hold on Y, and Y is a linear subspace of X.Definition 2.7.
LetX be a QLS. An element x∈X   is said to be symmetric provided that -x=x, and Xb denotes the set of all such elements. Further, Xr and Xs stand for the sets of all regular and singular elements in X, respectively.Theorem 2.8.
X
r,Xd,  and Xs∪{0} are subspaces of X.Proof.
X
r is a subspace since the element λx′+y′ is the inverse of λx+y.
X
s
∪
{
0
} is a subspace of X. Let x,y∈Xs∪{0} and λ∈ℝ. The assertion is clear for x=y=0. Let x≠0 and suppose that (x+λy)∉Xs∪{0}, that is, (x+λy)+u=0 for some u∈X. Then x+(λy+u)=0 and so x′=λy+u. This implies that x∈Xr. Analogously we obtain y∈Xr if y≠0. This contradiction shows that x+λy∈Xs∪{0}.
The proof forXd is similar.X
r, Xd, and Xs∪{0} are called regular, symmetric, and singular subspaces of X, respectively.Example 2.9.
LetX=KC(ℝ) and Z={0}∪{[a,b]:a,b∈ℝ and a≠b}.  Z is the singular subspace of X. However, the set {{a}:a∈ℝ} of all singletons constitutes Xr and is a linear subspace of X. In fact, for any normed linear space E, each singleton {a}, a∈E is identified with a, and hence E is considered as the regular subspace of both KC(E) and K(E).Proposition 2.10.
In a quasilinear spaceX every regular element is minimal.Proof.
We must show thaty≤x implies that y=x for each x∈Xr. Consider
(2.5)y≤x⟹y+x′≤x+x′=0⟹y+x′≤0.
Hence y+x′=0 by the minimality of 0. This implies that y=x by the uniqueness of the inverse element.Example 2.11.
Consider again the subspaceZ of KC(ℝ) in the former example. {0} is the only minimal element in Z, and there is no else minimal element in Z.LetX be a quasilinear space. A real function ∥·∥X:X→ℝ is called a norm, [1], if the The following conditions are satisfied:
(2.6)‖x‖X>0ifx≠0;(2.7)‖x+y‖X≤‖x‖X+‖y‖X;(2.8)‖α⋅x‖X=|α|⋅‖x‖X;(2.9)ifx≤y,then‖x‖X≤‖y‖X;(2.10)ifforanyε>0thereexistsanelementxε∈Xsuchthat,(2.11)x≤y+xε,‖xε‖X≤εthenx≤y.A quasilinear spaceX with a norm defined on it is callednormed quasilinear space. It follows from Lemma 2.3 that if any x∈X has an inverse, then the concept of a normed quasilinear space coincides with the concept of a real normed linear space.Hausdorff metric or norm metric on a normed QLSX is defined by the following equality:
(2.12)hX(x,y)=inf⁡{r≥0:x≤y+a1r,y≤x+a2r,‖air‖≤r,i=1,2}.Sincex≤y+(x-y) and y≤x+(y-x), the quantity hX(x,y) is well defined  for any elements x,y∈X, further hX(x,y)≤∥x-y∥X [1]. It is not hard to see that hX(x,y) satisfies all of the metric axioms.Lemma 2.12 (see [1]).
The operations of algebraic operations of addition and scalar multiplication are continuous with respect to the Hausdorff metric. The norm is continuous function with respect to the Hausdorff metric.Lemma 2.132.13 (see [1]).
(a) Suppose thatxn→x0 and yn→y0, and that xn≤yn for any positive integer n. Then x0≤y0.  (b) Suppose that xn→x0 and zn→x0. If xn≤yn≤zn for any n, then yn→x0. (c) Suppose that xn+yn→x0 and yn→0; then xn→x0.Example 2.142.14 (see [1]).
LetX be a real complete normed linear space (a real Banach space). Then X is a complete normed quasilinear space with partial ordering given by equality. Conversely, if X is complete normed quasilinear space and any x∈X has an inverse element x′∈X, then X is a real Banach space, and the partial ordering on X is the equality. In this case hx(x,y)=∥x-y∥X. Note that  hX(x,y)≠∥x-y∥X for nonlinear QLSs, in general.Example 2.152.15 (see [1]).
For example, ifE is a Banach space, then a norm on K(E) is defined by ∥A∥K(E)=sup∥a∥E. Then K(E) and KC(E) are normed quasilinear spaces. In this case the Hausdorff metric is defined as usual:
(2.13)h(A,B)=inf⁡{r≥0:A⊆B+Sr(0),B⊆A+Sr(0)},
where Sr(0) stands for 0-centered closed ball with radius r in E.


## 3. Topological Quasilinear Spaces

Definition 3.1.
A topological quasilinear space (TQLS, for short)X is a topological space and a quasilinear space such that the algebraic operation of addition and scalar multiplication are continuous, and, following conditions are satisfied for any x,y∈X:
(3.1)foranyU∈N0,x≤yandy∈Uimpliesx∈U,(3.2)foranyU∈Nx,y∈U⟺thereexistssomeV∈N0satisfyingx+V⊆U,suchthatx≤y+aforsomea∈Vory≤x+bforsomeb∈V.
Any topologyτ, which makes (X,τ) be a topological quasilinear space, will be called a quasilinear topology. The conditions (3.1) and (3.2) provide necessary harmony of the topology with the ordering structure on X.Example 3.2.
LetX be a TVS. Then, for any x,y∈X and for any U∈𝒩x, y∈U if and only if there exists a neighborhood V of 0 satisfying x+V⊆U such that x=y+a for some a∈V or y=x+b for some b∈V. In fact, this is true by the localization principle of TVSs since U-x and x-U are neighborhood of 0. So we can obtain desired V by taking V=U-x or V=x-U. This provides the condition (3.2). Further, the condition (3.1) obviously holds. Hence, X is a TQLS.We later show that some TQLSs maynot satisfy the localization principle.Remark 3.3.
In condition (3.2), for some U∈𝒩x, we may find a V∈𝒩0 satisfying x+V⊆U such that both x≤y+a and y≤x+b for some a,b∈V. This comfortable situation depends on the selection of U. However, we may not find such a suitable V∈𝒩0 for some U∈𝒩x even in TVSs.Example 3.4.
Consider real numbers with usual metric. Takex=3, y=5, and U=[2,7]∈𝒩x. Then any V∈𝒩0 satisfying 3+V⊆U must be a subset of [-1,4]. Further 3=5+a and 5=3+b gives a=-2, b=2, and hence V can only include b.Remark 3.5.
In a semimetrizable TQLS the condition (3.1) and the condition (3.2) can be reformulated by balls as follows:
(3.3)foranyε>0,x≤yandy∈Sε(0)impliesx∈Sε(0);
equivalently,
(3.1′)x≤yimpliesd(x,0)≤d(y,0),foranyε>0,y∈Sε(x)⟺thereexistssomeSε(0),withx+Sε(0)⊆Sε(x)suchthatx≤y+aforsomea∈Sε(0),ory≤x+bforsomeb∈Sε(0).
A TQLS with a (semi)metrizable quasilinear topology will be called a(semi)metric QLS.Example 3.6.
Any normed QLS is a Hausdorff TQLS. By the definitiony∈Sε(x)⇔h(x,y)≤ε⇔x≤y+a and y≤x+b for some a,b∈Sε(0), whence the condition (3.2) holds.Proposition 3.7.
Let X be a Hausdorff TQLS andx,y∈X. If for any V∈𝒩0 there exists some b∈V such that x≤y+b, then x≤y.Proof.
Suppose that there exists someb∈V satisfying x≤y+b for every V∈𝒩0, but x≤y is not true. Then there exists distinct open neighborhoods Ux and Uy of x and y, respectively. Since x∉Uy, this implies by the condition (3.2) that for any V∈𝒩0 with the property y+V⊆Uy we cannot find b∈V satisfying x≤y+b. This is a contradiction to the hypothesis.Example 3.8.
In Proposition3.7, the condition “X is Hausdorff” is indispensable. Let us consider KC(ℝ2) and the function
(3.4)p(A)=sup⁡{|x1|:(x1,x2)∈A}
for some A∈KC(ℝ2). We can construct a topology τ on KC(ℝ2) by p in such a way that U∈τ if and only if U⊇{A:p(A)<ε} for some ε>0 (we later call p as a seminorm on KC(ℝ2)). τ is a semimetrizable topology by the semimetric
(3.5)d(A,B)=inf⁡{r≥0:A⊆B+C1r,B⊆A+C2r;p(Cir)≤r,i=1,2}.
Let
(3.6)A={(0,t)∈R2:0≤t≤1},B={(0,t)∈R2:0≤t≤2}.
Then, there is not separate neighborhoods of the points A and B of KC(ℝ2) in this topology. So, τ cannot be a Hausdorff topology. Now let ε>0 be arbitrary and define
(3.7)Bε={(x1,x2)∈R2:0≤x1≤ε,0≤x2≤1}.
Then for every V∈𝒩0 there exists some Bε∈V such that B⊆A+Bε. But, B⊈A.Theorem 3.9.
LetX be a TQLS. Then Xr and Xd are closed in X.Proof.
{
x
i
} is a net in Xr converging to an x∈X. By the continuity of algebraic operations -xi→-x and xi-xi→x-x. This means x-x=0 since xi-xi=0 for each i, whence x∈Xr. The proof is easier for Xd.The result of this theorem may not be true forXs∪{0}. Let X=KC(ℝ) and define xn=[1,1+1/n]∈Xs∪{0} for each n∈ℕ. Then xn→{1}∉Xs∪{0}.Definition 3.10.
LetX be a quasilinear space. A paranorm on X is a function p:X→ℝ satisfying the following conditions. For every x,y∈X,(1)
p(0)=0,(2)
p(x)≥0,(3)
p(-x)=p(x),(4)
p(x+y)≤p(x)+p(y),(5)
if{tn} is a sequence of scalars with tn→t and {xn}⊂ X with p(xn)→p(x), then p(tnxn)→p(tx) and (continuity of scalar multiplication),(6)
ifx≤y, then p(x)≤p(y).
The pair(X,p) with the function p satisfying the conditions (1)–(6) is called a paranormed QLS.It follows from Lemma2.3 that if any x∈X has an inverse element x′∈X, then the concept of paranormed quasilinear space coincides with the concept of a real paranormed linear space.The paranorm is calledtotal if, in addition, we have
(3.8)p(x)=0⟺x=0,ifforanyε>0thereexistsanelementxε∈Xsuchthat,x≤y+xεandp(xε)≤ε,thenx≤y.The equality(3.9)d(x,y)=inf⁡{r≥0:x≤y+a1r,y≤x+a2r,p(air)≤r}defines a semimetric on a paranormed quasilinear spaceX. d is metric whenever p is total.Example 3.11.
Let us prove the above assertion. First of all we should note thatd is well defined since x≤y+(x-y) and y≤x+(y-x) at least. Now x≤y and y≤x if x=y, and so x≤y+a1,  y≤x+a2 for a1=a2=0 that implies d(x,y)=0 since p(a1)=p(a2)=0. Obviously d is symmetric. Further, for every element a1r and b2r such that x≤z+a1r and z≤y+b2r, observe that x≤y+b2r+a1r. Similarly, y≤x+a2r+b1r for every a2r and b1r such that y≤z+b1r and z≤x+a2r. Since p(a1r+b2r)≤p(a1r)+p(b2r) and p(a2r+b1r)≤p(a2r)+p(b1r), we get d(x,y)≤d(x,z)+d(z,y) by the definition.
Letp be total and d(x,y)=0. Then for any ε>0 there exist elements xε1,xε2∈X such that x≤y+xε1, and y≤x+xε2, for p(xεi)≤ε, i=1,2. Hence the totality conditions imply that x≤y and y≤x, that is, x=y.Further, we have the inequalityd(x,y)≤p(x-y).Note that these definitions are inspired from the definitions in [1] about normed quasilinear spaces. The proofs of some facts given here are quite similar to that of Aseev's corresponding results.If the first condition in the definition of norm in a QLS is relaxed into the condition(3.10)‖x‖≥0ifx≠0
and if the condition (2.10) of norm is removed, we then obtain the definition of a seminorm. A quasilinear space with a seminorm is called a seminormed QLS. By the same way in linear spaces one can prove that a seminorm on a QLS is a paranorm. Thus we have the following implication chain among the kinds of QLSs:(normed)seminormed QLS⇒ (total paranormed)paranormed QLS ⇒ (metric)semimetric QLS ⇒ (Hausdorff)TQLS.Example 3.12.
LetX be a QLS. The discrete topology on X is not a quasilinear topology since the continuity of the scalar multiplication is not satisfied.Example 3.13.
The function(3.11)p(A)=sup⁡{|x1|:(x1,x2)∈A}
in Example 3.8 is a seminorm on KC(ℝ2). Further, the function
(3.12)q(A)=p(A)1+p(A)
is a paranorm on KC(ℝ2) but is not a seminorm.Definition 3.14.
Let(X,d) be a semimetric QLS and x be an element of X. Then, the nonnegative number
(3.13)ρ(x)=d(x-x,0)
is called diameter of x.For each regular elementx, ρ(x)=0 since x-x=0. Hence this definition is redundant in linear spaces. Further it should not be confused with the classical notion of the diameter of a subset in a semimetric space for which it is defined by δ(U)=supx,y∈Ud(x,y) for any U⊂X.For example, inKC(ℝ), [-1,3]∈KC(ℝ) and
(3.14)ρ([-1,3])=h([-1,3]-[-1,3],0)=h([-4,4],0)=‖[-4,4]‖=sup⁡a∈[-4,4]|a|=4.
However, for the (singleton) subset U={[-1,3]} of KC(ℝ), δ(U)=0.following result is half of the localization principle of TVSsTheorem 3.15.
LetX be a TQLS, x∈X,  and U is a set containing 0. If x+U∈𝒩x, then U∈𝒩0.Proof.
The proof is only an application of the fact that the translation operatorfx:X→X, fx(v)=v+x, is continuous by the continuity of the algebraic sum operation.Although the converse of this theorem is true in TVSs, it may not be true in some TQLSs.Example 3.16.
ConsiderKC(ℝ) again and its closed unit ball S1(0). Now, for x=[2,3]∈KC(ℝ), we show that x+S1(0) is not a neighborhood of x. A careful observation shows that x+S1(0) doesnot contain elements (intervals) for which the diameter is smaller than 1. However, every x-centered ball Sr(x) with radius r contains a singleton if r≥(ρ(x)/2)=1/2 and contains an interval such as [2+(r/2),3-(r/2)] if r<1/2 since
(3.15)h([2,3],[2+r2,3-r2])=r2<r.
That is, Sr(x) contains elements with diameter smaller than 1. However, neither a singleton nor such an element belongs to x+Sr(0). This implies that Sr(x)⊈x+Sr(0) for every r>0. Eventually, the set x+S1(0) cannot contain an x-centered ball.
Thus, the localization principle may not be satisfied about a singular element inKC(ℝ). The example alludes that translation by a singular element destroys the property of being a neighborhood in a TQLS. The following theorem states that the translation by a regular element preserves neighborhoods, and so the localization principle holds for these elements.Theorem 3.17.
Let X be a TQLS andx∈Xr. Then U∈𝒩0⇔x+U∈𝒩x.Proof.
Consider again the operatorfx in the proof of Theorem 3.15. In this case the inverse fx-1 exists and just is the continuous operator f-x. Hence fx is a homeomorphism and so preserves the neighborhoods.



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