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| In [[mathematics]], [[linear map]]s form an important class of "simple" [[function (mathematics)|functions]] which preserve the algebraic structure of [[linear space]]s and are often used as approximations to more general functions (see [[linear approximation]]). If the spaces involved are also [[topological space]]s (that is, [[topological vector space]]s), then it makes sense to ask whether all linear maps are [[continuous map|continuous]]. It turns out that for maps defined on infinite-[[dimension (linear algebra)|dimensional]] topological vector spaces (e.g., infinite-dimensional [[normed space]]s), the answer is generally no: there exist '''discontinuous linear maps'''. If the domain of definition is [[complete space|complete]], such maps can be proven to exist, but the proof relies on the [[axiom of choice]] and does not provide an explicit example.
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| == A linear map from a finite dimensional space is always continuous ==
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| Let ''X'' and ''Y'' be two normed spaces and ''f'' a linear map from ''X'' to ''Y''. If ''X'' is [[finite-dimensional]], choose a base (''e''<sub>1</sub>, ''e''<sub>2</sub>, …, ''e''<sub>''n''</sub>) in ''X'' which may be taken to be unit vectors. Then,
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| :<math>f(x)=\sum^n_{i=1}x_if(e_i),</math>
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| and so by the [[triangle inequality]],
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| :<math>\|f(x)\|= \left\|\sum^n_{i=1}x_if(e_i)\right\| \le \sum^n_{i=1} |x_i|\|f(e_i)\|.</math>
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| Letting
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| :<math>M=\sup_i \{\|f(e_i)\|\},</math>
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| and using the fact that
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| :<math>\sum^n_{i=1}|x_i|\le C \|x\|</math>
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| for some ''C''>0 which follows from the fact that any two norms on a finite-dimensional space are equivalent, one finds
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| :<math>\|f(x)\|\le \left(\sum^n_{i=1}|x_i|\right)M\le CM\|x\|.</math>
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| Thus, ''f'' is a [[bounded linear operator]] and so is continuous.
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| If ''X'' is infinite-dimensional, this proof will fail as there is no guarantee that the [[supremum]] ''M'' exists. If ''Y'' is the zero space {0}, the only map between ''X'' and ''Y'' is the zero map which is trivially continuous. In all other cases, when ''X'' is infinite dimensional and ''Y'' is not the zero space, one can find a discontinuous map from ''X'' to ''Y''.
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| == A concrete example ==
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| Examples of discontinuous linear maps are easy to construct in spaces that are not complete; on any Cauchy sequence of independent vectors which does not have a limit, a linear operator may grow without bound. In a sense, the linear operators are not continuous because the space has "holes".
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| For example, consider the space ''X'' of real-valued [[smooth function]]s on the interval [0, 1] with the [[uniform norm]], that is,
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| : <math>\|f\|=\sup_{x\in [0, 1]}|f(x)|.</math>
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| The ''[[derivative]] at a point'' map, given by | |
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| :<math>T(f)=f'(0)\,</math>
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| defined on ''X'' and with real values, is linear, but not continuous. Indeed, consider the sequence
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| :<math>f_n(x)=\frac{\sin (n^2 x)}{n} </math>
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| for ''n''≥1. This sequence converges uniformly to the constantly zero function, but
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| :<math>T(f_n)=\frac{n^2\cos(n^2 \cdot 0)}{n}=n\to \infty</math>
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| as ''n''→∞ instead of <math>T(f_n)\to T(0)=0</math> which would hold for a continuous map. Note that ''T'' is real-valued, and so is actually a [[linear functional]] on ''X'' (an element of the algebraic [[dual space]] ''X''<sup>*</sup>). The linear map ''X'' → ''X'' which assigns to each function its derivative is similarly discontinuous. Note that although the derivative operator is not continuous, it is [[closed operator|closed]].
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| The fact that the domain is not complete here is important. Discontinuous operators on complete spaces require a little more work.
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| == A nonconstructive example ==
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| An algebraic basis for the [[real number]]s as a vector space over the [[rationals]] is known as a [[Hamel basis]] (note that some authors use this term in a broader sense to mean an algebraic basis of ''any'' vector space). Note that any two [[commensurability (mathematics)|noncommensurable]] numbers, say 1 and π, are linearly independent. One may find a Hamel basis containing them, and define a map ''f'' from '''R''' to '''R''' so that ''f''(π) = 0, ''f'' acts as the identity on the rest of the Hamel basis, and extend to all of '''R''' by linearity. Let {''r''<sub>''n''</sub>}<sub>''n''</sub> be any sequence of rationals which converges to π. Then lim<sub>''n''</sub> ''f''(''r''<sub>''n''</sub>) = π, but ''f''(π) = 0. By construction, ''f'' is linear over '''Q''' (not over '''R'''), but not continuous. Note that ''f'' is also not [[measurable function|measurable]]; an [[Additive function|additive]] real function is linear if and only if it is measurable, so for every such function there is a [[Vitali set]]. The construction of ''f'' relies on the axiom of choice.
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| This example can be extended into a general theorem about the existence of discontinuous linear maps on any infinite-dimensional normed space (as long as the codomain is not trivial).
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| == General existence theorem ==
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| Discontinuous linear maps can be proven to exist more generally even if the space is complete. Let ''X'' and ''Y'' be [[normed space]]s over the field ''K'' where ''K'' = '''R''' or ''K'' = '''C'''. Assume that ''X'' is infinite-dimensional and ''Y'' is not the zero space. We will find a discontinuous linear map ''f'' from ''X'' to ''K'', which will imply the existence of a discontinuous linear map ''g'' from ''X'' to ''Y'' given by the formula ''g''(''x'') = ''f''(''x'')''y''<sub>0</sub> where ''y''<sub>0</sub> is an arbitrary nonzero vector in ''Y''.
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| If ''X'' is infinite-dimensional, to show the existence of a linear functional which is not continuous then amounts to constructing ''f'' which is not bounded. For that, consider a [[sequence]] (''e''<sub>''n''</sub>)<sub>''n''</sub> (''n'' ≥ 1) of [[linearly independent]] vectors in ''X''. Define
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| :<math>T(e_n)=n\|e_n\|\,</math>
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| for each ''n'' = 1, 2, ... Complete this sequence of linearly independent vectors to a [[basis (vector space)|vector space basis]] of ''X'', and define ''T'' at the other vectors in the basis to be zero. ''T'' so defined will extend uniquely to a linear map on ''X'', and since it is clearly not bounded, it is not continuous.
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| Notice that by using the fact that any set of linearly independent vectors can be completed to a basis, we implicitly used the axiom of choice, which was not needed for the concrete example in the previous section.
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| == Axiom of choice ==
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| As noted above, the [[axiom of choice]] (AC) is used in the general existence theorem of discontinuous linear maps. In fact, there are no constructive examples of discontinuous linear maps with complete domain (for example, [[Banach space]]s). In analysis as it is usually practiced by working mathematicians, the axiom of choice is always employed (it is an axiom of [[ZFC]] [[set theory]]); thus, to the analyst, all infinite dimensional topological vector spaces admit discontinuous linear maps.
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| On the other hand, in 1970 [[Robert M. Solovay]] exhibited a [[model (model theory)|model]] of [[set theory]] in which every set of reals is measurable.<ref>{{citation
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| | last = Solovay | first = Robert M. | authorlink = Robert M. Solovay
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| | journal = [[Annals of Mathematics]]
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| | mr = 0265151
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| | pages = 1–56
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| | series = Second Series
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| | title = A model of set-theory in which every set of reals is Lebesgue measurable
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| | volume = 92
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| | year = 1970}}.</ref> This implies that there are no discontinuous linear real functions. Clearly AC does not hold in the model.
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| Solovay's result shows that it is not necessary to assume that all infinite-dimensional vector spaces admit discontinuous linear maps, and there are schools of analysis which adopt a more [[constructivism (mathematics)|constructivist]] viewpoint. For example H. G. Garnir, in searching for so-called "dream spaces" (topological vector spaces on which every linear map into a normed space is continuous), was led to adopt ZF + [[dependent choice|DC]] + [[Baire property|BP]] (dependent choice is a weakened form and the [[Baire property]] is a negation of strong AC) as his axioms to prove the [[Garnir–Wright closed graph theorem]] which states, among other things, that any linear map from an [[F-space]] to a TVS is continuous. Going to the extreme of [[Constructivism (mathematics)|constructivism]], there is [[Ceitin's theorem]], which states that ''every'' function is continuous (this is to be understood in the terminology of constructivism, according to which only representable functions are considered to be functions).<ref>{{citation|title=Handbook of Analysis and Its Foundations|first=Eric|last=Schechter|publisher=Academic Press|year=1996|isbn=9780080532998|page=136|url=http://books.google.com/books?id=eqUv3Bcd56EC&pg=PA136}}.</ref> Such stances are held by only a small minority of working mathematicians.
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| The upshot is that it is not possible to obviate the need for AC; it is consistent with set theory without AC that there are no discontinuous linear maps. A corollary is that constructible discontinuous operators such as the derivative cannot be everywhere-defined on a complete space.
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| == Closed operators ==
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| Many naturally occurring linear discontinuous operators occur are [[closed operator|closed]], a class of operators which share some of the features of continuous operators. It makes sense to ask the analogous question about whether all linear operators on a given space are closed. The [[closed graph theorem]] asserts that all everywhere-defined closed operators on a complete domain are continuous, so in the context of discontinuous closed operators, one must allow for operators which are not defined everywhere. Among operators which are not everywhere-defined, one can consider densely defined operators without loss of generality.
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| Thus let <math>T</math> be a map <math>X\to Y</math> with domain <math>\operatorname{Dom}(T)</math>. The graph <math>\Gamma(T)</math> of an operator <math>T</math> which is not everywhere-defined will admit a distinct closure <math>\overline{\Gamma(T)}</math>. If the closure of the graph is itself the graph of some operator <math>\overline{T}</math>, <math>T</math> is called closable, and <math>\overline{T}</math> is called the closure of <math>T</math>.
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| So the right question to ask about linear operators that are densely defined is whether they are closable. The answer is, "not necessarily;" one can prove that every infinite-dimensional normed space admits a nonclosable linear operator. The proof requires the axiom of choice and so is in general nonconstructive, though again, if ''X'' is not complete, there are constructible examples.
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| In fact, an example of a linear operator whose graph has closure ''all'' of ''X''×''Y'' can be given. Such an operator is not closable. Let ''X'' be the space of [[polynomial function]]s from [0,1] to '''R''' and ''Y'' the space of polynomial functions from [2,3] to '''R'''. They are subspaces of ''C''([0,1]) and ''C''([2,3]) respectively, and so normed spaces. Define an operator ''T'' which takes the polynomial function ''x'' ↦ ''p''(''x'') on [0,1] to the same function on [2,3]. As a consequence of the [[Stone–Weierstrass theorem]], the graph of this operator is dense in ''X''×''Y'', so this provides a sort of maximally discontinuous linear map (confer [[nowhere continuous function]]). Note that ''X'' is not complete here, as must be the case when there is such a constructible map.
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| == Impact for dual spaces ==
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| The [[dual space]] of a topological vector space is the collection of continuous linear maps from the space into the underlying field. Thus the failure of some linear maps to be continuous for infinite-dimensional normed spaces implies that for these spaces, one needs to distinguish the algebraic dual space from the continuous dual space which is then a proper subset. It illustrates the fact that an extra dose of caution is needed in doing analysis on infinite-dimensional spaces as compared to finite-dimensional ones.
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| == Beyond normed spaces ==
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| The argument for the existence of discontinuous linear maps on normed spaces can be generalized to all metrisable topological vector spaces, especially to all Fréchet-spaces, but there exist infinite dimensional locally convex topological vector spaces such that every functional is continuous. On the other hand, the [[Hahn–Banach theorem]], which applies to all locally convex spaces, guarantees the existence of many continuous linear functionals, and so a large dual space. In fact, to every convex set, the [[Minkowski gauge]] associates a continuous [[linear functional]]. The upshot is that spaces with fewer convex sets have fewer functionals, and in the worst case scenario, a space may have no functionals at all other than the zero functional. This is the case for the [[Lp space|''L''<sup>''p''</sup>('''R''',''dx'')]] spaces with 0 < ''p'' < 1, from which it follows that these spaces are nonconvex. Note that here is indicated the [[Lebesgue measure]] on the real line. There are other ''L''<sup>''p''</sup> spaces with 0 < ''p'' < 1 which do have nontrivial dual spaces.
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| Another such example is the space of real-valued [[measurable function]]s on the unit interval with [[quasinorm]] given by
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| :<math>||f|| = \int_I \frac{|f(x)|}{1+|f(x)|}dx.</math>
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| This non-locally convex space has a trivial dual space.
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| One can consider even more general spaces. For example, the existence of a homomorphism between complete separable metric [[group (mathematics)|group]]s can also be shown nonconstructively.
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| ==Notes==
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| {{reflist}}
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| ==References==
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| * Constantin Costara, Dumitru Popa, ''Exercises in Functional Analysis'', Springer, 2003. ISBN 1-4020-1560-7.
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| * Schechter, Eric, ''Handbook of Analysis and its Foundations'', Academic Press, 1997. ISBN 0-12-622760-8.
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| {{Functional Analysis}}
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| [[Category:Functional analysis]]
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| [[Category:Functions and mappings]]
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