(This is an extended blog post version of my talk “Ultraproducts as a Bridge Between Discrete and Continuous Analysis” that I gave at the Simons institute for the theory of computing at the workshop “Neo-Classical methods in discrete analysis“. Some of the material here is drawn from previous blog posts, notably “Ultraproducts as a bridge between hard analysis and soft analysis” and “Ultralimit analysis and quantitative algebraic geometry“‘. The text here has substantially more details than the talk; one may wish to skip all of the proofs given here to obtain a closer approximation to the original talk.)
Discrete analysis, of course, is primarily interested in the study of discrete (or “finitary”) mathematical objects: integers, rational numbers (which can be viewed as ratios of integers), finite sets, finite graphs, finite or discrete metric spaces, and so forth. However, many powerful tools in mathematics (e.g. ergodic theory, measure theory, topological group theory, algebraic geometry, spectral theory, etc.) work best when applied to continuous (or “infinitary”) mathematical objects: real or complex numbers, manifolds, algebraic varieties, continuous topological or metric spaces, etc. In order to apply results and ideas from continuous mathematics to discrete settings, there are basically two approaches. One is to directly discretise the arguments used in continuous mathematics, which often requires one to keep careful track of all the bounds on various quantities of interest, particularly with regard to various error terms arising from discretisation which would otherwise have been negligible in the continuous setting. The other is to construct continuous objects as limits of sequences of discrete objects of interest, so that results from continuous mathematics may be applied (often as a “black box”) to the continuous limit, which then can be used to deduce consequences for the original discrete objects which are quantitative (though often ineffectively so). The latter approach is the focus of this current talk.
The following table gives some examples of a discrete theory and its continuous counterpart, together with a limiting procedure that might be used to pass from the former to the latter:
(Discrete) | (Continuous) | (Limit method) |
Ramsey theory | Topological dynamics | Compactness |
Density Ramsey theory | Ergodic theory | Furstenberg correspondence principle |
Graph/hypergraph regularity | Measure theory | Graph limits |
Polynomial regularity | Linear algebra | Ultralimits |
Structural decompositions | Hilbert space geometry | Ultralimits |
Fourier analysis | Spectral theory | Direct and inverse limits |
Quantitative algebraic geometry | Algebraic geometry | Schemes |
Discrete metric spaces | Continuous metric spaces | Gromov-Hausdorff limits |
Approximate group theory | Topological group theory | Model theory |
As the above table illustrates, there are a variety of different ways to form a limiting continuous object. Roughly speaking, one can divide limits into three categories:
- Topological and metric limits. These notions of limits are commonly used by analysts. Here, one starts with a sequence (or perhaps a net) of objects
in a common space
, which one then endows with the structure of a topological space or a metric space, by defining a notion of distance between two points of the space, or a notion of open neighbourhoods or open sets in the space. Provided that the sequence or net is convergent, this produces a limit object
, which remains in the same space, and is “close” to many of the original objects
with respect to the given metric or topology.
- Categorical limits. These notions of limits are commonly used by algebraists. Here, one starts with a sequence (or more generally, a diagram) of objects
in a category
, which are connected to each other by various morphisms. If the ambient category is well-behaved, one can then form the direct limit
or the inverse limit
of these objects, which is another object in the same category
, and is connected to the original objects
by various morphisms.
- Logical limits. These notions of limits are commonly used by model theorists. Here, one starts with a sequence of objects
or of spaces
, each of which is (a component of) a model for given (first-order) mathematical language (e.g. if one is working in the language of groups,
might be groups and
might be elements of these groups). By using devices such as the ultraproduct construction, or the compactness theorem in logic, one can then create a new object
or a new space
, which is still a model of the same language (e.g. if the spaces
were all groups, then the limiting space
will also be a group), and is “close” to the original objects or spaces in the sense that any assertion (in the given language) that is true for the limiting object or space, will also be true for many of the original objects or spaces, and conversely. (For instance, if
is an abelian group, then the
will also be abelian groups for many
.)
The purpose of this talk is to highlight the third type of limit, and specifically the ultraproduct construction, as being a “universal” limiting procedure that can be used to replace most of the limits previously mentioned. Unlike the topological or metric limits, one does not need the original objects to all lie in a common space
in order to form an ultralimit
; they are permitted to lie in different spaces
; this is more natural in many discrete contexts, e.g. when considering graphs on
vertices in the limit when
goes to infinity. Also, no convergence properties on the
are required in order for the ultralimit to exist. Similarly, ultraproduct limits differ from categorical limits in that no morphisms between the various spaces
involved are required in order to construct the ultraproduct.
With so few requirements on the objects or spaces
, the ultraproduct construction is necessarily a very “soft” one. Nevertheless, the construction has two very useful properties which make it particularly useful for the purpose of extracting good continuous limit objects out of a sequence of discrete objects. First of all, there is Łos’s theorem, which roughly speaking asserts that any first-order sentence which is asymptotically obeyed by the
, will be exactly obeyed by the limit object
; in particular, one can often take a discrete sequence of “partial counterexamples” to some assertion, and produce a continuous “complete counterexample” that same assertion via an ultraproduct construction; taking the contrapositives, one can often then establish a rigorous equivalence between a quantitative discrete statement and its qualitative continuous counterpart. Secondly, there is the countable saturation property that ultraproducts automatically enjoy, which is a property closely analogous to that of compactness in topological spaces, and can often be used to ensure that the continuous objects produced by ultraproduct methods are “complete” or “compact” in various senses, which is particularly useful in being able to upgrade qualitative (or “pointwise”) bounds to quantitative (or “uniform”) bounds, more or less “for free”, thus reducing significantly the burden of “epsilon management” (although the price one pays for this is that one needs to pay attention to which mathematical objects of study are “standard” and which are “nonstandard”). To achieve this compactness or completeness, one sometimes has to restrict to the “bounded” portion of the ultraproduct, and it is often also convenient to quotient out the “infinitesimal” portion in order to complement these compactness properties with a matching “Hausdorff” property, thus creating familiar examples of continuous spaces, such as locally compact Hausdorff spaces.
Ultraproducts are not the only logical limit in the model theorist’s toolbox, but they are one of the simplest to set up and use, and already suffice for many of the applications of logical limits outside of model theory. In this post, I will set out the basic theory of these ultraproducts, and illustrate how they can be used to pass between discrete and continuous theories in each of the examples listed in the above table.
Apart from the initial “one-time cost” of setting up the ultraproduct machinery, the main loss one incurs when using ultraproduct methods is that it becomes very difficult to extract explicit quantitative bounds from results that are proven by transferring qualitative continuous results to the discrete setting via ultraproducts. However, in many cases (particularly those involving regularity-type lemmas) the bounds are already of tower-exponential type or worse, and there is arguably not much to be lost by abandoning the explicit quantitative bounds altogether.
— 1. Basic theory —
To set up the machinery of ultraproducts (and nonstandard analysis) we will need to pick a non-principal ultrafilter on the natural numbers
. By definition, this is a collection
of subsets of the natural numbers
that obeys the following axioms:
- (i)
contains
, but does not contain
.
- (ii) If
is in
, then any subset of
containing
is in
.
- (iii) If
lie in
, then
also lies in
.
- (iv) If
, then exactly one of
and
lies in
.
- (v) No finite set lies in
.
A collection that obeys axioms (i)-(iii) is a filter, a collection that obeys (i)-(iv) is an ultrafilter, and a collection that obeys (i)-(v) is a non-principal ultrafilter. (One can certainly build ultrafilters on other sets than the natural numbers , but for the type of applications we have in mind, ultrafilters on
are generally sufficient, much as how one can largely rely on sequences
instead of nets
when using considering topological or metric notions of a limit in concrete applications.)
If is an ultrafilter, a subset
of
is said to be
-large if it lies in
, and
-small otherwise. To emphasise the limit interpretation of ultrafilters, we will also use “for
sufficiently close to
” as a synonym for “for an
-large set of
“. Note from the above axioms that if
is partitioned into finitely many components, then exactly one of these components is
-large. One can thus think of an ultrafilter as a voting protocol, which converts the preferences of a countably infinite number of voters (indexed by the natural numbers) amongst a finite number of candidates into a “winner”, namely the candidate who amasses an
-large set of votes; this voting protocol obeys all the hypotheses of Arrow’s theorem (rationality, independence of irrelevant alternatives, etc.) but not its conclusion (there are no dictators), due to the infinite number of voters. One can also view an ultrafilter as a finitely additive,
-valued probability measure on the natural numbers, in which every subset of
is measurable.
Every natural number defines a principal ultrafilter
(that is, an ultrafilter that does not obey axiom (v)), defined by setting
if and only if
. By abuse of notation, we may identify
with
, so that the set of principal ultrafilters is identified with
. The set of all ultrafilters (principal and non-principal) is denoted
, and may be identified with the Stone-Cech compactification of the natural numbers; this space has a number of interesting structures on it (for instance, it is a left-continuous topological semigroup, which is a useful fact in Ramsey theory and topological dynamics, as discussed in this previous post), but we will not discuss these structures further here. In particular, the use of ultrafilters in establishing correspondence principles between discrete and continuous structures is unrelated to the use of ultrafilters (particularly minimal or idempotent ultrafilters) in Ramsey theory and topological dynamics that is discussed in that previous post. (However, it is certainly possible to use both types of ultrafilters in separate places for a single application; see this paper of Bergelson and myself for an example.)
The existence of a non-principal ultrafilter can be guaranteed by an application of Zorn’s lemma (basically by running the transfinite version of a greedy algorithm to build the collection of
-large and
-small sets):
Lemma 1 There exists a non-principal ultrafilter
.
Proof: Define the Frechet filter to be the collection of all the cofinite subsets of
, that is to say those subsets of
whose complement is finite. This is a filter. A routine application of Zorn’s lemma shows that this filter must be contained in at least one maximal filter
. If
is not an ultrafilter, then there is a set
which is neither
-large or
-small; if we then let
be the filter generated by
and
(that is,
consists of those subsets of
that either lie in
, or contain the intersection of
with an
-large set), then one checks that
is a filter that is strictly larger than
, contradicting the maximality of
. Thus
is an ultrafilter; since it contains
, it is non-principal as required.
Remark 1 The above argument relied upon the axiom of choice. One can construct ultrafilters using slightly weaker set-theoretic axioms than the axiom of choice (e.g. the Boolean prime ideal theorem), but if one has no choice-like axioms whatsoever (or more precisely, one uses just the axioms ZF of Zermelo-Fraenkel set theory) then the existence of non-principal ultrafilters is undecidable. However, there is a result of Gödel that asserts that if a result is finitary in the sense that it can be phrased as a first-order statement in Peano Arithmetic, and it can be proven using the axiom of choice (or more precisely in ZFC set theory), then it can also be proven without the axiom of choice (i.e. in ZF set theory). In practical terms, this means that one can ignore the reliance on the axiom of choice for any finitary application of ultraproduct methods. Alternatively, instead of using Zorn’s lemma to construct a genuine ultrafilter, it is often possible (though messy) to build some sort of “partial” or “incomplete” ultrafilter which is still close enough to an ultrafilter to prove a desired result, but which does not need the full strength of the axiom of choice to construct. We will not discuss such methods here, but see e.g. this paper of Palmgren. (See also this previous blog post for a “cheap” version of nonstandard analysis which uses the Frechet filter rather than an ultrafilter.) In any event, we will freely rely on the axiom of choice in the rest of this post.
Henceforth, we select a single non-principal ultrafilter to use in the rest of the post. The choice of this ultrafilter is highly non-unique (
is uncountable), but for the purposes of establishing a correspondence between discrete and continuous mathematics, the precise choice of ultrafilter
will not be relevant, as long as it is kept fixed throughout the discussion.
We can use the ultrafilter to form limits of sequences
, even if these sequences have no limit in the topological or metric senses. For instance, if
takes values in a single finite space
for all natural numbers
, then we can define the ultralimit to be the unique element
of
such that
for
sufficiently close to
; this element exists and is unique by the ultrafilter axioms (i)-(iv). For instance, the ultralimit
of the sequence
is either
or
, with the former occurring if the even numbers are
-large, and the latter occurring if the odd numbers are
-large. So the ultralimit here depends on
, but once
is fixed, the ultralimit is well-defined. One can also view
as the outcome of an “election” among candidates in
, in which each “voter”
has
as a preferred candidate, and the ultrafilter
is used as the election protocol. (See this previous post for further discussion of this viewpoint.)
Now we consider the more general situation in which the to not lie in a single finite space
, but instead each
lies in a space
which may depend on
, and may also be infinite. Here, there does not necessarily exist a single object
that is equal to the
for
sufficiently close to
. The situation here is similar to that in metric spaces, in that a Cauchy sequence in a metric space
need not be convergent if the space
is infinite. In the latter case, the problem can be resolved by constructing the metric completion
of
, which can be defined (slightly non-rigorously) as the space of formal limits
of Cauchy sequences
, with two formal limits
,
declared to be equal if
converges to zero (in the classical sense) as
. To construct this Cauchy completion rigorous within the framework of set theory, one can define
to be the set of equivalence classes of tuples
of Cauchy sequences in
, with the equivalence relation
holding if and only if
converges to zero as
. In order to view
as a subset of its completion
, one usually identifies each point
with the equivalence class of the corresponding constant sequence
. With this construction, one can for instance build the real numbers
as the metric completion of the rationals
(and this is indeed one of the most popular ways to construct the reals, which is often covered in undergraduate analysis classes). Note though while one can use this set-theoretic machinery of equivalence classes of Cauchy sequences of rationals to construct the reals, for the purposes of using the real numbers
for mathematical applications, this set-theoretic construction is not relevant; the only thing one needs to retain is that Cauchy sequences of rationals (or of reals) will converge to a real, and conversely every real is the limit of a Cauchy sequence of rationals.
We can take a similar tack to construct ultralimits of sequences
in different spaces
. If one is willing to be slightly non-rigorous, the definition is almost the same: we can view these ultralimits as formal objects, with two ultralimits
and
declared to be equal if and only if
for
sufficiently close to
. To do things rigorously within the framework of set theory, one has to take a little extra care to avoid the set-theoretic issues associated to Russell’s paradox (or more precisely, avoiding the uses of proper classes that are too large to be sets). One way to deal with this is as follows. One can postulate the existence of a standard universe
that contains all the objects of interest for one’s particular mathematical problem: for instance, if one is interested in a sequence of groups
, then
might contain all the elements of all of the
. The only requirements we make of this standard universe are that (a) it is a set (rather than a proper class), and (b) it is fixed throughout the mathematical discussion. The former requirement means that
, in general, cannot contain all spaces of a particular type; for instance, one cannot make
contain all groups, all vector spaces, all graphs, etc., as one would soon run into Russell-type paradoxes if this occurred. However, in practice, for any given mathematical problem (other than those arising within mathematical logic), one usually does not need to work simultaneously with all spaces; usually a much smaller number of spaces, e.g. a countable or uncountable family of such spaces, will suffice. Henceforth we will take the existence of a standard universe
for granted. Elements of this universe will be referred to as standard objects, and subsets of the universe as standard spaces; for instance, we will usually place the classical number systems
, etc. inside this standard universe, so elements of
become standard natural numbers, elements of
become standard reals, and so forth. We then have:
Definition 2 (Formal definition of ultralimits and ultraproducts) Let
be a sequence of standard objects, defined for an
-large set
(thus
for all
). The ultralimit
is then defined to be the equivalence class of tuples
of standard objects defined on an
-large set
, such that
for
sufficiently close to
in the common domain
of definition. Such an ultralimit is called a nonstandard object, and the set of all ultralimits is called the nonstandard universe
. We identify every standard object
with the nonstandard object
, thus embedding
in
.
Given a sequence
of standard spaces (i.e. subsets of
) defined for
sufficiently close to
, the ultraproduct
is defined as the set of all ultralimits
, where
lies in
for an
-large set of
. Such an ultraproduct (which is a subset of
) will be called a nonstandard space (also known as an internal space). Similarly, the ultraproduct of a sequence of standard groups will be called a nonstandard group (or internal group), the ultraproduct of a sequence of standard fields will be called a nonstandard field (or internal field), and so forth.
If
is a standard space, the nonstandard space
(that is, the space of ultralimits of sequences in
) will be called the ultrapower of
and is denoted
; note that
embeds as a subset of
. The ultrapower
of the standard natural numbers will be referred to as the nonstandard natural numbers, the ultrapower
of the standard reals will be referred to as the nonstandard real numbers (also known as the umber), and so forth.
One can verify that when is finite, the ultrapower
is equal to
itself, and that the notion of an ultralimit
in the case when all the
lie in
corresponds to the notion of an ultralimit defined previously.
The basic ontological Venn diagram is this: the standard universe embeds into the larger nonstandard universe
, and both exist inside the even larger “external universe” of ZFC set theory, which we will not give a name to (it is not a set, but is instead a proper class). This allows us to study various mathematical objects on three different levels: standard, nonstandard, and external. For instance, we have standard groups (groups in
) and nonstandard groups (ultraproducts of groups in
); both are examples of external groups (groups that are somewhere in the external universe), but there are certainly examples of external groups that are neither standard groups nor nonstandard groups. It is also worth cautioning that while we identify standard objects
with their nonstandard counterparts
, we do not identify standard spaces
with their nonstandard counterparts
; in particular, we do not view standard groups as examples of nonstandard groups (except in the finite case), nor do we view standard fields as examples of nonstandard fields, etc. Instead, one can view the nonstandard space
as a “completion” of the standard space
, analogous to metric completion; see this previous blog post for further discussion of this perspective. A related perspective is to view
as a double-precision version of
, so for instance
can be viewed as the space of “double-precision real numbers” as opposed to the “single-precision” real numbers in
, or similarly
may be viewed as a space of “long integers“, with
being a space of “short integers”.
The analogues of standard groups, nonstandard groups, and external groups in finitary mathematics would be “groups that do not depend on an asymptotic parameter
“, “groups
that may depend on an asymptotic parameter
“, and “informal group-like objects (such as the “group” of all “bounded” integers
) that may require asymptotic notation to define” respectively. The latter concept is hard to pin down rigorously in finitary mathematics, even though the intuition it captures (e.g. that the “set” of “bounded” integers should be closed under addition) is fairly clear; but once one uses ultraproducts to separate the three levels of standard, nonstandard, and external objects, it is possible to make rigorous sense of these sorts of intuitions, as we shall see later.
Given a sequence of standard functions between standard sets
for an
-large set of
, we define the ultralimit
of this sequence to be the function
from the nonstandard space
to the nonstandard space
defined by the formula
for all sequences that lie in
for an
-large set of
. It is easy to see that this ultralimit is well-defined; we refer to such functions as nonstandard functions.
From the above construction, we may now transfer operations and relations on standard spaces to their nonstandard counterparts. For instance, if is a sequence of standard groups, then one can take the ultralimit of the multiplication operations
to obtain a multiplication operation
on the ultraproduct
; similarly, the inversion operation on
gives rise to an inversion operation on
. Similarly, the arithmetic operations on the standard natural numbers
can be transferred to arithmetic operations on the nonstandard natural numbers
, and properties and relations on the natural numbers can similarly be transferred. For instance, a nonstandard number
can be said to be prime if the
are prime for an
-large set of
(i.e. the ultralimit of the truth value of “
is prime” is true); one nonstandard number
can be said to be larger than another
if one has
for an
-large set of
; and so forth.
One can then check by hand that statements that are true for standard objects are also true for their nonstandard counterparts. For instance, because the group operations of the standard groups are associative, the group operation on the nonstandard group
is also associative, and in fact
will also be a group (as viewed externally). Similarly, addition and multiplication in the nonstandard natural numbers
obey the usual commutative, associative, and distributive laws, because these transfer from the corresponding laws for the standard natural numbers
. For a more topical example, it is now a theorem that given any standard natural number
, there exist standard primes
such that
; it is an instructive exercise to check that the same result then automatically holds in the nonstandard setting, thus for every nonstandard natural number
there exist nonstandard primes
such that
.
These facts are special cases of the transfer principle, and can be formalised by Łos’s theorem. Informally, this theorem asserts that if an “elementary” sentence holds for (an -large subsequence of) a sequence of standard objects, then it also holds in the ultralimit, and conversely. To make this assertion rigorous, we need some of the notation from first-order logic; this is somewhat formal and the reader may wish to skim briefly over the definitions and proofs that follow. To simplify the discussion, we restrict attention to one-sorted languages, although in practice one often works with many-sorted languages instead.
Definition 3 (Languages and structures, formal definition) A signature is a collection of formal operation symbols
and relation symbols
, each of which is assigned an arity
(a non-negative integer). (For instance, the signature of the language of groups would consist of the
-ary operation
, the
-ary operation
, and the
-ary operation
.)
-ary operations are also known as constant symbols. Given a signature and an infinite supply of variable symbols
, define a term to be a formal string generated by the following rules:
- Every variable symbol
is a term.
- If
is a
-ary operation and
are terms, then
is a term.
By abuse of notation, we often move operation symbols to more traditional locations, for instance writing
as
,
as
, etc.. By further abuse of notation, parentheses are usually omitted when there is no loss of ambiguity, e.g.
is often abbreviated as
.
A formula
involving some finite number of distinct variable symbols
(known as the free variables of the formula) for some
is then a formal string generated by the following rules:
- If
is a
-ary relation and
are terms which only involve variables from
, then
is a formula of
.
- If
are terms only involving variables from
, then
is a formula with free variables
.
- If
are formulae with free variables
, then
, and
are formulae with free variables
.
- If
is a formula with free variables
(or some permutation thereof), then
and
are formulae with free variables
.
A formula with no free variables is known as a sentence. As before, we abuse notation by moving relation symbols to more traditional locations, e.g. writing
as
, and by removing parentheses whenever there is no loss of ambiguity; we also permit concatenation of quantifiers, for instance abbreviating
as
. Thus, for instance, in the language of the natural numbers,
is a formula of one variable
, and
is a sentence (which, in this case, encodes the even Goldbach conjecture).
We refer to the collection
of such formulae as the first-order language (or language, for short) associated with the given signature (and to the supply of variable symbols).
A structure
for a first-order language
is a set
, together with a map
for every
-ary operation
, and a boolean relation
for every
-ary relation
. (For instance, a group is a structure for the first-order language of groups.) Any term
of
variables
may be interpreted as a function
by viewing the variable symbols
as ranging in
, and replacing each operation
or relation
with their respective interpretations
. Similarly, any formula
may be interpreted as a function
, and in particular any sentence
is interpreted to be either true or false (and we write
if the former occurs), by interpreting quantifiers such as
and
as quantification over
. (For instance,
is interpreted as true for
if there exists
such that
is true.)
Given a sequence of standard structures for a given first-order language
, we can form the ultraproduct
in the obvious manner, with the nonstandard interpretations
of the operator and relation symbols
being the ultralimits of their standard counterparts. We refer to this ultraproduct as a nonstandard structure for the first-order language
; both standard structures and nonstandard structures are examples of external structures, but as remarked before we do not consider standard structures as examples of nonstandard structures (except when the structure is finite).
Theorem 4 (Łos’s theorem) Let
be a sequence of standard structures for a first-order language
, and let
be the associated nonstandard structure.
- (i) If
is a term involving the variables
, then
is the ultralimit of the
.
- (ii) If
is a formula with free variables
, then
is the ultralimit of
.
- (iii) If
is a sentence, then
is true if and only if
is true for
sufficiently close to
.
Informally, this theorem asserts that first-order logic is continuous with respect to ultralimits.
Proof: The claim (i) is obtained by a routine induction on the length of the term and the ultrafilter axioms, while the claim (iii) is a consequence of (ii). The claim (ii) is similarly obtained by a routine induction on the length of the formula
and the ultrafilter axioms; the only non-trivial claim to verify is that if the formula
is the ultralimit of the formulae
, then the formula
is the ultralimit of the formulae
, and similarly for the universal quantifier
.
We just prove the claim for the existential quantifier , as the claim for
is similar (and can be deduced from the existential case by rewriting
in the equivalent form
. Suppose first that
for
are such that
holds for
sufficiently close to
; by the axiom of choice, we may thus find
such that
holds for
sufficiently close to
. Taking ultralimits and using the induction hypothesis, we conclude that
where
, so that
is true. Conversely, suppose that
fails for
sufficiently close to
; then for any
in
,
fails for
sufficiently close to
, and hence on taking ultralimits
fails also, and the claim follows.
We now give a classic consequence of Łos’s theorem to logic, namely the countable case of the compactness theorem:
Corollary 5 (Compactness theorem, countable case) Let
be a first-order language, and let
be a sequence of sentences. Suppose that for each natural number
, there exists a structure
for
such that
are satisfied by this structure. Then there exists a structure
such that
are simultaneously satisfied by this structure.
The general case of the compactness theorem may be established by using ultraproducts on more general sets than the natural numbers; we leave the verification of this fact to the reader.
Proof: We select the standard universe to contain all of the
, so that the
are all standard structures. If we then set
to be the nonstandard structure
, the claim follows from Łos’s theorem.
— 2. Rank decompositions —
We can now give a simple example of how ultralimits may be used to connect quantitative finitary statements to qualitative infinitary statements, by giving an easy case of the polyomial regularity lemma, introduced by Ben Green and myself. Given a finite-dimensional vector space over a field
and a natural number
, we define a polynomial
of degree at most
on
to be a function of the form
for any basis of
and some coefficients
; it is easy to see that the choice of basis is irrelevant for this definition. If
is infinite dimensional instead of finite dimensional, we say that
is a polynomial of degree at most
if its restriction to any finite-dimensional subspace is still a polynomial of degree at most
. The space of such polynomials will be denoted
; this is itself a vector space over
.
If for some
, we define the rank
to be the least integer
such that we can find
such that
is a function of the
, that is to say there exists a function
such that
for all
. When
is finite-dimensional, the rank is necessarily finite (just take
to be the coordinate functions), but the rank may be infinite when
is infinite dimensional. This notion of rank is analogous to the notion of the rank of a quadratic form (which is essentially the
case of the above notion).
We then have the following simple fact:
Lemma 6 (Polynomial regularity lemma) Let
be a non-negative integer, and let
be a function. Then there exists a constant
with the following properties: for any
, any vector space
over a field
, and any polynomials
, there exists polynomials
for some
and a quantity
with the following properties:
- (i) (Representation modulo low rank) For each
, there exists a representation
, where
and
.
- (ii) (Independence modulo low rank) For every
, not all zero, we have
.
(In applications, one actually needs an iterated version of this lemma, in which the degree polynomials involved in
are themselves regularised in terms of high rank or lower degree polynomials, and so on and so forth down to the linear polynomials; for simplicity we will not discuss this iterated version here, but see the above-mentioned paper of Ben and myself for more discussion.)
The standard proof of this lemma is not difficult, and can be described by the following algorithm:
- (Step 0) Initialise
,
for
, and
.
- (Step 1) If property (ii) holds then STOP. Otherwise, move on to Step 2.
- (Step 2) By the failure of (ii), and by permuting the
if necessary, we may write
as a linear combination of
, plus a polynomial of rank at most
. If we then delete
, we see that every
is still a linear combination of
, plus an error of rank at most
.
- (Step 3) Replace
by
(thus deleting
), replace
by
, and return to Step 1.
Since decreases by one at each loop of the algorithm, it loops at most
times, and the claim follows.
The above quantitative lemma can be deduced instead from the following basic fact in linear algebra, a variant of the Steinitz exchange lemma:
Lemma 7 Let
be a finite collection of vectors in a vector space
. Then there exists a linearly independent set of vectors
in
for some
such that each
is a linear combination of the
.
Indeed, one just sets to be a basis of the linear span of the
. The
can also be constructed from the
by an algorithm extremely similar to the one given above; we leave this to the reader as an exercise.
From Lemma 7 we immediately obtain a qualitative version of Lemma 6:
Corollary 8 (Qualitative polynomial regularity lemma) Let
be a non-negative integer. Then for any
, any vector space
over a field
, and any polynomials
, there exists polynomials
for some
with the following properties:
- (i) (Representation modulo low rank) For each
, there exists a representation
, where
and
.
- (ii) (Independence modulo low rank) For every
, not all zero, we have
.
Proof: Let be the set of all polynomials in
of finite rank; this is clearly a subspace of
, so we may form the quotient space
, which is still a vector space over
. If we then apply Lemma 7 to the projection
of the
to this quotient space
, we obtain the claim.
While Corollary 8 certainly looks very similar to Lemma 6, it appears at first glance that it cannot be used to prove Lemma 6, because the latter lemma has meaningful content when is finite-dimensional, whereas the former Corollary is trivial in that setting. However, this can be rectified by passing from the finitary setting to the infinitary setting. This can be done in a number of ways, but we will do this using the ultrafilter machinery just developed.
Proof: (Proof of Lemma 6 using Corollary 8.) We use the “compactness and contradiction” method. Suppose for contradiction that Lemma 6 failed. Carefully negating the quantifiers, and using the axiom of choice, this means that there exists and
, with the property that for each
, we can find a vector space
over a field
and polynomials
, such that for any
, there does NOT exist
,
, obeying the properties (i), (ii) of Lemma 6 with the given data.
We may place all of the objects just constructed in a standard universe . Taking ultralimits (and using Łos’s theorem repeatedly), we obtain a nonstandard field
, a nonstandard vector space
over that field, polynomials
, with the property that for any standard integer
, there does NOT exist
,
, obeying the properties (i), (ii) of Lemma 6 with the given data. However, if one applies Corollary 8, we can find
obeying the conclusions (i), (ii) of Corollary 8. This implies the conclusions (i), (ii) of Lemma 6 if
is chosen large enough, giving the required contradiction.
— 3. Saturation and colouring —
Ultraproducts enjoy a very useful compactness-type property, known as countable saturation (or more precisely, -saturation). This property may be phrased in many ways, but we will use the following version which emphasises the analogy with topological compactness.
Let be a nonstandard set, thus
for some standard sets
. We call an internal subset or nonstandard subset of
to be any subset
of
of the form
; by Łos’s theorem we see that
for
sufficiently close to
. For instance, in the nonstandard natural numbers
, the nonstandard intervals
are internal sets for any nonstandard natural number
; indeed, if
, then
is the ultraproduct of the standard intervals
. More generally, from Łos’s theorem we see that any subset of
that is defined by a first-order predicate is an internal set. On the other hand, as we shall see later, the standard natural numbers
are not an internal subset of
(and are thus merely an external subset of
).
From Łos’s theorem we see that the internal subsets of a nonstandard set form a boolean algebra. We then have the following compactness property:
Proposition 9 (Countable saturation) Every countable cover of
by internal sets
has a finite subcover. Equivalently, if
are a countable sequence of internal sets such that
is non-empty for each
, then
is also non-empty.
We remark that if we had used ultraproducts on larger index sets than the natural numbers, then we would be able to obtain stronger saturation properties than countable saturation, although it is never possible to get unlimited saturation (since every point in a nonstandard set is an internal set). In model theoretic applications it can be technically convenient to work with an extremely saturated model (e.g. a structure which is saturated up to an inaccessible cardinal), but for most applications outside of logic and set theory, such “monster models” are not necessary, and the more modest device of ultraproducts over countable index sets is often sufficient.
Proof: It suffices to prove the second claim, as the former follows by taking complements.
Write , then for each
,
is the ultraproduct of
. In particular,
is non-empty for all
in an
-large subset
of the natural numbers. By shrinking the
as necessary we may assume that they are monotone, thus
, and such that
does not contain any natural number less than
; in particular,
. For any
, let
denote the largest natural number
such that
, and then let
denote an element of
. Then by construction, for each
, we have
for all
, and thus the nonstandard object
lies in
for all
, and thus
is non-empty as required.
This shows for instance that (as claimed previously) is not an internal subset of
, since it can be countably covered by the singleton sets
for
which are internal, but for which no finite cover exists. Among other things, this establishes the overspill principle: if a nonstandard formula
holds for all standard natural numbers, then it must hold for at least one unbounded natural number (defined as a nonstandard natural number that is not a standard natural number).
Another immediate corollary of the above proposition is that if a nonstandard set is covered by a countable sequence
of internal subsets, then the topology
on
generated by
is compact (because it has a countable base of internal susbets, and Proposition 9 then gives countable compactness).
As an application of this compactness observation, we use ultraproducts to illustrate the topological dynamics version of the Furstenberg correspondence principle, that connects Ramsey theory to topological dynamics. More precisely, we consider the following results:
Theorem 10 (van der Waerden’s theorem) For any
there exists
such that whenever
is partitioned into colour classes
, one of the colour classes
contains an arithmetic progression
of length
with some
.
Theorem 11 (Topological multiple recurrence) Let
be a non-empty compact topological space, and let
be a homeomorphism. Then for any open cover
of
and any
, there exists an open set
in this cover, a point
, and a positive integer
such that
.
It is not difficult to use Theorem 10 to establish Theorem 11. Conversely, we will use ultraproducts to show that Theorem 11 implies Theorem 10. (We will not prove either of these theorems here, but see e.g. this previous blog post for a proof.)
Again, we use compactness and contradiction. Suppose for contradiction that Theorem 10 failed. Then there exists such that for any standard
, we may partition
into colour classes
, none of which contain any
-term arithmetic progressions. Taking ultraproducts, we obtain a partition
of the nonstandard interval
associated to the unbounded natural number
into internal colour classes
, none of which contains a nonstandard
-term arithmetic progression.
Now consider the shifted colour classes for
and
. These are a countable family of internal sets that cover
, and so by countable saturation, this gives
the structure of a compact topological space.
We would like to use the shift map on
. Unfortunately, this map is not quite a bijection on
. To get around this, we work in the slightly smaller space
A further application of countable saturation reveals that is still compact (with the induced topology from
). Furthermore, the shift map
can be verified to be a homeomorphism on
, and as
is unbounded, we see from the overspill principle that
is non-empty. It is covered by the open sets
, so by Theorem 11, we can find
and a (standard) positive integer
such that
lie in a single
, thus
contains a non-standard
-term arithmetic progression, giving the required contradiction.
— 4. Algebraic geometry and ultraproducts —
Another use of ultraproducts is to provide a bridge between quantitative algebraic geometry and qualitative algebraic geometry. This topic is discussed in detail in this previous post; we will just give some key results here without proof.
Theorem 12 (Algebraic geometry is continuous with respect to ultralimits) Let
be a sequence of algebraically closed fields, let
be a natural number, and let
be a (standard) affine algebraic set, that is to say the solution set of some finite number of polynomials
. We define the complexity of an algebraic set
to be the least
such that
is cut out by at most
polynomials, each of degree at most
.
Then the nonstandard set
is an algebraic set if and only if the complexity of the
are uniformly bounded for
sufficiently close to
. Furthermore, if
is indeed an algebraic set, then:
A similar statement holds for constructive sets: an ultraproduct of constructive sets
is constructive if and only if the original sets have uniformly bounded complexity for
sufficiently close to
. These claims are proven in the previous blog post; the basic idea is to express basic concepts such as dimension, irreducibility, and degree in first-order terms, so that Łos’s theorem may be applied.
Using this theorem and the compactness and contradiction method, one can easily convert a number of qualitative algebraic results into quantitative ones. For instance, it is a basic fact in qualitative algebraic geometry that every algebraic set decomposes into a finite number of irreducible sets. Using the above theorem (and a relationship between degree and complexity), one can then show that the number of such sets is bounded by a quantity depending only on the degree of the original set (and in particular, uniform in the choice of field); again, see the previous blog post for details. Such quantitative bounds can be obtained by other means (for instance, by using the machinery of schemes), but the ultrafilter approach, being so general in nature, requires almost no actual algebraic geometry to set up and use.
— 5. Metric completion and Gromov-Hausdorff limits —
We previously gave an analogy between ultraproducts and metric completion. It turns out that this analogy can be made substantially more precise. We first need some basic nonstandard analysis notation. Call a nonstandard real number bounded if one has
for some standard
, and infinitesimal if one has
for all standard
. For instance, if
is an unbounded natural number, then
is bounded (but not standard), and
is infinitesimal. We write
and
to denote the assertions that
is bounded and infinitesimal respectively.
Proposition 13 (Bolzano-Weierstrass theorem) If
is a bounded nonstandard real, then there exists a unique standard real
, called the standard part of
, such that
, i.e.
is infinitesimal.
Proof: Uniqueness is clear (as no non-zero standard real can be infinitesimal). For existence, we consider the “Dedekind cut” , which is a non-empty bounded half-line in
. Taking
to be the supremum of this cut, we easily verify that
for any standard
, and the claim follows.
One can also prove this theorem by the usual Bolzano-Weierstrass argument, trapping in a nested sequence of dyadic standard intervals; we leave this argument to the interested reader.
One can view the standard part operation algebraically, as a homomorphism from the bounded nonstandard reals
to the standard reals with kernel
; note that the sets
are perfectly well-defined as an (external) set in the nonstandard analysis formalism, even though it does not quite make rigorous set-theoretic sense in finitary mathematics (one cannot use finitary asymptotic notation such as
inside set-builder notation). Thus for instance we can say that
is an ideal in the ring
, which is an assertion which is intuitively obvious in the finitary setting, but a bit hard to formalise properly. Note that
can then be interpreted as the image under the standard part map of the bounded nonstandard rationals
. This can in fact be used to give an alternative definition of the real numbers, which is the nonstandard version of the Cauchy completion construction; we leave this construction to the reader.
We can perform similar constructions with other metric spaces. Actually, in order to have a reaonable notion of boundedness, it is convenient to work in the category of pointed metric spaces , that is to say a metric space
with a preferred “origin”
. If one has a sequence
of standard pointed metric spaces, one can take ultralimits and create a nonstandard pointed metric space
. Here,
is the ultraproduct of the
,
is a point in
, and
is the ultralimit of the
.
At present, is a nonstandard metric space, but not an external metric space, because the nonstandard distance
between two points in
is a nonstandard real, and not necessarily a bounded one. To create an external metric space, we cut down the size of
in two different ways. Firstly, we restrict attention to the bounded portion
of
. Next, we place an equivalence relation
on
by declaring
if
. The quotient space
, which we will denote suggestively as
can then be checked to be a metric space with metric given by the formula
whenever , with corresponding equivalence classes
. The quotient map
will be called the standard part map, as it generalises the map in Proposition 13.
We refer to the pointed external metric spaces as the nonstandard hull of the standard pointed metric spaces
; it is also known as the ultralimit of these spaces, although we avoid this terminology here as we are using the term “ultralimit” for a slightly different (although certainly related) operation. These spaces are automatically complete, as can easily be verified using countable saturation. If the spaces
are asymptotically uniformly locally totally bounded in the sense that for every
there exists
such that for
sufficiently close to
, one can cover the balls
by at most
balls of radius
, then the nonstandard hull
is also locally totally bounded by Łos’s theorem, and thus locally compact by the Heine-Borel theorem. Furthermore, it is not difficult to show in this case that the
converge along
to
in the pointed Gromov-Hausdorff sense, thus for every
, the Gromov-Hausdorff distance between
and
is less than
for
sufficiently close to
. In particular, this demonstrates the basic fact that any sequence of asymptotically uniformly locally totally bounded pointed metric spaces has a convergent subsequence in the pointed Gromov-Hausdorff sense.
There are several interesting special cases of the nonstandard hull construction. For instance, if the spaces are equal to a single locally totally bounded space, then the nonstandard hull becomes a metric completion
of
, with every bounded sequence
in
giving rise to a limit point
in
. When the metric spaces are normed vector spaces, in which nonstandard analysis can be used as a framework to describe the theory of concentration compactness; see this previous blog post for further discussion. Finally, if one starts with a finitely generated group
with a word metric
, then by taking the nonstandard hull of
with a rescaled word metric
for a well-chosen set of radii
, one can obtain a useful metric space known as the asymptotic cone of
, which for instance can be used to establish Gromov’s theorem on groups of polynomial growth; see this paper of van den Dries and Wilkie for details. Related to this, one can take the non-standard hull of a sequence of approximate groups (and the groups generated by such approximate groups) to obtain open neighbourhoods of locally compact groups, allowing one to use the theory of Hilbert’s fifth problem (which classifies the latter) to study approximate groups; see this text of mine for more discussion.
— 6. Loeb measure and regularity —
Measure theory, with its emphasis on countable additivity, is not obviously a first-order theory, and so it is not a priori obvious that it interacts well with ultraproducts. Nevertheless, thanks primarily to the countable saturation property of ultraproducts, one can often obtain a good notion of measure on nonstandard spaces, by carefully taking the ultralimit of measures on standard spaces. We give a fundamental such construction here, namely the Loeb measure construction, although for simplicity we restrict attention to the setting of nonstandard finite sets (also known as hyperfinite sets) to avoid some technicalities. Loeb measures are a special case of the more general concept of a Kiesler measure in model theory, but we will not discuss this more general concept here.
Let be a sequence of standard non-empty finite sets, so that the ultraproduct
is a nonstandard non-empty finite set. On each of the
, we can define the uniform probability measure
, which assigns the measure
to each subset
of
. Of course,
is a finitely additive probability measure. Taking ultraproducts and then taking standard parts, we can then define a finitely additive probability measure
on the boolean algebra
of internal subsets
of
, by the formula
One easily verifies that this is a finitely additive probability measure. Furthermore, thanks to the countable saturation property, we see that is a premeasure, that is to say that one has the countable additivity property
whenever are a family of disjoint internal subsets of
whose union is also an internal subset. Applying the Caratheodory extension theorem (or more precisely, the Hahn-Kolmogorov theorem), we can then extend
to a countably additive probability measure
on the
-algebra
generated by
; we refer to
as a Loeb space, with
being the Loeb probability measure and
being the Loeb
-algebra.
Remark 2 One technical caveat: in general, the Loeb
-algebra will not be countably generated, and so in particular the Lebesgue spaces
associated to Loeb spaces will not be separable. However, in most finitary applications, one can often work with countably generated sub-
-algebras of the Loeb
-algebra, in which case separability can be restored.
The relationship between and
is closely analogous to that between the elementary measure (or Jordan measure) of elementary subsets of (say) the unit cube, and that of Lebesgue measure of Borel subsets of that cube; see e.g. this text of mine for the basic theory here. For instance, it is not difficult to show that every Loeb measurable set
is “almost internal” in the sense that for any standard
, one can find an internal set
which is
-close to
in the sense that the outer measure
of the symmetric difference is at most
. Related to this, the Loeb measure and the outer measure agree on any Loeb measurable set, and the simple internal functions on
(i.e. finite linear combinations of indicator functions of internal sets) will be dense in
for any (standard)
.
For instance, if is an unbounded natural number, then the set
is not an internal subset of
, but it is the intersection of the countable family
of internal sets for
. Each of the internal sets
has measure
, and so
is a Loeb measurable set with Loeb measure zero. As another example, for any standard
and
, the residue class
is an internal subset of
of Loeb measure exactly
(regardless of what the remainder of
is modulo
).
As a quick application of Loeb measure, we give an instance of the Furstenberg correspondence principle, closely analogous to the topological dynamics example from a few sections earlier. Specifically, we connect the following two theorems:
Theorem 14 (Szemeredi’s theorem) For any
and
there exists
such that whenever
has density
at least
,
contains an arithmetic progression
of length
with some
.
Theorem 15 (Furstenberg multiple recurrence) Let
be a probability space, and let
be an almost everywhere defined bijection that is measure-preserving. Then for any set
of positive measure and any
, there exists a point
, and a positive integer
such that
.
Again, it is not difficult to show that Theorem 14 implies Theorem 15. To show the converse, we again use the compactness and contradiction method. If Theorem 14 failed, then there exist and
, and a sequence
going to infinity, together with subsets
of density at least
which contain no
-term arithmetic progressions. Taking ultralimits, we obtain an unbounded natural number
and an internal subset
of Loeb measure at least
which contains no non-standard
-term arithmetic progressions. The shift map
is defined and bijective almost everywhere on
, and is measure-preserving, and Theorem 15 then provides the required contradiction. (As remarked earlier, this probability space is likely to be inseparable, but one can make it separable simply by reducing
to the
-algebra generated by
and its (standard) shifts
.)
Remark 3 The ultralimit construction actually gives a lot more relevant structure on
than just that of a measure-preserving system. For instance, one can view the space
of parallelograms as a special subset of
, which one can also endow with a Loeb measure, and these spaces (as well as higher-dimensional analogues) which can be used to analyse the further additive structure of
(in a manner that closely parallels the structural theory of Host and Kra on measure-preserving systems); see this paper of Szegedy for some details of this approach.
The above example already shows the power of basic measure-theoretic tools (such as the Hahn-Kolmogorov theorem) in connecting discrete and continuous results together. Now we turn to some applications of other basic measure theory tools, such as product measure and conditional expectation. Specifically, we will use ultraproducts and measure theory to prove the following “strong” form of the Szemerédi regularity lemma:
Lemma 16 (Szemerédi regularity lemma) Let
and
be a function. Then there exists
with the following property: whenever
is a finite non-empty set and
is a function, there exists
and a decomposition
where
- (Structure)
takes values in
, and there exists a partition
such that
is constant on
for all
.
- (Smallness)
takes values in
, and
.
- (Pseudorandomness) For any
, one has
.
The connection between the regularity lemma and nonstandard measure theory was first obtained by Elek and Szegedy, in which the extension of the arguments here to hypergraphs was also obtained.
We will deduce Lemma 16 from the following infinitary version:
Lemma 17 (Infinitary regularity lemma) Let
be standard, and let
be a nonstandard finite non-empty set. If
is a Loeb measurable function on
, then there exists a decomposition
where
- (Structure)
takes values in
, and there exists a partition
into finitely many internal sets such that
is constant on
for all
.
- (Smallness)
takes values in
, and
.
- (Pseudorandomness) For any measurable
, one has
.
We will prove Lemma 17 shortly, but let us first see how it implies Lemma 16. We once again use the compactness and contradiction method. If Lemma 16 fails, then there exists and
, and for each
there exists a finite non-empty set
and a function
, such that for no
does there exist a decomposition
obeying the conclusions of Lemma 16. We then take ultralimits to obtain a nonstandard finite non-empty set and an internal function
. The standard part
is then a Loeb measurable function on
taking values in
. We apply Lemma 17 to obtain a decomposition
with the stated properties for some finite . Note that
is already a simple internal function. The function
need not be simple internal, but may be approximated to arbitrary accuracy in
by a simple internal function. Thus we may find a decomposition
where is simple internal and is such that
for all measurable , and
is simple internal, takes values in
, and is such that
By Łos’s theorem, an analogous decomposition then holds for for
sufficiently close to
, but this contradicts the construction of the
.
Now we prove Lemma 17. The proof hinges on a comparison between two spaces, the Loeb space
on the product space , and the subtly different probability space
that is the product of the Loeb space with itself, thus
is the
-algebra on
generated by rectangles
with
Loeb measurable in
, and
is the product measure, which is the unique probability measure on
such that
for all Loeb measurable .
It is not difficult to show that the former probability space is a refinement of the latter, thus contains
, and
and
agree on their common domain
of definition. However, the former space is larger in general; the basic reason for this is for large finite spaces
, it is possible to find subsets of
that are not well approximable by bounded boolean combinations of rectangles
(e.g. random subsets of
will have this property with high probability in the asymptotic limit when
goes to infinity). Despite this disparity, we may still form the conditional expectation
of
, which one can define as the orthogonal projection of
in the Hilbert space
to the closed subspace
. We then have a decomposition
where is orthogonal to all
-measurable functions; in particular, it is orthogonal to
for any Loeb measurable
, so that
for all such .
Next, we know that is generated (up to null sets) by products
of internal sets, so we may approximate
to arbitary error in
by a simple function
that is a finite linear combination of indicators
of rectangles; as
takes values in
, we can ensure that
and
. This gives a decomposition
and one easily verifies that all the required properties of Lemma 17 are obeyed.
Remark 4 It is instructive to deconstruct this proof and compare it with the standard “energy increment” proof of the regularity lemma. The energy increment process is now concealed within the standard proof of the existence of orthogonal projections in Hilbert spaces (see e.g. Proposition 1 of this previous blog post), so on some level the two proofs of the regularity lemma are essentially equivalent. However, the ultrafilter proof allows one to hide many of the ingredients of the argument into existing Hilbert space theory.
Remark 5 A similar construction allows one to extract a graph limit from a sequence of finite graphs
, by first forming the ultraproduct
and then the conditional expectation
, which is an
-measurable function from
to
. At this point we encounter the technical issue noted previously that
is not countably generated. However, we may find a countably generated sub-
-algebra
of
with the property that
is equal
-almost everywhere with a
-measurable function
, by expressing
as the almost everywhere limit of simple functions (bounded linear combinations of rectangles
with
) and then letting
be the
-algebra generated by the
. The function
is then essentially a graphon, after lifting the separable probability space
to the unit interval with uniform Lebesgue measure in the standard fashion. Among other things, this construction can give an alternate proof that every sequence of graphs has a subsequence converging to a graphon.
Remark 6 Although it is not needed here, one convenient fact about Loeb spaces on products is that they obey the following Fubini-Tonelli type theorem: if
are nonstandard finite spaces and
is Loeb measurable on
, then for all
, the function
is Loeb measurable on
, the integral
is Loeb measurable on
, and we have the identity
Similarly if the roles of
and
are swapped; in particular we have the familiar identity
These identities are obvious when
is an internal simple function (as it follows from the corresponding claim in the finite case), and the general case follows from a standard approximation argument (using the monotone convergence theorem repeatedly). One can also obtain an analogous claim in the absolutely integrable category, in the spirit of Fubini’s theorem; we leave this to the interested reader.
33 comments
Comments feed for this article
7 December, 2013 at 10:44 pm
Terrence Tao Blog: Bridging Discrete & Continuous Analysis | Math Online Tom Circle
[…] https://terrytao.wordpress.com/2013/12/07/ultraproducts-as-a-bridge-between-discrete-and-continuous-a… […]
8 December, 2013 at 2:05 am
Victor Porton
Another approach to discrete mathematics is to use funcoids and reloid. A funcoid may represent both proximal space or a topological space, or a discrete object such as a graph. Such things as continuity are defined for funcoids, generalizing both continuous and discrete cases.
http://www.mathematics21.org/algebraic-general-topology.html
8 December, 2013 at 6:23 am
g
Pedantic note: “Los” should really be “Łoś”.
[Corrected, thanks – T.]
8 December, 2013 at 6:38 am
Alexander Shamov
In the discussion after Proposition 13 “bounded nonstandard integers
” should be “rationals”.
[Corrected, thanks – T.]
8 December, 2013 at 8:28 am
Bo Jacoby
Sorry for being off topic. I wish to know if this elementary result is really new? http://www.academia.edu/3247833/Statistical_induction_and_prediction
8 December, 2013 at 12:09 pm
Victor Porton
Limits to ultrafilters are somehow similar to my attempt to define a theory of generalized limits (in singularity points), but I consider filters rather than only ultrafilters. My attempt to construct in my way a theory in singularities is inhibited by some problems (some of which are precisely formulated and some are not), like these open problems.
9 December, 2013 at 1:51 am
J
Could this approach be useful in Graph theory problems such as Graph capaity http://en.wikipedia.org/wiki/Shannon_capacity_of_a_graph? When can solutions to semidefinite relaxations be thought of representing a property of a graph limit when the sequences of graphs are constructed in a particular way? Noga Alon with his student has show the capacity problem could be undecidable because the convergence property is true but the pace of convergence could have jumps. Can such difficult problems be studied with the technique at hand?
9 December, 2013 at 7:31 am
Boolean Algebra |
[…] Ultraproducts as a Bridge Between Discrete and Continuous … https://terrytao.wordpress.com/Some of the material here is drawn from previous blog posts, notably “Ultraproducts as a bridge between hard analysis and soft analysis” and “Ultralimit analysis and quantitative algebraic geometry“'. The text … Discrete analysis, of course, is primarily interested in the study of discrete (or “finitary”) mathematical objects: integers, rational numbers (which can be viewed as ratios of integers), finite sets, finite graphs, finite or discrete metric spaces, and so forth. However … […]
9 December, 2013 at 10:32 am
Ultraprodukte | UGroh's Weblog
[…] In der Vorlesung zur Funktionalanalysis hatte ich Ultrafilter als ein Möglichkeit angesprochen, kompakte topologische Räume zu definieren. Dass diese auf H. Cartan zurückgehende Definition auch für viele andere mathematische Fragestellung sinnvoll ist belegt der Artikel von T. Tao. […]
9 December, 2013 at 3:23 pm
Anonymous
Near the end of definition 3, “for every k-ary operation M” should be “for every k-ary operation O”
[Corrected, thanks – T.]
11 December, 2013 at 2:50 pm
Blake Stacey
Typo: “Gromov-Hausorff limits”
[Corrected, thanks – T.]
24 January, 2014 at 4:57 pm
Michelangelo
I don’t know if it can be useful, there are two articles on a similar topic by Bruno de Finetti: “La struttura delle distribuzioni in un insieme astratto qualsiasi” and “Sulla teoria astratta della misura e dell’integrazione”; english translations (“The structure of distributions on abstract spaces” and “On the abstract theory of measure and integration”) can be found in “Probability, Induction and Statistics: The art of guessing”, J. Wiley, N. Y., 1972.
5 May, 2014 at 3:36 pm
Hindman’s Theorem | Finite Playground
[…] reading the posts on ultrafilters by Terry Tao [1,2], I find the following result […]
5 June, 2014 at 9:56 am
When is correlation transitive? | What's new
[…] (i.e. in the formalism of inner product spaces) we will need a non-principal ultrafilter (see e.g this previous blog post for basic theory of ultrafilters); we leave it as an exercise to the reader to figure out how to […]
25 June, 2014 at 10:07 am
Lebesgue measure as the invariant factor of Loeb measure | What's new
[…] some basic familiarity with nonstandard analysis and ultraproducts, as covered for instance in this previous blog post.) Given an unbounded nonstandard natural number , one can define two external additive subgroups of […]
7 July, 2014 at 2:20 am
The subspace theorem approach to Siegel’s theorem on integral points on curves via nonstandard analysis | What's new
[…] out that finiteness theorems are very compatible with the language of nonstandard analysis. (See this previous blog post for a review of the basics of nonstandard analysis, and in particular for the nonstandard […]
12 October, 2014 at 11:57 am
Additive limits | What's new
[…] analysis (or of ultraproducts); see for instance this paper of Elek and Szegedy, Section 6 of this previous blog post, or this paper of Towsner. (In this post we assume some familiarity with nonstandard analysis, as […]
20 July, 2015 at 8:23 pm
A nonstandard analysis proof of Szemeredi’s theorem | What's new
[…] of a standard part of a bounded real number, and the Loeb measure construction), see for instance this previous blog post for a […]
20 July, 2015 at 10:52 pm
Lior Silberman
Correction: after Remark 1, in “One can also view [the ultralimit of a sequence in a finite set] as the outcome of an “election” among candidates in {X}, in which each “voter”
has
as a preferred candidate”, the second n should be
, I think.
[Corrected, thanks – T.]
16 September, 2015 at 7:09 pm
The One About .999… |
[…] than 1, you might at some point want to learn about the hyperreal number system, and the concept of ultralimits. In this context, .999… is less than 1, and for a very appealing reason: since each individual […]
5 March, 2016 at 10:11 am
Sean Eberhard
Dear Terry,
I’m trying to flesh out the details of Remark 5 here. Is it true for some reason that if
is a hyperfinite set and
any separable sub-
-algebra of the Loeb
-algebra then
is a standard probability space (in the sense of https://en.wikipedia.org/wiki/Standard_probability_space)?
5 March, 2016 at 11:40 pm
Terence Tao
My guess would be that these spaces would not exactly be standard probability spaces, but ought to be equivalent modulo null sets to a standard probability space. If I recall correctly, there is some discussion of these issues in Furstenberg’s book, something along the lines that every separable probability space has a standard probability space model which is equivalent up to null sets. But I don’t have that book handy right now.
25 September, 2016 at 11:45 pm
Maths student
Dear Prof. Tao,
in remark 1, it seems as though “ultrafilters” must be replaced by “non-principal ultrafilters”, for the existence of ultrafilters is given by the principal ultrafilters.
[Corrected, thanks – T.]
28 September, 2016 at 2:31 am
Maths student
Dear Prof. Tao,
It seems as though in Definition 2 in the last line of the first paragraph (“We identify every standard object…”), the subscript from the limit has to be dropped, or one would set
for all
.
[Corrected, thanks – T.]
1 March, 2017 at 11:59 am
Special cases of Shannon entropy | What's new
[…] As before, every linear inequality or equality that is valid for the information-theoretic quantities discussed above, is automatically valid for the linear algebra counterparts for subspaces of a vector space over a finite field by applying the above specialisation (and dividing out by the normalising factor of ). In fact, the requirement that the field be finite can be removed by applying the compactness theorem from logic (or one of its relatives, such as Los’s theorem on ultraproducts, as done in this previous blog post). […]
2 September, 2017 at 8:39 pm
espressonator
Perhaps instead of “finite subspace”, you meant “finite dimensional subspace”?
[Corrected, thanks – T.]
14 July, 2018 at 3:05 pm
Fausto di Biase
It seems to me that the information encoded by a filter, say alfa, is given by the ”small” sets it contains. Indeed, if alfa contains a set A, it also necessarily contains the supersets of A, but it does not necessarily contain any given subset of A. So, I am not sure why you choose to call ”alfa-large” the members of alfa, rather than ”alfa-small”.
17 July, 2018 at 2:52 pm
Terence Tao
“Members of” is not the same as “information encoded by”. As you note, the larger the set is, the more likely it is to lie in the filter
, so it is natural to view sets in the filter as being large instead of small. For instance, in the cofinite filter, the only sets that lie in the filter are those that are so large that their complements are finite.
21 July, 2018 at 4:21 pm
Fausto di Biase
You are right. Thank you!
I guess what tricked me is the fact that if we pick a point
”at random” in the powerset of
(with the hope of getting elements of a given filter
of subsets of
), and if we are lucky and end up finding that
belongs to
, then the interesting thing to do, in order to find other elements of
, is to go ”downwards” and pick a subset of
”at random”, with the hope of finding another element of
(since the supersets of
will be trivially be elements of
).
I guess I had this in mind when I wrote that the ”information is given by the small sets”.
On the other hand, if we are unlucky and find out that
is not an element of
, then the thing to do is to go ”upwards” and pick a superset of
”at random”, with the hope of finding an element of
, since no subset of
will belong to
in this case. We could say that this
is not ”large enough” to belong to
.
A curious fact about the cofinite filter
is that, if
belongs to it, and if we look for an ascending chain
of distinct elements of
starting from
, then we will only find finite chains, while if we look for descending chains
of distinct elements of $ latex \alpha$ starting from
, we will find infinite chains. There is no ”smallest” element in
contained in a given
. Indeed, the intersection of all elements of
is empty.
Thank you for this beautiful post.
3 October, 2020 at 6:27 pm
porton
Terry,
Previously I have been written in this comment stream that I “attempt” to construct “noncontinuous” analysis (common generalization of continuous analysis and discrete analysis, as well as analysis of any arbitrary functions (having some topological structure)). I succeeded!!
I already defined (generalized) limit of an arbitrary (even discontinuous) function. Now I have written a text how to manipulate these limits (e.g. add or multiply them). I even defined what a noncontinuous solution of a differential equation means.
Need to say that it makes obvious to define derivatives and integrals (as well as infinite sums) for arbitrary functions?
Hm, probably my generalized limit is equivalent to the limit \union all the ultralimits on ultrafilters over the given filter (not checked the statement given in this paragraph yet). Quite an obvious idea, but nobody formulated it.
Here is the text about generalized limit:
https://mathematics21.org/limit-of-discontinuous-function/
Moreover, this generalized limit trivially generalizes further to limits on arbitrary “spaces”. I define the concept of “space” that encompasses all kinds of spaces in topology, including topological, proximity, uniform, metric spaces, locales and frames, etc. in this text:
https://mathematics21.org/the-algebra-of-general-topology/
Nominate me for Abel and Breakthrough prizes for these works! Seriously.
5 October, 2020 at 8:17 pm
Professor Van Nostrand
Dear Victor Porton,
I have just studied your work on algebraic general topology and I am nominating you for Abel prize.
Best of luck.
Van Nostrand
5 October, 2020 at 8:37 pm
porton
Prof. Van,
Your reply would be absolutely feasible, unless one reason:
You had too little time to really study several hundreds pages. So, what you say is definitely a silly joke.
BTW, here are short introductions:
Click to access present.pdf
Click to access intro.pdf
Oops, both those two introductions miss the discovery (probably, my main discovery) from
https://mathematics21.org/the-algebra-of-general-topology/
6 October, 2020 at 11:35 am
Anonymous
Self-promoting comments are not allowed in this blog.