Proof of DHJ(3) via density-increment: Difference between revisions

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==Introduction==
==Introduction==


This article is intended to contain a proof outline of DHJ(<math>3</math>) via the [[Density_increment_method|density-increment method]].  The proofs of each step in the outline will appear in separate articles.  The goal is to rigorously codify the [[A_second_outline_of_a_density-increment_argument|"second outline"]] proof.  A secondary goal is to write the proof in such a way that it becomes "easy" to see the generalization to DHJ(<math>k</math>).   
This article is intended to contain a proof outline of DHJ(<math>3</math>) via the [[Density_increment_method|density-increment method]].  The proofs of each step in the outline will appear in separate articles.  The goal is to rigorously codify the [[A_second_outline_of_a_density-increment_argument|"second outline"]] proof.  A secondary goal is to write the proof in such a way that it becomes "easy" to see the generalization to DHJ(<math>k</math>).  Each step of the outline has a "Proofread By" section to which people can add their names.




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===1. Sets in <math>[2]^n</math> have lines===
===1. Sets in <math>[2]^n</math> have lines===
<b>Proofread By:</b> <i>no one yet</i>


This is simply Sperner's Theorem.  Our version, with the Pólya Urn distribution, is:
This is simply Sperner's Theorem.  Our version, with the Pólya Urn distribution, is:
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: '''[[Proof of Sperner's Theorem]]'''.  For now, the proof more or less appears in the article on [[Sperner%27s_theorem#Proof_of_the_theorem|Sperner's Theorem]]; we might want to use the writeup ideas in the current article on [[Equal-slices_distribution_for_DHJ(k)|Equal Slices]].  The easiest proof involves first passing from Pólya to Equal Slices.  I think you only need <math>n_1(\delta) > 1/\delta^2 + 1</math> or something.
: '''[[Proof of Sperner's Theorem]]'''.  For now, the proof more or less appears in the article on [[Sperner%27s_theorem#Proof_of_the_theorem|Sperner's Theorem]]; we might want to use the writeup ideas in the current article on [[Equal-slices_distribution_for_DHJ(k)|Equal Slices]].  The easiest proof involves first passing from Pólya to Equal Slices.  I think you only need <math>n_1(\delta) > 1/\delta^2 + 1</math> or something.


===2. Sets in <math>[2]^n</math> have subspaces===
===2. Sets in <math>[2]^n</math> have subspaces===
<b>Proofread By:</b> <i>no one yet</i>


The next step is to extend DHJ(<math>2</math>) from lines to subspaces of arbitrary dimension.
The next step is to extend DHJ(<math>2</math>) from lines to subspaces of arbitrary dimension.
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: '''Theorem 2:'''  Let <math>A \subseteq [2]^n</math> have <math>\nu_2</math>-density at least <math>\delta</math>, and let <math>d \geq 1</math>. Assume that <math>n \geq n_2(\delta,d)</math>.  Then <math>A</math> contains a <math>d</math>-dimensional combinatorial subspace.  Here <math>n_2(\delta,d)</math> probably only needs to be <math>O(1/\delta)^{2^{d+1}}</math>
: '''Theorem 2:'''  Let <math>A \subseteq [2]^n</math> have <math>\nu_2</math>-density at least <math>\delta</math>, and let <math>d \geq 1</math>. Assume that <math>n \geq n_2(\delta,d)</math>.  Then <math>A</math> contains a <math>d</math>-dimensional combinatorial subspace.  Here <math>n_2(\delta,d)</math> probably only needs to be <math>O(1/\delta)^{2^{d+1}}</math>


This sort of result has been shown for the uniform distribution case by Gunderson-Rödl-Sidorenko, from which one can easily conclude the Pólya distribution case by [[passing between measures]].  Alternatively, one can prove the result with a (much) worse bound on <math>n_2</math> using an [[DHJ(k)_implies_multidimensional_DHJ(k)|argument which generalizes to <math>[k]^n</math>]].  A few technical bits need to be filled into this argument; namely, showing that if one does Pólya on some small random subset <math>S \subseteq [n]</math>, and then combines this with an independent Pólya draw on <math>[n] \setminus S</math>, the overall draw is very close in total variation distance to a normal Pólya draw.  This is proved rather explicitly in the [[Passing_between_measures|passing between measures]] article. (Presumably there is also literature from the Pólya Urn studiers on this, too.)
This sort of result has been shown for the uniform distribution case by [[http://home.cc.umanitoba.ca/~gunderso/published_work/paper7.pdf|Gunderson-Rödl-Sidorenko]], from which one can easily conclude the Pólya distribution case by [[passing between measures]].  Alternatively, one can prove the result with a (much) worse bound on <math>n_2</math> using an [[DHJ(k)_implies_multidimensional_DHJ(k)|argument which generalizes to <math>[k]^n</math>]].  A few technical bits need to be filled into this argument; namely, showing that if one does Pólya on some small random subset <math>S \subseteq [n]</math>, and then combines this with an independent Pólya draw on <math>[n] \setminus S</math>, the overall draw is very close in total variation distance to a normal Pólya draw.  This is proved rather explicitly in the [[Passing_between_measures|passing between measures]] article. (Presumably there is also literature from the Pólya Urn studiers on this, too.)


===3. <math>ij</math>-insensitive sets in <math>[3]^n</math> have subspaces===
===3. <math>ij</math>-insensitive sets in <math>[3]^n</math> have subspaces===
<b>Proofread By:</b> <i>no one yet</i>


Let <math>i,j \in [k]</math> be distinct characters.  We define <math>A \subseteq [k]^n</math> to be an "<math>ij</math>-insensitive set" if for all strings <math>x</math>, changing <math>i</math>'s to <math>j</math>'s in <math>x</math> or vice versa does not change whether or not <math>x \in A</math>.
Let <math>i,j \in [k]</math> be distinct characters.  We define <math>A \subseteq [k]^n</math> to be an "<math>ij</math>-insensitive set" if for all strings <math>x</math>, changing <math>i</math>'s to <math>j</math>'s in <math>x</math> or vice versa does not change whether or not <math>x \in A</math>.
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The statement we prove here is:
The statement we prove here is:


: '''Lemma 3:''' Let <math>A \subseteq [3]^n</math> be an <math>ij</math>-insensitive set with <math>\nu_2</math>-density at least <math>\delta</math>.  Assume that <math>n \geq n_3(\delta) = \sqrt{2/\delta} \cdot n_2(\delta/2, d)</math>.  Then <math>A</math> contains a <math>d</math>-dimensional combinatorial subspace.
: '''Lemma 3:''' Let <math>A \subseteq [3]^n</math> be an <math>ij</math>-insensitive set with <math>\nu_3</math>-density at least <math>\delta</math>, and let <math>d \geq 1</math>.  Assume that <math>n \geq n_3(\delta,d) = \sqrt{2/\delta} \cdot n_2(\delta/2, d)</math>.  Then <math>A</math> contains a <math>d</math>-dimensional combinatorial subspace.




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===4. <math>ij</math>-insensitive sets are subspace rich===
===4. <math>ij</math>-insensitive sets are subspace rich===


This is sketched originally [[A_second_outline_of_a_density-increment_argument#Step_1:_a_dense_1-set_contains_an_abundance_of_combinatorial_subspaces|here]], and should be provable rather nicely using the ideas in the last paragraph of [[http://www.cs.cmu.edu/~odonnell/more-ordered-partitions.pdf|this document]].
<b>Proofread By:</b> <i>no one yet</i>
 
: '''Lemma 4:'''  Let <math>A \subseteq [3]^n</math> be an <math>ij</math>-insensitive set with <math>\nu</math>-density at least <math>\delta</math>, and let <math>d \geq 1</math>.  Assume that <math>n \geq n_4(\delta,d) = n_3(\delta/2,d)</math>.  Then a random <math>d</math>-dimensional subspace drawn from <math>\nu_{3+d}</math> is in <math>A</math> with probability at least <math>\eta_4(\delta, d) = XXX</math>.
 
This is sketched originally [[A_second_outline_of_a_density-increment_argument#Step_1:_a_dense_1-set_contains_an_abundance_of_combinatorial_subspaces|here]].  Here is a more complete argument:
 
: '''Proof:'''  For any <math>3 \leq m \leq n</math> one can draw a string <math>h \sim \nu_3^n</math> as follows:  First, draw <math>f \sim \nu_m^n</math>; then independently draw <math>g \sim \nu_3^m</math>; finally, set <math>h = g \circ f</math>.  This notation means that <math>h_i = g_{f_i}</math>.  The fact that this indeed gives the distribution <math>\nu_3^n</math> is justified in [[http://www.cs.cmu.edu/~odonnell/more-ordered-partitions.pdf|this document]], but should be simplified and ported to the wiki.
 
: By assumption, <math>\mathbf{Pr}[h \in A] \geq \delta</math>; hence with probability at least <math>\delta/2</math> over the choice of <math>f</math> we get that <math>A_f \subseteq [3]^m</math> has <math>\nu_3</math>-density at least <math>\delta/2</math>.  Here <math>A_f</math> of course denotes <math>\{g \in [3]^m : g \circ f \in A</math>.  Crucially, <math>A_f</math> is an <math>ij</math>-insensitive set because <math>A</math>.  (This takes a slight bit of reflection but is, I think, easily confirmed.)  Call an <math>f</math> "good" if indeed <math>\nu_3(A_f) \geq \delta/2</math>.
 
: We therefore select <math>m = n_3(\delta/2,d)</math> (which is allowable as <math>n \geq n_3(\delta/2,d)</math>) and use Lemma 3 to conclude that for each good <math>f</math>, the set <math>A_f</math> contains some <math>d</math>-dimensional subspace.  In these cases, a <i>randomly</i> chosen subspace <math>\sigma \sim [3+d]^m</math> is in <math>A_f</math> with some positive probability.  To be continued...


===5. <math>ij</math>-insensitive sets are subspace partitionable===
===5. <math>ij</math>-insensitive sets are subspace partitionable===
<b>Proofread By:</b> <i>no one yet</i>


This is currently written fairly thoroughly [[A_general_partitioning_principle|here]], though some of the details of the density/probability calculations are sketched.
This is currently written fairly thoroughly [[A_general_partitioning_principle|here]], though some of the details of the density/probability calculations are sketched.


===6. Intersections of <math>ij</math>-insensitive sets are subspace partitionable===
===6. Intersections of <math>ij</math>-insensitive sets are subspace partitionable===
<b>Proofread By:</b> <i>no one yet</i>


Currently written [[A_second_outline_of_a_density-increment_argument#Step_3:_a_dense_12-set_can_be_almost_entirely_partitioned_into_large_subspaces|here]].
Currently written [[A_second_outline_of_a_density-increment_argument#Step_3:_a_dense_12-set_can_be_almost_entirely_partitioned_into_large_subspaces|here]].


===7. Line-free sets increment on intersections of <math>ij</math>-insensitive sets===
===7. Line-free sets increment on intersections of <math>ij</math>-insensitive sets===
<b>Proofread By:</b> <i>no one yet</i>


Written mostly completely [[Line-free_sets_correlate_locally_with_complexity-1_sets|here]].
Written mostly completely [[Line-free_sets_correlate_locally_with_complexity-1_sets|here]].


===8. Line-free sets increment on subspaces===
===8. Line-free sets increment on subspaces===
<b>Proofread By:</b> <i>no one yet</i>


Sketch [[A_second_outline_of_a_density-increment_argument#How_the_proof_works|here]].
Sketch [[A_second_outline_of_a_density-increment_argument#How_the_proof_works|here]].


===9. Sets in <math>[3]^n</math> have lines===
===9. Sets in <math>[3]^n</math> have lines===
<b>Proofread By:</b> <i>no one yet</i>


The basic idea is described in the article on the [[density increment method]].
The basic idea is described in the article on the [[density increment method]].

Revision as of 10:54, 20 March 2009

Introduction

This article is intended to contain a proof outline of DHJ([math]\displaystyle{ 3 }[/math]) via the density-increment method. The proofs of each step in the outline will appear in separate articles. The goal is to rigorously codify the "second outline" proof. A secondary goal is to write the proof in such a way that it becomes "easy" to see the generalization to DHJ([math]\displaystyle{ k }[/math]). Each step of the outline has a "Proofread By" section to which people can add their names.


Notation and definitions

We'll call the main probability distribution we work with the Pólya Urn distribution. As a distribution on [math]\displaystyle{ [k]^n }[/math], we'll write it as [math]\displaystyle{ \nu_k^n }[/math], or as [math]\displaystyle{ \nu_k }[/math] or [math]\displaystyle{ \nu }[/math] if it's clear from context. (Note: even if one only wants to prove DHJ([math]\displaystyle{ 3 }[/math]), one needs to define [math]\displaystyle{ \nu_k^n }[/math] for general [math]\displaystyle{ k }[/math].) One way to define it is as follows: Order the coordinates [math]\displaystyle{ [n] }[/math] in a list according to a random permutation. Now choose [math]\displaystyle{ k-1 }[/math] distinct "partition points" uniformly at random from the [math]\displaystyle{ \binom{n+1}{k-1} }[/math] possibilities. This partitions the list of coordinates into [math]\displaystyle{ k }[/math] sublists; take the [math]\displaystyle{ 1 }[/math]st sublist of coordinates to be [math]\displaystyle{ 1 }[/math]'s, the [math]\displaystyle{ 2 }[/math]nd sublist to be [math]\displaystyle{ 2 }[/math]'s, etc. Note that any string drawn from the Pólya Urn distribution is nondegenerate, meaning it contains at least one of each character in [math]\displaystyle{ [3] }[/math].

A closely related distribution is called the Equal Slices distribution. We will denote this distribution by [math]\displaystyle{ \overline{\nu}_k^n }[/math]. It has the same definition as the Pólya Urn definition just given, except that the [math]\displaystyle{ k-1 }[/math] partition points are "allowed to be equal"; more precisely, we choose the [math]\displaystyle{ 1 }[/math]st partition point uniformly from the [math]\displaystyle{ n+1 }[/math] possibilities, then we choose the [math]\displaystyle{ 2 }[/math]nd partition point uniformly from the [math]\displaystyle{ n+2 }[/math] possibilities, etc. It should be clear from these definitions that the total variation distance between [math]\displaystyle{ \nu_k^n }[/math] and [math]\displaystyle{ \overline{\nu}_k^n }[/math] is small. Here is a proof that it is [math]\displaystyle{ O(k^2/n) }[/math].

We identify combinatorial lines in [math]\displaystyle{ [3]^n }[/math] with strings in [math]\displaystyle{ [4]^n }[/math], where the [math]\displaystyle{ 4 }[/math] character is treated as identifying the "wildcard" set. Similarly, we identify [math]\displaystyle{ 2 }[/math]-dimensional combinatorial subspaces in [math]\displaystyle{ [3]^n }[/math] with strings in [math]\displaystyle{ [5]^n }[/math], where the characters [math]\displaystyle{ 4 }[/math] and [math]\displaystyle{ 5 }[/math] identify the [math]\displaystyle{ 2 }[/math] wildcard sets. Etc. Note that a combinatorial line in [math]\displaystyle{ [3]^n }[/math] drawn from [math]\displaystyle{ \nu_4^n }[/math] is automatically nondegenerate. Henceforth, whenever we say "combinatorial line" or "combinatorial subspace" without qualification, the object is assumed to be nondegenerate.

Although we will prove DHJ([math]\displaystyle{ 3 }[/math]) for sets that are dense under [math]\displaystyle{ \nu_3 }[/math], this also proves it for sets that are dense under the usual uniform distribution; this should be explicated in the article on passing between measures.

Proof Outline

Here is the sequence of statements we prove:

1. Dense sets in [math]\displaystyle{ [2]^n }[/math] contain lines (i.e., DHJ([math]\displaystyle{ 2 }[/math])).

2. Dense sets in [math]\displaystyle{ [2]^n }[/math] contain large subspaces.

3. Dense ij-insensitive sets in [math]\displaystyle{ [3]^n }[/math] contain large subspaces.

4. Dense [math]\displaystyle{ ij }[/math]-insensitive sets in [math]\displaystyle{ [3]^n }[/math] are large-subspace rich.

5. Dense [math]\displaystyle{ ij }[/math]-insensitive sets in [math]\displaystyle{ [3]^n }[/math] are large-subspace partitionable.

6. Dense intersections of [math]\displaystyle{ ij }[/math]-insensitive sets in [math]\displaystyle{ [3]^n }[/math] are large-subspace partitionable.

7. Line-free sets in [math]\displaystyle{ [3]^n }[/math] have density increments on dense intersections of [math]\displaystyle{ ij }[/math]-insensitive sets.

8. Line-free sets in [math]\displaystyle{ [3]^n }[/math] have density increments on large subspaces.

9. Dense sets in [math]\displaystyle{ [3]^n }[/math] contain lines (i.e., DHJ([math]\displaystyle{ 3 }[/math])).

1. Sets in [math]\displaystyle{ [2]^n }[/math] have lines

Proofread By: no one yet

This is simply Sperner's Theorem. Our version, with the Pólya Urn distribution, is:

Theorem 1: Let [math]\displaystyle{ A \subseteq [2]^n }[/math] have [math]\displaystyle{ \nu_2 }[/math]-density at least [math]\displaystyle{ \delta }[/math]. Assume that [math]\displaystyle{ n \geq n_1(\delta) }[/math], where [math]\displaystyle{ n_1(\delta) = O(1/\delta^2) }[/math]. Then [math]\displaystyle{ A }[/math] contains a combinatorial ([math]\displaystyle{ 2 }[/math]-)line.
Proof of Sperner's Theorem. For now, the proof more or less appears in the article on Sperner's Theorem; we might want to use the writeup ideas in the current article on Equal Slices. The easiest proof involves first passing from Pólya to Equal Slices. I think you only need [math]\displaystyle{ n_1(\delta) \gt 1/\delta^2 + 1 }[/math] or something.


2. Sets in [math]\displaystyle{ [2]^n }[/math] have subspaces

Proofread By: no one yet

The next step is to extend DHJ([math]\displaystyle{ 2 }[/math]) from lines to subspaces of arbitrary dimension.

Theorem 2: Let [math]\displaystyle{ A \subseteq [2]^n }[/math] have [math]\displaystyle{ \nu_2 }[/math]-density at least [math]\displaystyle{ \delta }[/math], and let [math]\displaystyle{ d \geq 1 }[/math]. Assume that [math]\displaystyle{ n \geq n_2(\delta,d) }[/math]. Then [math]\displaystyle{ A }[/math] contains a [math]\displaystyle{ d }[/math]-dimensional combinatorial subspace. Here [math]\displaystyle{ n_2(\delta,d) }[/math] probably only needs to be [math]\displaystyle{ O(1/\delta)^{2^{d+1}} }[/math]

This sort of result has been shown for the uniform distribution case by [[1]], from which one can easily conclude the Pólya distribution case by passing between measures. Alternatively, one can prove the result with a (much) worse bound on [math]\displaystyle{ n_2 }[/math] using an argument which generalizes to [math]\displaystyle{ [k]^n }[/math]. A few technical bits need to be filled into this argument; namely, showing that if one does Pólya on some small random subset [math]\displaystyle{ S \subseteq [n] }[/math], and then combines this with an independent Pólya draw on [math]\displaystyle{ [n] \setminus S }[/math], the overall draw is very close in total variation distance to a normal Pólya draw. This is proved rather explicitly in the passing between measures article. (Presumably there is also literature from the Pólya Urn studiers on this, too.)

3. [math]\displaystyle{ ij }[/math]-insensitive sets in [math]\displaystyle{ [3]^n }[/math] have subspaces

Proofread By: no one yet

Let [math]\displaystyle{ i,j \in [k] }[/math] be distinct characters. We define [math]\displaystyle{ A \subseteq [k]^n }[/math] to be an "[math]\displaystyle{ ij }[/math]-insensitive set" if for all strings [math]\displaystyle{ x }[/math], changing [math]\displaystyle{ i }[/math]'s to [math]\displaystyle{ j }[/math]'s in [math]\displaystyle{ x }[/math] or vice versa does not change whether or not [math]\displaystyle{ x \in A }[/math].

An [math]\displaystyle{ ij }[/math]-insensitive in [math]\displaystyle{ [k]^n }[/math] is elsewhere on the blog called a "[math]\displaystyle{ 1 }[/math]-set", being a special case of a special set of complexity [math]\displaystyle{ 1 }[/math]. See also this article discussing the complexity of sets.

The statement we prove here is:

Lemma 3: Let [math]\displaystyle{ A \subseteq [3]^n }[/math] be an [math]\displaystyle{ ij }[/math]-insensitive set with [math]\displaystyle{ \nu_3 }[/math]-density at least [math]\displaystyle{ \delta }[/math], and let [math]\displaystyle{ d \geq 1 }[/math]. Assume that [math]\displaystyle{ n \geq n_3(\delta,d) = \sqrt{2/\delta} \cdot n_2(\delta/2, d) }[/math]. Then [math]\displaystyle{ A }[/math] contains a [math]\displaystyle{ d }[/math]-dimensional combinatorial subspace.


We sketch the proof here, for now.


Proof: (Sketch.) Assume without loss of generality that [math]\displaystyle{ i = 2 }[/math], [math]\displaystyle{ j = 3 }[/math]. We can think of a draw [math]\displaystyle{ x \sim \nu_3^n }[/math] by first conditioning on the set of coordinates [math]\displaystyle{ S }[/math] where [math]\displaystyle{ x }[/math] has its [math]\displaystyle{ 3 }[/math]'s, and then drawing the remainder of the string as [math]\displaystyle{ y \sim \nu_2^{|\overline{S}|} }[/math], where [math]\displaystyle{ \overline{S} = [n] \setminus S }[/math]. (This requires a quick justification.) Inventing some notation, we have [math]\displaystyle{ \mathbf{E}_S[\nu_2(A_S)] = \delta }[/math]. Further, it should be easy to check that [math]\displaystyle{ \mathbf{Pr}[|\overline{S}| \lt \gamma n] \leq \gamma^2 }[/math] (or perhaps only a tiny bit higher). Hence [math]\displaystyle{ \mathbf{E}_S[\nu_2(A_S) \mid |\overline{S}| \geq \gamma n] \geq \delta - \gamma^2. }[/math] We set [math]\displaystyle{ \gamma = \sqrt{\delta/2} }[/math] and conclude that there exists a particular set of [math]\displaystyle{ 3 }[/math]-coordinates [math]\displaystyle{ S_0 }[/math] such that [math]\displaystyle{ \nu_2(A_{S_0}) \geq \delta/2 }[/math] and [math]\displaystyle{ |\overline{S_0}| \geq \sqrt{\delta/2} n }[/math]. By choice of [math]\displaystyle{ n_2 }[/math], this lets us apply Theorem 2 to conclude that [math]\displaystyle{ A_{S_0} \subseteq [2]^{S_0} }[/math] contains a [math]\displaystyle{ d }[/math]-dimensional combinatorial subspace; call it [math]\displaystyle{ \sigma }[/math].
Pulling [math]\displaystyle{ \sigma }[/math] back into [math]\displaystyle{ [3]^n }[/math] by putting [math]\displaystyle{ 3 }[/math]'s into the [math]\displaystyle{ S }[/math] coordinates, we get a [math]\displaystyle{ d }[/math]-dimensional "[math]\displaystyle{ 2 }[/math]-subspace" in [math]\displaystyle{ A \subseteq [3]^n }[/math]. But in fact, all of the strings necessary to fill this out into a complete [math]\displaystyle{ d }[/math]-dimensional subspace in [math]\displaystyle{ [3]^n }[/math] must also be present in [math]\displaystyle{ A }[/math], because [math]\displaystyle{ A }[/math] is [math]\displaystyle{ 23 }[/math]-insensitive. [math]\displaystyle{ \Box }[/math] (somewhat poorly explained)

4. [math]\displaystyle{ ij }[/math]-insensitive sets are subspace rich

Proofread By: no one yet

Lemma 4: Let [math]\displaystyle{ A \subseteq [3]^n }[/math] be an [math]\displaystyle{ ij }[/math]-insensitive set with [math]\displaystyle{ \nu }[/math]-density at least [math]\displaystyle{ \delta }[/math], and let [math]\displaystyle{ d \geq 1 }[/math]. Assume that [math]\displaystyle{ n \geq n_4(\delta,d) = n_3(\delta/2,d) }[/math]. Then a random [math]\displaystyle{ d }[/math]-dimensional subspace drawn from [math]\displaystyle{ \nu_{3+d} }[/math] is in [math]\displaystyle{ A }[/math] with probability at least [math]\displaystyle{ \eta_4(\delta, d) = XXX }[/math].

This is sketched originally here. Here is a more complete argument:

Proof: For any [math]\displaystyle{ 3 \leq m \leq n }[/math] one can draw a string [math]\displaystyle{ h \sim \nu_3^n }[/math] as follows: First, draw [math]\displaystyle{ f \sim \nu_m^n }[/math]; then independently draw [math]\displaystyle{ g \sim \nu_3^m }[/math]; finally, set [math]\displaystyle{ h = g \circ f }[/math]. This notation means that [math]\displaystyle{ h_i = g_{f_i} }[/math]. The fact that this indeed gives the distribution [math]\displaystyle{ \nu_3^n }[/math] is justified in [document], but should be simplified and ported to the wiki.
By assumption, [math]\displaystyle{ \mathbf{Pr}[h \in A] \geq \delta }[/math]; hence with probability at least [math]\displaystyle{ \delta/2 }[/math] over the choice of [math]\displaystyle{ f }[/math] we get that [math]\displaystyle{ A_f \subseteq [3]^m }[/math] has [math]\displaystyle{ \nu_3 }[/math]-density at least [math]\displaystyle{ \delta/2 }[/math]. Here [math]\displaystyle{ A_f }[/math] of course denotes [math]\displaystyle{ \{g \in [3]^m : g \circ f \in A }[/math]. Crucially, [math]\displaystyle{ A_f }[/math] is an [math]\displaystyle{ ij }[/math]-insensitive set because [math]\displaystyle{ A }[/math]. (This takes a slight bit of reflection but is, I think, easily confirmed.) Call an [math]\displaystyle{ f }[/math] "good" if indeed [math]\displaystyle{ \nu_3(A_f) \geq \delta/2 }[/math].
We therefore select [math]\displaystyle{ m = n_3(\delta/2,d) }[/math] (which is allowable as [math]\displaystyle{ n \geq n_3(\delta/2,d) }[/math]) and use Lemma 3 to conclude that for each good [math]\displaystyle{ f }[/math], the set [math]\displaystyle{ A_f }[/math] contains some [math]\displaystyle{ d }[/math]-dimensional subspace. In these cases, a randomly chosen subspace [math]\displaystyle{ \sigma \sim [3+d]^m }[/math] is in [math]\displaystyle{ A_f }[/math] with some positive probability. To be continued...

5. [math]\displaystyle{ ij }[/math]-insensitive sets are subspace partitionable

Proofread By: no one yet

This is currently written fairly thoroughly here, though some of the details of the density/probability calculations are sketched.

6. Intersections of [math]\displaystyle{ ij }[/math]-insensitive sets are subspace partitionable

Proofread By: no one yet

Currently written here.

7. Line-free sets increment on intersections of [math]\displaystyle{ ij }[/math]-insensitive sets

Proofread By: no one yet

Written mostly completely here.

8. Line-free sets increment on subspaces

Proofread By: no one yet

Sketch here.

9. Sets in [math]\displaystyle{ [3]^n }[/math] have lines

Proofread By: no one yet

The basic idea is described in the article on the density increment method.