<p>Given a graph <i>F</i> and a positive integer <i>n</i>, the weak <i>F</i>-saturation number <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq1.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="89" /> </InlineMediaObject> <EquationSource Format="TEX">\({\textrm{wsat}}(K_n,F)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mtext>wsat</mtext> <mo stretchy="false">(</mo> <msub> <mi>K</mi> <mi>n</mi> </msub> <mo>,</mo> <mi>F</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> is the minimum number of edges in a graph <i>H</i> on <i>n</i> vertices such that the edges missing in <i>H</i> can be added, one at a time, so that every edge creates a copy of <i>F</i>. Kalai in 1985 introduced a linear algebraic approach that became one of the most efficient tools to prove lower bounds on weak saturation numbers. Let <i>W</i> be a vector space spanned by vectors <i>w</i>(<i>e</i>) assigned to edges <i>e</i> of <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="24" /> </InlineMediaObject> <EquationSource Format="TEX">\(K_n\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>K</mi> <mi>n</mi> </msub> </math></EquationSource> </InlineEquation>. Suppose that, for every copy <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq3.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="64" /> </InlineMediaObject> <EquationSource Format="TEX">\(F'\subset K_n\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mi>F</mi> <mo>′</mo> </msup> <mo>⊂</mo> <msub> <mi>K</mi> <mi>n</mi> </msub> </mrow> </math></EquationSource> </InlineEquation> of <i>F</i>, there exist non-zero scalars <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq4.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">\(\lambda _e\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>λ</mi> <mi>e</mi> </msub> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq5.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="73" /> </InlineMediaObject> <EquationSource Format="TEX">\(e\in E(F')\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>e</mi> <mo>∈</mo> <mi>E</mi> <mo stretchy="false">(</mo> <msup> <mi>F</mi> <mo>′</mo> </msup> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>, satisfying <InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq6.gif" Format="GIF" Height="23" Rendition="HTML" Resolution="72" Type="Linedraw" Width="146" /> </InlineMediaObject> <EquationSource Format="TEX">\(\sum _{e\in E(F')}\lambda _e w(e)=0\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mo>∑</mo> <mrow> <mi>e</mi> <mo>∈</mo> <mi>E</mi> <mo stretchy="false">(</mo> <msup> <mi>F</mi> <mo>′</mo> </msup> <mo stretchy="false">)</mo> </mrow> </msub> <msub> <mi>λ</mi> <mi>e</mi> </msub> <mi>w</mi> <mrow> <mo stretchy="false">(</mo> <mi>e</mi> <mo stretchy="false">)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </math></EquationSource> </InlineEquation>. Then <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq7.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="157" /> </InlineMediaObject> <EquationSource Format="TEX">\(\textrm{dim}W\le {\textrm{wsat}}(K_n,F)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mtext>dim</mtext> <mi>W</mi> <mo>≤</mo> <mtext>wsat</mtext> <mo stretchy="false">(</mo> <msub> <mi>K</mi> <mi>n</mi> </msub> <mo>,</mo> <mi>F</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>. In this paper, we prove limitations of this approach: we find infinitely many <i>F</i> such that, for every vector space <i>W</i> as above, <InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="493_2025_174_Article_IEq8.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="157" /> </InlineMediaObject> <EquationSource Format="TEX">\(\textrm{dim}W&lt;{\textrm{wsat}}(K_n,F)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mtext>dim</mtext> <mi>W</mi> <mo>&lt;</mo> <mtext>wsat</mtext> <mo stretchy="false">(</mo> <msub> <mi>K</mi> <mi>n</mi> </msub> <mo>,</mo> <mi>F</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>. We also introduce a modification of this approach that yields tight lower bounds even when the original direct approach is insufficient. Finally, we generalise our results to random graphs, complete multipartite graphs, and hypergraphs.</p>

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Weak saturation rank: a failure of the linear algebraic approach to weak saturation

  • Nikolai Terekhov,
  • Maksim Zhukovskii

摘要

Given a graph F and a positive integer n, the weak F-saturation number \({\textrm{wsat}}(K_n,F)\) wsat ( K n , F ) is the minimum number of edges in a graph H on n vertices such that the edges missing in H can be added, one at a time, so that every edge creates a copy of F. Kalai in 1985 introduced a linear algebraic approach that became one of the most efficient tools to prove lower bounds on weak saturation numbers. Let W be a vector space spanned by vectors w(e) assigned to edges e of \(K_n\) K n . Suppose that, for every copy \(F'\subset K_n\) F K n of F, there exist non-zero scalars \(\lambda _e\) λ e , \(e\in E(F')\) e E ( F ) , satisfying \(\sum _{e\in E(F')}\lambda _e w(e)=0\) e E ( F ) λ e w ( e ) = 0 . Then \(\textrm{dim}W\le {\textrm{wsat}}(K_n,F)\) dim W wsat ( K n , F ) . In this paper, we prove limitations of this approach: we find infinitely many F such that, for every vector space W as above, \(\textrm{dim}W<{\textrm{wsat}}(K_n,F)\) dim W < wsat ( K n , F ) . We also introduce a modification of this approach that yields tight lower bounds even when the original direct approach is insufficient. Finally, we generalise our results to random graphs, complete multipartite graphs, and hypergraphs.