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On the Complexity of Distance-$d$ Independent Set Reconfiguration

Duc A. Hoang

TL;DR

We study Distance-$d$ Independent Set Reconfiguration (D$d$ISR) for fixed $d\ge3$ under Token Sliding (TS) and Token Jumping (TJ). By linking D$d$IS to IS on graph powers $G^{d-1}$ and employing a suite of reductions (from ISR, 3-SAT Reconfiguration, and NCL), we classify the problem’s complexity across key graph classes. Notably, on chordal graphs TJ yields a polynomial-time algorithm for even $d$ and PSPACE-completeness for odd $d$, while on split graphs a TS-based dichotomy exists between $d=2$ and $d=3$ (with TJ showing a complementary dichotomy). We extend many $d=2$ hardness results to $d\ge3$ for perfect and planar graphs, provide a general TJ reduction on general graphs, and establish polynomial-time solvability on graphs with bounded diameter components (e.g., cographs) and related classes. The paper also outlines open problems for trees, highlighting a path toward a complete dichotomy and the role of rigid tokens and caterpillars as future directions.

Abstract

For a fixed positive integer $d \geq 2$, a distance-$d$ independent set (D$d$IS) of a graph is a vertex subset whose distance between any two members is at least $d$. Imagine that there is a token placed on each member of a D$d$IS. Two D$d$ISs are adjacent under Token Sliding ($\mathsf{TS}$) if one can be obtained from the other by moving a token from one vertex to one of its unoccupied adjacent vertices. Under Token Jumping ($\mathsf{TJ}$), the target vertex needs not to be adjacent to the original one. The Distance-$d$ Independent Set Reconfiguration (D$d$ISR) problem under $\mathsf{TS}/\mathsf{TJ}$ asks if there is a corresponding sequence of adjacent D$d$ISs that transforms one given D$d$IS into another. The problem for $d = 2$, also known as the Independent Set Reconfiguration problem, has been well-studied in the literature and its computational complexity on several graph classes has been known. In this paper, we study the computational complexity of D$d$ISR on different graphs under $\mathsf{TS}$ and $\mathsf{TJ}$ for any fixed $d \geq 3$. On chordal graphs, we show that D$d$ISR under $\mathsf{TJ}$ is in $\mathtt{P}$ when $d$ is even and $\mathtt{PSPACE}$-complete when $d$ is odd. On split graphs, there is an interesting complexity dichotomy: D$d$ISR is $\mathtt{PSPACE}$-complete for $d = 2$ but in $\mathtt{P}$ for $d=3$ under $\mathsf{TS}$, while under $\mathsf{TJ}$ it is in $\mathtt{P}$ for $d = 2$ but $\mathtt{PSPACE}$-complete for $d = 3$. Additionally, certain well-known hardness results for $d = 2$ on perfect graphs and planar graphs of maximum degree three and bounded bandwidth can be extended for $d \geq 3$.

On the Complexity of Distance-$d$ Independent Set Reconfiguration

TL;DR

We study Distance- Independent Set Reconfiguration (DISR) for fixed under Token Sliding (TS) and Token Jumping (TJ). By linking DIS to IS on graph powers and employing a suite of reductions (from ISR, 3-SAT Reconfiguration, and NCL), we classify the problem’s complexity across key graph classes. Notably, on chordal graphs TJ yields a polynomial-time algorithm for even and PSPACE-completeness for odd , while on split graphs a TS-based dichotomy exists between and (with TJ showing a complementary dichotomy). We extend many hardness results to for perfect and planar graphs, provide a general TJ reduction on general graphs, and establish polynomial-time solvability on graphs with bounded diameter components (e.g., cographs) and related classes. The paper also outlines open problems for trees, highlighting a path toward a complete dichotomy and the role of rigid tokens and caterpillars as future directions.

Abstract

For a fixed positive integer , a distance- independent set (DIS) of a graph is a vertex subset whose distance between any two members is at least . Imagine that there is a token placed on each member of a DIS. Two DISs are adjacent under Token Sliding () if one can be obtained from the other by moving a token from one vertex to one of its unoccupied adjacent vertices. Under Token Jumping (), the target vertex needs not to be adjacent to the original one. The Distance- Independent Set Reconfiguration (DISR) problem under asks if there is a corresponding sequence of adjacent DISs that transforms one given DIS into another. The problem for , also known as the Independent Set Reconfiguration problem, has been well-studied in the literature and its computational complexity on several graph classes has been known. In this paper, we study the computational complexity of DISR on different graphs under and for any fixed . On chordal graphs, we show that DISR under is in when is even and -complete when is odd. On split graphs, there is an interesting complexity dichotomy: DISR is -complete for but in for under , while under it is in for but -complete for . Additionally, certain well-known hardness results for on perfect graphs and planar graphs of maximum degree three and bounded bandwidth can be extended for .
Paper Structure (12 sections, 15 theorems, 8 figures, 1 table)

This paper contains 12 sections, 15 theorems, 8 figures, 1 table.

Key Result

proposition 1

Let $\calG$ and $\calH$ be two graph classes and suppose that for every $G \in \calG$ we have $G^{d-1} \in \calH$ for some fixed integer $d \geq 2$. If ISR under $\sfTJ$ on $\calH$ can be solved in polynomial time, so does D$d$ISR under $\sfTJ$ on $\calG$.

Figures (8)

  • Figure 1: Construction of a D$d$ISR's instance $(G, I, J, \sfTS)$ satisfying Proposition \ref{['prop:TS-power-graph']}. Paths $P_1, \dots, P_k$ are marked by light gray boxes. Paths $Q_{v_i^\star, v_j}$ and $Q_{w_i^\star, w_j}$ of length $d-1$ are represented by bold dashed egdes, where $1 \leq i, j \leq k$ and $i \neq j$. Tokens in $I$ (resp. $J$) are marked with black (resp. gray) color.
  • Figure 2: An example of constructing a chordal graph $\Gp$ from $G$ for $d = 5$. Vertices in a light-gray box form a clique. Vertices in $V(\Gp) - V(G)$ are marked with the gray color.
  • Figure 3: An example of constructing $\Gp$ from a given graph $G$ for some values of $d \in \{2,3,4\}$ (in case $d = 2$, we have $\Gp = G$). Vertices in $V(\Gp) - V(G)$ are marked with the gray color.
  • Figure 4: An example of constructing the graphs $G$ and $\Gp$ from a 3SAT formula $\varphi$ used in ItoDHPSUU11 having three variables $x_1$, $x_2$, and $x_3$ and three clauses $c_1 = \{x_1, \overline{x_2}\}$, $c_2 = \{\overline{x_1}, x_2, x_3\}$, and $c_3 = \{\overline{x_2}, \overline{x_3}\}$. Paths of length $d-1$ are represented by dotted edges.
  • Figure 5: An example of constructing the perfect graphs $\Gp$ and $\Gpp$ from $\Gtil$. Vertices in a light-gray box form a clique. Vertices in $V(\Gpp) - V(\Gp)$ are marked with the gray color.
  • ...and 3 more figures

Theorems & Definitions (25)

  • proposition 1
  • corollary 1
  • proposition 2
  • proof
  • proposition 3
  • proof
  • corollary 2
  • proof
  • corollary 3
  • theorem 1
  • ...and 15 more