arXiv subjects

Nicole Schirrmacher

Publications and source records attributed to Nicole Schirrmacher.

8 recordsLinked to original sources

arXiv2026

A Logic for Minor-Free Graph Classes: Model Checking, Dependence, and Combinatorial Reconfiguration

We introduce \emph{sub-connectivity logic}, denoted by $\textsf{FOscon}$, an extension of first-order logic for graphs with a specified set $Z$ of admissible edges. Its additional atom $\textsf{scon}(x,y;\bar z)$ asserts that $x$ and $y$ are connected by a path using only edges of $Z$ and avoiding the vertices in $\bar z$. Our main structural result states that, for every weakly sparse graph class $\mathscr C$, the class of all expansions of graphs in $\mathscr C$ by rooted spanning forest orders has bounded twin-width if and only if $\mathscr C$ excludes a fixed minor. When $\mathscr C$ excludes a fixed minor, we can also compute an additional linear order that preserves bounded twin-width in polynomial time. We translate $\textsf{FOscon}$ into first-order logic over an expansion by a depth-first spanning forest order of the admissible-edge graph. Combining this translation with our structural result, we obtain a model checking algorithm for $\textsf{FOscon}$ with running time $f(|ϕ|,h(G))\cdot |G|^c$, where $f$ is computable, $c$ is an absolute constant, and $h(G)$ is the Hadwiger number of $G$. The translation and model-checking algorithm extend to binary relational structures, with the Hadwiger number measured on the Gaifman graph. For a graph class $\mathscr C$ let $\mathscr C_Z:=\{(G,Z):G\in\mathscr C,\ Z\subseteq E(G)\}$. We show that for every weakly sparse graph class $\mathscr C$, the class $\mathscr C_Z$ is monadically dependent for $\textsf{FOscon}$ if and only if $\mathscr C$ excludes a fixed minor. For monotone classes that admit efficient minor encodings, a corresponding hardness result makes this frontier computationally tight. We give applications to combinatorial reconfiguration and solution discovery problems, and study a guarded extension of $\textsf{FOscon}$ motivated by database queries.

cs.LO↗

arXiv2026

Separating Feasibility and Movement in Solution Discovery: The Case of Path Discovery

We study solution discovery, where the goal is to obtain a feasible solution to a problem from an initial configuration by a bounded sequence of local moves. In many applications, however, the graph that defines which vertex sets are feasible is not the same as the graph that governs how tokens, agents, or resources may move. Existing models such as token sliding and token jumping typically do not distinguish the problem graph and the movement graph. Motivated by this mismatch, we introduce a directed weighted two-graph model that cleanly separates feasibility from movement. A problem graph specifies the desired combinatorial objects, while a movement graph specifies admissible relocations and their costs. This yields a flexible framework that captures asymmetry, heterogeneous movement constraints, and weighted transitions, while subsuming classical discovery models as special cases. We investigate this model through \textsc{Path Discovery} and \textsc{Shortest Path Discovery}, where the task is to realize a vertex set containing an $s$-$t$-path or a shortest $s$-$t$-path in the problem graph. These problems are particularly natural in applications, since directed and weighted shortest paths are among the most fundamental algorithmic primitives. At the same time, previous work has already shown that discovery can be computationally hard even when the underlying optimization problem is easy. Our results show that this phenomenon persists, and becomes especially rich, in the two-graph setting. We obtain a detailed complexity picture, identifying tractable cases as well as strong hardness results.

cs.DM↗

arXiv2026

Model Checking for Low Monodimensionality Fragments of CMSO on Topological-Minor-Free Graph Classes

Algorithmic meta-theorems explain the tractability of large classes of computational problems by linking logical expressibility with structural graph properties. While extensions of first-order logic such as FO+dp admit efficient model checking on graph classes excluding a fixed topological minor, comparable results for richer fragments of CMSO were previously unknown. We further develop the framework of Sau, Stamoulis, and Thilikos [SODA 2025] for fragmenting CMSO via annotated graph parameters, which restrict set quantification to vertex sets satisfying bounded structural conditions. Following this approach, we identify a fragment of CMSO, namely the one defined by allowing quantification only over sets having what we call low monodimensionality, that generalizes several previously-known logics and we show that model checking for this fragment, enhanced with the disjoint-paths predicate, is fixed-parameter tractable on topological-minor-free graph classes. Such classes essentially delimit the tractability for this logic on subgraph-closed classes. As a consequence, our results lift several known algorithmic meta-theorems beyond first-order logic to the topological-minor-free setting.

cs.LO↗

arXiv2026

Model Checking Disjoint-Paths Logic on Topological-Minor-Free Graph Classes

Disjoint-paths logic, denoted $\mathsf{FO}$+$\mathsf{dp}$, extends first-order logic ($\mathsf{FO}$) with atomic predicates $\mathsf{dp}_r[(x_1,y_1),\ldots,(x_r,y_r)]$, expressing the existence of vertex-disjoint paths between $x_i$ and $y_i$, for $1\leq i\leq r$. We prove that for every graph class excluding some fixed graph as a topological minor, the model checking problem for $\mathsf{FO}$+$\mathsf{dp}$ is fixed-parameter tractable. This essentially settles the question of tractable model checking for this logic on subgraph-closed classes, since the problem is hard on subgraph-closed classes not excluding a topological minor (assuming a further mild condition of efficiency of encoding).

cs.LO↗

arXiv2026

Weighted Treedepth is NP-complete on Graphs of Bounded Degree

A treedepth decomposition of an undirected graph $G$ is a rooted forest $F$ on the vertex set of $G$ such that every edge $uv\in E(G)$ is in ancestor-descendant relationship in $F$. Given a weight function $w\colon V(G)\rightarrow \mathbb{N}$, the weighted depth of a treedepth decomposition is the maximum weight of any path from the root to a leaf, where the weight of a path is the sum of the weights of its vertices. It is known that deciding weighted treedepth is NP-complete even on trees. We prove that weighted treedepth is also NP-complete on bounded degree graphs. On the positive side, we prove that the problem is efficiently solvable on paths and on 1-subdivided stars.

cs.DM↗

arXiv2025

Elimination Distance to Dominated Clusters

In the Dominated Cluster Deletion problem, we are given an undirected graph $G$ and integers $k$ and $d$ and the question is to decide whether there exists a set of at most $k$ vertices whose removal results in a graph in which each connected component has a dominating set of size at most $d$. In the Elimination Distance to Dominated Clusters problem, we are again given an undirected graph $G$ and integers $k$ and $d$ and the question is to decide whether we can recursively delete vertices up to depth $k$ such that each remaining connected component has a dominating set of size at most $d$. Bentert et al.~[Bentert et al., MFCS 2024] recently provided an almost complete classification of the parameterized complexity of Dominated Cluster Deletion with respect to the parameters $k$, $d$, $c$, and $Δ$, where $c$ and $Δ$ are the degeneracy, and the maximum degree of the input graph, respectively. In particular, they provided a non-uniform algorithm with running time $f(k,d)\cdot n^{O(d)}$. They left as an open problem whether the problem is fixed-parameter tractable with respect to the parameter $k+d+c$. We provide a uniform algorithm running in time $f(k,d)\cdot n^{O(d)}$ for both Dominated Cluster Deletion and Elimination Distance to Dominated Clusters. We furthermore show that both problems are FPT when parameterized by $k+d+\ell$, where $\ell$ is the semi-ladder index of the input graph, a parameter that is upper bounded and may be much smaller than the degeneracy $c$, positively answering the open question of Bentert et al. We further complete the picture by providing an almost full classification for the parameterized complexity and kernelization complexity of Elimination Distance to Dominated Clusters. The one difficult base case that remains open is whether treedepth (the case $d=0$) is NP-hard on graphs of bounded maximum degree.

cs.DM↗

arXiv2021

First-Order Logic with Connectivity Operators

First-order logic (FO) can express many algorithmic problems on graphs, such as the independent set and dominating set problem, parameterized by solution size. On the other hand, FO cannot express the very simple algorithmic question of whether two vertices are connected. We enrich FO with connectivity predicates that are tailored to express algorithmic graph properties that are commonly studied in parameterized algorithmics. By adding the atomic predicates $conn_k (x, y, z_1 ,\ldots, z_k)$ that hold true in a graph if there exists a path between (the valuations of) $x$ and $y$ after (the valuations of) $z_1,\ldots,z_k$ have been deleted, we obtain separator logic $FO + conn$. We show that separator logic can express many interesting problems such as the feedback vertex set problem and elimination distance problems to first-order definable classes. We then study the limitations of separator logic and prove that it cannot express planarity, and, in particular, not the disjoint paths problem. We obtain the stronger disjoint-paths logic $FO + DP$ by adding the atomic predicates $disjoint-paths_k [(x_1, y_1 ),\ldots , (x_k , y_k )]$ that evaluate to true if there are internally vertex disjoint paths between (the valuations of) $x_i$ and $y_i$ for all $1 \le i \le k$. Disjoint-paths logic can express the disjoint paths problem, the problem of (topological) minor containment, the problem of hitting (topological) minors, and many more. Finally, we compare the expressive power of the new logics with that of transitive closure logics and monadic second-order logic.

cs.LO↗

arXiv2021

Algorithms and data structures for first-order logic with connectivity under vertex failures

We introduce a new data structure for answering connectivity queries in undirected graphs subject to batched vertex failures. Precisely, given any graph G and integer k, we can in fixed-parameter time construct a data structure that can later be used to answer queries of the form: ``are vertices s and t connected via a path that avoids vertices $u_1,..., u_k$?'' in time $2^{2^{O(k)}}$. In the terminology of the literature on data structures, this gives the first deterministic data structure for connectivity under vertex failures where for every fixed number of failures, all operations can be performed in constant time. With the aim to understand the power and the limitations of our new techniques, we prove an algorithmic meta theorem for the recently introduced separator logic, which extends first-order logic with atoms for connectivity under vertex failures. We prove that the model-checking problem for separator logic is fixed-parameter tractable on every class of graphs that exclude a fixed topological minor. We also show a weak converse. This implies that from the point of view of parameterized complexity, under standard complexity assumptions, the frontier of tractability of separator logic is almost exactly delimited by classes excluding a fixed topological minor. The backbone of our proof relies on a decomposition theorem of Cygan et al. [SICOMP '19], which provides a tree decomposition of a given graph into bags that are unbreakable. Crucially, unbreakability allows to reduce separator logic to plain first-order logic within each bag individually. We design our model-checking algorithm using dynamic programming over the tree decomposition, where the transition at each bag amounts to running a suitable model-checking subprocedure for plain first-order logic. This approach is robust enough to provide also efficient enumeration of queries expressed in separator logic.

cs.DS↗