The problem
Deleting junctions from a network can leave many disconnected pieces. Does one fixed lower bound on removals per remaining piece force a closed route through every junction exactly once, regardless of network size? For a noncomplete finite simple graph, toughness is , where the minimum is over deletions with at least two components remaining. Complete graphs are assigned . A Hamiltonian cycle visits every vertex once before returning to its start. The conjecture asks for an absolute such that and imply such a cycle.[1] [2]
Scope
Existence of an absolute toughness threshold guaranteeing Hamiltonian cycles in all finite simple graphs on at least three vertices.
What remains open
Non-Hamiltonian examples rule out thresholds below 9/4. Size-dependent sufficient bounds do not establish a constant. Christoph–Hunter–Sudakov prove a cycle of length (1−o(1))n for t=ω(log³n), whereas Shan–Tanyel prove exact Hamiltonicity for an induced-subgraph-restricted class at toughness 11.[1] [2]
Why it matters
Removing one or more junctions from a round trip cannot leave more separated pieces than junctions removed. That gives a way to rule out a spanning trip by inspecting how a network breaks apart, without trying every route. Toughness asks whether a stronger version of this necessary fragmentation test can become a general guarantee. It connects resistance to splitting with the existence of one complete traversal.[1] [2]
Ordinary vertex connectivity counts how many deletions can disconnect a graph; toughness also counts how many pieces each deletion creates. That distinction matters for a spanning cycle, whose surviving arcs place a simultaneous constraint on the number of pieces after every cut. The conjecture asks whether sufficiently strong fragmentation control can provide a route-existence criterion independent of graph size or a specially forbidden induced subgraph. It connects a family of separation certificates to the global arrangement of all vertices on one cycle.[1] [2]
Research directions
1 direction to explore
Remove growth and omissions
Find a size-independent sufficient toughness threshold or graphs of arbitrarily high toughness without Hamiltonian cycles.
Definitions
2 terms
toughness
The smallest ratio of removed vertices to remaining components, considering every deletion that leaves at least two components. A large value rules out cuts that create many pieces cheaply. Complete graphs are assigned infinite toughness.[1] [2]
induced
An induced subgraph on selected vertices retains every edge of the original graph between those vertices. Excluding a specified induced pattern restricts the graph family; a theorem with that exclusion need not hold for all graphs.[2]
Sources
Partial results
Almost spanning cycles from growing toughness. Scope: t=ω(log³n), arbitrary finite simple graphs.
Neither an absolute threshold nor all-vertex coverage.
Source date: 2026-09-24Theorem 1.7 gives (1−o(1))n cycle vertices.Read the source ↗A fixed threshold works for a new forbidden-induced-subgraph class. Scope: 11-tough (2 P₂∪P₁)-free graphs on at least three vertices.
The induced-subgraph restriction is essential to the stated result.
Source date: 2025-06-15Theorem 2 gives a Hamiltonian cycle.Read the source ↗- Thinning and sprinkling: from robust sampling to almost Hamiltonicity
Notes on Thinning and sprinkling: from robust sampling to almost Hamiltonicity
Theorem1.7 requires t/log³n→∞. Theorem1.8 requires d/(log³n loglogn)→∞; neither theorem gives a spanning cycle at constant toughness or all degrees.
- Hamilton cycles in tough (2P₂ ∪ P₁)-free graphs
Notes on Hamilton cycles in tough (2P₂ ∪ P₁)-free graphs
Supports constant-toughness formulation and a restricted forbidden-induced-subgraph theorem; excludes generality beyond that graph class.