Synchronising the clocks of processes is a fundamental problem in distributed computing. We consider message-passing systems in which processes start in an arbitrary initial state (self-stabilisation) and up to $f$ processes may be non-transiently faulty. It is well known that synchronising clocks \emph{exactly} is at least as hard as consensus and requires $Θ(f)$ time. In contrast, without self-stabilisation, clocks can be synchronised \emph{approximately} much faster, in time independent of the number of non-transient faults [Srikanth and Toueg, JACM 1987; Welch and Lynch, Inf. Comput. 1988]. In this work, we show that deterministic self-stabilising approximate clock synchronisation tasks require $Ω(f)$ time to stabilise. This gives the first non-trivial time lower bound for these tasks, whose time complexity has remained open for over two decades [Dolev and Welch, JACM 2004; Dolev, Függer, Schmid and Lenzen, JACM 2014]. In particular, this answers the open question whether self-stabilising approximate clock synchronisation tasks are as hard as consensus or as easy as approximate agreement [Lenzen and Rybicki, JACM 2019]. The results show that guaranteeing \emph{both} transient and non-transient fault-tolerance simultaneously is expensive even for approximate synchronisation tasks. The lower bounds hold in a very strong model: the faulty processes can only crash, the local clocks of processes have no clock drift, and the message delay is bounded and known to all processes. The proof is based on a combinatorial topological argument showing that no fast finite-state protocol can ensure that the clocks behave consistently across all executions. To our knowledge, this is the first use of topological arguments to prove time lower bounds in the self-stabilising setting.

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