  The distributed computing literature considers multiple options for modeling
communication. Most simply, communication is categorized as either synchronous
or asynchronous. Synchronous communication assumes that messages get delivered
within a publicly known timeframe and that parties' clocks are synchronized.
Asynchronous communication, on the other hand, only assumes that messages get
delivered eventually. A more nuanced approach, or a middle ground between the
two extremes, is given by the partially synchronous model, which is arguably
the most realistic option. This model comes in two commonly considered flavors:
  (i) The Global Stabilization Time (GST) model: after an (unknown) amount of
time, the network becomes synchronous. This captures scenarios where network
issues are transient.
  (ii) The Unknown Latency (UL) model: the network is, in fact, synchronous,
but the message delay bound is unknown.
  This work formally establishes that any time-agnostic property that can be
achieved by a protocol in the UL model can also be achieved by a (possibly
different) protocol in the GST model. By time-agnostic, we mean properties that
can depend on the order in which events happen but not on time as measured by
the parties. Most properties considered in distributed computing are
time-agnostic. The converse was already known, even without the time-agnostic
requirement, so our result shows that the two network conditions are, under one
sensible assumption, equally demanding.
