  Elements of networks interact in many ways, so modeling them with graphs
requires multiple types of edges (or network layers). Here we show that such
multiplex networks are generically more vulnerable to global cascades than
simplex networks. We generalize the threshold cascade model [D. J. Watts, Proc.
Natl. Acad. Sci. U.S.A. 99, 5766 (2002)] to multiplex networks, in which a node
activates if a sufficiently large fraction of neighbors in any layer are
active. We show that both combining layers (i.e., realizing other interactions
play a role) and splitting a network into layers (i.e., recognizing distinct
kinds of interactions) facilitate cascades. Notably, layers unsusceptible to
global cascades can cooperatively achieve them if coupled. On one hand, this
suggests fundamental limitations on predicting cascades without full knowledge
of a system's multiplexity; on the other hand, it offers feasible means to
control cascades by introducing or removing sparse layers in an existing
network.
