  In most philosophical discussions of computer simulation, the more useful concept is the one defined in 1.2. The exception is when it is explicitly the goal of the discussion to understand computer simulation as an example of simulation more generally (see section 5). Examples of simulations that are not computer simulations include the famous physical model of the San Francisco Bay (Huggins &amp; Schultz 1973).  This is a working hydraulic scale model of the San Francisco Bay and Sacramento-San Joaquin River Delta System built in the 1950s by the Army Corps of engineers to study possible engineering interventions in the Bay. Another nice example, which is discussed extensively in (Dardashti et al., 2015, 2019) is the use of acoustic “dumb holes” made out of Bose-Einstein condensates to study the behavior of Black Holes. Physicist Bill Unruh noted that in certain fluids, something akin to a black hole would arise if there were regions of the fluid that were moving so fast that waves would have to move faster than the speed of sound (something they cannot do) in order to escape from them (Unruh 1981). Such regions would in effect have sonic event horizons. Unruh called such a physical setup a “dumb hole” (“dumb” as in “mute”) and proposed that it could be studied in order to learn things we do not know about black holes. For some time, this proposal was viewed as nothing more than a clever idea, but physicists have recently come to realize that, using Bose-Einstein condensates, they can actually build and study dumb holes in the laboratory. It is clear why we should think of such a setup as a simulation: the dumb hole simulates the black hole. Instead of finding a computer program to simulate the black holes, physicists find a fluid dynamical setup for which they believe they have a good model and for which that model has fundamental mathematical similarities to the model of the systems of interest. They observe the behavior of the fluid setup in the laboratory in order to make inferences about the black holes. The point, then, of the definitions of simulation in this section is to try to understand in what sense computer simulation and these sorts of activities are species of the same genus. We might then be in a better situation to understand why a simulation in the sense of 1.3 which happens to be run on a computer overlaps with a simulation in the sense of 1.2. We will come back to this in section 5.