Eater 2

Eater 2 (or block on hat siamese hat) is an eater that was found by David Buckingham in the 1970s.[1] Mostly it works like the standard eater (see eater 1) but with two slight differences that make it useful despite its size; it takes longer to recover from each bite and it acts like an eater in two directions. The first property means that, among other things, it can eat a glider in a position that would destroy an eater 1. This novel glider-eating action is occasionally of use in itself, and combined with the symmetry means that an eater 2 can eat gliders along four different paths.

Eater 2
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Pattern type Strict still life
Eater
Number of cells 19
Bounding box 7×7
Frequency class 36.0
Discovered by David Buckingham
Year of discovery Unknown

An eater 2 variant noticed by Stephen Silver in May 1998 that is useful for obtaining smaller bounding boxes is shown below. Note that the canonical version of eater 2 is a strict still life because the outside 15-cell component is not stable without the block (it is, rather, an inductee), but the eater 2 variant below is a pseudo still life because it is made up of an aircraft carrier, block and hat, each of which are stable.

Eater 2 can also be used to eat objects other than gliders. For example, one of them can eat a lightweight or middleweight spaceship, two of them can eat a 60P5H2V0, two or three of them can eat the bulk of a 2-engine or 3-engine Cordership respectively, and seven of them can be arranged to eat the majority of the 7-in-a-row Cordership.

The eater 2 is made up of 2 siamese hats supported by a block. Variants involving siamese loops and eleven loops also function.

It serves as the logo of Catagolue.

Synthesis

On January 29, 2004 Mark Niemiec found a 9-glider synthesis of a variation of eater 2 that consists of a hat, a block, and a table. On October 9th, 2014, David S. Miller found a natural eater 2 in a soup from Adam P. Goucher's apgsearch script[2], from which Tanner Jacobi derived a 6-glider synthesis.[3]

Eater 2 variant
gollark: So you can presumably predict Olivia messages with less training time than hypothetical GTech™ initiatives.
gollark: Humans are meant to be more sample efficient than neural networks, including language models, yes?
gollark: My total messages added to 11MB some time last year.
gollark: To emulate Olivia I'd need megabytes of Olivia messages and ideally context.
gollark: Definitely not from my phone, or very fast.

See also

References
  1. Dean Hickerson's oscillator stamp collection. Retrieved on March 14, 2020.
  2. David S. Miller (October 10, 2014). Re: apgsearch: a high-performance soup searcher (discussion thread) at the ConwayLife.com forums
  3. Tanner Jacobi (November 8, 2014). Re: Soup search results (discussion thread) at the ConwayLife.com forums
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