Species entropy and thermodynamics

Abstract

We analyse particle species and the species scale in quantum gravity from a thermodynamic perspective. In close analogy to black hole thermodynamics, we propose that particle species have an entropy and a temperature, which is determined by the species scale. This is identical to the Bekenstein-Hawking entropy of a corresponding minimal black hole and agrees with the number of species in a given tower of states. Through the species entropy, we find that certain entropy bounds are connected to recent swampland constraints. Moreover, the concept of species entropy and temperature allow us to formulate the laws of species thermodynamics, which are argued to govern the variations of moduli in string theory. They can be viewed as general rules that imply certain swampland conjectures, and vice versa.

Cosmic acceleration and turns in the Swampland

“…For instance, the species scale Λ s tends to zero (see e.g. [48,86]), while corrections to the Kähler-and super-potential of the EFT vanish. The scalar potential and the gravitino mass approach zero value [42,43,63,64], while the entropy instead increases (see e.g.…”

“…The scalar potential and the gravitino mass approach zero value [42,43,63,64], while the entropy instead increases (see e.g. [48]). Our work adds to this list of properties by showing that asymptotic acceleration is primarily geodesic.…”

“…It should be noted that the most common strategy to construct an effective (supergravity) model is to stabilize all fields except one, which drives the acceleration phase. However, despite its simplicity, this approach may not be the most natural and often demands precise control over the effective theory.3 It has also been pointed out that the limits of small (AdS) cosmological constant[41], small gravitino mass[42][43][44] and small/large entropy[45][46][47][48] lead to analogous conclusions 4. In the context of inflationary cosmology, it has been shown[57][58][59][60][61][62] that non-compact symmetries and negative curvature of the field space are key features for an excellent fit to the observational data.…”