Free fermions beyond Jordan and Wigner

SciPost Physics SciPost 16:4 (2024) 102

Authors:

Paul Fendley, Balazs Pozsgay

Abstract:

The Jordan-Wigner transformation is frequently utilised to rewrite quantum spin chains in terms of fermionic operators. When the resulting Hamiltonian is bilinear in these fermions, i.e. the fermions are free, the exact spectrum follows from the eigenvalues of a matrix whose size grows only linearly with the volume of the system. However, several Hamiltonians that do not admit a Jordan-Wigner transformation to fermion bilinears still have the same type of free-fermion spectra. The spectra of such "free fermions in disguise" models can be found exactly by an intricate but explicit construction of the raising and lowering operators. We generalise the methods further to find a family of such spin chains. We compute the exact spectrum, and generalise an elegant graph-theory construction. We also explain how this family admits an N=2 lattice supersymmetry.

Emergent polar order in non-polar mixtures with non-reciprocal interactions

(2024)

Authors:

Giulia Pisegna, Suropriya Saha, Ramin Golestanian

Unpredictable tunneling in a retarded bistable potential

Chaos An Interdisciplinary Journal of Nonlinear Science AIP Publishing 34:4 (2024) 043117

Authors:

Álvaro G López, Rahil N Valani

Dynamical theory of topological defects II: universal aspects of defect motion

Journal of Statistical Mechanics Theory and Experiment IOP Publishing 2024:3 (2024) 033208

Authors:

Jacopo Romano, Benoît Mahault, Ramin Golestanian

Bias in the arrival of variation can dominate over natural selection in Richard Dawkins's biomorphs

PLoS Computational Biology Public Library of Science 20:3 (2024) e1011893

Authors:

Nora S Martin, Chico Q Camargo, Ard A Louis

Abstract:

Biomorphs, Richard Dawkins’s iconic model of morphological evolution, are traditionally used to demonstrate the power of natural selection to generate biological order from random mutations. Here we show that biomorphs can also be used to illustrate how developmental bias shapes adaptive evolutionary outcomes. In particular, we find that biomorphs exhibit phenotype bias, a type of developmental bias where certain phenotypes can be many orders of magnitude more likely than others to appear through random mutations. Moreover, this bias exhibits a strong preference for simpler phenotypes with low descriptional complexity. Such bias towards simplicity is formalised by an information-theoretic principle that can be intuitively understood from a picture of evolution randomly searching in the space of algorithms. By using population genetics simulations, we demonstrate how moderately adaptive phenotypic variation that appears more frequently upon random mutations can fix at the expense of more highly adaptive biomorph phenotypes that are less frequent. This result, as well as many other patterns found in the structure of variation for the biomorphs, such as high mutational robustness and a positive correlation between phenotype evolvability and robustness, closely resemble findings in molecular genotype-phenotype maps. Many of these patterns can be explained with an analytic model based on constrained and unconstrained sections of the genome. We postulate that the phenotype bias towards simplicity and other patterns biomorphs share with molecular genotype-phenotype maps may hold more widely for developmental systems.