Chiral Dirac Equation and Its Spacetime and CPT Symmetries

The Dirac equation with chiral symmetry is derived using the irreducible representations of the Poincaré group, the Lagrangian formalism, and a novel method of projection operators that takes as its starting point the minimal assumption of four linearly independent physical states. We thereby demonstrate the fundamental nature of this form of the Dirac equation. The resulting equation is then examined within the context of spacetime and CPT symmetries with a discussion of the implications for the general formulation of physical theories.

Clitic Doubling in a Doubling World

This chapter places Clitic Doubling in Argentinean Spanish into the broad perspective of pronominal doubling phenomena. A series of diagnostics is presented based on the interaction of Clitic Doubling with its PF/pragmatic effects, on the one hand, and its syntactic/LF effects, on the other. An important conclusion is that Clitic Doubling must be kept apart from Clitic Right Dislocation and Clitic Left Dislocation. Clitic Doubling is thus conceived of the morphological reflex of the abstract composition of object DPs; concretely, it is an A-dependency triggered whenever the object possesses a [person]-feature, an observation called the Person Feature Condition. So, under the minimal assumption that [3P] features can be optionally encoded on lexical DPs in Argentinean Spanish, but that it is only specified for pronouns in other Spanish dialects, variation facts associated with this phenomenon are explained. By the same token, the different behavior of doubled and nondoubled objects in several syntactic/LF configurations also follows.

Minimal-assumption inference from population-genomic data

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of coalescence or recombination, allowing it to analyze arbitrarily large samples without phasing while making no assumptions about ancestral structure, linked selection, or gene conversion. Using simulated data, we show that the performance of MAGIC is comparable to that of PSMC’ even on single diploid samples generated with standard coalescent and recombination models. Applying MAGIC to a sample of human genomes reveals evidence of non-demographic factors driving coalescence.

Minimal-assumption inference from population-genomic data

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. Current methods that take advantage of this linkage information rely on models of recombination and coalescence, limiting the sample sizes and populations that they can analyze. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of recombination, demography or selection. Using simulated data, we show that MAGIC’s performance is comparable to PSMC’ on single diploid samples generated with standard coalescent and recombination models. More importantly, MAGIC can also analyze arbitrarily large samples and is robust to changes in the coalescent and recombination processes. Using MAGIC, we show that the inferred coalescence time histories of samples of multiple human genomes exhibit inconsistencies with a description in terms of an effective population size based on single-genome data.