The mechanisms that heat the solar chromosphere and corona, and that drive the solar dynamo, arguably remain some of the foremost questions in solar and stellar physics. Here, we focus on the question of how energy is transported and released in the solar chromosphere. During the past 20 years, numerical simulations of the chromosphere have been used, with increasing degree of sophistication, to validate various proposed heating mechanisms. These studies have gradually come to recognise that the mechanisms that are likely dominant may be different in different parts of chromospheric fine structures. To make progress, we therefore need constraints from highly resolved observational data. Recently, I implemented an inversion code that allows estimates of the overall chromospheric heating from spatially and spectrally resolved observational maps. Our results have unveiled very finely structured heating distributions with much larger amplitudes than the hitherto assumed canonical values. But a limitation is that this implementation cannot directly discriminate between the different heating mechanisms that have been proposed. The goal of MAGHEAT is to identify what mechanisms are heating the chromosphere, characterize the energy flux that is being released into the chromosphere and separate the contribution from each mechanism in active regions and flares. This goal is achievable with the combination of the proposed development of novel non-LTE inversion methods, new hybrid rMHD/particle simulations, and the availability of datasets with unprecedented high spatial resolution, large field-of-view, and high S/N ratio from DKIST, the Sunrise III mission, NASA’s IRIS satellite and updated instrumentation at the Swedish 1-m Solar Telescope. We will use observational data from these facilities to reconstruct new 3D empirical models of the photosphere and chromosphere, which will allow us to identify the mechanisms that are responsible for the energy deposition.
Understanding how adaptive combinations of traits are maintained is a central question in evolutionary biology. Supergenes are clusters of genes that can maintain favorable trait combinations because they are inherited as a unit. Studying supergenes allows us to address fundamental questions on the origin and evolution of complex adaptations and the effects of suppressed recombination, and is therefore of broad significance. Distylous plants offer a particularly promising opportunity to study supergene evolution. In distylous plants there are two floral morphs that differ reciprocally in the placement of stigma and anthers. These character combinations are maintained by a supergene, the distyly S-locus. While distyly has interested many generations of biologists, we still know little about the origin and evolution of this supergene, and progress on this front has been hampered by the lack of molecular genetic data on the S-locus. Here, we aim to make full use of the latest advances in genome sequencing technology to bring the study of distyly into the genomic era. Specifically, we will develop the classic Linum genus as a model for supergene evolution. We will first combine de novo assembly of the genomes of six Linum species with genetic studies to identify S-linked regions. Then, we will test whether the S-locus exhibits similarities to sex chromosomes with respect to recombination suppression, genetic degeneration and gene expression evolution. Finally, we will investigate the genetic causes and population genetic consequences of recurrent loss of distyly in Linum. The high-quality genome assemblies produced during this project will pave the way for future studies of the molecular basis of adaptive floral differences first identified by Darwin. The results from this project are of great general importance for our understanding of the evolution of coadapted gene complexes and will shed new light on the important and fascinating phenomenon of supergenes.
How individuals choose mates is a fundamental question in evolutionary biology. Mating decisions have broad consequences, influencing individual fitness and population-level evolutionary and ecological processes, including diversification, speciation, and extinction. Discriminating against potential mates from closely related co-occurring species is a vital step in finding an appropriate mate. However, individuals from many species learn with whom to mate by first observing a variety of conspecifics, which risks mistakenly learning from co-occurring species with similar phenotypes. Genetic divergence among species in sensory perception is widely hypothesized to reduce this risk, but the underlying mechanisms and, therefore, the evolutionary causes and consequences are poorly understood. My proposal aims to uncover the causes and consequences of genetic divergence in auditory learning of songs, key species discrimination traits in birds. I have developed a powerful study system to distinguish the influences of genes and learning on species-specific song perception, employing two closely related Ficedula flycatcher species. I will use this tractable system to: (i) evaluate alternative evolutionary drivers of genetic divergence in song discrimination, (ii) determine the interplay between genetic effects and auditory learning throughout development, and (iii) associate species differences in discrimination with gene expression and, ultimately, divergence in gene regulation. To achieve these goals, I will integrate behavioural and neurogenomic approaches on populations across the flycatchers’ native range and from captive-reared populations, leveraging ongoing sequencing of songbird genomes to place flycatcher results in a broader evolutionary context. This integrative project will have the potential to radically change our understanding of the genetic basis of species differences in learned behaviors and will allow me to develop transformative, career-level research.
The current theoretical description of the fundamental constituents of matter is the Standard Model of particle physics. Despite the unprecedented experimental verification, most of its predictive power is limited to the regime where particles interact weakly, hence impeding the study of bound states, such as baryons, where interactions are strong. This proposal aims to study suitable generalizations of these particle excitations – "baryonic" operators composed of a number N of fundamental fields at a common point in spacetime – in quantum field theories that possess conformal symmetry and admit a large-N limit. These conditions are essential for the methods used in this proposal, which are based on quantum integrability of the relevant theory and on techniques for analytic resummation of Feynman diagrams. The proposed research will extend in a non-trivial way the recent progress in solving correlation functions at finite coupling in maximally supersymmetric Yang-Mills theory. Specifically, we plan to advance the state of the art of integrability, in the form of the Quantum Spectral Curve formalism originally designed for two-point correlators, to describe a class of three-point correlators involving baryonic (also known as determinant or giant-graviton) operators. We also strive to achieve a finite-coupling description of baryonic correlators through an appropriate diagrammatical methodology. Specifically, we plan to realize this goal in the non-supersymmetric gamma-deformation of the Yang-Mills theory and, finally, to adapt it to the quantum mechanical model proposed by Sachdev, Ye and Kitaev. The complicated perturbative description of baryons is both the challenge and the novelty, compared to earlier works for single-trace operators in the same theories. This proposal details a plan for dissemination and communication of its results to specialists and the general public, as well as training for the benefit of the experienced researcher.
In this project, I will study how individual and social motives interact to drive individual decisions, a question that has fallen between the cracks of different social-science approaches. I will use a common theoretical framework to approach an important, but badly understood, general question: do social motives reinforce or weaken the effect of changes in individual motives? By modifying this common framework to different applications, I will consider its predictions empirically in different large data sets with individual-level information. The planned applications include four subprojects in the social, political, and economic spheres: (i) decisions in China on the ethnicity of children in interethnic marriages and matching into such marriages, (ii) decisions on tax evasion in the U.K. and Sweden, (iii) decisions to give political campaign contributions in the U.S., and (iv) decisions about fertility in Sweden. I may also spell out the common lessons from the results on the interaction between individual and social motives in monograph format intended for a broader audience.