Electron spectral functions in a quantum dimer model for topological metals

We study single electron spectral functions in a quantum dimer model introduced by Punk, Allais and Sachdev (Ref. [1]). The Hilbert space of this model is spanned by hard-core coverings of the square lattice with two types of dimers: ordinary bosonic spin-singlets, as well as fermionic dimers carrying charge +e and spin 1/2, which can be viewed as bound-states of spinons and holons in a doped resonating valence bond (RVB) liquid. This model realizes a metallic phase with topological order and captures several properties of the pseudogap phase in hole-doped cuprates, such as a reconstructed Fermi surface with small hole-pockets and a highly anisotropic quasiparticle residue in the absence of any broken symmetries. Using a combination of exact diagonalization and analytical methods we compute electron spectral functions and show that this model indeed exhibits a sizeable antinodal pseudogap, with a momentum dependence deviating from a simple d-wave form, in accordance with experiments on underdoped cuprates.Comment: 13 pages, 7 figure

Exact solution of a two-species quantum dimer model for pseudogap metals

We present an exact ground state solution of a quantum dimer model introduced in Ref.[1], which features ordinary bosonic spin-singlet dimers as well as fermionic dimers that can be viewed as bound states of spinons and holons in a hole-doped resonating valence bond liquid. Interestingly, this model captures several essential properties of the metallic pseudogap phase in high-$T_c$ cuprate superconductors. We identify a line in parameter space where the exact ground state wave functions can be constructed at an arbitrary density of fermionic dimers. At this exactly solvable line the ground state has a huge degeneracy, which can be interpreted as a flat band of fermionic excitations. Perturbing around the exactly solvable line, this degeneracy is lifted and the ground state is a fractionalized Fermi liquid with a small pocket Fermi surface in the low doping limit.Comment: Revised version, 8 page

Signatures of correlated magnetic phases in the local two-particle density matrix

Experiments with quantum gas microscopes have started to explore the antiferromagnetic phase of the two-dimensional Fermi-Hubbard model and effects of doping with holes away from half filling. In this work we show how direct measurements of the system averaged two-spin density matrix and its full counting statistics can be used to identify different correlated magnetic phases with or without long-range order. We discuss examples of phases which are potentially realized in the Hubbard model close to half filling, including antiferrromagnetically ordered insulators and metals, as well as insulating spin-liquids and metals with topological order. For these candidate states we predict the doping- and temperature dependence of local correlators, which can be directly measured in current experiments.Comment: 15 pages, 7 figure

Empirical studies on language-learning, migration and trade

Language learning is a fundamental skill taught in schools all across the World. In the European Union1, e.g. almost 93% of the pupils in 2019 learn a foreign language already in primary education (Eurostat, 2021). Language learning in schools is usually compulsory, it is likely to come with few or no costs and the acquired skills might affect later decisions in live, e.g. migration decisions. On the contrary, many adults decide to acquire foreign language skills voluntarily. In that case the direction of causality can be the opposite to that with language learning during childhood or adolescence. The determinants of foreign language skills and their benets can be approached from two perspectives, the aggregated macro-perspective and the individual micro-perspective. While Part I focusses on adult language learning on the macro-level, Part II uses a micro perspective on language learning. Part III remains on the individual perspective, but concentrates more generally on migration intentions and aspirations, very important aspects of adult language learning

Autonomic Performance-Aware Resource Management in Dynamic IT Service Infrastructures

Model-based techniques are a powerful approach to engineering autonomic and self-adaptive systems. This thesis presents a model-based approach for proactive and autonomic performance-aware resource management in dynamic IT infrastructures. Core of the approach is an architecture-level modeling language to describe performance and resource management related aspects in such environments. With this approach, it is possible to autonomically find suitable system configurations at the model level

3D Face Tracking and Texture Fusion in the Wild

We present a fully automatic approach to real-time 3D face reconstruction from monocular in-the-wild videos. With the use of a cascaded-regressor based face tracking and a 3D Morphable Face Model shape fitting, we obtain a semi-dense 3D face shape. We further use the texture information from multiple frames to build a holistic 3D face representation from the video frames. Our system is able to capture facial expressions and does not require any person-specific training. We demonstrate the robustness of our approach on the challenging 300 Videos in the Wild (300-VW) dataset. Our real-time fitting framework is available as an open source library at http://4dface.org