Equilibration in low-dimensional quantum matrix models

Matrix models play an important role in studies of quantum gravity, being candidates for a formulation of M-theory, but are notoriously difficult to solve. In this work, we present a fresh approach by introducing a novel exact model provably equivalent with low-dimensional bosonic matrix models. In this equivalent model significant local structure becomes apparent and it can serve as a simple toy model for analytical and precise numerical study. We derive a substantial part of the low energy spectrum, find a conserved charge, and are able to derive numerically the Regge trajectories. To exemplify the usefulness of the approach, we address questions of equilibration starting from a non-equilibrium situation, building upon an intuition from quantum information. We finally discuss possible generalizations of the approach.Comment: 5+2 pages, 2 figures; v2: published versio

Phonon driven Floquet matter

A resonantly excited coherent phonon leads to a periodic oscillation of the atomic lattice in a crystal structure bringing the material into a non-equilibrium electronic configuration. Periodically oscillating quantum systems can be understood in terms of Floquet theory and we show these concepts can be applied to coherent lattice vibrations reflecting the underlying coupling mechanism between electrons and bosonic modes. This coupling leads to dressed quasi-particles imprinting specific signatures in the spectrum of the electronic structure. Taking graphene as a paradigmatic material we show how the phonon-dressed states display an intricate sideband structure revealing electron-phonon coupling and topological ordering. This work establishes that the recently demonstrated concept of light-induced non-equilibrium Floquet phases can also be applied when using coherent phonon modes for the dynamical control of material properties. The present results are generic for bosonic time-dependent perturbations and similar phenomena can be observed for plasmon, magnon or exciton driven materials

A first principles TDDFT framework for spin and time-resolved ARPES in periodic systems

We present a novel theoretical approach to simulate spin, time and angular-resolved photoelectron spectroscopy (ARPES) from first principles that is applicable to surfaces, thin films, few layer systems, and low-dimensional nanostructures. The method is based on a general formulation in the framework of time-dependent density functional theory (TDDFT) to describe the real time-evolution of electrons escaping from a surface under the effect of any external (arbitrary) laser field. By extending the so called t-SURFF method to periodic systems one can calculate the final photoelectron spectrum by collecting the flux of the ionization current trough an analysing surface. The resulting approach, that we named t-SURFFP, allows to describe a wide range of irradiation conditions without any assumption on the dynamics of the ionization process allowing for pump-probe simulations on an equal footing. To illustrate the wide scope of applicability of the method we present applications to graphene, mono- and bi-layer WSe$_2$, and hexagonal BN under different laser configurations

Continuous matrix product state tomography of quantum transport experiments

In recent years, a close connection between the description of open quantum systems, the input-output formalism of quantum optics, and continuous matrix product states in quantum field theory has been established. So far, however, this connection has not been extended to the condensed-matter context. In this work, we substantially develop further and apply a machinery of continuous matrix product states (cMPS) to perform tomography of transport experiments. We first present an extension of the tomographic possibilities of cMPS by showing that reconstruction schemes do not need to be based on low-order correlation functions only, but also on low-order counting probabilities. We show that fermionic quantum transport settings can be formulated within the cMPS framework. This allows us to present a reconstruction scheme based on the measurement of low-order correlation functions that provides access to quantities that are not directly measurable with present technology. Emblematic examples are high-order correlations functions and waiting times distributions (WTD). The latter are of particular interest since they offer insights into short-time scale physics. We demonstrate the functioning of the method with actual data, opening up the way to accessing WTD within the quantum regime.Comment: 11 pages, 4 figure

The relevance of depression-associated genes in neuronal in vitro systems.

Um neue Erkenntnisse über die Bedeutung der 15 „Depressionsgene“ im Gehirn für die Pathophysiologie der IFN-α-induzierten sowie der endogenen Depressionserkrankungen zu erlangen, wurde in dieser Dissertation zunächst ein in vitro-Zellkultursystem aus murinen hippocampalen und kortikalen Primärneuronen entwickelt. Durch Nachahmung einer Hepatitis-C-Virus-Therapie (HCV) durch Kostimulation mit murinem Interferon-alpha (mIFN-α) (1000 IU/ml) und dem TLR3-Agonisten Polyinosin:Polycytidylsäure (Poly(I:C)) (100 μg/ml) wurde eine starke Überexpression der „Depressionsgene“ Gch1, Disc1, Tor1b, Dynlt1 und Mef2a in primären Neuronen in vitro gezeigt. Stat1, Ube2L6, Rtp4 und Gbp1 wurden genau so wie in den in vitro Vorversuchen mit der hippocampalen HT22 Zelllinie höher als alle anderen „Depressionsgene“ exprimiert. Die schnelle Regulation dieser Gene lässt vermuten, dass diese als nützliche Marker für eine Depression geeignet sind. Die synergistische mIFN/Poly(I:C)-Wirkung förderte zugleich eine Überexpression der proinflammatorischen Zytokine Cxcl1, Cxcl10, Ccl5, Tnf, Il6 und Ifng auf molekularen und proteinbiochemischen Ebenen in hippocampalen und kortikalen Neuronen in vitro, die hauptsächlich einer STAT1-abhängigen transkriptionellen Antwort auf IFN-α unterliegen. Diese „Downstream“-Zytokine stellen einen möglichen Zusammenhang zwischen den Entzündungsprozessen im Gehirn und der Veränderung der Neurotransmitterbiosynthese durch eine synergetisch erhöhte Aktivität des Enzyms Indolamin-2,3-Dioxygenase (Ido1), des Serotonintransporters (Slc6a4) und -rezeptors (Htr1a) sowie durch eine gewebespezifische Veränderung der Expression des Dopamintransporters (Slc6a3) auf indirektem Weg in primären Neuronen in vitro dar. Da die transkriptionelle Antwort auf IFN-α in Neuronen vollständig von STAT1 abhängt, beeinflusst die in dieser Arbeit gefundene starke IFN/Poly(I:C)-vermittelte STAT1-Aktivierung in primären Neuronen die Induktion der proinflammatorischen Zytokine, die wiederum eine mögliche Überexpression von inflammatorischen Genen steuert. Durch einen gezielten STAT1-„Knockdown“ mittels RNAi- Technologie wurde eine signifikante Suppression der „Depressionsgene“ Gch1, Disc1, Mef2a in hippocampalen und kortikalen Neuronen in vitro nachgewiesen. Da erstens das Kandidatengen Gch1 in die Serotonin/Dopamin-Biosynthese involviert ist, zweitens Disc1 mit der Entstehung von Schizophrenie und Depression und drittens Mef2a mit der Hemmung des Neuritenwachstums und der kortikalen Entwicklung assoziiert ist, scheint die transiente STAT1-Suppression ein wirksames molekulares Target für die Hemmung der „Depressionsgen“-Funktion zu sein. Die STAT1-Suppression hat trotz anschließender mIFN/Poly(I:C)-Kostimulation ebenfalls eine signifikant hemmende Wirkung auf die Expression von Ccl5, Il6 und Cxcl10, der Ido1 und Slc6a4 in primären Neuronen. Somit spielt STAT1 eine wichtige Rolle im IFN-abhängigen Signalweg der Gehirnzellen und scheint ein Schlüsselmolekül in der Regulation der besonders wichtigen „Depressionsgene“, Neurotransmittermoleküle und der „Downstream“- Zytokine zu sein. Die gezielte STAT1-Suppression im Gehirn kann einem möglichen therapeutischen Ansatz zur Verbesserung/Minderung der Symptome einer exogenen/endogenen Depression dienen

Quantum field tomography

We introduce the concept of quantum field tomography, the efficient and reliable reconstruction of unknown quantum fields based on data of correlation functions. At the basis of the analysis is the concept of continuous matrix product states, a complete set of variational states grasping states in quantum field theory. We innovate a practical method, making use of and developing tools in estimation theory used in the context of compressed sensing such as Prony methods and matrix pencils, allowing us to faithfully reconstruct quantum field states based on low-order correlation functions. In the absence of a phase reference, we highlight how specific higher order correlation functions can still be predicted. We exemplify the functioning of the approach by reconstructing randomised continuous matrix product states from their correlation data and study the robustness of the reconstruction for different noise models. We also apply the method to data generated by simulations based on continuous matrix product states and using the time-dependent variational principle. The presented approach is expected to open up a new window into experimentally studying continuous quantum systems, such as encountered in experiments with ultra-cold atoms on top of atom chips. By virtue of the analogy with the input-output formalism in quantum optics, it also allows for studying open quantum systems.Comment: 31 pages, 5 figures, minor change