arXiv subjects

Hendrik Rose

Publications and source records attributed to Hendrik Rose.

7 recordsLinked to original sources

arXiv2026

Assessing the classicality of photon echo from excitons in lead halide perovskite nanocrystals

Photon echo (PE) spectroscopy is a powerful technique for probing decoherence mechanisms and charge carrier dynamics in semiconductor systems. Beyond traditional coherence measurements, characterizing the photon statistics of the echo signal is important for assessing its potential in quantum information applications and understanding the underlying quantum mechanical processes. Here, we study the photon statistics of PE signals generated by excitons in ensembles of lead halide perovskite CsPbI$_3$ nanocrystals at cryogenic temperature of 2 K using continuous-variable quantum state optical tomography based on homodyne detection. Pronounced Rabi oscillations of the PE amplitude allow us to evaluate the statistics for various pulse areas in the excitation sequence. The damping of the oscillations with increasing pulse area is attributed to spatial excitation inhomogeneity and excitation-induced dephasing. Despite the large ensemble of optically addressed excitons, the efficiency of generated PE signals is low which is attributed to the complex energy level structure of excitons and non-radiative recombination channels in CsPbI$_3$ nanocrystals. We analyze the statistical characteristics of PE via the second-order correlation function $g^{(2)}(0)$ and the characteristic function for different combinations of the areas of the excitation pulses. Our results show that $g^{(2)}(0) = 1$, and the characteristic function of the PE signal corresponds to classical behavior. The formation of photon echoes as well as $g^{(2)}(0) = 1$ at the echo time is reproduced by a quantized free-space multimode model. Despite the relatively low efficiency, the photon echo exhibits a high degree of coherence and minimal classical noise, consistent with Poissonian statistics.

cond-mat.mes-hall↗

arXiv2026

Flowcean - Model Learning for Cyber-Physical Systems

Effective models of Cyber-Physical Systems (CPS) are crucial for their design and operation. Constructing such models is difficult and time-consuming due to the inherent complexity of CPS. As a result, data-driven model generation using machine learning methods is gaining popularity. In this paper, we present Flowcean, a novel framework designed to automate the generation of models through data-driven learning that focuses on modularity and usability. By offering various learning strategies, data processing methods, and evaluation metrics, our framework provides a comprehensive solution, tailored to CPS scenarios. Flowcean facilitates the integration of diverse learning libraries and tools within a modular and flexible architecture, ensuring adaptability to a wide range of modeling tasks. This streamlines the process of model generation and evaluation, making it more efficient and accessible.

cs.LG↗

arXiv2026

Microscopic simulations of the coupled dynamics of cavity photons, excitons, and biexcitons

The coherent interaction between quantum light and material excitations in semiconductor nanostructures is investigated using a fully quantized microscopic approach that incorporates many-body Coulomb correlations. The simulations demonstrate that the quantum dynamics is influenced by biexciton continuum states and is highly sensitive to both the frequency of the cavity mode and the strength of the light-matter coupling.

cond-mat.mes-hall↗

arXiv2025

Microscopic approach to the quantized light-matter interaction in semiconductor nanostructures: Complex coupled dynamics of excitons, biexcitons, and photons

We present a microscopic and fully quantized model to investigate the interaction between semiconductor nanostructures and quantum light fields including the many-body Coloumb interaction between photoexcited electrons and holes. Our approach describes the coupled dynamics of the quantum light field and single and double electron-hole pairs, i.e., excitons and biexcitons, and exactly accounts for Coulomb many-body correlations and carrier band dispersions. Using a simplified yet exact approach, we study a one-dimensional two-band system interacting with a single-mode, two-photon quantum state within a Tavis$\unicode{x2013}$Cummings framework. By employing an exact coherent factorization scheme, the computational complexity is reduced significantly enabling numerical simulations. We also derive a simplified model which includes only the bound $1s$-exciton and biexciton states for comparison. Our simulations reveal distinct single- and two-photon Rabi oscillations, corresponding to photon-exciton and exciton-biexciton transitions. We demonstrate, in particular, that biexciton continuum states significantly modify the dynamics in a way that cannot be captured by simplified models which consider only bound states. Our findings emphasize the importance of a comprehensive microscopic modeling in order to accurately describe quantum optical phenomena of interacting electronic many-body systems.

cond-mat.mes-hall↗

arXiv2024

Accelerating the analysis of optical quantum systems using the Koopman operator

The prediction of photon echoes is a crucial technique for understanding optical quantum systems. However, it typically requires numerous simulations with varying parameters and input pulses, rendering numerical studies computationally expensive. This article investigates the use of data-driven surrogate models based on the Koopman operator to accelerate this process while maintaining accuracy over many time steps. To this end, we employ a bilinear Koopman model using extended dynamic mode decomposition to simulate the optical Bloch equations for an ensemble of inhomogeneously broadened two-level systems. These systems are well suited to describe the excitation of excitonic resonances in semiconductor nanostructures, such as ensembles of semiconductor quantum dots. We conduct a detailed study to determine the number of system simulations required for the resulting data-driven Koopman model to achieve sufficient accuracy across a wide range of parameter settings. We analyze the L2 error and the relative error of the photon echo peak and investigate how the control positions relate to stabilization. After proper training, our methods can predict the dynamics of the quantum ensemble accurately and with numerical efficiency.

quant-ph↗

arXiv2024

Numerical solution of nonlinear Schr\"odinger equation by a hybrid pseudospectral-variational quantum algorithm

The time-dependent one-dimensional nonlinear Schr\"odinger equation (NLSE) is solved numerically by a hybrid pseudospectral-variational quantum algorithm that connects a pseudospectral step for the Hamiltonian term with a variational step for the nonlinear term. The Hamiltonian term is treated as an integrating factor by forward and backward Fourier transformations, which are here carried out classically. This split allows us to avoid higher-order time integration schemes, to apply a first-order explicit time stepping for the remaining nonlinear NLSE term in a variational algorithm block, and thus to avoid numerical instabilities. We demonstrate that the analytical solution is reproduced with a small root mean square error for a long time interval over which a nonlinear soliton propagates significantly forward in space while keeping its shape. We analyze the accuracy of the quantum algorithm and compare it with classical approaches. Furthermore, we investigate the influence of algorithm parameters on the accuracy of the results, including the temporal step width and the depth of the quantum circuit.

quant-ph↗

arXiv2021

Analysis of the Operation of Industrial Trucks based on Position Data

Indoor positioning systems (IPSs) can make an important contribution to the analysis and optimization of internal transport processes. The overall aim of this work is to examine how position data can be used to analyze the operation of industrial trucks in warehouses. This is achieved by developing a concept for the analysis of industrial truck operations based merely on position data. The concept consists of a signal processing scheme to derive kinematic data and three analysis methods - Monitoring, Area analysis, and Motion analysis. Schemes for the signal processing and detection of motion events were developed and implemented as part of the TrOpLocerApp (Truck Operation Localization Analyzer-Application) for recording, displaying, and processing position data, according to the proposed system concept. The TrOpLocer-App source code is published on GitLab. Different filter algorithms were examined, as part of the signal processing scheme, from which the low pass Butterworth filter has shown the best results in static experiments. Validation of the motion detection scheme shows good detection quality for distinct events in a realistic movement experiment.

eess.SP↗