89 88 Principal Scientist Profiles Martin Gärttner Martin Gärttner Principal Scientist Profiles PROFESSOR OF QUANTUM INFORMATION THEORY Martin Gärttner is Professor for Quantum Information Theory at the Friedrich Schiller University Jena. He is leading the Quantum Information and Quantum Many Body Dynamics group at the Institute for Condensed Matter Theory and Optics (IFTO). Prof. Gärttner is active in networks on Quantum Technologies across Germany and Europe. He is coordinating student networks within the European Quantum Science and Technology Master program DigiQ (www.digiq.eu). Within the network EFEQT (www.efeqt.eu) he is organizing workshops and online quantum meetups for Master students. MARTIN GÄRTTNER RESEARCH AREAS Emerging quantum technologies will potentially transform important technological areas such as computing, communication, and sensing. What fascinates us as physicists is that many phenomena that arise when many particles interact at the quantum level are still poorly understood. Nevertheless these phenomena, such as entanglement, are what actually makes quantum devices potentially so powerful, and their better understanding is thus key. Towards this goal we develop analytical and numerical tools to model and simulate quantum many-body systems and search for efficient ways to prepare and probe interesting quantum states of matter. The Gärttner group focusses on • Efficient methods to extract information form data generated by quantum simulation experiments, for example entanglement detection or quantum state tomography • Machine learning assisted ab-initio methods for simulating the dynamics of strongly interacting quantum manybody systems • Thermalization of closed quantum systems, specifically of disordered spin systems TEACHING FIELDS Martin Gärttner gives specialized lectures on Quantum Information Theory, Quantum Technologies, Quantum Computing, and Computational Methods in Quantum Physics. His teaching is research oriented and he includes interactive elements like quizzes and small programming exercises in his lectures. QUANTUM OPTICS RESEARCH METHODS We use and develop many different numerical techniques for simulating the dynamics of quantum many-body systems. This includes exact diagonalization and semiclassical methods like the truncated Wigner approximation, but also variational methods using neural networks to approximate quantum many-body states. To improve the readout of quantum devices we develop entanglement witnesses, and use detector tomography and quantum state tomography, combined with Bayesian methods for parameter estimation. RECENT RESEARCH RESULTS Machine learning for complex quantum systems: Artificial neural networks have proven extremely successful for machine learning tasks such as computer vision and speech recognition. In quantum many-body physics they can help speeding up ab-initio simulations or processing of data from quantum experiments. For instance, generative models can be trained to approximate probability distributions based on data samples. Quantum states are represented by highdimensional probability distributions, inviting the use of generative models for finding efficient state representations. We use this approach to develop numerical tools for calculating the time evolution of quantum many-body states [1] and to do quantum state tomography [2]. Entanglement detection: Entanglement, which Erwin Schrödinger coined the characteristic treat of quantum mechanics, is the resource that renders many quantum technologies superior to their classical counterparts. At the same time entanglement is at the heart of many physical phenomena. For example, it explains why interacting quantum systems, even when perfectly isolated from their environment, can relax to thermal equilibrium. Thus, techniques for detecting and quantifying entanglement based on experimental data are direly needed. We develop such techniques taking into account the concrete measurement capabilities of quantum simulation platforms including cold atoms and photonic systems [3,4]. Thermalization in disordered spin systems: Disorder is present in many natural systems from glasses and amorphous solids to social networks with seemingly random connections. Such systems often show surprising emergent dynamical effects. In the realm of quantum many-body systems disorder can lead to hierarchical relaxation and glassy behavior. We study relaxation dynamics and transport in quantum spin systems where the inter-particle interactions are to some degree random. Such systems can be realized by cold atoms excited to Rydberg states. In these highly excited states the atoms interact via strong dipole-dipole interactions. We model these systems numerically [5] and try to come up with new ways for experimentally probing their properties [6]. DETECTING HIGH-DIMENSIONAL ENTANGLEMENT IN COLD-ATOM QUANTUM SIMULATORS Quantum entanglement has been identified as a crucial concept underlying many intriguing phenomena in condensed matter systems such as topological phases or many-body localization. What remains a challenge is the experimental detection of such fine-grained properties of quantum systems. The development of protocols for detecting entanglement in cold atom systems, which are one of the leading platforms for quantum simulation, is thus highly desirable and will open up new avenues for experimentally exploring quantum many-body physics. In a recent work, we have developed a method to bound the width of the so called entanglement spectrum, or entanglement dimension, of cold atoms in lattice geometries, requiring only measurements in two experimentally accessible bases and utilizing ballistic time-of-flight (ToF) expansion (see figure). We could show that this methods allows high dimensional entanglement certification under experimentally realistic conditions and using currently available experimental techniques [7]. [1] Reh et al, Phys. Rev. Lett. 127, 230501 (2021). [2] Schmale et al, npj Quantum Information 8, 115 (2022). [3] Gärttner et al, Phys. Rev. Lett. 131, 150201 (2023). [4] Bergh and Gärttner, Phys. Rev. Lett. 126, 190503 (2021). [5] Braemer et al, Phys. Rev. B 106, 134212 (2022). [6] Franz et al, ArXiv 2207.14216 (2022). [7] Euler and Gärttner, ArXiv 2305.07413. Contact: Phone: + 49 3641 9-47180 Email: martin.gaerttner@uni-jena.de
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