Observation of magnon bound states in the long-range, anisotropic Heisenberg model

Over the recent years coherent, time-periodic modulation has been established as a versatile tool for realizing novel Hamiltonians. Using this approach, known as Floquet engineering, we experimentally realize a long-ranged, anisotropic Heisenberg model with tunable interactions in a trapped ion quantum simulator. We demonstrate that the spectrum of the model contains not only single magnon excitations but also composite magnon bound states. For the long-range interactions with the experimentally realized power-law exponent, the group velocity of magnons is unbounded. Nonetheless, for sufficiently strong interactions we observe bound states of these unconventional magnons which possess a non-diverging group velocity. By measuring the configurational mutual information between two disjoint intervals, we demonstrate the implications of the bound state formation on the entanglement dynamics of the system. Our observations provide key insights into the peculiar role of composite excitations in the non-equilibrium dynamics of quantum many-body systems

Exploring Large-Scale Entanglement in Quantum Simulation

Entanglement is a distinguishing feature of quantum many-body systems, and uncovering the entanglement structure for large particle numbers in quantum simulation experiments is a fundamental challenge in quantum information science. Here we perform experimental investigations of entanglement based on the entanglement Hamiltonian, as an effective description of the reduced density operator for large subsystems. We prepare ground and excited states of a 1D XXZ Heisenberg chain on a 51-ion programmable quantum simulator and perform sample-efficient `learning' of the entanglement Hamiltonian for subsystems of up to 20 lattice sites. Our experiments provide compelling evidence for a local structure of the entanglement Hamiltonian. This observation marks the first instance of confirming the fundamental predictions of quantum field theory by Bisognano and Wichmann, adapted to lattice models that represent correlated quantum matter. The reduced state takes the form of a Gibbs ensemble, with a spatially-varying temperature profile as a signature of entanglement. Our results also show the transition from area to volume-law scaling of Von Neumann entanglement entropies from ground to excited states. As we venture towards achieving quantum advantage, we anticipate that our findings and methods have wide-ranging applicability to revealing and understanding entanglement in many-body problems with local interactions including higher spatial dimensions.Comment: 14 pages, 7 figure

Charakterisierung optischer faserbasierter Fabry-Pérot-Resonatoren

vorgelegt von Florian KranzlUniversität Innsbruck, Masterarbeit, 2017(VLID)232466

Incorporating grid expansion in an energy system optimisation model - A case study for Indonesia

Energy system optimisation models (ESOMs) are widely used for policy analyses particularly on topics related to climate change mitigation and renewable energy transition. Using ESOM to investigate regions that potentially require significant expansion of grid infrastructure requires incorporation of grid expansion problem within the optimisation. This study presents the development of SELARU, a Mixed-Integer Linear Programming (MILP) model for spatially explicit long-term energy infrastructure planning. The model is used to investigate the case study of Indonesia using various spatial treatments to demonstrate the impact of detailed spatial depiction of grid expansion. Results reveal significant difference in renewable energy deployment trajectory (up to 315% increase in generation capacity) between high-resolution spatial depiction of grid expansion vis-à-vis non spatially explicit energy system optimisation. SELARU’s high-resolution energy system optimization modelling also provides detailed information on the geographical extent of grid expansion requirement, which provides more realistic insights on governance challenges of renewable energy transition. Careful consideration of spatial representation is crucial when ESOM is used to evaluate scenarios that concern technology selection such as renewable energy deployment or climate change mitigation

European consensus on the concepts and measurement of the pathophysiological neuromuscular responses to passive muscle stretch

Background and purpose To support clinical decision-making in central neurological disorders, a physical examination is used to assess responses to passive muscle stretch. However, what exactly is being assessed is expressed and interpreted in different ways. A clear diagnostic framework is lacking. Therefore, the aim was to arrive at unambiguous terminology about the concepts and measurement around pathophysiological neuromuscular response to passive muscle stretch. Methods During two consensus meetings, 37 experts from 12 European countries filled online questionnaires based on a Delphi approach, followed by plenary discussion after rounds. Consensus was reached for agreement ≥75%. Results The term hyper-resistance should be used to describe the phenomenon of impaired neuromuscular response during passive stretch, instead of for example ‘spasticity’ or ‘hypertonia’. From there, it is essential to distinguish non-neural (tissue-related) from neural (central nervous system related) contributions to hyper-resistance. Tissue contributions are elasticity, viscosity and muscle shortening. Neural contributions are velocity dependent stretch hyperreflexia and non-velocity dependent involuntary background activation. The term ‘spasticity’ should only be used next to stretch hyperreflexia, and ‘stiffness’ next to passive tissue contributions. When joint angle, moment and electromyography are recorded, components of hyper-resistance within the framework can be quantitatively assessed. Conclusions A conceptual framework of pathophysiological responses to passive muscle stretch is defined. This framework can be used in clinical assessment of hyper-resistance and will improve communication between clinicians. Components within the framework are defined by objective parameters from instrumented assessment. These parameters need experimental validation in order to develop treatment algorithms based on the aetiology of the clinical phenomena