Quantum and classical criticality in a dimerized quantum antiferromagnet

A quantum critical point (QCP) is a singularity in the phase diagram arising because of quantum mechanical fluctuations. The exotic properties of some of the most enigmatic physical systems, including unconventional metals and superconductors, quantum magnets and ultracold atomic condensates, have been related to the importance of critical quantum and thermal fluctuations near such a point. However, direct and continuous control of these fluctuations has been difficult to realize, and complete thermodynamic and spectroscopic information is required to disentangle the effects of quantum and classical physics around a QCP. Here we achieve this control in a high-pressure, high-resolution neutron scattering experiment on the quantum dimer material TlCuCl3. By measuring the magnetic excitation spectrum across the entire quantum critical phase diagram, we illustrate the similarities between quantum and thermal melting of magnetic order. We prove the critical nature of the unconventional longitudinal (Higgs) mode of the ordered phase by damping it thermally. We demonstrate the development of two types of criticality, quantum and classical, and use their static and dynamic scaling properties to conclude that quantum and thermal fluctuations can behave largely independently near a QCP.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

Linked services for M2M communication with Enterprise IT systems

Linking the physical world to the Internet, also known as the Internet of Things, has increased available information and services in everyday life and in the Enterprise world. In Enterprise IT an increasing number of communication is done between IT backend systems and small IoT devices, for example sensor networks or RFID readers. This introduces some challenges in terms of complexity and integration. We are working on the integration of IoT devices into Enterprise IT by leveraging SOA techniques and Semantic Web technologies. We present a SOA based integration platform for connecting WSNs and large enterprise business processes. For ensuring interoperability our platform is based on Linked Services. These are thoroughly described, machine-readable, machine-reasonable service descriptions.

Translational diffusion of water in compacted clay systems

The translational diffusion of water in compacted clays at a high hydration level has been investigated by quasielastic neutron scattering at a time-of-flight spectrometer FOCUS (SINQ). Four compacted clays with systematic structural differences have been studied: Na-montmorillonite, Na-illite, kaolinite and pyrophyllite. The QENS experiments were performed using two different incident wavelengths in order to access a larger Q range and verify the data analysis. The translational diffusion coefficient for water in Na-montmorillonite and Na-illite are lower than those for bulk water, whereas the preliminary results for kaolinite and pyrophyllite show larger diffusion coefficient.

Climate change in Switzerland: a review of physical, institutional, and political aspects

Climate change is clearly discernible in observed climate records in Switzerland. It impacts on natural systems, ecosystems, and economic sectors such as agriculture, tourism, and energy, and it affects Swiss livelihood in various ways. The observed and projected changes call for a response from the political system, which in Switzerland is characterized by federalism and direct democratic instruments. Swiss climate science embraces natural and social sciences and builds on institutionalized links between researchers, public, and private stakeholders. In this article, we review the physical, institutional, and political aspects of climate change in Switzerland. We show how the current state of Swiss climate science and policy developed over the past 20 years in the context of international developments and national responses. Specific to Switzerland is its topographic setting with mountain regions and lowlands on both sides of the Alpine ridge, which makes climate change clearly apparent and for some aspects (tourist sector, hydropower, and extreme events) highly relevant and better perceivable (e.g., retreating glaciers). Not surprisingly the Alpine region is of central interest in Swiss climate change studies.

Real-time simulation of large open quantum spin systems driven by dissipation

We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

Grazing behaviour, physical activity and metabolic profile of two Holstein strains in an organic grazing system

The challenge for sustainable organic dairy farming is identification of cows that are well adapted to forage-based production systems. Therefore, the aim of this study was to compare the grazing behaviour, physical activity and metabolic profile of two different Holstein strains kept in an organic grazing system without concentrate supplementation. Twelve Swiss (HCH ; 566 kg body weight (BW) and 12 New Zealand Holstein-Friesian (HNZ ; 530 kg BW) cows in mid-lactation were kept in a rotational grazing system. After an adaptation period, the milk yield, nutrient intake, physical activity and grazing behaviour were recorded for each cow for 7 days. On three consecutive days, blood was sampled at 07:00, 12:00 and 17:00 h from each cow by jugular vein puncture. Data were analysed using linear mixed models. No differences were found in milk yield, but milk fat (3.69 vs. 4.05%, P = 0.05) and milk protein percentage (2.92 vs. 3.20%, P < 0.01) were lower in HCH than in HNZ cows. Herbage intake did not differ between strains, but organic matter digestibility was greater (P = 0.01) in HCH compared to HNZ cows. The HCH cows spent less (P = 0.04) time ruminating (439 vs. 469 min/day) and had a lower (P = 0.02) number of ruminating boli when compared to the HNZ cows. The time spent eating and physical activity did not differ between strains. Concentrations of IGF-1 and T3 were lower (P ≤ 0.05) in HCH than HNZ cows. In conclusion, HCH cows were not able to increase dry matter intake in order to express their full genetic potential for milk production when kept in an organic grazing system without concentrate supplementation. On the other hand, HNZ cows seem to compensate for the reduced nutrient availability better than HCH cows but could not use that advantage for increased production efficiency

Real-time dynamics of open quantum spin systems driven by dissipative processes

We study the real-time evolution of large open quantum spin systems in two spatial dimensions, whose dynamics is entirely driven by a dissipative coupling to the environment. We consider different dissipative processes and investigate the real-time evolution from an ordered phase of the Heisenberg or XY model towards a disordered phase at late times, disregarding unitary Hamiltonian dynamics. The corresponding Kossakowski-Lindblad equation is solved via an efficient cluster algorithm. We find that the symmetry of the dissipative process determines the time scales, which govern the approach towards a new equilibrium phase at late times. Most notably, we find a slow equilibration if the dissipative process conserves any of the magnetization Fourier modes. In these cases, the dynamics can be interpreted as a diffusion process of the conserved quantity.

Real-time simulation of nonequilibrium transport of magnetization in large open quantum spin systems driven by dissipation

Using quantum Monte Carlo, we study the nonequilibrium transport of magnetization in large open strongly correlated quantum spin-12 systems driven by purely dissipative processes that conserve the uniform or staggered magnetization, disregarding unitary Hamiltonian dynamics. We prepare both a low-temperature Heisenberg ferromagnet and an antiferromagnet in two parts of the system that are initially isolated from each other. We then bring the two subsystems in contact and study their real-time dissipative dynamics for different geometries. The flow of the uniform or staggered magnetization from one part of the system to the other is described by a diffusion equation that can be derived analytically.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.