Phase Diagram of Bosons in Two-Color Superlattices from Experimental Parameters

We study the zero-temperature phase diagram of a gas of bosonic 87-Rb atoms in two-color superlattice potentials starting directly from the experimental parameters, such as wavelengths and intensities of the two lasers generating the superlattice. In a first step, we map the experimental setup to a Bose-Hubbard Hamiltonian with site-dependent parameters through explicit band-structure calculations. In the second step, we solve the many-body problem using the density-matrix renormalization group (DMRG) approach and compute observables such as energy gap, condensate fraction, maximum number fluctuations and visibility of interference fringes. We study the phase diagram as function of the laser intensities s_2 and s_1 as control parameters and show that all relevant quantum phases, i.e. superfluid, Mott-insulator, and quasi Bose-glass phase, and the transitions between them can be investigated through a variation of these intensities alone.Comment: 4 pages, 3 figure

What have they been up to in Lübeck recently

This talk will give an overview over three related research prototypes for ambient interactive systems. We start by introducing NEMO, the Network Environment for Multimedia Objects. NEMO is a smart media environment for semantically rich, personalised, and device-specific access to and interaction with multimedia objects. Next, a shared electronic whiteboard called ShareBoard is decribed. The goal of ShareBoard is to deliver a natural user interface to working with electronic whiteboards. Integrated within ShareBoard are input devices to recognise the movement of users in the surrounding space and for sensing 3D-gesture. ShareBoard can make use of media objects in NEMO. Last, we introduce the Modular Awareness Construction Kit. MACK is a framework for developing context aware, ambient intelligent systems that blend seamlessly with the users’ everyday route, enabling unobtrusive in-situ interaction and facilitating enhanced cooperation and communication. In the future, MACK is to deliver contextual information to both NEMO and ShareBoard

Ultracold Bose gases in time-dependent 1D superlattices: response and quasimomentum structure

The response of ultracold atomic Bose gases in time-dependent optical lattices is discussed based on direct simulations of the time-evolution of the many-body state in the framework of the Bose-Hubbard model. We focus on small-amplitude modulations of the lattice potential as implemented in several recent experiment and study different observables in the region of the first resonance in the Mott-insulator phase. In addition to the energy transfer we investigate the quasimomentum structure of the system which is accessible via the matter-wave interference pattern after a prompt release. We identify characteristic correlations between the excitation frequency and the quasimomentum distribution and study their structure in the presence of a superlattice potential.Comment: 4 pages, 4 figure

Forensic Analysis of Smartphones: The Android Data Extractor Lite (ADEL)

Due to the ubiquitous use of smartphones, these devices become an increasingly important source of digital evidence in forensic investigations. Thus, the recovery of digital traces from smartphones often plays an essential role for the examination and clarification of the facts in a case. Although some tools already exist regarding the examination of smartphone data, there is still a strong demand to develop further methods and tools for forensic extraction and analysis of data that is stored on smartphones. In this paper we describe specifications of smartphones running Android. We further introduce a newly developed tool – called ADEL – that is able to forensically extract and analyze data from SQLite databases on Android devices. Finally, a detailed report containing the results of the examination is created by the tool. The whole process is fully automated and takes account of main forensic principles. Keywords: Android, Smartphones, Mobile devices, Forensics

Understanding Concept Identification as Consistent Data Clustering Across Multiple Feature Spaces

Identifying meaningful concepts in large data sets can provide valuable insights into engineering design problems. Concept identification aims at identifying non-overlapping groups of design instances that are similar in a joint space of all features, but which are also similar when considering only subsets of features. These subsets usually comprise features that characterize a design with respect to one specific context, for example, constructive design parameters, performance values, or operation modes. It is desirable to evaluate the quality of design concepts by considering several of these feature subsets in isolation. In particular, meaningful concepts should not only identify dense, well separated groups of data instances, but also provide non-overlapping groups of data that persist when considering pre-defined feature subsets separately. In this work, we propose to view concept identification as a special form of clustering algorithm with a broad range of potential applications beyond engineering design. To illustrate the differences between concept identification and classical clustering algorithms, we apply a recently proposed concept identification algorithm to two synthetic data sets and show the differences in identified solutions. In addition, we introduce the mutual information measure as a metric to evaluate whether solutions return consistent clusters across relevant subsets. To support the novel understanding of concept identification, we consider a simulated data set from a decision-making problem in the energy management domain and show that the identified clusters are more interpretable with respect to relevant feature subsets than clusters found by common clustering algorithms and are thus more suitable to support a decision maker.Comment: 10 pages, 6 figures, to be published in proceedings of 2022 IEEE International Conference on Data Mining Workshops (ICDMW