zfit: scalable pythonic fitting

Statistical modeling is a key element in many scientific fields and especially in High-Energy Physics (HEP) analysis. The standard framework to perform this task in HEP is the C++ ROOT/RooFit toolkit; with Python bindings that are only loosely integrated into the scientific Python ecosystem. In this paper, zfit, a new alternative to RooFit written in pure Python, is presented. Most of all, zfit provides a well defined high-level API and workflow for advanced model building and fitting, together with an implementation on top of TensorFlow, allowing a transparent usage of CPUs and GPUs. It is designed to be extendable in a very simple fashion, allowing the usage of cutting-edge developments from the scientific Python ecosystem in a transparent way. The main features of zfit are introduced, and its extension to data analysis, especially in the context of HEP experiments, is discussed.Comment: 12 pages, 2 figure

Dealing with development risk and complexity in planning situations within product engineering processes

Every product development process is unique and individual. Nevertheless, patterns of recurring and similar elements exist in different processes which experience specific characteristics depending on the type of project. In addition to the different objectives that form the basis of a product development process, projects differ primarily in their share of new development and their degree of complexity. In order to deal appropriately with the resulting uncertainty, implementing agile approaches in processes of mechatronic system development is becoming more popular with the aim of making the development project more flexible. However, it must be borne in mind that not every development process requires an agile approach. Although plan-driven approaches have a poor ability to react to changes, they provide clear structure that leads to a common understanding of the process and a clear definition of objectives. Since a development project does not only contain problems that are well-suited for an agile or a sequential approach it is important to adapt the process to the underlying situation and requirements. In sufficiently plannable situations a purely agile approach would entail the loss of structure. On the other hand, a purely sequential approach for highly uncertain problems means that the process has to be adapted frequently in order to react appropriately to changes and newly acquired knowledge. The approach of ASD – Agile Systems design helps developers to implement suitable development procedures at different process levels depending on the degree of planning stability. In this context, this contribution presents a methodology that examines the influence of new development and complexity on different elements and supports developers in process planning by combining flexible and structuring elements to avoid multiple replanning

The urban economy as a scale-free network

We present empirical evidence that land values are scale-free and introduce a network model that reproduces the observations. The network approach to urban modelling is based on the assumption that the market dynamics that generates land values can be represented as a growing scale-free network. Our results suggest that the network properties of trade between specialized activities causes land values, and likely also other observables such as population, to be power law distributed. In addition to being an attractive avenue for further analytical inquiry, the network representation is also applicable to empirical data and is thereby attractive for predictive modelling.Comment: Submitted to Phys. Rev. E. 7 pages, 3 figures. (Minor typos and details fixed