We present release 2.0 of the ALPS (Algorithms and Libraries for Physics Simulations) project, an open source software project to develop libraries and application programs for the simulation of strongly correlated quantum lattice models such as quantum magnets, lattice bosons, and strongly correlated fermion systems. The code development is centered on common XML and HDF5 data formats, libraries to simplify and speed up code development, common evaluation and plotting tools, and simulation programs. The programs enable non-experts to start carrying out serial or parallel numerical simulations by providing basic implementations of the important algorithms for quantum lattice models: classical and quantum Monte Carlo (QMC) using non-local updates, extended ensemble simulations, exact and full diagonalization (ED), the density matrix renormalization group (DMRG) both in a static version and a dynamic time-evolving block decimation (TEBD) code, and quantum Monte Carlo solvers for dynamical mean field theory (DMFT). The ALPS libraries provide a powerful framework for programers to develop their own applications, which, for instance, greatly simplify the steps of porting a serial code onto a parallel, distributed memory machine. Major changes in release 2.0 include the use of HDF5 for binary data, evaluation tools in Python, support for the Windows operating system, the use of CMake as build system and binary installation packages for Mac OS X and Windows, and integration with the VisTrails workflow provenance tool. The software is available from our web server at http://alps.comp-phys.org/.

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SUMMARYThe first Provenance Challenge was set up in order to provide a forum for the community to understand the capabilities of different provenance systems and the expressiveness of their provenance representations. To this end, a functional magnetic resonance imaging workflow was defined, which participants had to either simulate or run in order to produce some provenance representation, from which a set of identified queries had to be implemented and executed. Sixteen teams responded to the challenge, and submitted their inputs. In this paper, we present the challenge workflow and queries, and summarize the participants' contributions.

Abstract.We give an overview of VisTrails, a system that provides an infrastructure for systematically capturing detailed provenance and streamlining the data exploration process. A key feature that sets VisTrails apart from previous visualization and scientific workflow systems is a novel action-based mechanism that uniformly captures provenance for data products and workflows used to generate these products. This mechanism not only ensures reproducibility of results, but it also simplifies data exploration by allowing scientists to easily navigate through the space of workflows and parameter settings for an exploration task.

SUMMARYVisTrails is a new workflow and provenance management system that provides support for scientific data exploration and visualization. Whereas workflows have been traditionally used to automate repetitive tasks, for applications that are exploratory in nature, change is the norm. VisTrails uses a new changebased provenance mechanism, which was designed to handle rapidly evolving workflows. It uniformly and automatically captures provenance information for data products and for the evolution of the workflows used to generate these products. In this paper, we describe how the VisTrails provenance data are organized in layers and present a first approach for querying this data that we developed to tackle the Provenance Challenge queries.

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