GNU GPL Research Articles

A systematic review and meta-analysis of rescue revascularization with arterial conduits in liver transplantation.

Although aortohepatic conduits (AHCs) provide an effective technique for arterialization in liver transplantation (LT) when the native recipient artery is unusable, various publications report higher occlusion rates and impaired outcome compared to conventional anastomoses. This systematic review and meta-analysis investigates the published evidence of outcome and risk of AHCs in LT using bibliographic databases and following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Primary and secondary outcome were artery occlusion as well as graft and patient survival. Twenty-three retrospective studies were identified with a total of 22113 patients with LT, of whom 1900 patients (9%) received an AHC. An AHC was used in 33% of retransplantations. Early artery occlusion occurred in 7% (3%-16%) of patients with AHCs, compared to 2% (1%-3%) without conduit (OR 3.70; 1.63-8.38; P=.001). The retransplantation rate after occlusion was not significantly different in both groups (OR 1.46; 0.67-3.18; P=.35). Graft (HR 1.38; 1.17-1.63; P<.001) and patient (HR 1.57; 1.12-2.20; P=.009) survival was significantly lower in the AHC compared to the nonconduit group. In contrast, graft survival in retransplantations was comparable (HR 1.00; 0.82-1.22; P=.986). Although AHCs provide an important rescue option, when regular revascularization is not feasible during LT, transplant surgeons should be alert of the potential risk of inferior outcome.

A versatile open-source analysis of the limiting efficiency of photo electrochemical water-splitting

Understanding the fundamental thermodynamic limits of photo-electrochemical (PEC) water splitting is of great scientific and practical importance. In this work, a ‘detailed balance’ type model of solar quantum energy converters and non-linear circuit analysis is used to calculate the thermodynamic limiting efficiency of various configurations of PEC design. This model is released as freely accessible open-source (GNU GPL v3) code written in MATLAB with a graphical user interface (GUI). The capabilities of the model are demonstrated by simulating selected permutations of PEC design and results are validated against previous literature. This tool will enable solar fuel researchers to easily compare experimental results to theoretical limits to assess its realised performance using the GUI. Furthermore, the code itself is intended to be extendable and so can be modified to include non-ideal losses such as the over-potential required or complex optical phenomena.

Lab::Measurement—A portable and extensible framework for controlling lab equipment and conducting measurements

Lab::Measurement is a framework for test and measurement automatization using Perl 5. While primarily developed with applications in mesoscopic physics in mind, it is widely adaptable. Internally, a layer model is implemented. Communication protocols such as IEEE 488 [1], USB Test & Measurement [2], or, e.g., VXI-11 [3] are addressed by the connection layer. The wide range of supported connection backends enables unique cross-platform portability. At the instrument layer, objects correspond to equipment connected to the measurement PC (e.g., voltage sources, magnet power supplies, multimeters, etc.). The high-level sweep layer automates the creation of measurement loops, with simultaneous plotting and data logging. An extensive unit testing framework is used to verify functionality even without connected equipment. Lab::Measurement is distributed as free and open source software. Program summaryProgram Title: Lab::Measurement 3.660Program Files doi:http://dx.doi.org/10.17632/d8rgrdc7tz.1Program Homepage:https://www.labmeasurement.deLicensing provisions: GNU GPL v233The precise license terms are more permissive. Lab::Measurement is distributed under the same licensing conditions as Perl 5 itself, a frequent choice in the Perl ecosystem. This means that it can be used and distributed according to the terms of either the GNU General Public License (version 1 or any later version) or the Artistic License; the choice of license is up to the user.Programming language: Perl 5Nature of problem: Flexible, lightweight, and operating system independent control of laboratory equipment connected by diverse means such as IEEE 488 [1], USB [2], or VXI-11 [3]. This includes running measurements with nested measurement loops where a data plot is continuously updated, as well as background processes for logging and control.Solution method: Object-oriented layer model based on Moose [4], abstracting the hardware access as well as the command sets of the addressed instruments. A high-level interface allows simple creation of measurement loops, live plotting via GnuPlot [5], and data logging into customizable folder structures.[1] F. M. Hess, D. Penkler, et al., LinuxGPIB. Support package for GPIB (IEEE 488) hardware, containing kernel driver modules and a C user-space library with language bindings. http://linux-gpib.sourceforge.net/[2] USB Implementers Forum, Inc., Universal Serial Bus Test and Measurement Class Specification (USBTMC), revision 1.0 (2003). http://www.usb.org/developers/docs/devclass_docs/[3] VXIbus Consortium, VMEbus Extensions for Instrumentation VXIbus TCP/IP Instrument Protocol Specification VXI-11 (1995). http://www.vxibus.org/files/VXI_Specs/VXI-11.zip[4] Moose—Apostmodern object system for Perl 5. http://moose.iinteractive.com[5] E. A. Merritt, et al., Gnuplot. An Interactive Plotting Program. http://www.gnuplot.info/

A new pipeline for astrometry and photometry of asteroids

AbstractUsing Python 3, astropy and astrometry.net, we have developed a pipeline to obtain photometric light curves of asteroids automatically queried by the SkyBoT database from sequential FITS images. The pipeline provides: pre-reduction of data, astrometry, standard differential photometry and light curves by auto-selecting multiple comparison stars (maximum user-defined) from NOMAD catalog via VizieR. The code is an open source, free and hosted on GitHub with the GNU GPL v3 license.

Rapid multi-locus sequence typing direct from uncorrected long reads using Krocus.

Genome sequencing is rapidly being adopted in reference labs and hospitals for bacterial outbreak investigation and diagnostics where time is critical. Seven gene multi-locus sequence typing is a standard tool for broadly classifying samples into sequence types (STs), allowing, in many cases, to rule a sample out of an outbreak, or allowing for general characteristics about a bacterial strain to be inferred. Long-read sequencing technologies, such as from Oxford Nanopore, can produce read data within minutes of an experiment starting, unlike short-read sequencing technologies which require many hours/days. However, the error rates of raw uncorrected long read data are very high. We present Krocus which can predict a ST directly from uncorrected long reads, and which was designed to consume read data as it is produced, providing results in minutes. It is the only tool which can do this from uncorrected long reads. We tested Krocus on over 700 isolates sequenced using long-read sequencing technologies from Pacific Biosciences and Oxford Nanopore. It provides STs for isolates on average within 90 s, with a sensitivity of 94% and specificity of 97% on real sample data, directly from uncorrected raw sequence reads. The software is written in Python and is available under the open source license GNU GPL version 3.

DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers.

Synthetic lethality is a state when simultaneous loss of two genes is lethal to a cancer cell, while the loss of the individual genes is not. We developed an R package DiscoverSL to predict and visualize synthetic lethality in cancers using multi-omic cancer data. Mutation, copy number alteration and gene expression data from The Cancer Genome Atlas project were combined to develop a multi-parametric Random Forest classifier. The effects of selectively targeting the predicted synthetic lethal genes is tested in silico using shRNA and drug screening data from cancer cell line databases. The clinical outcome in patients with mutation in primary gene and over/under-expression in the synthetic lethal gene is evaluated using Kaplan-Meier analysis. The method helps to identify new therapeutic approaches by exploiting the concept of synthetic lethality. DiscoverSL package with user manual and sample workflow is available for download from github url: https://github.com/shaoli86/DiscoverSL/releases/tag/V1.0 under GNU GPL-3. Supplementary data are available at Bioinformatics online.

Technical Note: FreeCT_ICD: An open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization for CT imaging investigations.

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open-source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation ofa model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on trilinear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and released under the open-source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open-source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets.

Q2DTor: A program to treat torsional anharmonicity through coupled pair torsions in flexible molecules

The Q 2DTor program (Quantum 2-Dimensional Torsions) is designed to calculate accurate rotational–vibrational partition functions (also called rovibrational partition functions) and thermodynamic functions for molecular systems having two [1] or more torsions. Systems with more than two torsions can also be studied by treating the torsions by pairs. The program searches for all the torsional conformers and evaluates the rovibrational partition function using the multi-structural harmonic oscillator (MS-HO) approximation and the extended two-dimensional torsion (E2DT) approximation. The latter incorporates full coupling of the two torsions by means of the two-dimensional non-separable (2D-NS) approximation [2], and it also includes their influence on the remaining degrees of freedom. The program also calculates the ideal gas-phase standard-state thermodynamic functions at the requested temperatures. Twenty molecules have been used to test Q 2DTor. Program summaryProgram Title:Q2DTorProgram Files doi:http://dx.doi.org/10.17632/wbgchgc2kp.1Licensing provisions: GNU GPL v3Programming language: Python 2.7Nature of problem: Calculation of accurate partition functions and thermodynamic functions in molecular systems involving two torsional modes. Torsional anharmonicity is treated quantically and includes full coupling in the kinetic and potential energies between the torsions and between the torsions and the rest of the degrees of freedom.Solution method: The program uses the variational method to solve the Schrödinger equation of a two-dimensional torsional potential using Fourier series. All of the remaining degrees of freedom (non-torsional) are incorporated through a projected (the torsional modes are removed) rigid-rotator harmonic-oscillator partition function which is calculated at every torsional stationary point and that is allowed to vary with the torsional motion. The integration of the rovibrational partition function over the torsional space leads to a mixed quantum-classical vibrational partition function, which is transformed into a full quantum partition function by including the quantum contribution due to the torsions. For the evaluation of the integral, the rovibrational partition function at nonstationary points is carried out through a Delaunay triangulation procedure using the calculated rovibrational partition functions at the stationary points as nodes.Additional comments including Restrictions and Unusual features: The program is limited to two coupled torsional modes.

PREQUAL: detecting non-homologous characters in sets of unaligned homologous sequences.

Phylogenomic datasets invariably contain undetected stretches of non-homologous characters due to poor-quality sequences or erroneous gene models. The large-scale multi-gene nature of these datasets renders impractical or impossible detailed manual curation of sequences, but few tools exist that can automate this task. To address this issue, we developed a new method that takes as input a set of unaligned homologous sequences and uses an explicit probabilistic approach to identify and mask regions with non-homologous adjacent characters. These regions are defined as sharing no statistical support for homology with any other sequence in the set, which can result from e.g. sequencing errors or gene prediction errors creating frameshifts. Our methodology is implemented in the program PREQUAL, which is a fast and accurate tool for high-throughput filtering of sequences. The program is primarily aimed at amino acid sequences, although it can handle protein coding DNA sequences as well. It is fully customizable to allow fine-tuning of the filtering sensitivity. The program PREQUAL is written in C/C++ and available through a GNU GPL v3.0 at https://github.com/simonwhelan/prequal. Supplementary data are available at Bioinformatics online.

Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi

BackgroundGenome annotation is of key importance in many research questions. The identification of protein-coding genes is often based on transcriptome sequencing data, ab-initio or homology-based prediction. Recently, it was demonstrated that intron position conservation improves homology-based gene prediction, and that experimental data improves ab-initio gene prediction.ResultsHere, we present an extension of the gene prediction program GeMoMa that utilizes amino acid sequence conservation, intron position conservation and optionally RNA-seq data for homology-based gene prediction. We show on published benchmark data for plants, animals and fungi that GeMoMa performs better than the gene prediction programs BRAKER1, MAKER2, and CodingQuarry, and purely RNA-seq-based pipelines for transcript identification. In addition, we demonstrate that using multiple reference organisms may help to further improve the performance of GeMoMa. Finally, we apply GeMoMa to four nematode species and to the recently published barley reference genome indicating that current annotations of protein-coding genes may be refined using GeMoMa predictions.ConclusionsGeMoMa might be of great utility for annotating newly sequenced genomes but also for finding homologs of a specific gene or gene family. GeMoMa has been published under GNU GPL3 and is freely available at http://www.jstacs.de/index.php/GeMoMa.

Two C++ libraries for counting trees on a phylogenetic terrace.

MotivationThe presence of terraces in phylogenetic tree space, i.e. a potentially large number of distinct tree topologies that have exactly the same analytical likelihood score, was first described by Sanderson et al. However, popular software tools for maximum likelihood and Bayesian phylogenetic inference do not yet routinely report, if inferred phylogenies reside on a terrace, or not. We believe, this is due to the lack of an efficient library to (i) determine if a tree resides on a terrace, (ii) calculate how many trees reside on a terrace and (iii) enumerate all trees on a terrace.ResultsIn our bioinformatics practical that is set up as a programming contest we developed two efficient and independent C++ implementations of the SUPERB algorithm by Constantinescu and Sankoff (1995) for counting and enumerating trees on a terrace. Both implementations yield exactly the same results, are more than one order of magnitude faster, and require one order of magnitude less memory than a previous thirrd party python implementation.Availability and implementationThe source codes are available under GNU GPL at https://github.com/terraphast.Supplementary information Supplementary data are available at Bioinformatics online.

Investigating whether and how software developers understand open source software licensing

Software provided under open source licenses is widely used, from forming high-profile stand-alone applications (e.g., Mozilla Firefox) to being embedded in commercial offerings (e.g., network routers). Despite the high frequency of use of open source licenses, there has been little work about whether software developers understand the open source licenses that they use. To help understand whether or not developers understand the open source licenses they use, we conducted a survey that posed development scenarios involving three popular open source licenses (GNU GPL 3.0, GNU LGPL 3.0 and MPL 2.0) both alone and in combination. The 375 respondents to the survey, who were largely developers, gave answers consistent with those of a legal expert’s opinion in 62% of 42 cases. Although developers clearly understood cases involving one license, they struggled when multiple licenses were involved. To understand the context in which licensing issues arise in practice, we analyzed real-world questions posed by developers about the three licenses considered in the survey on online question-and-answer communities. We also interviewed practicing developers about license interaction problems they have faced. Among several lessons, we learnt that licensing issues can constrain software evolution and that developers are cautious of more restrictive licenses. Our results indicate a need for tool support to help guide developers in understanding the structure of the code and the technical details of a project while taking into account the exact requirements imposed by the licenses involved.

RANGER-DTL 2.0: rigorous reconstruction of gene-family evolution by duplication, transfer and loss.

SummaryRANGER-DTL 2.0 is a software program for inferring gene family evolution using Duplication-Transfer-Loss reconciliation. This new software is highly scalable and easy to use, and offers many new features not currently available in any other reconciliation program. RANGER-DTL 2.0 has a particular focus on reconciliation accuracy and can account for many sources of reconciliation uncertainty including uncertain gene tree rooting, gene tree topological uncertainty, multiple optimal reconciliations and alternative event cost assignments. RANGER-DTL 2.0 is open-source and written in C++ and Python.Availability and implementationPre-compiled executables, source code (open-source under GNU GPL) and a detailed manual are freely available from http://compbio.engr.uconn.edu/software/RANGER-DTL/.Supplementary information Supplementary data are available at Bioinformatics online.

AnnotSV: an integrated tool for structural variations annotation

Structural Variations (SV) are a major source of variability in the human genome that shaped its actual structure during evolution. Moreover, many human diseases are caused by SV, highlighting the need to accurately detect those genomic events but also to annotate them and assist their biological interpretation. Therefore, we developed AnnotSV that compiles functionally, regulatory and clinically relevant information and aims at providing annotations useful to (i) interpret SV potential pathogenicity and (ii) filter out SV potential false positive. In particular, AnnotSV reports heterozygous and homozygous counts of single nucleotide variations (SNVs) and small insertions/deletions called within each SV for the analyzed patients, this genomic information being extremely useful to support or question the existence of an SV. We also report the computed allelic frequency relative to overlapping variants from DGV (MacDonald et al., 2014), that is especially powerful to filter out common SV. To delineate the strength of AnnotSV, we annotated the 4751 SV from one sample of the 1000 Genomes Project, integrating the sample information of four million of SNV/indel, in less than 60 s. AnnotSV is implemented in Tcl and runs in command line on all platforms. The source code is available under the GNU GPL license. Source code, README and Supplementary data are available at http://lbgi.fr/AnnotSV/. Supplementary data are available at Bioinformatics online.

HyDe: A Python Package for Genome-Scale Hybridization Detection.

The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this article, we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).

NanoPack: visualizing and processing long-read sequencing data.

SummaryHere we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.Availability and implementationThe NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.Supplementary information Supplementary data are available at Bioinformatics online.

PlasmidTron: assembling the cause of phenotypes and genotypes from NGS data.

Increasingly rich metadata are now being linked to samples that have been whole-genome sequenced. However, much of this information is ignored. This is because linking this metadata to genes, or regions of the genome, usually relies on knowing the gene sequence(s) responsible for the particular trait being measured and looking for its presence or absence in that genome. Examples of this would be the spread of antimicrobial resistance genes carried on mobile genetic elements (MGEs). However, although it is possible to routinely identify the resistance gene, identifying the unknown MGE upon which it is carried can be much more difficult if the starting point is short-read whole-genome sequence data. The reason for this is that MGEs are often full of repeats and so assemble poorly, leading to fragmented consensus sequences. Since mobile DNA, which can carry many clinically and ecologically important genes, has a different evolutionary history from the host, its distribution across the host population will, by definition, be independent of the host phylogeny. It is possible to use this phenomenon in a genome-wide association study to identify both the genes associated with the specific trait and also the DNA linked to that gene, for example the flanking sequence of the plasmid vector on which it is encoded, which follows the same patterns of distribution as the marker gene/sequence itself. We present PlasmidTron, which utilizes the phenotypic data normally available in bacterial population studies, such as antibiograms, virulence factors, or geographical information, to identify traits that are likely to be present on DNA that can randomly reassort across defined bacterial populations. It is also possible to use this methodology to associate unknown genes/sequences (e.g. plasmid backbones) with a specific molecular signature or marker (e.g. resistance gene presence or absence) using PlasmidTron. PlasmidTron uses a k-mer-based approach to identify reads associated with a phylogenetically unlinked phenotype. These reads are then assembled de novo to produce contigs in a fast and scalable-to-large manner. PlasmidTron is written in Python 3 and is available under the open source licence GNU GPL3 from https://github.com/sanger-pathogens/plasmidtron.

POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening

High throughput virtual screening plays a crucial role in hit identification during the drug discovery process. With the rapid increase in the chemical libraries, virtual screening process becomes computationally challenging, thereby posing a demand for efficiently parallelized software pipelines. Here we present a GNU Parallel based pipeline-POAP that is programmed to run Open Babel and AutoDock suite under highly optimized parallelization. The ligand preparation module is a unique feature in POAP, as it offers extensive options for geometry optimization, conformer generation, parallelization and also quarantines erroneous datasets for seamless operation. POAP also features multi receptor docking that can be utilized for comparative virtual screening and drug repurposing studies. As demonstrated using different structural datasets, POAP proves to be an efficient pipeline that enables high scalability, seamless operability, dynamic file handling and optimal utilization of CPU’s for computationally demanding tasks. POAP is distributed freely under GNU GPL license and can be downloaded at https://github.com/inpacdb/POAP.

Open source Matrix Product States: Opening ways to simulate entangled many-body quantum systems in one dimension

Numerical simulations are a powerful tool to study quantum systems beyond exactly solvable systems lacking an analytic expression. For one-dimensional entangled quantum systems, tensor network methods, amongst them Matrix Product States (MPSs), have attracted interest from different fields of quantum physics ranging from solid state systems to quantum simulators and quantum computing. Our open source MPS code provides the community with a toolset to analyze the statics and dynamics of one-dimensional quantum systems. Here, we present our open source library, Open Source Matrix Product States (OSMPS), of MPS methods implemented in Python and Fortran2003. The library includes tools for ground state calculation and excited states via the variational ansatz. We also support ground states for infinite systems with translational invariance. Dynamics are simulated with different algorithms, including three algorithms with support for long-range interactions. Convenient features include built-in support for fermionic systems and number conservation with rotational U(1) and discrete Z2 symmetries for finite systems, as well as data parallelism with MPI. We explain the principles and techniques used in this library along with examples of how to efficiently use the general interfaces to analyze the Ising and Bose–Hubbard models. This description includes the preparation of simulations as well as dispatching and post-processing of them. Program summaryProgram title: Open Source Matrix Product States (OSMPS), v2.0Program Files doi:http://dx.doi.org/10.17632/vxm2mcmk4v.1Licensing provisions: GNU GPL v3Programming language: Python, Fortran2003, MPI for parallel computingCompilers (Fortran): gfortran, ifort, g95Dependencies: The minimal requirements in addition to the Fortran compiler are BLAS, LAPACK, ARPACK, python, numpy, scipy. Additional packages for plotting include matplotlib, dvipng, and LATEX packages. The Expokit package, available at the homepage http://www.maths.uq.edu.au/expokit/, is required to use the Local Runge–Kutta time evolution.Supplementary material: We provide programs to reproduce selected figures in the Appendices.Nature of problem: Solving the ground state and dynamics of a many-body entangled quantum system is a challenging problem; the Hilbert space grows exponentially with system size. Complete diagonalization of the Hilbert space to floating point precision is limited to less than forty qubits.Solution method: Matrix Product States in one spatial dimension overcome the exponentially growing Hilbert space by truncating the least important parts of it. The error can be well controlled. Local neighboring sites are variationally optimized in order to minimize the energy of the complete system. We can target the ground state and low lying excited states. Moreover, we offer various methods to solve the time evolution following the many-body Schrödinger equation. These methods include e.g. theSuzuki–Trotter decompositions using local propagators or the Krylov method, both approximating the propagator on the complete Hilbert space.

RECOLA2: REcursive Computation of One-Loop Amplitudes 2

We present the Fortran95 program Recola2 for the perturbative computation of next-to-leading-order transition amplitudes in the Standard Model of particle physics and extended Higgs sectors. New theories are implemented via model files in the ’t Hooft–Feynman gauge in the conventional formulation of quantum field theory and in the Background-Field method. The present version includes model files for Two-Higgs-Doublet Model and the Higgs-Singlet Extension of the Standard Model. We support standard renormalization schemes for the Standard Model as well as many commonly used renormalization schemes in extended Higgs sectors. Within these models the computation of next-to-leading-order polarized amplitudes and squared amplitudes, optionally summed over spin and colour, is fully automated for any process. Recola2 allows the computation of colour- and spin-correlated leading-order squared amplitudes that are needed in the dipole subtraction formalism. Recola2 is publicly available for download at http://recola.hepforge.org. Program summaryProgram Title:Recola2Program Files doi:http://dx.doi.org/10.17632/sn4wvmkd9k.1Licensing provisions: GNU GPL version 3Programming language:Fortran95Nature of problem: Evaluation of general tree-level and one-loop scattering amplitudes occurring in the calculation of observables in relativistic quantum field theories.Solution method: Tree-level and one-loop amplitudes are numerically calculated using a recursive algorithm. For one-loop amplitudes numerical results for tensor integrals are needed as input. These are provided by the Collier library. In addition, contributions of counterterms and rational terms are determined via dedicated Feynman rules.Restrictions: The code has been used for processes with up to 9 external particles at one-loop level and up to 10 external particles at tree level. For large multiplicities available internal storage may cause limitations. Presently besides the Standard Model, the Two-Higgs-Doublet Model and the Higgs-singlet extension of the Standard Model are supported.