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Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results; however, computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested and are hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests.

Rust and Julia are two modern languages aiming to advance computing in their unique way. Julia is a dynamic language striving to bridge the performance gap between dynamic languages like Python and statically typed ones like C/C++ while improving the ergonomics for scientific computing. Rust, on the other hand, is a statically typed language with a friendly compiler guiding developers to write reliable, correct, and concurrent code while ensuring memory safety and unlocking the highest performance. Both languages seem to be appealing to the scientific domain, especially because of their focus on performance. But choosing one depends on the type of your project. [ABSTRACT FROM AUTHOR]

In this paper, we show that ensembles of well-structured and unstructured proteins can be distinguished by borrowing concepts from non-equilibrium statistical mechanics. For this purpose, we represent proteins by two different polymer models and interpret the resulting polymer configurations as random walks of a diffusing particle in space. The first model is the trace of the Cα-atoms along the protein main chain, and the second is their projections onto the protein axis. The resulting trajectories are subsequently analyzed using the theory of the generalized Langevin equation. Velocities are replaced by displacements relating consecutive points on the discrete protein axes and equilibrium ensemble averages by averages over appropriate protein structure ensembles. The resulting displacement autocorrelation functions resemble those of the velocity autocorrelation functions of simple liquids and display a minimum, which can be related to the lengths of secondary structure elements. This minimum is clearly more pronounced for well-structured proteins than for unstructured ones, and the corresponding memory function displays a slower decay, indicating a stronger "folding memory." [ABSTRACT FROM AUTHOR]

Computational models lie at the heart of computational science, yet few scientists have a clear idea of what a computational model actually is. Is it software? Or an algorithm? How does it relate to mathematical models? What are suitable languages or notations for expressing a computational model in the literature? And will AI make computational models obsolete? [ABSTRACT FROM AUTHOR]

Experimental and observational sciences have developed robust practices for conducting experiments, maintaining their instruments, and record keeping for provenance. Computational science has only recently begun to confront the issue of quality of their instrument, the software, and the credibility of their scientific output. Most of the available literature in software engineering relates to enterprise software. While it can inform practices in scientific software, adjustments are usually needed. From time to time quality conscious practitioners have published collections of best practices for scientific software. This article provides one more such list but with updated suggestions, motivated by the need to keep up with the rapid changes in the computing industry. [ABSTRACT FROM AUTHOR]

Numba is a game-changing compiler for high-performance computing with Python. It produces machine code that runs outside of the single-threaded Python interpreter, and that fully utilizes the resources of modern CPUs. This means support for parallel multithreading and auto-vectorization if available, as with compiled languages such as C++ or Fortran. In this article, we document our experience developing PyExaFMM, a multithreaded Numba implementation of the fast multipole method, an algorithm with a nonlinear data structure and a large amount of data organization. We find that designing performant Numba code for complex algorithms can be as challenging as writing in a compiled language. [ABSTRACT FROM AUTHOR]

Scientific codes are complex software systems. Their engineering involves various stakeholders using various computer languages for defining artifacts at different abstraction levels and for different purposes. In this article, we review the overall processes leading to the development of scientific software, and discuss the role of computer languages in the definition of the different artifacts. We provide guidelines to make informed decisions when the time comes to choose a computer language to develop scientific software. [ABSTRACT FROM AUTHOR]

Research processes often rely on high-performance computing (HPC), but HPC is often seen as antithetical to "reproducibility": one would have to choose between software that achieves high performance and software that can be deployed in a reproducible fashion. However, by giving up on reproducibility we would give up on verifiability, a foundation of the scientific process. How can we conciliate performance and reproducibility? This article looks at two performance-critical aspects of HPC: message passing and CPU microarchitecture tuning. Engineering work that has gone into performance portability has already proved fruitful, but some areas remain unaddressed when it comes to CPU tuning. We propose package multiversioning, a technique developed for GNU Guix, a tool for reproducible software deployment, and show that it allows us to implement CPU tuning without compromising on reproducibility and provenance tracking. [ABSTRACT FROM AUTHOR]

This note gives highlights and key takeaways from Computing in Science & Engineering editors who attended the 2023 Society for Industrial and Applied Mathematics Conference on Computational Science and Engineering. The editors discuss themes such as the benefits of returning to in-person conferences, progress in scientific software development and adoption, domain-specific languages, machine learning applications, and community building activities. The editors provide their perspectives on notable sessions and presentations from the conference. [ABSTRACT FROM AUTHOR]

Anomalous diffusion is characterized by its asymptotic behavior for t → ∞. This makes it difficult to detect and describe in particle trajectories from experiments or computer simulations, which are necessarily of finite length. We propose a new approach using Bayesian inference applied directly to the observed trajectories sampled at different time scales. We illustrate the performance of this approach using random trajectories with known statistical properties and then use it for analyzing the motion of lipid molecules in the plane of a lipid bilayer. [ABSTRACT FROM AUTHOR]

Python is a widely used language in scientific computing. When the goal is high performance, however, Python lags far behind low-level languages such as C and Fortran. To support applications that stress performance, Python needs to access the full capabilities of modern CPUs. That means support for parallel multithreading. In this article, we describe PyOMP, a system that enables OpenMP in Python. Programmers write code in Python with OpenMP, Numba generates code that compiles to LLVM, and the resulting programs run with performance that approaches that from code written with C and OpenMP. In this article, we provide an update on the PyOMP project and explain how to install it and use it to write parallel multithreaded code in Python. [ABSTRACT FROM AUTHOR]

Crystallographic B‐factors provide direct dynamical information on the internal mobility of proteins that is closely linked to function, and are also widely used as a benchmark in assessing elastic network models. A significant question in the field is: what is the exact amount of thermal vibrations in protein crystallographic B‐factors? This work sets out to answer this question. First, we carry out a thorough, statistically sound analysis of crystallographic B‐factors of over 10 000 structures. Second, by employing a highly accurate all‐atom model based on the well‐known CHARMM force field, we obtain computationally the magnitudes of thermal vibrations of nearly 1000 structures. Our key findings are: (i) the magnitude of thermal vibrations, surprisingly, is nearly protein‐independent, as a corollary to the universality for the vibrational spectra of globular proteins established earlier; (ii) the magnitude of thermal vibrations is small, less than 0.1 Å2 at 100 K; (iii) the percentage of thermal vibrations in B‐factors is the lowest at low resolution and low temperature (<10%) but increases to as high as 60% for structures determined at high resolution and at room temperature. The significance of this work is that it provides for the first time, using an extremely large dataset, a thorough analysis of B‐factors and their thermal and static disorder components. The results clearly demonstrate that structures determined at high resolution and at room temperature have the richest dynamics information. Since such structures are relatively rare in the PDB database, the work naturally calls for more such structures to be determined experimentally. [ABSTRACT FROM AUTHOR]

Adaptive mesh refinement (AMR) is an important method that enables many mesh-based applications to run at effectively higher resolution within limited computing resources by allowing high resolution only where really needed. This advantage comes at a cost, however: greater complexity in the mesh management machinery and challenges with load distribution. With the current trend of increasing heterogeneity in hardware architecture, AMR presents an orthogonal axis of complexity. The usual techniques, such as asynchronous communication and hierarchy management for parallelism and memory that are necessary to obtain reasonable performance are very challenging to reason about with AMR. Different groups working with AMR are bringing different approaches to this challenge. Here, we examine the design choices of several AMR codes and also the degree to which demands placed on them by their users influence these choices. [ABSTRACT FROM AUTHOR]

Legate is a recently developed software system for constructing scalable simulation and data analysis programs using convenient, familiar notation. It demonstrates how coupling Python, with a runtime system originally designed for high-performance computing, can enable the creation of libraries that mimic the familiar interface of NumPy and Pandas for execution on both desktops and supercomputers. [ABSTRACT FROM AUTHOR]

Using simulations for scientific discovery requires that the software used in the simulations undergoes a rigorous design and development process similar to that of the lab instruments in the experimental sciences. To devise a good design methodology, it is critical to understand the requirements, constraints, and challenges. This article describes insights from the long-term stewardship of a multiphysics multicomponent software, FLASH, that was designed more than 20 years ago for astrophysics, now serves multiple communities, and has been successful in adapting to the changing world of high-performance computing. [ABSTRACT FROM AUTHOR]

Author(s): Nicolas P. Rougier, Konrad Hinsen Author Affiliations: Code reviewing puts extra demands on referees As editors-in-chief of http://rescience.github.io , we argue that the review of software codes used in [...]

In the present work, we propose a simple model-free approach for the computation of molecular diffusion tensors from molecular dynamics trajectories. The method uses a rigid body trajectory of the molecule under consideration, which is constructed a posteriori by an accumulation of quaternion-based superposition fits of consecutive conformations. From the rigid body trajectory, we compute the translational and angular velocities of the molecule and by integration of the latter also the corresponding angular trajectory. All quantities can be referred to the laboratory frame and a molecule-fixed frame. The 6 × 6 diffusion tensor is computed from the asymptotic slope of the tensorial mean square displacement and, for comparison, also from the Kubo integral of the velocity correlation tensor. The method is illustrated for two simple model systems - a water molecule and a lysozyme molecule in bulk water. We give estimations of the statistical accuracy of the calculations. [ABSTRACT FROM AUTHOR]

In all-atom molecular simulation studies of proteins, each atom in the protein is represented by a point mass and interactions are defined in terms of the atomic positions. In recent years, various simplified approaches have been proposed. These approaches aim to improve computational efficiency and to provide a better physical insight. The simplified models can differ widely in their description of the geometry and the interactions inside the protein. This study explores the most fundamental choice in the simplified protein models: the choice of a coordinate set defining the protein structure. A simplified model can use fewer point masses than the all-atom model and/or eliminate some of the internal coordinates of the molecule by setting them to an average or ideal value. We look at the implications of such choices for the overall protein structure. We find that care must be taken for angular coordinates, where even very small variations can lead to significant changes in the positions of far away atoms. In particular, we show that the φ/ψ torsion angles are not a sufficient coordinate set, whereas another coordinate set with two degrees of freedom per residue, virtual Cα backbone bond, and torsion angles performs satisfactorily. [ABSTRACT FROM AUTHOR]

The term "content-addressable storage" does not sound exciting, but superficial explanations can make it look like magic, to the point of raising suspicion. In this article, I will show that content-addressable storage is a technology that works, is already in widespread use, and holds many promises for the future of both scientific programming and the management of scientific data. I will start by outlining the theory, and then illustrate how it works in practice, using IPFS, the Inter-Planetary FileSystem. [ABSTRACT FROM AUTHOR]

We present an implementation of path integral molecular dynamics for sampling low temperature properties of doped helium clusters using Langevin dynamics. The robustness of the path integral Langevin equation and white-noise Langevin equation [M. Ceriotti, M. Parrinello, T. E. Markland, and D. E. Manolopoulos, J. Chem. Phys. 133, 124104 (2010)] sampling methods are considered for those weakly bound systems with comparison to path integral Monte Carlo (PIMC) in terms of efficiency and accuracy. Using these techniques, convergence studies are performed to confirm the systematic error reduction introduced by increasing the number of discretization steps of the path integral. We comment on the structural and energetic evolution of HeN-CO2 clusters from N = 1 to 20. To quantify the importance of both rotations and exchange in our simulations, we present a chemical potential and calculated band origin shifts as a function of cluster size utilizing PIMC sampling that includes these effects. This work also serves to showcase the implementation of path integral simulation techniques within the molecular modelling toolkit [K. Hinsen, J. Comp. Chem. 21, 79 (2000)], an open-source molecular simulation package. [ABSTRACT FROM AUTHOR]

We present a model for the local diffusion-relaxation dynamics of the Cα-atoms in proteins describing both the diffusive short-time dynamics and the asymptotic long-time relaxation of the position autocorrelation functions. The relaxation rate spectra of the latter are represented by shifted gamma distributions, where the standard gamma distribution describes anomalous slow relaxation in macromolecular systems of infinite size and the shift accounts for a smallest local relaxation rate in macromolecules of finite size. The resulting autocorrelation functions are analytic for any time t >= 0. Using results from a molecular dynamics simulation of lysozyme, we demonstrate that the model fits the position autocorrelation functions of the Cα-atoms exceptionally well and reveals moreover a strong correlation between the residue's solvent-accessible surface and the fitted model parameters. [ABSTRACT FROM AUTHOR]

We propose a rigorous method for removing rigid-body motions from a given molecular dynamics trajectory of a flexible macromolecule. The method becomes exact in the limit of an infinitesimally small sampling step for the input trajectory. In a recent paper [G. Kneller, J. Chem. Phys. 128, 194101 (2008)], one of us showed that virtual internal atomic displacements for small time increments can be derived from Gauss' principle of least constraint, which leads to a rotational superposition problem for the atomic coordinates in two consecutive time frames of the input trajectory. Here, we demonstrate that the accumulation of these displacements in a molecular-fixed frame, which evolves in time according to the virtual rigid-body motions, leads to the desired trajectory for internal motions. The atomic coordinates in the input and output trajectory are related by a roto-translation, which guarantees that the internal energy of the molecule is left invariant. We present a convenient implementation of our method, in which the accumulation of the internal displacements is performed implicitly. Two numerical examples illustrate the difference to the classical approach for removing macromolecular rigid-body motions, which consists of aligning its configurations in the input trajectory with a fixed reference structure. [ABSTRACT FROM AUTHOR]

We propose a simple analytical model for the elastic incoherent structure factor of proteins measured by neutron scattering, which allows extracting the distribution of atomic position fluctuations from a fit of the model to the experimental data. The method is validated by applying it to elastic incoherent structure factors of lysozyme which have been obtained by molecular dynamics simulation and by normal mode analysis, respectively, and for which distributions of the atomic position fluctuations can be generated numerically for direct comparison with the predictions of the model. The comparison shows a remarkable agreement, in particular, concerning the lower limit for the position fluctuations, which is pronounced in the numerical data. [ABSTRACT FROM AUTHOR]

Demonstrates that the dynamics around a stable equilibrium state can be described by a midrange force field made up of the chemical bond structure terms and harmonic terms with a distance-dependent force constant. Normal mode analysis' reproduction of the experimental density of states and a molecular dynamics simulation using a standard force field.

VersionClimber is an automated system to help update the package and data infrastructure of a software application based on priorities that the user has indicated (e.g., I care more about having a recent version of this package than that one). The system does a systematic and heuristically efficient exploration (using bounded upward compatibility) of a version search space in a sandbox environment (Virtual Env or conda env), finally delivering a lexicographically maximum configuration based on the user-specified priority order. It works for Linux and Mac OS on the cloud. [ABSTRACT FROM AUTHOR]

Investigates intramolecular proton transfer in the enol form of acetylacetone at various temperatures. Use of computer simulations; Modeling of the potential energy surface; Classical and centroid potential of mean force for the reaction coordinate; Comparison of two different reaction coordinates.

Using a simple data analysis as an example, the author explores the relative merits of general-purpose library code and code written for a specific narrow application scenario. [ABSTRACT FROM AUTHOR]

If you have been following developments in software engineering in recent years, you have probably noticed that the term DSL (domain-specific language) has become a minor buzzword in that field. You may have concluded that this is a hot new idea that is certainly not ready for application in real life. But, as I will show in this article, computational scientists (and others) have been using DSLs for decades. What is new is not DSLs per se, but the name and the attention given to them. [ABSTRACT FROM AUTHOR]

Frustrated by another failed software installation? Wondering why you can't reproduce your colleagues' computations? This story will tell you why. It won't magically solve your problems, but it does point out a glimpse of hope for the future. [ABSTRACT FROM PUBLISHER]

Many of us write code regularly as part of our scientific activity, perhaps even as a full-time job. But even though we write--and use--more and more code, we rarely think about the roles that this code will have in our research, in our publications, and ultimately in the scientific record. In this article, the author outlines some frequent roles of code in computational science. These roles aren't exclusive; in fact, it's common for a piece of code to have several roles, at the same time or as an evolution over time. Thinking about these roles, ideally before starting to write the code, is a good habit to develop. [ABSTRACT FROM PUBLISHER]

Computers are the only research tools that by design exhibit chaotic behavior: a minimal change in the input to a computation can change its output in any imaginable way. Developers and users of scientific software should be aware of this feature and set up safety nets for protecting themselves against bad surprises. [ABSTRACT FROM PUBLISHER]

Technical debt is a useful metaphor for understanding the long-term impact of technical choices. The analysis of technical debt has found its place in the software industry, with results that are applicable to scientific software as well. But technical debt is also a useful concept to look at how we use computers in doing scientific research. [ABSTRACT FROM PUBLISHER]

A coarse-grained geometrical model for protein secondary-structure description and analysis is presented which uses only the positions of the Cα atoms. A space curve connecting these positions by piecewise polynomial interpolation is constructed and the folding of the protein backbone is described by a succession of screw motions linking the Frenet frames at consecutive Cα positions. Using the ASTRAL subset of the SCOPe database of protein structures, thresholds are derived for the screw parameters of secondary-structure elements and demonstrate that the latter can be reliably assigned on the basis of a Cα model. For this purpose, a comparative study with the widely used DSSP ( Define Secondary Structure of Proteins) algorithm was performed and it was shown that the parameter distribution corresponding to the ensemble of all pure Cα structures in the RCSB Protein Data Bank matches that of the ASTRAL database. It is expected that this approach will be useful in the development of structure-refinement techniques for low-resolution data. [ABSTRACT FROM AUTHOR]

Numerical solutions of mathematical equations in scientific models are the result of several approximation steps. Konrad Hinsen uses a simulation of the solar system as an example for illustrating these approximations and explaining their role in the difficult problem of testing scientific software. [ABSTRACT FROM AUTHOR]

Here, Konrad Hinsen talks about how one aspect of validating a piece of software is to check that it does what it's expected to do. But how do you write down your expectations? [ABSTRACT FROM AUTHOR]