CALMIP

, where N is proportional to the system size. Therefore, performing accurate calculations on chemically meaningful systems requires (i) approximations that can lower the computational scaling and (ii) efficient implementations that take advantage of modern massively parallel architectures. Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multireference second-order perturbation theory (PT2). The determinant-driven framework allows the programmer to include any arbitrary set of determinants in the reference space, hence providing greater methodological freedom. The sCI method implemented in Quantum Package is based on the CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively) algorithm which complements the variational sCI energy with a PT2 correction. Additional external plugins have been recently added to perform calculations with multireference coupled cluster theory and range-separated density-functional theory. All the programs are developed with the IRPF90 code generator, which simplifies collaborative work and the development of new features. Quantum Package strives to allow easy implementation and experimentation of new methods, while making parallel computation as simple and efficient as possible on modern supercomputer architectures. Currently, the code enables, routinely, to realize runs on roughly 2 000 CPU cores, with tens of millions of determinants in the reference space. Moreover, we have been able to push up to 12 288 cores in order to test its parallel efficiency. In the present manuscript, we also introduce some key new developments: (i) a renormalized second-order perturbative correction for efficient extrapolation to the full CI limit and (ii) a stochastic version of the CIPSI selection performed simultaneously to the PT2 calculation at no extra cost.

In this paper, we present a domain-specific, open access, reference ontology (ROMAIN) for the maintenance management domain. We use a hybrid approach, based on a top-down alignment to an open source top-level ontology, the Basic Formal Ontology (BFO), and a bottom up focus on classes that are groun ded in maintenance practice. We constrain the scope of the ontology to the classes that are unique to the maintenance management practice, such as maintenance strategy, degradation, and work order management, rather than modeling the entire domain of maintenance. This approach reduces the scope of the development task and enables reasoning to be tested at a manageable scale. ROMAIN provides a unifying framework that can be used in conjunction with other BFO compliant sub-domain ontologies, such as planning and scheduling ontologies. The proposed ontology is validated using real-life data in the context of a use case related to evaluating the effectiveness of maintenance strategy.

Aims. For the first time, the motion of granules (solar plasma on the surface on scales larger than 2.5 Mm) has been followed over the entire visible surface of the Sun, using SDO/HMI white-light data.

Abstract This paper concerns the 3D simulation of corona discharge using high performance computing (HPC) managed with the message passing interface (MPI) library. In the field of finite volume methods applied on non-adaptive mesh grids and in the case of a specific 3D dynamic benchmark test devoted to streamer studies, the great efficiency of the iterative R&B SOR and BiCGSTAB methods versus the direct MUMPS method was clearly demonstrated in solving the Poisson equation using HPC resources. The optimization of the parallelization and the resulting scalability was undertaken as a function of the HPC architecture for a number of mesh cells ranging from 8 to 512 million and a number of cores ranging from 20 to 1600. The R&B SOR method remains at least about four times faster than the BiCGSTAB method and requires significantly less memory for all tested situations. The R&B SOR method was then implemented in a 3D MPI parallelized code that solves the classical first order model of an atmospheric pressure corona discharge in air. The 3D code capabilities were tested by following the development of one, two and four coplanar streamers generated by initial plasma spots for 6 ns. The preliminary results obtained allowed us to follow in detail the formation of the tree structure of a corona discharge and the effects of the mutual interactions between the streamers in terms of streamer velocity, trajectory and diameter. The computing time for 64 million of mesh cells distributed over 1000 cores using the MPI procedures is about 30 min ns −1 , regardless of the number of streamers.

Context. The measurement of the Sun’s surface motions with a high spatial and temporal resolution is still a challenge.

Context. Caustic crossing is the clearest signature of binary lenses in microlensing. In the present context, this signature is diluted by the large source star but a detailed analysis has allowed the companion signal to be extracted.

The first imaging devices of optical interferometry are likely to be of weak phase, typically: a set of three-element arrays independently observing the same object. The study of their imaging capabilities refers to appropriate optimization methods, which essentially address the self-calibration process and its stability. A general survey of these techniques is given, and it is shown, in particular, how the related algorithms can be used for examining the imaging capabilities of weak-phase interferometric devices. The phase-calibration algorithm involved in the self-calibration cycles is based on the principle underlying the trust-region methods. It benefits from certain remarkable properties, the analysis of which appeals to algebraic graph theory. The Fourier synthesis operation, which is also involved in these cycles, is performed by means of Wipe, a methodology recently introduced in radio imaging and optical interferometry. (Wipe is reminiscent of Clean, a widely used technique in astronomy). In the related theoretical framework the stability of the image-reconstruction process is controlled by considering certain elements of the singular-value decomposition of the derivative of the self-calibration operator. For example, the largest singular value of this derivative, which depends on the interferometric configuration and on the object thus imaged, provides a key indication of the observational limits of these experimental devices.

We present an algorithm and its parallel implementation for solving a self-consistent problem as encountered in Hartree-Fock or density functional theory. The algorithm takes advantage of the sparsity of matrices through the use of local molecular orbitals. The implementation allows one to exploit efficiently modern symmetric multiprocessing (SMP) computer architectures. As a first application, the algorithm is used within the density-functional-based tight binding method, for which most of the computational time is spent in the linear algebra routines (diagonalization of the Fock/Kohn-Sham matrix). We show that with this algorithm (i) single point calculations on very large systems (millions of atoms) can be performed on large SMP machines, (ii) calculations involving intermediate size systems (1000-100 000 atoms) are also strongly accelerated and can run efficiently on standard servers, and (iii) the error on the total energy due to the use of a cutoff in the molecular orbital coefficients can be controlled such that it remains smaller than the SCF convergence criterion.

New methods for redundant spacing calibration (RSC) are proposed. These are based on recent studies concerning phase calibration and the related phase unwrapping problem. In the corresponding theoretical framework, two subspaces of the baseline phase space, the variational spectral phase space K and the aberration baseline phase space L, play an important role. An interferometric device for which K∩L is reduced to {0} is said to be of full phase. For any imaging device of this type, including those for which the traditional recursive approach fails, the phase restoration problem can be solved in the least-squares sense. When the closure phases are strongly blurred, global instabilities may occur. Their analysis appeals to elementary concepts of algebraic number theory: ℤ lattice, reduced basis, and closest node. In all cases, the separation angle between K and L must be as large as possible. The imaging devices based on the RSC principle should be designed accordingly. All these points are illustrated by considering the phase restoration problems encountered in passive remote sensing by aperture synthesis. The difficulties related to possible correlator failures are examined in this context.

A new (to the author’s knowledge) approach to phase calibration is proposed. The corresponding theoretical framework calls on elementary concepts of algebraic graph theory (spanning trees, cycles) and computational algebraic number theory (reduced basis, closest node). The notion of phase closure is revisited in this context. One main result of this analysis is to provide all the elements for understanding the phase calibration instabilities that may occur. The phase unwrapping problem in question can be solved, directly, by minimizing the size of certain arcs. The corresponding direct methods are often quite efficient. The problem can also be solved in an indirect manner. The bulk of the work is then to minimize the length of certain chords. The pros and cons of the related methods are considered, and a link is made with the techniques developed so far. The problem of phase averaging, which is evidently much simpler, can be dealt with in a similar manner. As the corresponding results are intuitively obvious, one then has access to a more global understanding of the matter. In practice, the implications of this approach therefore concern all the methodologies in which the notions of phase closure and phase averaging prove to play an important role: self-calibration techniques in radio imaging and in optical interferometry, redundant spacing calibration in microwave imaging by aperture synthesis, etc.

A new class of phase-calibration algorithms is presented. The originality of these algorithms, as well as their efficiency, results from certain particular structures, the analysis of which calls on algebraic graph theory. The corresponding optimization process, which is based on the principle of the trust-region methods, proves to be well suited to these structures. The main message that emerges from the study is very clear: The traditional notions of phase closure imaging can be understood and refined in a wider framework. The implications of this research therefore concern all the fields in which the notion of phase closure plays a key role: weak-phase imaging in optical interferometry, radio imaging, remote sensing by aperture synthesis, etc.

Ontologies are logical theories that are used in computer science for describing different items such as web services, agents in multi-agent systems, or domain knowledge. Many ontologies exist, expressing various domains of knowledge with different abstraction levels (domain ontologies, top-level ontologies, and task ontologies are the usual categories). The conceptualization of the knowledge contained in an ontology is subject to change, whether because the context of its use changes, because the domain evolves, or because an ontology needs to interoperate with other elements using other ontologies. Change in logical theories is a form of defeasible reasoning, in which some formulas need to be added or removed from a knowledge base. Adaptive Logics (AL) is a logic managing defeasible reasoning that we investigate in this paper for managing change in ontologies expressed with Description Logics (DL). The adaptation of AL for DL will help express the context in which formulas remain valid or can be added to a DL knowledge base, and ease the interoperability between ontologies.

International audience

International audience

International audience

International audience

International audience

International audience

International audience

The main goal of the present communication is to test, in terms of computing time cost and precision, Poisson equation solvers in a cubic 3D configuration for further applications in 3D streamer simulation using High Performance Parallel Computing. The Poisson equation is discretized with the Finite Volume Method and the cubic domain is divided into n×n×n nodal points (n being 50, 100 or 200). The chosen configuration could be a basic block of a larger discretized domain distributed on several processors. The upper and the lower planes of the cubic domain are respectively the anode and the cathode, while the other lateral surfaces are open space. The calculation is either performed for the geometric field (Laplace equation) or takes into account the propagation of ananalytical space charge density.