Pablo Echenique

Improved routing strategies for Internet traffic delivery.

We analyze different strategies aimed at optimizing routing policies in the Internet. We first show that for a simple deterministic algorithm the local properties of the network deeply influence the time needed for packet delivery between two arbitrarily chosen nodes. We next rely on a real Internet map at the autonomous system level and introduce a score function that allows us to examine different routing protocols and their efficiency in traffic handling and packet delivery. Our results suggest that actual mechanisms are not the most efficient and that they can be integrated in a more general, though not too complex, scheme.

Dynamics of jamming transitions in complex networks

We numerically investigate jamming transitions in complex heterogeneous networks. Inspired by Internet routing protocols, we study a general model that incorporates local traffic information through a tunable parameter. The results show that whether the transition from a low-traffic regime to a congested phase is of first- or second-order type is determined by the protocol at work. The microscopic dynamics reveals that these two radically different behaviors are due to the way in which traffic jams propagate through the network. Our results are discussed in the context of Internet dynamics and other transport processes that take place on complex networks and provide insights for the design of routing policies based on traffic awareness in communication systems.

Exploring the Free Energy Landscape: From Dynamics to Networks and Back

Knowledge of the Free Energy Landscape topology is the essential key to understanding many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers there are, what the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times and rate constants, or hierarchical relationships among basins, completes the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides.

Modified Ehrenfest Formalism for Efficient Large-Scale ab initio Molecular Dynamics.

We present in detail the recently derived ab initio molecular dynamics (AIMD) formalism [Alonso et al. Phys. Rev. Lett. 2008, 101, 096403], which due to its numerical properties, is ideal for simulating the dynamics of systems containing thousands of atoms. A major drawback of traditional AIMD methods is the necessity to enforce the orthogonalization of the wave functions, which can become the bottleneck for very large systems. Alternatively, one can handle the electron-ion dynamics within the Ehrenfest scheme where no explicit orthogonalization is necessary, however the time step is too small for practical applications. Here we preserve the desirable properties of Ehrenfest in a new scheme that allows for a considerable increase of the time step while keeping the system close to the Born-Oppenheimer surface. We show that the automatically enforced orthogonalization is of fundamental importance for large systems because not only it improves the scaling of the approach with the system size but it also allows for an additional very efficient parallelization level. In this work, we provide the formal details of the new method, describe its implementation, and present some applications to some test systems. Comparisons with the widely used Car-Parrinello molecular dynamics method are made, showing that the new approach is advantageous above a certain number of atoms in the system. The method is not tied to a particular wave function representation, making it suitable for inclusion in any AIMD software package.

A mathematical and computational review of Hartree–Fock SCF methods in quantum chemistry

We present a review of the fundamental topics of Hartree–Fock theory in quantum chemistry. From the molecular Hamiltonian, using and discussing the Born–Oppenheimer approximation, we arrive at the Hartree and Hartree–Fock equations for the electronic problem. Special emphasis is placed on the most relevant mathematical aspects of the theoretical derivation of the final equations, and on the results regarding the existence and uniqueness of their solutions. All Hartree–Fock versions with different spin restrictions are systematically extracted from the general case, thus providing a unifying framework. The discretization of the one-electron orbital space is then reviewed and the Roothaan–Hall formalism introduced. This leads to an exposition of the basic underlying concepts related to the construction and selection of Gaussian basis sets, focusing on algorithmic efficiency issues. Finally, we close the review with a section in which the most relevant modern developments (especially those related to the design of linear-scaling methods) are commented on and linked to the issues discussed. The paper is intentionally introductory and rather self-contained, and may be useful for non-experts intending to use quantum chemical methods in interdisciplinary applications. Moreover, much material that can be found scattered in the literature has been put together to facilitate comprehension and to serve as a handy reference.

Distance-d covering problems in scale-free networks with degree correlations

A number of problems in communication systems demand the distributed allocation of network resources in order to provide better services, sampling, and distribution methods. The solution to these issues is becoming more challenging due to the increasing size and complexity of communication networks. We report here on a heuristic method to find near-optimal solutions to the covering problem in real communication networks, demonstrating that whether a centralized or a distributed design is to be used relies upon the degree correlations between connected vertices. We also show that the general belief that by targeting the hubs one can efficiently solve most problems on networks with a power-law degree distribution is not valid for assortative networks.

Immunization of real complex communication networks

Abstract.Most communication networks are complex. In this paper, we address one of the fundamental problems we are facing nowadays, namely, how we can efficiently protect these networks. To this end, we study an immunization strategy and found that it works almost as good as targeted immunization, but using only local information about the network topology. Our findings are supported with numerical simulations of the Susceptible-Infected-Removed (SIR) model on top of real communication networks, where immune nodes are previously identified by a covering algorithm. The results provide useful hints in the way to designing and deploying a digital immune system.

The Quixote project: Collaborative and Open Quantum Chemistry data management in the Internet age

Computational Quantum Chemistry has developed into a powerful, efficient, reliable and increasingly routine tool for exploring the structure and properties of small to medium sized molecules. Many thousands of calculations are performed every day, some offering results which approach experimental accuracy. However, in contrast to other disciplines, such as crystallography, or bioinformatics, where standard formats and well-known, unified databases exist, this QC data is generally destined to remain locally held in files which are not designed to be machine-readable. Only a very small subset of these results will become accessible to the wider community through publication.In this paper we describe how the Quixote Project is developing the infrastructure required to convert output from a number of different molecular quantum chemistry packages to a common semantically rich, machine-readable format and to build respositories of QC results. Such an infrastructure offers benefits at many levels. The standardised representation of the results will facilitate software interoperability, for example making it easier for analysis tools to take data from different QC packages, and will also help with archival and deposition of results. The repository infrastructure, which is lightweight and built using Open software components, can be implemented at individual researcher, project, organisation or community level, offering the exciting possibility that in future many of these QC results can be made publically available, to be searched and interpreted just as crystallography and bioinformatics results are today.Although we believe that quantum chemists will appreciate the contribution the Quixote infrastructure can make to the organisation and and exchange of their results, we anticipate that greater rewards will come from enabling their results to be consumed by a wider community. As the respositories grow they will become a valuable source of chemical data for use by other disciplines in both research and education.The Quixote project is unconventional in that the infrastructure is being implemented in advance of a full definition of the data model which will eventually underpin it. We believe that a working system which offers real value to researchers based on tools and shared, searchable repositories will encourage early participation from a broader community, including both producers and consumers of data. In the early stages, searching and indexing can be performed on the chemical subject of the calculations, and well defined calculation meta-data. The process of defining more specific quantum chemical definitions, adding them to dictionaries and extracting them consistently from the results of the various software packages can then proceed in an incremental manner, adding additional value at each stage.Not only will these results help to change the data management model in the field of Quantum Chemistry, but the methodology can be applied to other pressing problems related to data in computational and experimental science.

Introduction to protein folding for physicists

The prediction of the three-dimensional native structure of proteins from the knowledge of their amino acid sequence, known as the protein folding problem, is one of the most important yet unsolved issues of modern science. Since the conformational behaviour of flexible molecules is nothing more than a complex physical problem, increasingly more physicists are moving into the study of protein systems, bringing with them powerful mathematical and computational tools, as well as the sharp intuition and deep images inherent to the physics discipline. This work attempts to facilitate the first steps of such a transition. In order to achieve this goal, we provide an exhaustive account of the reasons of enormous relevance underlying the protein folding problem and summarize the present-day status of the methods aimed at solving it. We also provide an introduction to the particular structure of these biological heteropolymers, and we physically define the problem stating the assumptions behind this (commonly implicit) definition. Finally, we review the ‘special flavour’ of statistical mechanics that is typically used to study the astronomically large phase spaces of macromolecules. Throughout the whole work, much material that is found scattered in the literature has been put together here to improve comprehension and to serve as a handy reference.

Quantum mechanical calculation of the effects of stiff and rigid constraints in the conformational equilibrium of the alanine dipeptide

If constraints are imposed on a macromolecule, two inequivalent classical models may be used: the stiff and the rigid one. This work studies the effects of such constraints on the conformational equilibrium distribution (CED) of the model dipeptide HCO‐L‐Ala‐NH2without any simplifying assumption. We use ab initio quantum mechanics calculations including electron correlation at the MP2 level to describe the system, and we measure the conformational dependence of all the correcting terms to the naive CED based in the potential energy surface that appear when the constraints are considered. These terms are related to mass‐metric tensors determinants and also occur in the Fixmans compensating potential. We show that some of the corrections are non‐negligible if one is interested in the whole Ramachandran space. On the other hand, if only the energetically lower region, containing the principal secondary structure elements, is assumed to be relevant, then, all correcting terms may be neglected up to peptides of considerable length. This is the first time, as far as we know, that the analysis of the conformational dependence of these correcting terms is performed in a relevant biomolecule with a realistic potential energy function.