The cosmological simulation code GADGET-2

We discuss the cosmological simulation code GADGET-2, a new massively parallel TreeSPH code, capable of following a collisionless fluid with the N-body method, and an ideal gas by means of smoothed particle hydrodynamics (SPH). Our implementation of SPH manifestly conserves energy and entropy in regions free of dissipation, while allowing for fully adaptive smoothing lengths. Gravitational forces are computed with a hierarchical multipole expansion, which can optionally be applied in the form of a TreePM algorithm, where only short-range forces are computed with the `tree'-method while long-range forces are determined with Fourier techniques. Time integration is based on a quasi-symplectic scheme where long-range and short-range forces can be integrated with different timesteps. Individual and adaptive short-range timesteps may also be employed. The domain decomposition used in the parallelisation algorithm is based on a space-filling curve, resulting in high flexibility and tree force errors that do not depend on the way the domains are cut. The code is efficient in terms of memory consumption and required communication bandwidth. It has been used to compute the first cosmological N-body simulation with more than 10^10 dark matter particles, reaching a homogeneous spatial dynamic range of 10^5 per dimension in a 3D box. It has also been used to carry out very large cosmological SPH simulations that account for radiative cooling and star formation, reaching total particle numbers of more than 250 million. We present the algorithms used by the code and discuss their accuracy and performance using a number of test problems. GADGET-2 is publicly released to the research community.Comment: submitted to MNRAS, 31 pages, 20 figures (reduced resolution), code available at http://www.mpa-garching.mpg.de/gadge

In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study

<p>Abstract</p> <p>Background</p> <p>Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and <it>a priori </it>knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange.</p> <p>Results</p> <p>The <it>in silico </it>models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions.</p> <p>Conclusion</p> <p>The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive <it>a priori </it>information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis.</p

A network approach to public goods

Suppose agents can exert costly effort that creates nonrival, heterogeneous benefits for each other. At each possible outcome, a weighted, directed network describing marginal externalities is defined. We show that Pareto efficient outcomes are those at which the largest eigenvalue of the network is 1. An important set of efficient solutions - Lindahl outcomes - are characterized by contributions being proportional to agents' eigenvector centralities in the network. The outcomes we focus on are motivated by negotiations. We apply the results to identify who is essential for Pareto improvements, how to efficiently subdivide negotiations, and whom to optimally add to a team

Is Evolution an Algorithm? Effects of local entropy in unsupervised learning and protein evolution

L'abstract è presente nell'allegato / the abstract is in the attachmen

Closest-vector problem and the zero-temperature p-spin landscape for lossy compression

We consider a high-dimensional random constrained optimization problem in which a set of binary variables is subjected to a linear system of equations. The cost function is a simple linear cost, measuring the Hamming distance with respect to a reference configuration. Despite its apparent simplicity, this problem exhibits a rich phenomenology. We show that different situations arise depending on the random ensemble of linear systems. When each variable is involved in at most two linear constraints, we show that the problem can be partially solved analytically, in particular we show that upon convergence, the zero-temperature limit of the cavity equations returns the optimal solution. We then study the geometrical properties of more general random ensembles. In particular we observe a range in the density of constraints at which the system enters a glassy phase where the cost function has many minima. Interestingly, the algorithmic performances are only sensitive to another phase transition affecting the structure of configurations allowed by the linear constraints. We also extend our results to variables belonging to GF(q), the Galois field of order q. We show that increasing the value of q allows to achieve a better optimum, which is confirmed by the replica-symmetric cavity method predictions

Randomised algorithms for counting and generating combinatorial structures

SIGLEAvailable from British Library Document Supply Centre- DSC:D85048 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Numerical Ricci-flat metrics on K3

We develop numerical algorithms for solving the Einstein equation on Calabi-Yau manifolds at arbitrary values of their complex structure and Kahler parameters. We show that Kahler geometry can be exploited for significant gains in computational efficiency. As a proof of principle, we apply our methods to a one-parameter family of K3 surfaces constructed as blow-ups of the T^4/Z_2 orbifold with many discrete symmetries. High-resolution metrics may be obtained on a time scale of days using a desktop computer. We compute various geometric and spectral quantities from our numerical metrics. Using similar resources we expect our methods to practically extend to Calabi-Yau three-folds with a high degree of discrete symmetry, although we expect the general three-fold to remain a challenge due to memory requirements.Comment: 38 pages, 10 figures; program code and animations of figures downloadable from http://schwinger.harvard.edu/~wiseman/K3/ ; v2 minor corrections, references adde

Asynchronous iterative solution for dominant eigenvectors with applications in performance modelling and PageRank

Imperial Users onl

Automated manipulation of musical grammars to support episodic interactive experiences

Music is used to enhance the experience of participants and visitors in a range of settings including theatre, film, video games, installations and theme parks. These experiences may be interactive, contrastingly episodic and with variable duration. Hence, the musical accompaniment needs to be dynamic and to transition between contrasting music passages. In these contexts, computer generation of music may be necessary for practical reasons including distribution and cost. Automated and dynamic composition algorithms exist but are not well-suited to a highly interactive episodic context owing to transition-related problems including discontinuity, abruptness, extended repetitiveness and lack of musical granularity and musical form. Addressing these problems requires algorithms capable of reacting to participant behaviour and episodic change in order to generate formic music that is continuous and coherent during transitions. This thesis presents the Form-Aware Transitioning and Recovering Algorithm (FATRA) for realtime, adaptive, form-aware music generation to provide continuous musical accompaniment in episodic context. FATRA combines stochastic grammar adaptation and grammar merging in real time. The Form-Aware Transition Engine (FATE) implementation of FATRA estimates the time-occurrence of upcoming narrative transitions and generates a harmonic sequence as narrative accompaniment with a focus on coherent, form-aware music transitioning between music passages of contrasting character. Using FATE, FATRA has been evaluated in three perceptual user studies: An audioaugmented real museum experience, a computer-simulated museum experience and a music-focused online study detached from narrative. Music transitions of FATRA were benchmarked against common approaches of the video game industry, i.e. crossfading and direct transitions. The participants were overall content with the music of FATE during their experience. Transitions of FATE were significantly favoured against the crossfading benchmark and competitive against the direct transitions benchmark, without statistical significance for the latter comparison. In addition, technical evaluation demonstrated capabilities of FATRA including form generation, repetitiveness avoidance and style/form recovery in case of falsely predicted narrative transitions. Technical results along with perceptual preference and competitiveness against the benchmark approaches are deemed as positive and the structural advantages of FATRA, including form-aware transitioning, carry considerable potential for future research