Wavemoth -- Fast spherical harmonic transforms by butterfly matrix compression

We present Wavemoth, an experimental open source code for computing scalar spherical harmonic transforms (SHTs). Such transforms are ubiquitous in astronomical data analysis. Our code performs substantially better than existing publicly available codes due to improvements on two fronts. First, the computational core is made more efficient by using small amounts of precomputed data, as well as paying attention to CPU instruction pipelining and cache usage. Second, Wavemoth makes use of a fast and numerically stable algorithm based on compressing a set of linear operators in a precomputation step. The resulting SHT scales as O(L^2 (log L)^2) for the resolution range of practical interest, where L denotes the spherical harmonic truncation degree. For low and medium-range resolutions, Wavemoth tends to be twice as fast as libpsht, which is the current state of the art implementation for the HEALPix grid. At the resolution of the Planck experiment, L ~ 4000, Wavemoth is between three and six times faster than libpsht, depending on the computer architecture and the required precision. Due to the experimental nature of the project, only spherical harmonic synthesis is currently supported, although adding support or spherical harmonic analysis should be trivial.Comment: 13 pages, 6 figures, accepted by ApJ

Compressed Online Dictionary Learning for Fast fMRI Decomposition

We present a method for fast resting-state fMRI spatial decomposi-tions of very large datasets, based on the reduction of the temporal dimension before applying dictionary learning on concatenated individual records from groups of subjects. Introducing a measure of correspondence between spatial decompositions of rest fMRI, we demonstrates that time-reduced dictionary learning produces result as reliable as non-reduced decompositions. We also show that this reduction significantly improves computational scalability

Entropy-scaling search of massive biological data

Many datasets exhibit a well-defined structure that can be exploited to design faster search tools, but it is not always clear when such acceleration is possible. Here, we introduce a framework for similarity search based on characterizing a dataset's entropy and fractal dimension. We prove that searching scales in time with metric entropy (number of covering hyperspheres), if the fractal dimension of the dataset is low, and scales in space with the sum of metric entropy and information-theoretic entropy (randomness of the data). Using these ideas, we present accelerated versions of standard tools, with no loss in specificity and little loss in sensitivity, for use in three domains---high-throughput drug screening (Ammolite, 150x speedup), metagenomics (MICA, 3.5x speedup of DIAMOND [3,700x BLASTX]), and protein structure search (esFragBag, 10x speedup of FragBag). Our framework can be used to achieve "compressive omics," and the general theory can be readily applied to data science problems outside of biology.Comment: Including supplement: 41 pages, 6 figures, 4 tables, 1 bo

Shock waves in tidally compressed stars by massive black holes

We interest in the case of a main-sequence star deeply penetrating within the tidal radius of a massive black hole. We focus on the compression phase leading to a so-called pancake configuration of the star at the instant of maximal compression. The aim is to study the tidal compression process paying particular attention to the development of shock waves;to deduce reliable estimates of the thermodynamical quantities involved in the pancake star; and to solve a controversy about whether or not thermonuclear reactions can be triggered in the core of a tidally compressed star. We have set up a one-dimensional hydrodynamical model well-adapted to the geometry of the problem. Based on the high-resolution shock-capturing Godunov-type approach, it allows to study the compression phase undergone by the star in the direction orthogonal to its orbital plane. We show the existence of two regimes depending on whether shock waves develop before or after the instant of maximal core compression. In both cases we confirm high compression and heating factors in the stellar core able to trigger a thermonuclear explosion. Moreover, we show that the shock waves carry outwards a brief but very high peak of temperature from the centre to the surface of the star. We tentatively conclude that the phenomenon could give rise to hard electromagnetic radiation, to be compared to some X-ray flares already observed in some galactic nuclei harbouring massive black holes. Finally, we estimate that the rate of pancake stars should be about $10^{-5}$ per galaxy per year. If generated in hard X- or $\gamma$-ray band, several events of this kind per year should be detectable within the full observable universe.Comment: 19 pages, 38 figures, 7 tables; v2 : corrected to match version accepted in Astron. Astrophys. Tables and references added, new simulations also performed for adiabatic index 4/

Structure of the hDmc1-ssDNA filament reveals the principles of its architecture

In eukaryotes, meiotic recombination is a major source of genetic diversity, but its defects in humans lead to abnormalities such as Down's, Klinefelter's and other syndromes. Human Dmc1 (hDmc1), a RecA/Rad51 homologue, is a recombinase that plays a crucial role in faithful chromosome segregation during meiosis. The initial step of homologous recombination occurs when hDmc1 forms a filament on single-stranded (ss) DNA. However the structure of this presynaptic complex filament for hDmc1 remains unknown. To compare hDmc1-ssDNA complexes to those known for the RecA/Rad51 family we have obtained electron microscopy (EM) structures of hDmc1-ssDNA nucleoprotein filaments using single particle approach. The EM maps were analysed by docking crystal structures of Dmc1, Rad51, RadA, RecA and DNA. To fully characterise hDmc1-DNA complexes we have analysed their organisation in the presence of Ca2+, Mg2+, ATP, AMP-PNP, ssDNA and dsDNA. The 3D EM structures of the hDmc1-ssDNA filaments allowed us to elucidate the principles of their internal architecture. Similar to the RecA/Rad51 family, hDmc1 forms helical filaments on ssDNA in two states: extended (active) and compressed (inactive). However, in contrast to the RecA/Rad51 family, and the recently reported structure of hDmc1-double stranded (ds) DNA nucleoprotein filaments, the extended (active) state of the hDmc1 filament formed on ssDNA has nine protomers per helical turn, instead of the conventional six, resulting in one protomer covering two nucleotides instead of three. The control reconstruction of the hDmc1-dsDNA filament revealed 6.4 protein subunits per helical turn indicating that the filament organisation varies depending on the DNA templates. Our structural analysis has also revealed that the N-terminal domain of hDmc1 accomplishes its important role in complex formation through domain swapping between adjacent protomers, thus providing a mechanistic basis for coordinated action of hDmc1 protomers during meiotic recombination