Antiproton and Positron Signal Enhancement in Dark Matter Mini-Spikes Scenarios

The annihilation of dark matter (DM) in the Galaxy could produce specific imprints on the spectra of antimatter species in Galactic cosmic rays, which could be detected by upcoming experiments such as PAMELA and AMS02. Recent studies show that the presence of substructures can enhance the annihilation signal by a "boost factor" that not only depends on energy, but that is intrinsically a statistical property of the distribution of DM substructures inside the Milky Way. We investigate a scenario in which substructures consist of $\sim 100$ "mini-spikes" around intermediate-mass black holes. Focusing on primary positrons and antiprotons, we find large boost factors, up to a few thousand, that exhibit a large variance at high energy in the case of positrons and at low energy in the case of antiprotons. As a consequence, an estimate of the DM particle mass based on the observed cut-off in the positron spectrum could lead to a substantial underestimate of its actual value.Comment: 13 pages, 9 figures, minor changes, version accepted for publication in PR

'Datafication': Making sense of (big) data in a complex world

This is a pre-print of an article published in European Journal of Information Systems. The definitive publisher-authenticated version is available at the link below. Copyright @ 2013 Operational Research Society Ltd.No abstract available (Editorial

Galactic secondary positron flux at the Earth

Secondary positrons are produced by spallation of cosmic rays within the interstellar gas. Measurements have been typically expressed in terms of the positron fraction, which exhibits an increase above 10 GeV. Many scenarios have been proposed to explain this feature, among them some additional primary positrons originating from dark matter annihilation in the Galaxy. The PAMELA satellite has provided high quality data that has enabled high accuracy statistical analyses to be made, showing that the increase in the positron fraction extends up to about 100 GeV. It is therefore of paramount importance to constrain theoretically the expected secondary positron flux to interpret the observations in an accurate way. We find the secondary positron flux to be reproduced well by the available observations, and to have theoretical uncertainties that we quantify to be as large as about one order of magnitude. We also discuss the positron fraction issue and find that our predictions may be consistent with the data taken before PAMELA. For PAMELA data, we find that an excess is probably present after considering uncertainties in the positron flux, although its amplitude depends strongly on the assumptions made in relation to the electron flux. By fitting the current electron data, we show that when considering a soft electron spectrum, the amplitude of the excess might be far lower than usually claimed. We provide fresh insights that may help to explain the positron data with or without new physical model ingredients. PAMELA observations and the forthcoming AMS-02 mission will allow stronger constraints to be aplaced on the cosmic--ray transport parameters, and are likely to reduce drastically the theoretical uncertainties.Comment: 15 pages, 12 figures. The recent PAMELA data on the positron fraction (arXiv:0810.4995) have been included and the ensuing discussion has been extended. Accepted version in A&

Utilization of NIRS and Minolta Chromameter in selection for increased carotenoids content in cassava roots. [SP10-03]

Significant progress has been made increasing carotenoids content in cassava roots. The information was used to test the usefulness of NIRs and the Minolta Chromameter in predicting carotenoids content (and other relevant traits). Quantification was made of fresh root tissue (not lyophilized). The dataset (2129 data points) was first cleaned of outlying or suspicious data points to develop reliable prediction equations. R2 values between NIRs prediction and actual measurements were 0.91 for total carotenoids content (TCC); 0.93 for total ?-carotene (TBC), and 0.95 for dry matter content, but is less efficient for cyanogenic potential (0,81). Standard error of cross validation (SECV) for TCC and TBC were (1.191 and 0.837, respectively) while the residual predictive deviations (RPD) were also acceptable (above 3.0). These results suggest that NIRs can be used to reliably predict different variables based on fresh root samples. The Minolta Chromameter can also be used for pre-selection as its R2 values were 0.58 for TCC and 0.64 for TBC. Relative concentration of different carotenoids and precursors did not suggest the existence of a major blockage in the metabolic pathway towards the synthesis of ?-carotene. Once phytoene is synthesized most to the different pigments in the metabolic pathway are found, as expected, in correlated proportions. (Résumé d'auteur

Mrk 421, Mrk 501, and 1ES 1426+428 at 100 GeV with the CELESTE Cherenkov Telescope

We have measured the gamma-ray fluxes of the blazars Mrk 421 and Mrk 501 in the energy range between 50 and 350 GeV (1.2 to 8.3 x 10^25 Hz). The detector, called CELESTE, used first 40, then 53 heliostats of the former solar facility "Themis" in the French Pyrenees to collect Cherenkov light generated in atmospheric particle cascades. The signal from Mrk 421 is often strong. We compare its flux with previously published multi-wavelength studies and infer that we are straddling the high energy peak of the spectral energy distribution. The signal from Mrk 501 in 2000 was weak (3.4 sigma). We obtain an upper limit on the flux from 1ES 1426+428 of less than half that of the Crab flux near 100 GeV. The data analysis and understanding of systematic biases have improved compared to previous work, increasing the detector's sensitivity.Comment: 15 pages, 14 figures, accepted to A&A (July 2006) August 19 -- corrected error in author lis

Antimatter signals of singlet scalar dark matter

We consider the singlet scalar model of dark matter and study the expected antiproton and positron signals from dark matter annihilations. The regions of the viable parameter space of the model that are excluded by present data are determined, as well as those regions that will be probed by the forthcoming experiment AMS-02. In all cases, different propagation models are investigated, and the possible enhancement due to dark matter substructures is analyzed. We find that the antiproton signal is more easily detectable than the positron one over the whole parameter space. For a typical propagation model and without any boost factor, AMS-02 will be able to probe --via antiprotons-- the singlet model of dark matter up to masses of 600 GeV. Antiprotons constitute, therefore, a promising signal to constraint or detect the singlet scalar model.Comment: 24 pages, 8 figures. v2: minor improvements. Accepted for publication in JCA

Cosmic-ray antiproton constraints on light dark matter candidates

Some direct detection experiments have recently collected excess events that could be interpreted as a dark matter (DM) signal, pointing to particles in the $\sim$10 GeV mass range. We show that scenarios in which DM can self-annihilate with significant couplings to quarks are likely excluded by the cosmic-ray (CR) antiproton data, provided the annihilation is S-wave dominated when DM decouples in the early universe. These limits apply to most of supersymmetric candidates, eg in the minimal supersymmetric standard model (MSSM) and in the next-to-MSSM (NMSSM), and more generally to any thermal DM particle with hadronizing annihilation final states.Comment: Contribution to the proceedings of TAUP-2011 (Munich, 5-9 IX 2011). 4 page

Scalar Multiplet Dark Matter

We perform a systematic study of the phenomenology associated to models where the dark matter consists in the neutral component of a scalar SU(2)_L n-uplet, up to n=7. If one includes only the pure gauge induced annihilation cross-sections it is known that such particles provide good dark matter candidates, leading to the observed dark matter relic abundance for a particular value of their mass around the TeV scale. We show that these values actually become ranges of values -which we determine- if one takes into account the annihilations induced by the various scalar couplings appearing in these models. This leads to predictions for both direct and indirect detection signatures as a function of the dark matter mass within these ranges. Both can be largely enhanced by the quartic coupling contributions. We also explain how, if one adds right-handed neutrinos to the scalar doublet case, the results of this analysis allow to have altogether a viable dark matter candidate, successful generation of neutrino masses, and leptogenesis in a particularly minimal way with all new physics at the TeV scale.Comment: 43 pages, 20 figure

Randomized planning of dynamic motions avoiding forward singularities

The final publication is available at link.springer.comForward singularities, also known as direct, or actuator singularities, cause many problems to the planning and control of robot motions. They yield position errors and rigidity losses of the robot, and generate unbounded actions in typical control laws. To circumvent these issues, this paper proposes a randomized kinodynamic planner for computing trajectories avoiding such singularities. Given initial and final states for the robot, the planner attempts to connect them by means of a dynamically-feasible, singularity-free trajectory that also respects the force limits of the actuators. The performance of the strategy is illustrated in simulation by means of a parallel robot performing a highly- dynamic task.Peer ReviewedPostprint (author's final draft

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types