There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

This paper presents cosmological results based on full-mission Planck observations of temperature and polarization anisotropies of the cosmic microwave background (CMB) radiation. Our results are in very good agreement with the 2013 analysis of the Planck nominal-mission temperature data, but with increased precision. The temperature and polarization power spectra are consistent with the standard spatially-flat 6-parameter ΛCDM cosmology with a power-law spectrum of adiabatic scalar perturbations (denoted “base ΛCDM” in this paper). From the Planck temperature data combined with Planck lensing, for this cosmology we find a Hubble constant, H0 = (67.8 ± 0.9) km s-1Mpc-1, a matter density parameter Ωm = 0.308 ± 0.012, and a tilted scalar spectral index with ns = 0.968 ± 0.006, consistent with the 2013 analysis. Note that in this abstract we quote 68% confidence limits on measured parameters and 95% upper limits on other parameters. We present the first results of polarization measurements with the Low Frequency Instrument at large angular scales. Combined with the Planck temperature and lensing data, these measurements give a reionization optical depth of τ = 0.066 ± 0.016, corresponding to a reionization redshift of . These results are consistent with those from WMAP polarization measurements cleaned for dust emission using 353-GHz polarization maps from the High Frequency Instrument. We find no evidence for any departure from base ΛCDM in the neutrino sector of the theory; for example, combining Planck observations with other astrophysical data we find Neff = 3.15 ± 0.23 for the effective number of relativistic degrees of freedom, consistent with the value Neff = 3.046 of the Standard Model of particle physics. The sum of neutrino masses is constrained to ∑ mν < 0.23 eV. The spatial curvature of our Universe is found to be very close to zero, with | ΩK | < 0.005. Adding a tensor component as a single-parameter extension to base ΛCDM we find an upper limit on the tensor-to-scalar ratio of r0.002< 0.11, consistent with the Planck 2013 results and consistent with the B-mode polarization constraints from a joint analysis of BICEP2, Keck Array, and Planck (BKP) data. Adding the BKP B-mode data to our analysis leads to a tighter constraint of r0.002 < 0.09 and disfavours inflationarymodels with a V(φ) ∝ φ2 potential. The addition of Planck polarization data leads to strong constraints on deviations from a purely adiabatic spectrum of fluctuations. We find no evidence for any contribution from isocurvature perturbations or from cosmic defects. Combining Planck data with other astrophysical data, including Type Ia supernovae, the equation of state of dark energy is constrained to w = −1.006 ± 0.045, consistent with the expected value for a cosmological constant. The standard big bang nucleosynthesis predictions for the helium and deuterium abundances for the best-fit Planck base ΛCDM cosmology are in excellent agreement with observations. We also constraints on annihilating dark matter and on possible deviations from the standard recombination history. In neither case do we find no evidence for new physics. The Planck results for base ΛCDM are in good agreement with baryon acoustic oscillation data and with the JLA sample of Type Ia supernovae. However, as in the 2013 analysis, the amplitude of the fluctuation spectrum is found to be higher than inferred from some analyses of rich cluster counts and weak gravitational lensing. We show that these tensions cannot easily be resolved with simple modifications of the base ΛCDM cosmology. Apart from these tensions, the base ΛCDM cosmology provides an excellent description of the Planck CMB observations and many other astrophysical data sets.

/pdf/planck-2015-results-xiii-cosmological-parameters-5ghxckgd73.pdf

Planck 2015 results - XIII. Cosmological parameters

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

http://risa.stanford.edu/teaching/362/particledarkmatter.pdf

Particle dark matter: Evidence, candidates and constraints

Approximate formulae for exotic GCR anti-protons and anti-deuterons: Fluxes and astrophysical uncertainties

The vertical diffusive halo size of the Galaxy, $L$, is a key parameter for dark matter indirect searches. It can be better determined thanks to recent AMS-02 data. We set constraints on $L$ from Be/B and $^{10}$Be/Be data, and we performed a consistency check with positron data. We detail the dependence of Be/B and $^{10}$Be/Be on $L$ and forecast on which energy range better data would be helpful for future $L$ improvements. We used USINE v3.5 for the propagation of nuclei, and $e^+$ were calculated with the pinching method of Boudaud et al. (2017). The current AMS-02 Be/B ($\sim3\%$ precision) and ACE-CRIS $^{10}$Be/Be ($\sim 10\%$ precision) data bring similar and consistent constraints on $L$. The AMS-02 Be/B data alone constrain $L=5^{+3}_{-2}$~kpc at a 68\% confidence level (spanning different benchmark transport configurations), a range for which most models do not overproduce positrons. Future experiments need to deliver percent-level accuracy on $^{10}$Be/$^9$Be anywhere below 10 GV to further constrain $L$. Forthcoming AMS-02, HELIX, and PAMELA $^{10}$Be/$^9$Be results will further test and possibly tighten the limits derived here. Elemental ratios involving radioactive species with different lifetimes (e.g. Al/Mg and Cl/Ar) are also awaited to provide complementary and robuster constraints.

Galactic halo size in the light of recent AMS-02 data

Approximate formulae for exotic GCR anti-protons and anti-deuterons: fluxes and astrophysical uncertainties

Context. Top-of-atmosphere (TOA) cosmic-ray (CR) fluxes from satellites and balloon-borne experiments are snapshots of the solar activity imprinted on the interstellar (IS) fluxes. Given a series of snapshots, the unknown IS flux shape and the level of modulation (for each snapshot) can be recovered. Aims. We wish (i) to provide the most accurate determination of the IS H and He fluxes from TOA data alone, (ii) to obtain the associated modulation levels (and uncertainties) while fully accounting for the correlations with the IS flux uncertainties, and (iii) to inspect whether the minimal force-field approximation is sufficient to explain all the data at hand. Methods. Using H and He TOA measurements, including the recent high-precision AMS, BESS-Polar, and PAMELA data, we performed a non-parametric fit of the IS fluxes JIS H, He and modulation level φi for each data-taking period. We relied on a Markov chain Monte Carlo (MCMC) engine to extract the probability density function and correlations (hence the credible intervals) of the sought parameters. Results. Although H and He are the most abundant and best measured CR species, several datasets had to be excluded from the analysis because of inconsistencies with other measurements. From the subset of data passing our consistency cut, we provide readyto-use best-fit and credible intervals for the H and He IS fluxes from MeV/n to PeV/n energy (with a relative precision in the range [2− 10%] at 1σ). Given the strong correlation between JIS and φi parameters, the uncertainties on JIS translate into ∆φ ≈ ±30 MV (at 1σ) for all experiments. We also find that the presence of 3He in He data biases φ towards higher φ values by ∼ 30 MV. The force-field approximation, despite its limitation, gives an excellent (χ2/dof= 1.02) description of the recent high-precision TOA H and He fluxes. Conclusions. The analysis must be extended to different charge species and more realistic modulation models. It would benefit from the AMS-02 unique capability of providing frequent high-precision snapshots of the TOA fluxes over a full solar cycle.

/pdf/non-parametric-determination-of-h-and-he-interstellar-fluxes-2ikczs4q1j.pdf

Non-parametric determination of H and He interstellar fluxes from cosmic-ray data (Corrigendum)

Measurements of ultra heavy nuclei at GeV/n energies in the galactic cosmic radiation address the question of the sources (nucleosynthetic s- and r-processes). As such, the determination of CR source abundances is a promising way to discriminate between existing nucleosynthesis models. For primary species (nuclei present and accelerated at sources), it is generally assumed that the relative propagated abundances, if they are close in mass, are not too different from their relative source abundances. Besides, the range of the correction factor associated to propagation has been estimated in weighted slab models only. Heavy CRs that are detected near Earth were accelerated from regions that are closer to us than were the light nuclei. Hence, the geometry of sources in the Solar neighbourhood, and as equally important, the geometry of gas in the same region, must be taken into account. In this paper, a two zone diffusion model is used, and as was previously investigated for radioactive species, we report here on the impact of the local interstellar medium (LISM) feature (under-dense medium over a scale∼ 100 pc) on primary and secondary stable nuclei propagated abundances. Going down to Fe nuclei, the connection between heavy and light abundances is also inspected. A general trend is found that decreases the UHCR source abundances relative to the HCR ones. This could have an impact on the level of r-process required to reproduce the data.

/pdf/spallation-dominated-propagation-of-heavy-cosmic-rays-and-30qc4eqo0x.pdf

David Maurin

Papers

Approximate formulae for exotic GCR anti-protons and anti-deuterons: Fluxes and astrophysical uncertainties

Galactic halo size in the light of recent AMS-02 data

Approximate formulae for exotic GCR anti-protons and anti-deuterons: fluxes and astrophysical uncertainties

Non-parametric determination of H and He interstellar fluxes from cosmic-ray data (Corrigendum)

Spallation-dominated propagation of heavy cosmic rays and the Local Interstellar Medium (LISM)