Fast and automated oscillation frequency extraction using Bayesian multi-modality

Since the advent of CoRoT, and NASA Kepler and K2, the number of low- and intermediate-mass stars classified as pulsators has increased very rapidly with time, now accounting for several $10^4$ targets. With the recent launch of NASA TESS space mission, we have confirmed our entrance to the era of all-sky observations of oscillating stars. TESS is currently releasing good quality datasets that already allow for the characterization and identification of individual oscillation modes even from single 27-days shots on some stars. When ESA PLATO will become operative by the next decade, we will face the observation of several more hundred thousands stars where identifying individual oscillation modes will be possible. However, estimating the individual frequency, amplitude, and lifetime of the oscillation modes is not an easy task. This is because solar-like oscillations and especially their evolved version, the red giant branch (RGB) oscillations, can vary significantly from one star to another depending on its specific stage of the evolution, mass, effective temperature, metallicity, as well as on its level of rotation and magnetism. In this perspective I will present a novel, fast, and powerful way to derive individual oscillation mode frequencies by building on previous results obtained with \diamonds. I will show that the oscillation frequencies obtained with this new approach can reach precisions of about 0.1 % and accuracies of about 0.01 % when compared to published literature values for the RGB star KIC~12008916.Comment: 10 pages, 2 figures, accepted for publication in Frontiers in Astronomy and Space Sciences. Invited contribution for the research topic "The Future of Asteroseismology

DIAMONDS: a new Bayesian Nested Sampling tool. Application to Peak Bagging of solar-like oscillations

To exploit the full potential of Kepler light curves, sophisticated and robust analysis tools are now required more than ever. Characterizing single stars with an unprecedented level of accuracy and subsequently analyzing stellar populations in detail are fundamental to further constrain stellar structure and evolutionary models. We developed a new code, termed Diamonds, for Bayesian parameter estimation and model comparison by means of the nested sampling Monte Carlo (NSMC) algorithm, an efficient and powerful method very suitable for high-dimensional and multi-modal problems. A detailed description of the features implemented in the code is given with a focus on the novelties and differences with respect to other existing methods based on NSMC. Diamonds is then tested on the bright F8 V star KIC~9139163, a challenging target for peak-bagging analysis due to its large number of oscillation peaks observed, which are coupled to the blending that occurs between $\ell=2,0$ peaks, and the strong stellar background signal. We further strain the performance of the approach by adopting a 1147.5 days-long Kepler light curve. The Diamonds code is able to provide robust results for the peak-bagging analysis of KIC~9139163. We test the detection of different astrophysical backgrounds in the star and provide a criterion based on the Bayesian evidence for assessing the peak significance of the detected oscillations in detail. We present results for 59 individual oscillation frequencies, amplitudes and linewidths and provide a detailed comparison to the existing values in the literature. Lastly, we successfully demonstrate an innovative approach to peak bagging that exploits the capability of Diamonds to sample multi-modal distributions, which is of great potential for possible future automatization of the analysis technique.Comment: 22 pages, 14 figures, 3 tables. Accepted for publication in A&

Peak Bagging of red giant stars observed by Kepler: first results with a new method based on Bayesian nested sampling

The peak bagging analysis, namely the fitting and identification of single oscillation modes in stars' power spectra, coupled to the very high-quality light curves of red giant stars observed by Kepler, can play a crucial role for studying stellar oscillations of different flavor with an unprecedented level of detail. A thorough study of stellar oscillations would thus allow for deeper testing of stellar structure models and new insights in stellar evolution theory. However, peak bagging inferences are in general very challenging problems due to the large number of observed oscillation modes, hence of free parameters that can be involved in the fitting models. Effciency and robustness in performing the analysis is what may be needed to proceed further. For this purpose, we developed a new code implementing the Nested Sampling Monte Carlo (NSMC) algorithm, a powerful statistical method well suited for Bayesian analyses of complex problems. In this talk we show the peak bagging of a sample of high signal-to-noise red giant stars by exploiting recent Kepler datasets and a new criterion for the detection of an oscillation mode based on the computation of the Bayesian evidence. Preliminary results for frequencies and lifetimes for single oscillation modes, together with acoustic glitches, are therefore presented.Comment: Conference Proceeding - CoRoT3-KASC7 The Space Photometry Revolution, Toulouse, France, July 6-11 2014, 4 pages, 3 figure

Asteroseismic stellar activity relations

In asteroseismology an important diagnostic of the evolutionary status of a star is the small frequency separation which is sensitive to the gradient of the mean molecular weight in the stellar interior. It is thus interesting to discuss the classical age-activity relations in terms of this quantity. Moreover, as the photospheric magnetic field tends to suppress the amplitudes of acoustic oscillations, it is important to quantify the importance of this effect by considering various activity indicators. We propose a new class of age-activity relations that connects the Mt. Wilson $S$ index and the average scatter in the light curve with the small frequency separation and the amplitude of the p-mode oscillations. We used a Bayesian inference to compute the posterior probability of various empirical laws for a sample of 19 solar-like active stars observed by the Kepler telescope. We demonstrate the presence of a clear correlation between the Mt. Wilson $S$ index and the relative age of the stars as indicated by the small frequency separation, as well as an anti-correlation between the $S$ index and the oscillation amplitudes. We argue that the average activity level of the stars shows a stronger correlation with the small frequency separation than with the absolute age that is often considered in the literature. The phenomenological laws discovered in this paper have the potential to become new important diagnostics to link stellar evolution theory with the dynamics of global magnetic fields. In particular we argue that the relation between the Mt. Wilson $S$ index and the oscillation amplitudes is in good agreement with the findings of direct numerical simulations of magneto-convection.Comment: 5 pages, 4 figures, 2 tables. Accepted for publication in A&

High-precision acoustic helium signatures in 18 low-mass low-luminosity red giants. Analysis from more than four years of Kepler observations

High-precision frequencies of acoustic modes in red giant stars are now available thanks to the long observing length and high-quality of the light curves provided by the NASA Kepler mission, thus allowing to probe the interior of evolved cool low-mass stars with unprecedented level of detail. We characterize the acoustic signature of the helium second ionization zone in a sample of 18 low-mass low-luminosity red giants by exploiting new mode frequency measurements derived from more than four years of Kepler observations. We analyze the second frequency differences of radial acoustic modes in all the stars of the sample by using the Bayesian code Diamonds. We find clear acoustic glitches due to the signature of helium second ionization in all the stars of the sample. We measure the acoustic depth and the characteristic width of the acoustic glitches with a precision level on average around $\sim$2% and $\sim$8%, respectively. We find good agreement with theoretical predictions and existing measurements from the literature. Lastly, we derive the amplitude of the glitch signal at $\nu_\mathrm{max}$ for the second differences and for the frequencies with an average precision of $\sim$6%, obtaining values in the range 0.14-0.24 $\mu$Hz, and 0.08-0.33 $\mu$Hz, respectively, which can be used to investigate the helium abundance in the stars.Comment: 12 pages, 19 figures, 3 tables. Accepted for publication in A&

Bayesian peak bagging analysis of 19 low-mass low-luminosity red giants observed with Kepler

The currently available Kepler light curves contain an outstanding amount of information but a detailed analysis of the individual oscillation modes in the observed power spectra, also known as peak bagging, is computationally demanding and challenging to perform on a large number of targets. Our intent is to perform for the first time a peak bagging analysis on a sample of 19 low-mass low-luminosity red giants observed by Kepler for more than four years. This allows us to provide high-quality asteroseismic measurements that can be exploited for an intensive testing of the physics used in stellar structure models, stellar evolution and pulsation codes, as well as for refining existing asteroseismic scaling relations in the red giant branch regime. For this purpose, powerful and sophisticated analysis tools are needed. We exploit the Bayesian code Diamonds, using an efficient nested sampling Monte Carlo algorithm, to perform both a fast fitting of the individual oscillation modes and a peak detection test based on the Bayesian evidence. We find good agreement for the parameters estimated in the background fitting phase with those given in the literature. We extract and characterize a total of 1618 oscillation modes, providing the largest set of detailed asteroseismic mode measurements ever published. We report on the evidence of a change in regime observed in the relation between linewidths and effective temperatures of the stars occurring at the bottom of the RGB. We show the presence of a linewidth depression or plateau around $\nu_\mathrm{max}$ for all the red giants of the sample. Lastly, we show a good agreement between our measurements of maximum mode amplitudes and existing maximum amplitudes from global analyses provided in the literature, useful as empirical tools to improve and simplify the future peak bagging analysis on a larger sample of evolved stars.Comment: 78 pages, 46 figures, 22 tables. Accepted for publication in A&

Riscrittura e autocensura nei Dialoghi di Torquato Tasso

Il contributo ripercorre in particolare il dialogo del Gonzaga di Torquato Tasso nella luce di premesse metodologiche atte a illustrare la relazione tra la vicenda ‘pubblica’ del testo e la sua divulgazione manoscritta (che nel caso dei dialoghi tassiani avviene sovente in modo parallelo e tangenziale). Ne risultano, con nuova evidenza, gli scrupoli dell’autore su un argomento (quello dell’inquisizione spagnola in Napoli) particolarmente delicato, che portarono a rivedere non pochi luoghi del testo attraverso forme rilevanti di autocensura

Techniques and Patterns for Safe and Efficient Real-Time Middleware

Over 90 percent of all microprocessors are now used for real-time and embedded applications. The behavior of these applications is often constrained by the physical world. It is therefore important to devise higher-level languages and middleware that meet conventional functional requirements, as well as dependably and productively enforce real-time constraints. Real-Time Java is emerging as a safe, real-time environment. In this thesis we use it as our experimentation platform; however, our findings are easily adapted to other similar platforms. This thesis provides the following contributions to the study of safe and efficient real-time middleware. First, it identifies potential bottlenecks and problem with respect to guaranteeing real-time performance in middleware. Second, it presents a series of techniques and patterns that allow the design and implementation of safe, predictable, and highly efficient real-time middleware. Third, it provides a set of architectural and design patterns that application developers can use when designing real-time systems. Finally, it provides a methodology for evaluating the merits and benefits of real-time middleware. Empirical results are presented using that methodology for the techniques presented in this thesis. The methodology helps compare the performance and predictability of general, real-time middleware platforms

The status of music education in the public schools of Massachusetts as of the year 1948-1949

Thesis (Ed. M.)--Boston University, 195