Reconstruction of undersampled periodic signals

Originally presented as author's thesis (M.S.--Massachusetts Institute of Technology), 1986.Bibliography: p. 105-106.Supported in part by the Advanced Research Projects Agency monitored by ONR under contract no. N00014-81-K-0742 Supported in part by the National Science Foundation under grant ECS-8407285Anthony J. Silva

VIBRATION TRANSMISSIBILITY OF THE COFFEE FRUIT-PEDUNCLE SYSTEM: A FORCED VIBRATION STUDY OF HIGH FREQUENCY AIMING MECHANICAL HARVESTING

ABSTRACT Semi-mechanized and mechanized harvesting use machines that promote the transference of vibrational energy and impact to achieve the detachment of coffee fruits. The aim of this study was to evaluate the vibration transmissibility in coffee fruit-peduncle systems, using high-speed cameras, submitted to high frequency harmonic excitation in different combinations between frequency and amplitude of vibration, identifying working ranges suitable to perform selective harvesting. Vibration transmissibility was determined for the coffee fruit-peduncle systems, for the maturation stages unripe and ripe that were subjected to a sinusoidal harmonic displacement, in which the input parameters were frequency (35, 45 and 55 Hz) and peak-to-peak amplitude (3.5, 5.0 and 6.5 mm). An experiment was used to study the effect of frequency and amplitude on vibration transmissibility in a completely randomized design in a factorial scheme 3 x 3 x 2, with three replications. The frequency of 35 Hz, associated with the amplitudes 3.5-6.5 mm, was the one that most influenced the results of vibration transmissibility. For the frequency of 55 Hz and amplitude of 6.5 mm, in the ripe maturation stage, the vibration transmissibility was higher than 1.0, which could be a suitable combination for selective coffee harvesting

Asteroseismology and pulsation timing of the A-type stars observed by Kepler.

The A-type stars are arguably some of the most diverse stars found across the HR diagram, encompassing a wide range of physics, including rotation, pulsation, magnetic interactions, and chemical peculiarities. In this thesis, I develop a series of frameworks and tools to investigate a subset of the A-type stars: the delta Scuti and rapidly oscillating Ap (roAp) type stars, primarily using data from the Kepler and TESS space missions. I discuss the roAp stars within the context of the Kepler mission and identify six new members by exploiting irregularities in the sampling cadence. I then provide methods for the precise calculation of luminosities for A-type stars and apply them to the Kepler delta Scuti sample to improve the observational instability strip. I extend this work to a new class of young, high frequency delta Scuti stars discovered in the TESS data, which possess stable and regularly spaced modes, opening them up as potential candidates for mode identification via asteroseismology. I develop a framework for analysing delta Scuti stars in binary systems, through timing of their pulsations, and provide an open-source package to facilitate their analysis. Following this, I search for transits around the delta Scuti stars by iteratively subtracting their pulsations and identify three possible candidates in the Kepler data. Finally, I discuss the eclipsing binaries in the context of the inverse problem, and detail tested methods to rapidly obtain orbital parameters from the light curve with no prior knowledge

Bayesian techniques for astrophysical inference from gravitational-waves of compact binary coalescences: an application to the Third LIGO-Virgo-KAGRA observing run

A major challenge in gravitational-wave astrophysics is the interpretation of observations, which requires accurate inference of the astrophysical parameters and a rigorous statistical framework. The main focus of this thesis is the analysis of modelled gravitational-wave sources and its enhancement with machine learning and other statistical techniques. Bayesian statistics is at the base of gravitational-wave analysis and interpretation since each observation is unique and can often be assumed to be independent of all others. The unifying thread of this thesis is Bayes’s theorem: how it is routinely leveraged for gravitational-wave analysis, allowing much of the work presented here, and how its use can be extended to develop new analysis techniques. The most notable application of Bayesian statistics in the field is the parameter estimation of compact binary coalescence. Chapter 2 reports the work done to reproduce the first Gravitational-Wave Transients Catalogue (GWTC-1) with the Bayesian Inference Library: bilby. The rigorous comparison between previous GWTC-1 results and the one presented here allowed bilby’s specific tuning towards the gravitational-wave inference problem. Chapter 3, presents the author’s work related to the discovery of the first neutronstar black-hole (NSBH) mergers GW200105 and GW200115, where bilby was used to estimate the parameter of the observed sources. This chapter also illustrates the role of gravitational-wave observations in our understanding of the astrophysical origins of binary sources. Chapter 4 describes a novel effective likelihood method to quantitively compare astrophysical distributions inferred from gravitational-wave observations and distributions obtained with theoretical simulations. This method, which is driven by a Bayesian philosophy, is applied to a set of globular cluster simulations and real data from the third Gravitational-Wave Transients Catalogue (GWTC-3). Chapter 5, presents a novel density estimation tool for parameter estimation products from gravitational-wave observations, based on Gaussian Processes which are a Bayesian machine learning technique. This density estimation method was found to be advantageous over other traditional methods for several gravitational wave applications since we need both the accurate treatment of individual event samples, e.g. standard siren analysis, but also robust propagation of systematics when combining multiple observations, e.g. measure of systematic errors. Finally, Chapter 6 presents a study that makes use of bilby to re-analyse the binary neutron star (BNS) event GW190425, in light of its potential electromagnetic counterpart FRB20190425A, and makes use of a Gaussian Process density estimator to calculate the Bayesian odds of the claimed association. This work is extended by performing a standard siren measurement for GW190425 and its potential host galaxy to determine the value of the Hubble constant