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Daniel Robins

Publications and source records attributed to Daniel Robins.

5 recordsLinked to original sources

Synchrotron and free-free mapping with simulated REACH observations between 50-170 MHz

Global 21cm experiments aim to detect the hydrogen 21cm signal by separating it from foreground emission that can be orders of magnitude brighter than the signal. REACH (the Radio Experiment for the Analysis of Cosmic Hydrogen) forward-models the sky by jointly fitting signal and foreground spectral parameters to an existing sky map. The fitted parameters yield spectrally constrained, absolutely calibrated maps of the radio sky across the full 50-170 MHz observing band, among the lowest continuous frequencies yet mapped. We assess REACH's ability to fit the 21cm signal and recover accurate foreground maps, using physically motivated foreground models of increasing complexity (starting from a pure synchrotron power law model, then introducing variable amplitudes, curvature, and a free-free component). We evaluate these models against simulated REACH observations of correspondingly complex foregrounds, based on the Global Sky Model and the Python Sky Model. To recover the 21cm signal, more complex datasets require correspondingly complex models, but this introduces degeneracies which limit accurate recovery of foreground parameters. Fitting a foreground with independent synchrotron and free-free emission enables component-separated sky mapping, which has applications beyond radio cosmology; synchrotron is well-recovered across the sky, but free-free recovery is limited. REACH is therefore capable of probing Galactic physics at uniquely low frequencies, alongside its primary goal of detecting the 21cm signal.

astro-ph.CO

Optimisation of calibration sources for global 21-cm experiments: the REACH case

The spin-flip 21-cm signal from the Cosmic Dawn and the Epoch of Reionization is an essential probe of the conditions that led to the formation of the first luminous objects in the early Universe. However, its detection remains a major challenge owing to its low strength compared to the bright foregrounds and the requirement of precise calibration of the instrument to prevent systematics that could hinder a detection or lead to false inferences. REACH (Radio Experiment for the Analysis of Cosmic Hydrogen) is a radiometer experiment designed to detect this sky-averaged signal in the frequency range of 50--130~MHz. Using a wide-beam antenna, REACH calibration relies on internal reference sources, covering a broad range of temperatures and reflection coefficients. The choice of type and number of calibrators used significantly influences the quality of the calibration. This work investigates these effects and introduces a novel method for selecting an optimal set of calibration sources. With an optimised set, we aim to reduce calibration time, thereby increasing sky integration time while preserving calibration accuracy. We explore two optimisation strategies: one applied across the full receiver band and another performed on a frequency-by-frequency basis. Finally, we demonstrate that, with a total calibration time comparable to the conventional full-calibrator set, an optimised set with fewer calibrators achieves approximately a $15~\%$ reduction in calibrated temperature noise and improved absolute calibration of the instrument. This has implications for better calibration strategies in similar radiometer experiments.

astro-ph.IM

Circuit Modeling for In Situ 21 cm Radiometer Calibration

Recent experiments in cosmology, particularly those aimed at detecting the faint, redshifted, global 21 cm hydrogen line (depth < ~200 mK, z > 7.5), have imposed stringent new requirements on radiometer calibration. In this work, we present a framework for circuit modeling and parameter inference to strengthen these calibration pipelines. This new approach enables in situ characterization of otherwise immeasurable systematics using physically motivated models. A combination of frequentist and Bayesian techniques are employed in a pipeline that supports iterative modeling, robust parameter estimation, and detailed uncertainty quantification. The framework is applied to the REACH telescope, where the precise correction of variations in the radio signal paths arising from component aging or environmental effects is critical. Circuit models of REACH's calibration sources are developed, with the goal of predicting source temperature corrections that are conventionally obtained from laboratory measurements. By fitting the models to measured data using a convolutional cost function, a strong agreement with RMS residuals no worse than -37 dB is obtained. However, Bayesian inference reveals that the resulting temperature corrections can have uncertainties on the order of 1 to 2 K, caused by reflection coefficient degeneracies, measurement noise, and errors in the models. To combat this, posteriors obtained from laboratory measurements are employed as updated priors, reducing correction uncertainties down to 75 mK. Ultimately, the framework provides a means of dynamically accounting for drift in system non-idealities over time, addressing the increasing precision demands of global 21 cm radio astronomy.

astro-ph.IM

Discovering neutron stars with LISA via measurements of orbital eccentricity in Galactic binaries

LISA will detect $\sim \! 10^4$ Galactic binaries, the majority being double white dwarfs. However, approximately $\sim \! 1 \textrm{--} 5 \%$ of these systems will contain neutron stars which, if they can be correctly identified, will provide new opportunities for studying binary evolution pathways involving mass reversal and supernovae as well as being promising targets for multi-messenger observations. Eccentricity, expected from neutron star natal kicks, will be a key identifying signature for binaries containing a neutron star. Eccentric binaries radiate at widely-spaced frequency harmonics that must first be identified as originating from a single source and then analysed coherently. A multi-harmonic heterodyning approach for this type of data analysis is used to perform Bayesian parameter estimation on a range of simulated eccentric LISA signals. This is used to: (i) investigate LISA's ability to measure orbital eccentricity and to quantify the minimum detectable eccentricity; (ii) demonstrate how eccentricity and periastron precession help to break the mass degeneracy allowing the individual component masses to be inferred, potentially confirming the presence of a neutron star; (iii) investigate the possibility of source misidentification when the individual harmonics of an eccentric binary masquerade as separate circular binaries; and (iv) investigate the possibility of source reclassification, where parameter estimation results of multiple circular analyses are combined in postprocessing to quickly infer the parameters of an eccentric source. The broader implications of this for the ongoing design of the LISA global fit are also discussed.

astro-ph.HE

Balotage in Argentina 2015, a sentiment analysis of tweets

Twitter social network contains a large amount of information generated by its users. That information is composed of opinions and comments that may reflect trends in social behavior. There is talk of trend when it is possible to identify opinions and comments geared towards the same shared by a lot of people direction. To determine if two or more written opinions share the same address, techniques Natural Language Processing (NLP) are used. This paper proposes a methodology for predicting reflected in Twitter from the use of sentiment analysis functions NLP based on social behaviors. The case study was selected the 2015 Presidential in Argentina, and a software architecture Big Data composed Vertica data base with the component called Pulse was used. Through the analysis it was possible to detect trends in voting intentions with regard to the presidential candidates, achieving greater accuracy in predicting that achieved with traditional systems surveys.

cs.IR