A PSF-based Approach to TESS High quality data Of Stellar clusters (PATHOS) – II. Search for exoplanets in open clusters of the Southern ecliptic hemisphere and their frequency

ABSTRACT The scope of the project ‘A PSF-based Approach to TESS High Quality data Of Stellar clusters’ (PATHOS) is the extraction and analysis of high-precision light curves of stars in stellar clusters and young associations for the identification of candidate exoplanets and variable stars. The cutting-edge tools used in this project allow us to measure the real flux of stars in dense fields, minimizing the effects due to contamination by neighbour sources. We extracted about 200 000 light curves of stars in 645 open clusters located in the Southern ecliptic hemisphere and observed by TESS during the first year of its mission. We searched for transiting signals and we found 33 objects of interest, 11 of which are strong candidate exoplanets. Because of the limited SNR, we did not find any Earth or super-Earth. We identified two Neptune-size planets orbiting stars with $R_{\star }\lt 1.5\, \mathrm{\it R}_{\odot }$, implying a frequency $f_{\star }=1.34 \pm 0.95\, {{\ \rm per\ cent}}$, consistent with the frequency around field stars. The seven Jupiter candidates around stars with $R_{\star }\lt \, 1.5\, \mathrm{\it R}_{\odot }$ imply a frequency $f_{\star }=0.19\pm 0.07\, {{\ \rm per\ cent}}$, which is smaller than in the field. A more complete estimate of the survey completeness and false positive rate is needed to confirm these results. Light curves used in this work will be made available to the astronomical community on the Mikulski Archive for Space Telescope under the project PATHOS.

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A PSF-based Approach to TESS High quality data Of Stellar clusters (PATHOS) – I. Search for exoplanets and variable stars in the field of 47 Tuc

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stz2878 ◽

2019 ◽

Vol 490 (3) ◽

pp. 3806-3823 ◽

Cited By ~ 6

Author(s):

D Nardiello ◽

L Borsato ◽

G Piotto ◽

L S Colombo ◽

E E Manthopoulou ◽

...

Keyword(s):

High Precision ◽

Variable Stars ◽

Eclipsing Binaries ◽

Light Curves ◽

Quality Data ◽

Stellar Clusters ◽

High Quality ◽

High Quality Data ◽

Stellar Cluster ◽

Crowded Environments

ABSTRACT The TESS mission will survey ∼85 per cent of the sky, giving us the opportunity of extracting high-precision light curves of millions of stars, including stellar cluster members. In this work, we present our project ‘A PSF-based Approach to TESS High quality data Of Stellar clusters’ (PATHOS), aimed at searching and characterize candidate exoplanets and variable stars in stellar clusters using our innovative method for the extraction of high-precision light curves of stars located in crowded environments. Our technique of light-curve extraction involves the use of empirical point spread functions (PSFs), an input catalogue and neighbour-subtraction. The PSF-based approach allows us to minimize the dilution effects in crowded environments and to extract high-precision photometry for stars in the faint regime (G > 13). For this pilot project, we extracted, corrected, and analysed the light curves of 16 641 stars located in a dense region centred on the globular cluster 47 Tuc. We were able to reach the TESS magnitude T ∼ 16.5 with a photometric precision of ${\sim} 1{{\ \rm per\ cent}}$ on the 6.5-h time-scale; in the bright regime we were able to detect transits with depth of ∼34 parts per million. We searched for variables and candidate transiting exoplanets. Our pipeline detected one planetary candidate orbiting a main-sequence star in the Galactic field. We analysed the period–luminosity distribution for red-giant stars of 47 Tuc and the eclipsing binaries in the field. Light curves are uploaded on the Mikulski Archive for Space Telescopes under the project PATHOS.

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A PSF-based Approach to TESS High quality data Of Stellar clusters (PATHOS) – III. Exploring the properties of young associations through their variables, dippers, and candidate exoplanets

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa2745 ◽

2020 ◽

Vol 498 (4) ◽

pp. 5972-5989

Author(s):

D Nardiello

Keyword(s):

Variable Stars ◽

Open Clusters ◽

Light Curves ◽

Quality Data ◽

Stellar Systems ◽

Satellite Mission ◽

Open Clusters And Associations ◽

Star Forming ◽

Star Forming Regions ◽

Strong Candidate

ABSTRACT Young associations in star-forming regions are stellar systems that allow us to understand the mechanisms that characterize the stars in their early life and what happens around them. In particular, the analysis of the discs and of the exoplanets around young stars allows us to know the key processes that prevail in their evolution and understand the properties of the exoplanets orbiting older stars. The Transiting Exoplanet Survey Satellite mission is giving us the opportunity to extract and analyse the light curves of association members with high accuracy, but the crowding that affects these regions makes difficult the light curve extraction. In the PATHOS project, cutting-edge tools are used to extract high-precision light curves and identify variable stars and transiting exoplanets in open clusters and associations. In this work, I analysed the light curves of stars in five young (≲10 Myr) associations, searching for variables and candidate exoplanets. Using the rotational periods of the association members, I constrained the ages of the five stellar systems (∼2–10 Myr). I searched for dippers, and I investigated the properties of the dust that forms the circumstellar discs. Finally, I searched for transiting signals, finding six strong candidate exoplanets. No candidates with radius RP ≲ 0.9 RJ have been detected, in agreement with the expectations. The frequency of giant planets resulted to be ∼2–3 per cent, higher than that expected for field stars (≲ 1 per cent); the low statistic makes this conclusion not strong, and new investigations on young objects are mandatory to confirm this result.

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Asteroseismology in Open Clusters

International Astronomical Union Colloquium ◽

10.1017/s0252921100037337 ◽

1995 ◽

Vol 155 ◽

pp. 327-328 ◽

Cited By ~ 1

Author(s):

S. Frandsen ◽

M. Viskum ◽

M.M. Hernandéz ◽

J.A. Belmonte

Keyword(s):

Time Series ◽

Stellar Evolution ◽

Open Clusters ◽

Photometric Data ◽

Quality Data ◽

High Quality ◽

High Quality Data ◽

Scuti Stars ◽

The Eu

Within two groups or networks we are trying to build the observational fundamentals for better tests of stellar evolution. The first group is STACC (Small Telescope Array with CCD Cameras) and the second the EU HCM program ANTENA (involving institutes in Spain, France and Denmark).The first information needed is photometric data. Colour-Luminosity diagrams and time series photometry must be obtained. The time series require extensive campaigns in order to give the high quality data needed for asteroseismology. Ideally one should have time series of several quantities (see Balona & Stobie 1979, Mantegazza et al. 1994).The second type of observations is of spectroscopic nature. It is needed to ascertain membership of the stars in a given cluster and to check binarity. Also rotational velocities must be observed to help the attempt to identify the modes in 6 Scuti stars. Finally some information about metallicity and peculiarity is required.

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Collecting High-Quality Data

10.1093/oso/9780199366088.003.0007 ◽

2018 ◽

Author(s):

Mary Kay Gugerty ◽

Dean Karlan

Keyword(s):

Data Collection ◽

Social Desirability ◽

Measurement Errors ◽

Monitoring And Evaluation ◽

Quality Data ◽

Social Desirability Bias ◽

High Quality ◽

High Quality Data ◽

Evaluation Systems ◽

Demand Effect

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

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Developmental Impacts of Remittances on Migrant-Sending Households: Micro-Level Evidence from Punjab, Pakistan

Journal of South Asian Development ◽

10.1177/0973174119887302 ◽

2019 ◽

Vol 14 (3) ◽

pp. 338-366

Author(s):

Kashif Imran ◽

Evelyn S. Devadason ◽

Cheong Kee Cheok

Keyword(s):

Human Development ◽

Human Development Index ◽

Quality Data ◽

High Quality ◽

High Quality Data ◽

Development Index ◽

Policy Interventions ◽

Education And Health ◽

Micro Level ◽

The Government

This article analyzes the overall and type of developmental impacts of remittances for migrant-sending households (HHs) in districts of Punjab, Pakistan. For this purpose, an HH-based human development index is constructed based on the dimensions of education, health and housing, with a view to enrich insights into interactions between remittances and HH development. Using high-quality data from a HH micro-survey for Punjab, the study finds that most migrant-sending HHs are better off than the HHs without this stream of income. More importantly, migrant HHs have significantly higher development in terms of housing in most districts of Punjab relative to non-migrant HHs. Thus, the government would need policy interventions focusing on housing to address inequalities in human development at the district-HH level, and subsequently balance its current focus on the provision of education and health.

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Capturing sexual assault data: An information system designed by forensic clinicians and healthcare researchers

Health Information Management Journal ◽

10.1177/1833358316687575 ◽

2017 ◽

Vol 47 (1) ◽

pp. 46-55 ◽

Cited By ~ 1

Author(s):

S Aqif Mukhtar ◽

Debbie A Smith ◽

Maureen A Phillips ◽

Maire C Kelly ◽

Renate R Zilkens ◽

...

Keyword(s):

Information System ◽

Sexual Assault ◽

Data Management ◽

Sexual Violence ◽

Western Australia ◽

Management System ◽

Data Management System ◽

Quality Data ◽

High Quality ◽

High Quality Data

Background: The Sexual Assault Resource Center (SARC) in Perth, Western Australia provides free 24-hour medical, forensic, and counseling services to persons aged over 13 years following sexual assault. Objective: The aim of this research was to design a data management system that maintains accurate quality information on all sexual assault cases referred to SARC, facilitating audit and peer-reviewed research. Methods: The work to develop SARC Medical Services Clinical Information System (SARC-MSCIS) took place during 2007–2009 as a collaboration between SARC and Curtin University, Perth, Western Australia. Patient demographics, assault details, including injury documentation, and counseling sessions were identified as core data sections. A user authentication system was set up for data security. Data quality checks were incorporated to ensure high-quality data. Results: An SARC-MSCIS was developed containing three core data sections having 427 data elements to capture patient’s data. Development of the SARC-MSCIS has resulted in comprehensive capacity to support sexual assault research. Four additional projects are underway to explore both the public health and criminal justice considerations in responding to sexual violence. The data showed that 1,933 sexual assault episodes had occurred among 1881 patients between January 1, 2009 and December 31, 2015. Sexual assault patients knew the assailant as a friend, carer, acquaintance, relative, partner, or ex-partner in 70% of cases, with 16% assailants being a stranger to the patient. Conclusion: This project has resulted in the development of a high-quality data management system to maintain information for medical and forensic services offered by SARC. This system has also proven to be a reliable resource enabling research in the area of sexual violence.

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We Need High Quality Data in Our Diversity Articles

Academic Radiology ◽

10.1016/j.acra.2020.11.029 ◽

2021 ◽

Author(s):

Daniel B. Chonde ◽

Seifu J. Chonde

Keyword(s):

Quality Data ◽

High Quality ◽

High Quality Data

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Fooled by Performance Randomness: Overrewarding Luck

Review of Economics and Statistics ◽

10.1162/rest_a_00783 ◽

2019 ◽

Vol 101 (4) ◽

pp. 658-666 ◽

Cited By ~ 5

Author(s):

Romain Gauriot ◽

Lionel Page

Keyword(s):

Causal Effect ◽

Experimental Situation ◽

Quality Data ◽

High Quality ◽

High Quality Data ◽

Economic Organizations ◽

Quasi Experimental ◽

Similar Location ◽

Do So

We provide evidence of a violation of the informativeness principle whereby lucky successes are overly rewarded. We isolate a quasi-experimental situation where the success of an agent is as good as random. To do so, we use high-quality data on football (soccer) matches and select shots on goal that landed on the goal posts. Using nonscoring shots, taken from a similar location on the pitch, as counterfactuals to scoring shots, we estimate the causal effect of a lucky success (goal) on the evaluation of the player's performance. We find clear evidence that luck is overly influencing managers' decisions and evaluators' ratings. Our results suggest that this phenomenon is likely to be widespread in economic organizations.

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R factors in Rietveld analysis: How good is good enough?

Powder Diffraction ◽

10.1154/1.2179804 ◽

2006 ◽

Vol 21 (1) ◽

pp. 67-70 ◽

Cited By ~ 508

Author(s):

Brian H. Toby

Keyword(s):

Rietveld Analysis ◽

Poor Quality ◽

Quality Data ◽

High Quality ◽

High Quality Data ◽

Poor Quality Data ◽

Error Index ◽

R Factors ◽

Very High

The definitions for important Rietveld error indices are defined and discussed. It is shown that while smaller error index values indicate a better fit of a model to the data, wrong models with poor quality data may exhibit smaller values error index values than some superb models with very high quality data.

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