Enhancing Exoplanet Ephemerides by Leveraging Professional and Citizen Science Data: A Test Case with WASP-77 A b

We present an updated ephemeris, and physical parameters, for the exoplanet WASP-77 A b. In this effort, we combine 64 ground- and space-based transit observations, 6 space-based eclipse observations, and 32 radial velocity observations to produce this target´s most precise orbital solution to date aiding in the planning of James Webb Space Telescope and Ariel observations and atmospheric studies. We report a new orbital period of 1.360029395 ± 5.7 × 10−8 days, a new mid-transit time of 2459957.337860 ± 4.3 × 10−5 Barycentric Julian Date in the Barycentric Dynamical Timescale (BJDTDB) and a new mid-eclipse time of 2459956.658192 ± 6.7 × 10−5 BJDTDB. Furthermore, the methods presented in this study reduce the uncertainties in the planet´s mass 1.6654 ± 4.5 × 10−3MJup and orbital period 1.360029395 ± 5.7 × 10−8 days by factors of 15.1 and 10.9, respectively. Through a joint fit analysis comparison of transit data taken by space-based and citizen science-led initiatives, our study demonstrates the power of including data collected by citizen scientists compared to a fit of the space-based data alone. Additionally, by including a vast array of citizen science data from ExoClock, Exoplanet Transit Database, and Exoplanet Watch, we can increase our observational baseline and thus acquire better constraints on the forward propagation of our ephemeris than what is achievable with Transiting Exoplanet Survey Satellite data alone.Fil: Noguer, Federico R.. Arizona State University; Estados UnidosFil: Corley, Suber. National Aeronautics and Space Administration; Estados UnidosFil: Pearson, Kyle A.. California Institute Of Technology; Estados UnidosFil: Zellem, Robert T.. California Institute Of Technology; Estados UnidosFil: Simon, Molly N.. Arizona State University; Estados UnidosFil: Burt, Jennifer A.. California Institute Of Technology; Estados UnidosFil: Huckabee, Isabela. California Institute Of Technology; Estados UnidosFil: August, Prune C.. Technical University of Denmark; DinamarcaFil: Weiner Mansfield, Megan. University of Arizona; Estados UnidosFil: Dalba, Paul A.. University of California; Estados UnidosFil: Smith, Peter C. B.. Arizona State University; Estados UnidosFil: Banks, Timothy. Harper College; Estados UnidosFil: Bell, Ira. Arizona State University; Estados UnidosFil: Daniel, Dominique. ExoClock Project Citizen Scientist; Estados UnidosFil: Dawson, Lindsay. Thomas More University; Estados UnidosFil: De Mula, Jesús. Exoplanet Watch Citizen Scientist Contributor; Estados UnidosFil: Deldem, Marc. ExoClock Project Citizen Scientist Contributor; Estados UnidosFil: Deligeorgopoulos, Dimitrios. ExoClock Project Citizen Scientist Contributor; Estados UnidosFil: Di Sisto, Romina Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Dymock, Roger. British Astronomical Association; Reino UnidoFil: Evans, Phil. El Sauce Observatory; ChileFil: Follero, Giulio. INAF. Osservatorio Astronomico di Capodimonte; ItaliaFil: Fowler, Martin J. F.. Les Rocquettes Observatory and Exoplanet Factory; Reino UnidoFil: Fernandez Lajus, Eduardo Eusebio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Hamrick, Alex. Stanford Online High School; Estados UnidosFil: Iannascoli, Nicoletta. INAF. Osservatorio Astronomico di Capodimonte; ItaliaFil: Kovacs, Andre O.. Exoplanet Watch Citizen Scientist Contributor; Estados UnidosFil: Kulh, Denis Henrique. Alfa Crucis; Estados UnidosFil: Lopresti, Claudio. ExoClock Project Citizen Scientist Contributor; Estados UnidosFil: Marino, Antonio. INAF. Osservatorio Astronomico di Capodimonte; Itali

RAFT aqueous dispersion polymerization yields poly(ethylene glycol)-based diblock copolymer nano-objects with predictable single phase morphologies

A poly(ethylene glycol) (PEG) macromolecular chain transfer agent (macro-CTA) is prepared in high yield (>95%) with 97% dithiobenzoate chain-end functionality in a three-step synthesis starting from a monohydroxy PEG113 precursor. This PEG113-dithiobenzoate is then used for the reversible addition-fragmentation chain transfer (RAFT) aqueous dispersion polymerization of 2-hydroxypropyl methacrylate (HPMA). Polymerizations conducted under optimized conditions at 50 °C led to high conversions as judged by 1H NMR spectroscopy and relatively low diblock copolymer polydispersities (Mw/Mn < 1.25) as judged by GPC. The latter technique also indicated good blocking efficiencies, since there was minimal PEG113 macro-CTA contamination. Systematic variation of the mean degree of polymerization of the core-forming PHPMA block allowed PEG113-PHPMAx diblock copolymer spheres, worms, or vesicles to be prepared at up to 17.5% w/w solids, as judged by dynamic light scattering and transmission electron microscopy studies. Small-angle X-ray scattering (SAXS) analysis revealed that more exotic oligolamellar vesicles were observed at 20% w/w solids when targeting highly asymmetric diblock compositions. Detailed analysis of SAXS curves indicated that the mean number of membranes per oligolamellar vesicle is approximately three. A PEG 113-PHPMAx phase diagram was constructed to enable the reproducible targeting of pure phases, as opposed to mixed morphologies (e.g., spheres plus worms or worms plus vesicles). This new RAFT PISA formulation is expected to be important for the rational and efficient synthesis of a wide range of biocompatible, thermo-responsive PEGylated diblock copolymer nano-objects for various biomedical applications

ExoClock Project III: 450 new exoplanet ephemerides from ground and space observations

The ExoClock project has been created with the aim of increasing the efficiency of the Ariel mission. It will achieve this by continuously monitoring and updating the ephemerides of Ariel candidates over an extended period, in order to produce a consistent catalogue of reliable and precise ephemerides. This work presents a homogenous catalogue of updated ephemerides for 450 planets, generated by the integration of $\sim$18000 data points from multiple sources. These sources include observations from ground-based telescopes (ExoClock network and ETD), mid-time values from the literature and light-curves from space telescopes (Kepler/K2 and TESS). With all the above, we manage to collect observations for half of the post-discovery years (median), with data that have a median uncertainty less than one minute. In comparison with literature, the ephemerides generated by the project are more precise and less biased. More than 40\% of the initial literature ephemerides had to be updated to reach the goals of the project, as they were either of low precision or drifting. Moreover, the integrated approach of the project enables both the monitoring of the majority of the Ariel candidates (95\%), and also the identification of missing data. The dedicated ExoClock network effectively supports this task by contributing additional observations when a gap in the data is identified. These results highlight the need for continuous monitoring to increase the observing coverage of the candidate planets. Finally, the extended observing coverage of planets allows us to detect trends (TTVs - Transit Timing Variations) for a sample of 19 planets. All products, data, and codes used in this work are open and accessible to the wider scientific community.Comment: Recommended for publication to ApJS (reviewer's comments implemented). Main body: 13 pages, total: 77 pages, 7 figures, 7 tables. Data available at http://doi.org/10.17605/OSF.IO/P298

ExoClock Project. III. 450 New Exoplanet Ephemerides from Ground and Space Observations

The ExoClock project has been created to increase the efficiency of the Ariel mission. It will achieve this by continuously monitoring and updating the ephemerides of Ariel candidates, in order to produce a consistent catalog of reliable and precise ephemerides. This work presents a homogenous catalog of updated ephemerides for 450 planets, generated by the integration of ∼18,000 data points from multiple sources. These sources include observations from ground-based telescopes (the ExoClock network and the Exoplanet Transit Database), midtime values from the literature, and light curves from space telescopes (Kepler, K2, and TESS). With all the above, we manage to collect observations for half of the postdiscovery years (median), with data that have a median uncertainty less than 1 minute. In comparison with the literature, the ephemerides generated by the project are more precise and less biased. More than 40% of the initial literature ephemerides had to be updated to reach the goals of the project, as they were either of low precision or drifting. Moreover, the integrated approach of the project enables both the monitoring of the majority of the Ariel candidates (95%), and also the identification of missing data. These results highlight the need for continuous monitoring to increase the observing coverage of the candidate planets. Finally, the extended observing coverage of planets allows us to detect trends (transit-timing variations) for a sample of 19 planets. All the products, data, and codes used in this work are open and accessible to the wider scientific community

Optimal policy for labeling training samples

Confirming the labels of automatically classified patterns is generally faster than entering new labels or correcting incorrect labels. Most labels assigned by a classifier, even if trained only on relatively few pre-labeled patterns, are correct. Therefore the overall cost of human labeling can be decreased by interspersing labeling and classification. Given a parameterized model of the error rate as an inverse power law function of the size of the training set, the optimal splits can be computed rapidly. Projected savings in operator time are over 60 % for a range of empirical error functions for hand-printed digit classification with ten different classifiers