Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDisentangling Atmospheric Compositions of K2-18 b with Next Generation Facilities
58
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Recent analysis of the planet K2-18b has shown the presence of water vapour in its atmosphere. While the H2O detection is significant, the Hubble Space Telescope (HST) WFC3 spectrum suggests three possible solutions of very different nature which can equally match the data. The three solutions are a primary cloudy atmosphere with traces of water vapour (cloudy sub-Neptune), a secondary atmosphere with a substantial amount (up to 50% Volume Mixing Ratio) of H2O (icy/water world) and/or an undetectable gas such as N2 (super-Earth). Additionally, the atmospheric pressure and the possible presence of a liquid/solid surface cannot be investigated with currently available observations. In this paper we used the best fit parameters from Tsiaras et al. (2019) to build James Webb Space Telescope (JWST) and Ariel simulations of the three scenarios. We have investigated 18 retrieval cases, which encompass the three scenarios and different observational strategies with the two observatories. Retrieval results show that twenty combined transits should be enough for the Ariel mission to disentangle the three scenarios, while JWST would require only two transits if combining NIRISS and NIRSpec data. This makes K2-18b an ideal target for atmospheric follow-ups by both facilities and highlights the capabilities of the next generation of space-based infrared observatories to provide a complete picture of low mass planets.
rate research
Read More
In their Letter, Tsiaras et al.$^1$ reported the detection of water vapour in the atmosphere of K2-18 b, an exoplanet of 7 to 10 Earth masses located in the habitable zone of an M-dwarf star. The detection is based on an absorption feature seen at 1.4 $mu$m in observations of the transiting exoplanet with the Hubble Space Telescope/Wide Field Camera 3. We have simulated the mean temperature structure and composition of K2-18b using a radiative-convective equilibrium model$^{2-4}$ and we present here the corresponding transit spectroscopy calculations. We argue that the reported absorption is most likely due to methane, a gas expected to be abundant in the hydrogen-helium atmosphere of cold sub-Neptunes. More generally, we show that the 1.4-$mu$m absorption seen in transit spectra is not diagnostic of the presence of water vapour for sub-Neptunes having an effective temperature less than 600 K and that water vapour dominates over methane at this wavelength only at larger temperatures.
High-redshift Gamma-Ray Bursts (GRBs) beyond redshift $sim6$ are potentially powerful tools to probe the distant early Universe. Their detections in large numbers and at truly high redshifts call for the next generation of high-energy wide-field instruments with unprecedented sensitivity at least one order of magnitude higher than the ones currently in orbit. On the other hand, follow-up observations of the afterglows of high-redshift GRBs and identification of their host galaxies, which would be difficult for the currently operating telescopes, require new, extremely large facilities of at multi-wavelengths. This chapter describes future experiments that are expected to advance this exciting field, both being currently built and being proposed. The legacy of Swift will be continued by SVOM, which is equipped with a set of space-based multi-wavelength instruments as well as and a ground segment including a wide angle camera and two follow-up telescopes. The established Lobster-eye X-ray focusing optics provides a promising technology for the detection of faint GRBs at very large distances, based on which the {THESEUS}, {Einstein Probe} and other mission concepts have been proposed. Follow-up observations and exploration of the reionization era will be enabled by large facilities such as {SKA} in the radio, the 30m class telescopes in the optical/near-IR, and the space-borne {WFIRST} and {JWST} in the optical/near-IR/mid-IR. In addition, the X-ray and $gamma$-ray polarization experiment POLAR is also introduced.
We describe the Next Generation Transit Survey (NGTS), which is a ground-based project searching for transiting exoplanets orbiting bright stars. NGTS builds on the legacy of previous surveys, most notably WASP, and is designed to achieve higher phot
ometric precision and hence find smaller planets than have previously been detected from the ground. It also operates in red light, maximising sensitivity to late K and early M dwarf stars. The survey specifications call for photometric precision of 0.1 per cent in red light over an instantaneous field of view of 100 square degrees, enabling the detection of Neptune-sized exoplanets around Sun-like stars and super-Earths around M dwarfs. The survey is carried out with a purpose-built facility at Cerro Paranal, Chile, which is the premier site of the European Southern Observatory (ESO). An array of twelve 20cm f/2.8 telescopes fitted with back-illuminated deep-depletion CCD cameras are used to survey fields intensively at intermediate Galactic latitudes. The instrument is also ideally suited to ground-based photometric follow-up of exoplanet candidates from space telescopes such as TESS, Gaia and PLATO. We present observations that combine precise autoguiding and the superb observing conditions at Paranal to provide routine photometric precision of 0.1 per cent in 1 hour for stars with I-band magnitudes brighter than 13. We describe the instrument and data analysis methods as well as the status of the survey, which achieved first light in 2015 and began full survey operations in 2016. NGTS data will be made publicly available through the ESO archive.
Vetting of exoplanet candidates in transit surveys is a manual process, which suffers from a large number of false positives and a lack of consistency. Previous work has shown that Convolutional Neural Networks (CNN) provide an efficient solution to these problems. Here, we apply a CNN to classify planet candidates from the Next Generation Transit Survey (NGTS). For training datasets we compare both real data with injected planetary transits and fully-simulated data, as well as how their different compositions affect network performance. We show that fewer hand labelled lightcurves can be utilised, while still achieving competitive results. With our best model, we achieve an AUC (area under the curve) score of $(95.6pm{0.2})%$ and an accuracy of $(88.5pm{0.3})%$ on our unseen test data, as well as $(76.5pm{0.4})%$ and $(74.6pm{1.1})%$ in comparison to our existing manual classifications. The neural network recovers 13 out of 14 confirmed planets observed by NGTS, with high probability. We use simulated data to show that the overall network performance is resilient to mislabelling of the training dataset, a problem that might arise due to unidentified, low signal-to-noise transits. Using a CNN, the time required for vetting can be reduced by half, while still recovering the vast majority of manually flagged candidates. In addition, we identify many new candidates with high probabilities which were not flagged by human vetters.
Gamma-ray Bursts (GRB) were discovered by satellite-based detectors as powerful sources of transient $gamma$-ray emission. The Fermi satellite detected an increasing number of these events with its dedicated Gamma-ray Burst Monitor (GBM), some of which were associated with high energy photons $(E > 10, mathrm{GeV})$, by the Large Area Telescope (LAT). More recently, follow-up observations by Cherenkov telescopes detected very high energy emission $(E > 100, mathrm{GeV})$ from GRBs, opening up a new observational window with implications on the interpretation of their central engines and on the propagation of very energetic photons across the Universe. Here, we use the data published in the 2nd Fermi-LAT Gamma Ray Burst Catalogue to characterise the duration, luminosity, redshift and light curve of the high energy GRB emission. We extrapolate these properties to the very high energy domain, comparing the results with available observations and with the potential of future instruments. We use observed and simulated GRB populations to estimate the chances of detection with wide-field ground-based $gamma$-ray instruments. Our analysis aims to evaluate the opportunities of the Southern Wide-field-of-view Gamma-ray Observatory (SWGO), to be installed in the Southern Hemisphere, to complement CTA. We show that a low-energy observing threshold $(E_{low} < 200, mathrm{GeV})$, with good point source sensitivity $(F_{lim} approx 10^{-11}, mathrm{erg, cm^{-2}, s^{-1}}$ in $1, mathrm{yr})$, are optimal requirements to work as a GRB trigger facility and to probe the burst spectral properties down to time scales as short as $10, mathrm{s}$, accessing a time domain that will not be available to IACT instruments.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
