An official website of the United States government
Aims.Because of their limited angular resolution, far-infrared telescopes are usually affected by the confusion phenomenon. Since several galaxies can be located in the same instrumental beam, only the brightest objects emerge from the fluctuations caused by fainter sources. The PRobe far-Infrared Mission for Astrophysics imager (PRIMAger) will observe the mid- and far-infrared (25–235 μm) sky both in intensity and polarization. We aim to provide predictions of the confusion level and its consequences for future surveys. Methods.We produced simulated PRIMAger maps affected only by the confusion noise using the simulated infrared extragalactic sky (SIDES) semi-empirical simulation. We then estimated the confusion limit in these maps and extracted the sources using a basic blind extractor. By comparing the input galaxy catalog and the extracted source catalog, we derived various performance metrics as completeness, purity, and the accuracy of various measurements (e.g., the flux density in intensity and polarization or the polarization angle). Results.In intensity maps, we predict that the confusion limit increases rapidly with increasing wavelength (from 21 μJy at 25 μm to 46 mJy at 235 μm). The confusion limit in polarization maps is more than two orders of magnitude lower (from 0.03 mJy at 96 μm to 0.25 mJy at 235 μm). Both in intensity and polarization maps, the measured (polarized) flux density is dominated by the brightest galaxy in the beam, but other objects also contribute in intensity maps at longer wavelengths (∼30% at 235 μm). We also show that galaxy clustering has a mild impact on confusion in intensity maps (up to 25%), while it is negligible in polarization maps. In intensity maps, a basic blind extraction will be sufficient to detect galaxies at the knee of the luminosity function up toz ∼ 3 and 1011M⊙main-sequence galaxies up toz ∼ 5. In polarization for the most conservative sensitivity forecast (payload requirements), ∼200 galaxies can be detected up toz = 1.5 in two 1500 h surveys covering 1 deg2and 10 deg2. For a conservative sensitivity estimate, we expect ∼8000 detections up toz = 2.5, opening a totally new window on the high-zdust polarization. Finally, we show that intensity surveys at short wavelengths and polarization surveys at long wavelengths tend to reach confusion at similar depth. There is thus a strong synergy between them.
more »
« less
Overcoming confusion noise with hyperspectral imaging from PRIMAger
ABSTRACT The PRobe far-Infrared Mission for Astrophysics (PRIMA) concept aims to perform mapping with spectral coverage and sensitivities inaccessible to previous FIR space telescopes. PRIMA’s imaging instrument, PRIMAger, provides unique hyperspectral imaging simultaneously covering 25–235 µm. We synthesize images representing a deep, 1500 h deg−2 PRIMAger survey, with realistic instrumental and confusion noise. We demonstrate that we can construct catalogues of galaxies with a high purity (>95 per cent) at a source density of 42 k deg−2 using PRIMAger data alone. Using the XID+ deblending tool, we show that we measure fluxes with an accuracy better than 20 per cent to flux levels of 0.16, 0.80, 9.7, and 15 mJy at 47.4, 79.7, 172, and 235 µm, respectively. These are a factor of ∼2 and ∼3 fainter than the classical confusion limits for 72–96 and 126–235 µm, respectively. At $$1.5 \le z \le 2$$, we detect and accurately measure fluxes in 8–10 of the 10 channels covering 47–235 µm for sources with $$2 \lesssim \log ({\rm SFR}) \lesssim 2.5$$, a 0.5 dex improvement on what might be expected from the classical confusion limit. Recognizing that PRIMager will operate in a context where high-quality data will be available at other wavelengths, we investigate the benefits of introducing additional prior information. We show that by introducing even weak prior flux information when employing a higher source density catalogue (more than one source per beam), we can obtain accurate fluxes an order of magnitude below the classical confusion limit for 96–235 µm.
more »
« less
- Award ID(s):
- 2108140
- PAR ID:
- 10550050
- Publisher / Repository:
- OUP
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 532
- Issue:
- 2
- ISSN:
- 0035-8711
- Page Range / eLocation ID:
- 1966 to 1979
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)ABSTRACT We present a catalogue of 22 755 objects with slitless, optical, Hubble Space Telescope (HST) spectroscopy from the Grism Lens-Amplified Survey from Space (GLASS). The data cover ∼220 sq. arcmin to 7-orbit (∼10 ks) depth in 20 parallel pointings of the Advanced Camera for Survey’s G800L grism. The fields are located 6 arcmin away from 10 massive galaxy clusters in the HFF and CLASH footprints. 13 of the fields have ancillary HST imaging from these or other programs to facilitate a large number of applications, from studying metal distributions at z ∼ 0.5, to quasars at z ∼ 4, to the star formation histories of hundreds of galaxies in between. The spectroscopic catalogue has a median redshift of 〈z〉 = 0.60 with a median uncertainty of $$\Delta z / (1+z)\lesssim 2{{\ \rm per\ cent}}$$ at $$F814\mathit{ W}\lesssim 23$$ AB. Robust continuum detections reach a magnitude fainter. The 5 σ limiting line flux is $$f_{\rm lim}\approx 5\times 10^{-17}\rm ~erg~s^{-1}~cm^{-2}$$ and half of all sources have 50 per cent of pixels contaminated at ≲1 per cent. All sources have 1D and 2D spectra, line fluxes/uncertainties and identifications, redshift probability distributions, spectral models, and derived narrow-band emission-line maps from the Grism Redshift and Line Analysis tool (grizli). We provide other basic sample characterizations, show data examples, and describe sources and potential investigations of interest. All data and products will be available online along with software to facilitate their use.more » « less
-
Abstract Reionization leads to large spatial fluctuations in the intergalactic temperature that can persist well after its completion. We study the imprints of such fluctuations on the $$z$$ ∼ 5 Ly α forest flux power spectrum using a set of radiation-hydrodynamic simulations that model different reionization scenarios. We find that large-scale coherent temperature fluctuations bring $${\sim}20\text{--}60{{\ \rm per\ cent}}$$ extra power at k ∼ 0.002 s km−1, with the largest enhancements in the models where reionization is extended or ends the latest. On smaller scales (k ≳ 0.1 s km−1), we find that temperature fluctuations suppress power by $${\lesssim}10{{\ \rm per\ cent}}$$. We find that the shape of the power spectrum is mostly sensitive to the reionization mid-point rather than temperature fluctuations from reionization’s patchiness. However, for all of our models with reionization mid-points of $$z$$ ≤ 8 ($$z$$ ≤ 12), the shape differences are $${\lesssim}20{{\ \rm per\ cent}}$$ ($${\lesssim}40{{\ \rm per\ cent}}$$) because of a surprisingly well-matched cancellation between thermal broadening and pressure smoothing that occurs for realistic thermal histories. We also consider fluctuations in the ultraviolet background, finding their impact on the power spectrum to be much smaller than temperature fluctuations at k ≳ 0.01 s km−1. Furthermore, we compare our models to power spectrum measurements, finding that none of our models with reionization mid-points of $$z$$ < 8 is strongly preferred over another and that all of our models with mid-points of $$z$$ ≥ 8 are excluded at 2.5σ. Future measurements may be able to distinguish between viable reionization models if they can be performed at lower k or, alternatively, if the error bars on the high-k power can be reduced by a factor of 1.5.more » « less
-
ABSTRACT We present the results of a proof-of-concept experiment that demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in Hubble Space Telescope(HST) ultraviolet-optical imaging of nearby spiral galaxies ($$D\lesssim 20\, \textrm{Mpc}$$) in the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS)–HST survey. Given the relatively small nature of existing, human-labelled star cluster samples, we transfer the knowledge of state-of-the-art neural network models for real-object recognition to classify star clusters candidates into four morphological classes. We perform a series of experiments to determine the dependence of classification performance on neural network architecture (ResNet18 and VGG19-BN), training data sets curated by either a single expert or three astronomers, and the size of the images used for training. We find that the overall classification accuracies are not significantly affected by these choices. The networks are used to classify star cluster candidates in the PHANGS–HST galaxy NGC 1559, which was not included in the training samples. The resulting prediction accuracies are 70 per cent, 40 per cent, 40–50 per cent, and 50–70 per cent for class 1, 2, 3 star clusters, and class 4 non-clusters, respectively. This performance is competitive with consistency achieved in previously published human and automated quantitative classification of star cluster candidate samples (70–80 per cent, 40–50 per cent, 40–50 per cent, and 60–70 per cent). The methods introduced herein lay the foundations to automate classification for star clusters at scale, and exhibit the need to prepare a standardized data set of human-labelled star cluster classifications, agreed upon by a full range of experts in the field, to further improve the performance of the networks introduced in this study.more » « less
-
ABSTRACT Although stellar radii from asteroseismic scaling relations agree at the per cent level with independent estimates for main sequence and most first-ascent red giant branch (RGB) stars, the scaling relations over-predict radii at the tens of per cent level for the most luminous stars ($$R \gtrsim 30 \, \mathrm{R}_{\odot }$$). These evolved stars have significantly superadiabatic envelopes, and the extent of these regions increase with increasing radius. However, adiabaticity is assumed in the theoretical derivation of the scaling relations as well as in corrections to the large frequency separation. Here, we show that a part of the scaling relation radius inflation may arise from this assumption of adiabaticity. With a new reduction of Kepler asteroseismic data, we find that scaling relation radii and Gaia radii agree to within at least 2 per cent for stars with $$R \lesssim 30\, \mathrm{R}_{\odot }$$, when treated under the adiabatic assumption. The accuracy of scaling relation radii for stars with $$50\, \mathrm{R}_{\odot }\lesssim R \lesssim 100\, \mathrm{R}_{\odot }$$, however, is not better than $$10~{{\ \rm per \, cent}}-15~{{\ \rm per \, cent}}$$ using adiabatic large frequency separation corrections. We find that up to one third of this disagreement for stars with $$R \approx 100\, \mathrm{R}_{\odot }$$ could be caused by the adiabatic assumption, and that this adiabatic error increases with radius to reach 10 per cent at the tip of the RGB. We demonstrate that, unlike the solar case, the superadiabatic gradient remains large very deep in luminous stars. A large fraction of the acoustic cavity is also in the optically thin atmosphere. The observed discrepancies may therefore reflect the simplified treatment of convection and atmospheres.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/mnras/stae1539
