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1. [CII] luminosity models and large-scale image cubes based on COSMOS 2020 and ALPINE-ALMA [CII] data back to the epoch of reionisation

   https://doi.org/10.1051/0004-6361/202450300  

   Clarke, J; Karoumpis, C; Riechers, D; Magnelli, B; Okada, Y; Dev, A; Nikola, T; Bertoldi, F (September 2024, Astronomy & Astrophysics)

   Aims.We have implemented a novel method to create simulated [CII] emission line intensity mapping (LIM) data cubes using COSMOS 2020 galaxy catalogue data. It allows us to provide solid lower limits for previous simulation-based model predictions and the expected signal strength of upcoming surveys. Methods.We applied [CII]158 μm luminosity models to COSMOS 2020 to create LIM cubes covering a 1.2 × 1.2deg²sky area. These models were derived using galaxy bulk property data from the ALPINE-ALMA survey over the redshift range of 4.4 < z < 5.9, while additional models were taken from the literature. The LIM cubes cover 3.42 < z < 3.87, 4.14 < z < 4.76, 5.34 < z < 6.31, and 6.75 < z < 8.27, matched to planned observations from the EoR-Spec module of the Prime-Cam instrument in the Fred Young Submillimeter Telescope (FYST). We also created predictions including additional galaxies below current detection limits by ‘extrapolating’ from the faint end of the COSMOS 2020 luminosity function, comparing these to predictions from the literature. In addition, we computed the signal-to-noise (S/N) ratios for the power spectra, using parameters from the planned FYST survey with predicted instrumental noise levels. Results.We find lower limits for the expected power spectrum using the likely incomplete empirical data: when normalised by 2π², the amplitudes atk = 1 Mpc⁻¹are 3.06 × 10⁷, 1.43 × 10⁷, 9.80 × 10⁵, 2.77 × 10⁵ (Jy sr⁻¹)²for the aforementioned redshift ranges. For the extrapolated sample, the power spectra are consistent with prior predictions, indicating that extrapolation is a viable method for creating mock LIM cubes. In this case, we expect a result of S/N> 1 when using FYST parameters. However, our high-redshift results remain inconclusive because of the poor completeness of COSMOS 2020 atz > 6.3. These predictions will be improved on the basis of future JWST data. 

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2. HETDEX Public Source Catalog 1—Stacking 50,000 Lyman Alpha Emitters ^∗

   https://doi.org/10.3847/1538-4357/ace4c2  

   Davis, Dustin; Gebhardt, Karl; Cooper, Erin Mentuch; Bowman, William P.; Garcia Castanheira, Barbara; Chisholm, John; Ciardullo, Robin; Fabricius, Maximilian; Farrow, Daniel J.; Finkelstein, Steven L.; et al (September 2023, The Astrophysical Journal)

   Abstract We describe the ensemble properties of the 1.9 <z< 3.5 Lyman alpha emitters (LAEs) found in the HETDEX survey’s first public data release, HETDEX Public Source Catalog 1. Stacking the low-resolution (R∼ 800) spectra greatly increases the signal-to-noise ratio (S/N), revealing spectral features otherwise hidden by noise, and we show that the stacked spectrum is representative of an average member of the set. The flux-limited, LyαS/N restricted stack of 50,000 HETDEX LAEs shows the ensemble biweightaveragez∼ 2.6 LAE to be a blue (UV continuum slope ∼ −2.4 andE(B – V)< 0.1), moderately bright (M_UV∼ −19.7) star-forming galaxy with strong Lyαemission (logL_Lyα∼ 42.8 andW_λ(Lyα) ∼ 114 Å), and potentially significant leakage of ionizing radiation. The rest-frame UV light is dominated by a young, metal-poor stellar population with an average age of 5–15 Myr and metallicity of 0.2–0.3Z_⊙. 

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3. Scattering Delay Mitigation in High-accuracy Pulsar Timing: Cyclic Spectroscopy Techniques

   https://doi.org/10.3847/1538-4357/acb6fd  

   Turner, Jacob E.; Stinebring, Daniel R.; McLaughlin, Maura A.; Archibald, Anne M.; Dolch, Timothy; Lynch, Ryan S. (February 2023, The Astrophysical Journal)

   Abstract We simulate scattering delays from the interstellar medium to examine the effectiveness of three estimators in recovering these delays in pulsar timing data. Two of these estimators use the more traditional process of fitting autocorrelation functions to pulsar dynamic spectra to extract scintillation bandwidths, while the third estimator uses the newer technique of cyclic spectroscopy on baseband pulsar data to recover the interstellar medium’s impulse response function. We find that either fitting a Lorentzian or Gaussian distribution to an autocorrelation function or recovering the impulse response function from the cyclic spectrum are, on average, accurate in recovering scattering delays, although autocorrelation function estimators have a large variance, even at high signal-to-noise ratio (S/N). We find that, given sufficient S/N, cyclic spectroscopy is more accurate than both Gaussian and Lorentzian fitting for recovering scattering delays at specific epochs, suggesting that cyclic spectroscopy is a superior method for scattering estimation in high-quality data. 

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4. Hyperfine group ratio: a recipe for deriving kinetic temperature from the ammonia inversion lines

   https://doi.org/10.1093/mnras/staa3059  

   Wang, Shen; Ren, Zhiyuan; Li, Di; Kauffmann, Jens; Zhang, Qizhou; Shi, Hui (October 2020, Monthly Notices of the Royal Astronomical Society)

   Although ammonia is a widely used interstellar thermometer, the estimation of its rotational and kinetic temperatures can be affected by the blended hyperfine components (HFCs). We have developed a new recipe, referred to as the hyperfine group ratio (HFGR), which utilizes only direct observables, namely the intensity ratios between the grouped HFCs. As tested on the model spectra, the empirical formulae in the HFGR can derive the rotational temperature (Trot) from the HFC group ratios in an unambiguous manner. We compared the HFGR with two other classical methods, intensity ratio and hyperfine fitting, based on both simulated spectra and real data. The HFGR has three major improvements. First, it does not require modelling the HFC or fitting the line profiles, so it is more robust against the effect of HFC blending. Second, the simulation-enabled empirical formulae are much faster than fitting the spectra over the parameter space, so both computer time and human time can be saved. Third, the statistical uncertainty of the temperature ΔTrot as a function of the signal-to-noise ratio (S/N) is a natural product of the HFGR recipe. The internal error of the HFGR is ΔTrot ≤ 0.5 K over a broad parameter space of rotational temperature (10-60 K), linewidth (0.3-4 km s-1) and optical depth (0-5). When there is spectral noise, the HFGR can also maintain a reasonable uncertainty level at ΔTrot ≤ 1.0 K when S/N > 4. 

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5. Spectral stacking of radio-interferometric data

   https://doi.org/10.1051/0004-6361/202346129  

   Neumann, Lukas; den Brok, Jakob S.; Bigiel, Frank; Leroy, Adam; Usero, Antonio; Barnes, Ashley T.; Bešlić, Ivana; Eibensteiner, Cosima; Held, Malena; Jiménez-Donaire, María J.; et al (July 2023, Astronomy & Astrophysics)

   Context.Mapping molecular line emission beyond the bright low-JCO transitions is still challenging in extragalactic studies, even with the latest generation of (sub-)millimetre interferometers, such as ALMA and NOEMA. Aims.We summarise and test a spectral stacking method that has been used in the literature to recover low-intensity molecular line emission, such as HCN(1−0), HCO⁺(1−0), and even fainter lines in external galaxies. The goal is to study the capabilities and limitations of the stacking technique when applied to imaged interferometric observations. Methods.The core idea of spectral stacking is to align spectra of the low S/N spectral lines to a known velocity field calculated from a higher S/N line expected to share the kinematics of the fainter line (e.g. CO(1−0) or 21 cm emission). Then these aligned spectra can be coherently averaged to produce potentially high S/N spectral stacks. Here we used imaged simulated interferometric and total power observations at different S/N levels, based on real CO observations. Results.For the combined interferometric and total power data, we find that the spectral stacking technique is capable of recovering the integrated intensities even at low S/N levels across most of the region where the high S/N prior is detected. However, when stacking interferometer-only data for low S/N emission, the stacks can miss up to 50% of the emission from the fainter line. Conclusions.A key result of this analysis is that the spectral stacking method is able to recover the true mean line intensities in low S/N cubes and to accurately measure the statistical significance of the recovered lines. To facilitate the application of this technique we provide a public Python package, called PYSTACKER. 

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