Marta Spinelli

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Spinelli

First Name

Marta

ORCID

0000-0003-0148-3254

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Publications 1 - 10 of 11

Measurements of the diffuse Galactic synchrotron spectral index and curvature from MeerKLASS pilot data
Irfan, Melis O.; Bull, Philip; Santos, Mario G.; et al. (2022)
Monthly Notices of the Royal Astronomical Society
21 cm intensity mapping experiments are bringing an influx of high spectral resolution observational data in the similar to 100 MHz1 GHz regime. We use pilot 971-1075 MHz data from MeerKAT in single-dish mode, recently used to test the calibration and data reduction scheme of the upcoming MeerKLASS survey, to probe the spectral index of diffuse synchrotron emission below 1 GHz within 145 degrees < alpha < 180 degrees, -1 degrees < delta < 8 degrees. Through comparisons with data from the OVRO Long Wavelength Array and the Maipu and MU surveys, we find an average spectral index of -2.75 < beta < -2.71 between 45 and 1055 MHz. By fitting for spectral curvature with a spectral index of the form beta + c ln(nu/73 MHz), we measure beta = -2.55 +/- 0.13 and c = -0.12 +/- 0.05 within our target field. Our results are in good agreement (within 1s) with existing measurements from experiments such as ARCADE2 and EDGES. These results show the calibration accuracy of current data and demonstrate that MeerKLASS will also be capable of achieving a secondary science goal of probing the interstellar medium.
Constraining beyond ΛCDM models with 21cm intensity mapping forecasted observations combined with latest CMB data
Berti, Maria; Spinelli, Marta; Haridasu, Balakrishna S.; et al. (2022)
Journal of Cosmology and Astroparticle Physics
We explore constraints on dark energy and modified gravity with forecasted 21cm intensity mapping measurements using the Effective Field Theory approach. We construct a realistic mock data set forecasting a low redshift 21cm signal power spectrum P₂₁(z,k) measurement from the MeerKAT radio-telescope. We compute constraints on cosmological and model parameters through Monte-Carlo Markov-Chain techniques, testing both the constraining power of P₂₁(k) alone and its effect when combined with the latest Planck 2018 CMB data. We complement our analysis by testing the effects of tomography from an ideal mock data set of observations in multiple redshift bins. We conduct our analysis numerically with the codes EFTCAMB/EFTCosmoMC, which we extend by implementing a likelihood module fully integrated with the original codes. We find that adding P₂₁(k) to CMB data provides significantly tighter constraints on Ω꜀h² and H₀, with a reduction of the error with respect to Planck results at the level of more than 60%. For the parameters describing beyond ΛCDM theories, we observe a reduction in the error with respect to the Planck constraints at the level of ≲ 10%. The improvement increases up to ∼ 35% when we constrain the parameters using ideal, tomographic mock observations. We conclude that the power spectrum of the 21cm signal is sensitive to variations of the parameters describing the examined beyond ΛCDM models and, thus, P₂₁(k) observations could help to constrain dark energy. The constraining power on such theories is improved significantly by tomography.
Gravitational waves × HI intensity mapping: cosmological and astrophysical applications
Scelfo, Giulio; Spinelli, Marta; Raccanelli, Alvise; et al. (2022)
Journal of Cosmology and Astroparticle Physics
Two of the most rapidly growing observables in cosmology and astrophysics are gravitational waves (GW) and the neutral hydrogen (HI) distribution. In this work, we investigate the cross-correlation between resolved gravitational wave detections and HI signal from intensity mapping (IM) experiments. By using a tomographic approach with angular power spectra, including all projection effects, we explore possible applications of the combination of the Einstein Telescope and the SKAO intensity mapping surveys. We focus on three main topics: (i) statistical inference of the observed redshift distribution of GWs; (ii) constraints on dynamical dark energy models as an example of cosmological studies; (iii) determination of the nature of the progenitors of merging binary black holes, distinguishing between primordial and astrophysical origin. Our results show that: (i) the GW redshift distribution can be calibrated with good accuracy at low redshifts, without any assumptions on cosmology or astrophysics, potentially providing a way to probe astrophysical and cosmological models; (ii) the constrains on the dynamical dark energy parameters are competitive with IM-only experiments, in a complementary way and potentially with less systematics; (iii) it will be possible to detect a relatively small abundance of primordial black holes within the gravitational waves from resolved mergers. Our results extend towards GW × IM the promising field of multi-tracing cosmology and astrophysics, which has the major advantage of allowing scientific investigations in ways that would not be possible by looking at single observables separately.
H I intensity mapping with MeerKAT: power spectrum detection in cross-correlation with WiggleZ galaxies
Cunnington, Steven; Li, Yichao; Santos, Mario G.; et al. (2023)
Monthly Notices of the Royal Astronomical Society
We present a detection of correlated clustering between MeerKAT radio intensity maps and galaxies from the WiggleZ Dark Energy Survey. We find a 7.7σ detection of the cross-correlation power spectrum, the amplitude of which is proportional to the product of the HI density fraction (ΩHI), HI bias (bHI), and the cross-correlation coefficient (r). We therefore obtain the constraint ΩHIbHIr [0.86±0.10(stat)±0.12(sys)]×10−3, at an effective scale of keff ∼ 0.13hMpc−1. The intensity maps were obtained from a pilot survey with the MeerKAT telescope, a 64-dish pathfinder array to the SKA Observatory (SKAO). The data were collected from 10.5 h of observations using MeerKAT’s L-band receivers over six nights covering the 11 h field of WiggleZ, in the frequency range 1015–973 MHz (0.400
Multipole expansion for 21 cm intensity mapping power spectrum: Forecasted cosmological parameters estimation for the SKA observatory
Berti, Maria; Spinelli, Marta; Viel, Matteo (2023)
Monthly Notices of the Royal Astronomical Society
The measurement of the large-scale distribution of neutral hydrogen in the late Universe, obtained with radio telescopes through the hydrogen 21 cm line emission, has the potential to become a key cosmological probe in the upcoming years. We explore the constraining power of 21 cm intensity mapping observations on the full set of cosmological parameters that describe the A CDM model. We assume a single-dish survey for the SKA Observatory and simulate the 21 cm linear power spectrum monopole and quadrupole within six redshift bins in the range z = 0.25-3. Forecasted constraints are computed numerically through Markov Chain Monte Carlo techniques. We extend the sampler COSMOMC by implementing the likelihood function for the 21 cm power spectrum multipoles. We assess the constraining power of the mock data set alone and combined with Planck 2018 CMB observations. We find that 21 cm multipoles observations alone are enough to obtain constraints on the cosmological parameters comparable with other probes. Combining the 21 cm data set with CMB observations results in significantly reduced errors on all the cosmological parameters. The strongest effect is on O(c)h(2) and H-0 , for which the error is reduced by almost a factor four. The percentage errors we estimate are O(c)h(2) = 0 . 25 percent and sH(0 )= 0 . 16 per cent , to be compared with the Planck only results O(c)h(2) = 0 . 99 per cent and sH(0 )= 0 . 79 per cent . We conclude that 21 cm SKAO observations will provide a competitive cosmological probe, complementary to CMB and, thus, pivotal for gaining statistical significance on the cosmological parameters constraints, allowing a stress test for the current cosmological model.
21 cm intensity mapping cross-correlation with galaxy surveys: Current and forecasted cosmological parameters estimation for the SKAO
Berti, Maria; Spinelli, Marta; Viel, Matteo (2024)
Monthly Notices of the Royal Astronomical Society
We present a comprehensive set of forecasts for the cross-correlation signal between 21 cm intensity mapping and galaxy redshift surveys. We focus on the data sets that will be provided by the SKAO for the 21 cm signal, DESI and Euclid for galaxy clustering. We build a likelihood which takes into account the effect of the beam for the radio observations, the Alcock-Paczynski effect, a simple parametrization of astrophysical nuisances, and fully exploit the tomographic power of such observations in the range z = 0.7-1.8 at linear and mildly non-linear scales (k < 0.25h Mpc-1). The forecasted constraints, obtained with Monte Carlo Markov Chains techniques in a Bayesian framework, in terms of the six base parameters of the standard ΛCDM model, are promising. The predicted signal-to-noise ratio for the cross-correlation can reach ∼50 for z ∼1 and k ∼0.1h Mpc-1. When the cross-correlation signal is combined with current Cosmic Microwave Background (CMB) data from Planck, the error bar on and H0 is reduced by factors 3 and 6, respectively, compared to CMB only data, due to the measurement of matter clustering provided by the two observables. The cross-correlation signal has a constraining power that is comparable to the autocorrelation one and combining all the clustering measurements a sub-per cent error bar of 0.33 per cent on H0 can be achieved, which is about a factor 2 better than CMB only measurements. Finally, as a proof of concept, we test the full pipeline on the real data measured by the MeerKat collaboration (Cunnington et al. 2022) presenting some (weak) constraints on cosmological parameters.
The foreground transfer function for H I intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications
Cunnington, Steven; Wolz, Laura; Bull, Philip; et al. (2023)
Monthly Notices of the Royal Astronomical Society
Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish H I intensity mapping surveys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable across all scales. Constructing a corrective transfer function using mock signal injection into the contaminated data has been a practice relied on for H I intensity mapping experiments. However, assessing whether this approach is viable for future intensity mapping surveys, where precision cosmology is the aim, remains unexplored. In this work, using simulations, we validate for the first time the use of a foreground transfer function to reconstruct power spectra of foreground-cleaned low-redshift intensity maps and look to expose any limitations. We reveal that even when aggressive foreground cleaning is required, which causes >50 per cent negative bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-per cent accuracy. We specifically outline the recipe for constructing an unbiased transfer function, highlighting the pitfalls if one deviates from this recipe, and also correctly identify how a transfer function should be applied in an autocorrelation power spectrum. We validate a method that utilizes the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ±100 per cent bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing <5 per cent bias in recovered values).
The stability of deep learning for 21cm foreground removal across various sky models and frequency-dependent systematics
Chen, Tianyue; Bianco, Michele; Tolley, Emma E.; et al. (2024)
Monthly Notices of the Royal Astronomical Society
Deep learning (DL) has recently been proposed as a novel approach for 21cm foreground removal. Before applying DL to real observations, it is essential to assess its consistency with established methods, its performance across various simulation models, and its robustness against instrumental systematics. This study develops a commonly used U-Net and evaluates its performance for post-reionization foreground removal across three distinct sky simulation models based on pure Gaussian realizations, the Lagrangian perturbation theory, and the Planck sky model. Consistent outcomes across the models are achieved provided that training and testing data align with the same model. On average, the residual foreground in the U-Net reconstructed data is of the signal across angular scales at the considered redshift range. Comparable results are found with traditional approaches. However, blindly using a network trained on one model for data from another model yields inaccurate reconstructions, emphasizing the need for consistent training data. The study then introduces frequency-dependent Gaussian beams and bandpass fluctuations to the test data. The network struggles to denoise data affected by 'unexpected' systematics without prior information. However, after re-training consistently with systematics-contaminated data, the network effectively restores its reconstruction accuracy. Our results highlight the importance of incorporating prior knowledge during network training compared with established blind methods. Our work provides critical guidelines for using DL for 21cm foreground removal, tailored to specific data attributes. Notably, it is the first time that DL has been applied to the Planck sky model being most realistic foregrounds at present.
Author Correction: The REACH radiometer for detecting the 21-cm hydrogen signal from redshift z ≈ 7.5–28
de Lera Acedo, Eloy; de Villiers, Dirk I.L.; Razavi-Ghods, Nima; et al. (2022)
Nature Astronomy
SKAO H I intensity mapping: blind foreground subtraction challenge
Spinelli, Marta; Carucci, Isabella P.; Cunnington, Steven; et al. (2022)
Monthly Notices of the Royal Astronomical Society
Neutral Hydrogen Intensity Mapping (H I IM) surveys will be a powerful new probe of cosmology. However, strong astrophysical foregrounds contaminate the signal and their coupling with instrumental systematics further increases the data cleaning complexity. In this work, we simulate a realistic single-dish H I IM survey of a 5000 deg² patch in the 950–1400 MHz range, with both the MID telescope of the SKA Observatory (SKAO) and MeerKAT, its precursor. We include a state-of-the-art H I simulation and explore different foreground models and instrumental effects such as non-homogeneous thermal noise and beam side lobes. We perform the first Blind Foreground Subtraction Challenge for H I IM on these synthetic data cubes, aiming to characterize the performance of available foreground cleaning methods with no prior knowledge of the sky components and noise level. Nine foreground cleaning pipelines joined the challenge, based on statistical source separation algorithms, blind polynomial fitting, and an astrophysical-informed parametric fit to foregrounds. We devise metrics to compare the pipeline performances quantitatively. In general, they can recover the input maps’ two-point statistics within 20 per cent in the range of scales least affected by the telescope beam. However, spurious artefacts appear in the cleaned maps due to interactions between the foreground structure and the beam side lobes. We conclude that it is fundamental to develop accurate beam deconvolution algorithms and test data post-processing steps carefully before cleaning. This study was performed as part of SKAO preparatory work by the H I IM Focus Group of the SKA Cosmology Science Working Group.

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