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Register a new userInterpreting LOFAR 21-cm signal upper limits at z~9.1 in the context of high-z galaxy and reionisation observations
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Using the latest upper limits on the 21-cm power spectrum at $zapprox9.1$ from the Low Frequency Array (LOFAR), we explore regions of parameter space which are inconsistent with the data. We use 21CMMC, a Monte Carlo Markov Chain sampler of 21cmFAST which directly forward models the 3D cosmic 21-cm signal in a fully Bayesian framework. We use the astrophysical parameterisation from 21cmFAST, which includes mass-dependent star formation rates and ionising escape fractions as well as soft-band X-ray luminosities to place limits on the properties of the high-$z$ galaxies. Further, we connect the disfavoured regions of parameter space with existing observational constraints on the Epoch of Reionisation such as ultra-violet (UV) luminosity functions, background UV photoionisation rate, intergalactic medium (IGM) neutral fraction and the electron scattering optical depth. We find that all models exceeding the 21-cm signal limits set by LOFAR at $zapprox9.1$ are excluded at $gtrsim2sigma$ by other probes. Finally, we place limits on the IGM spin temperature from LOFAR, disfavouring at 95 per cent confidence spin temperatures below $sim2.6$ K across an IGM neutral fraction range of $0.15 lesssim bar{x}_{H{scriptscriptstyle I}} lesssim 0.6$. Note, these limits are only obtained from 141 hrs of data in a single redshift bin. With tighter upper limits, across multiple redshift bins expected in the near future from LOFAR, more viable models will be ruled out. Our approach demonstrates the potential of forward modelling tools such as 21CMMC in combining 21-cm observations with other high-$z$ probes to constrain the astrophysics of galaxies.
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A new upper limit on the 21-cm signal power spectrum at a redshift of $z approx 9.1$ is presented, based on 141 hours of data obtained with the Low-Frequency Array (LOFAR). The analysis includes significant improvements in spectrally-smooth gain-calibration, Gaussian Process Regression (GPR) foreground mitigation and optimally-weighted power spectrum inference. Previously seen `excess power due to spectral structure in the gain solutions has markedly reduced but some excess power still remains with a spectral correlation distinct from thermal noise. This excess has a spectral coherence scale of $0.25 - 0.45$,MHz and is partially correlated between nights, especially in the foreground wedge region. The correlation is stronger between nights covering similar local sidereal times. A best 2-$sigma$ upper limit of $Delta^2_{21} < (73)^2,mathrm{mK^2}$ at $k = 0.075,mathrm{h,cMpc^{-1}}$ is found, an improvement by a factor $approx 8$ in power compared to the previously reported upper limit. The remaining excess power could be due to residual foreground emission from sources or diffuse emission far away from the phase centre, polarization leakage, chromatic calibration errors, ionosphere, or low-level radio-frequency interference. We discuss future improvements to the signal processing chain that can further reduce or even eliminate these causes of excess power.
We present upper limits on the 21 cm power spectrum at $z = 5.9$ calculated from the model-independent limit on the neutral fraction of the intergalactic medium of $x_{rm H{small I }} < 0.06 + 0.05 (1sigma)$ derived from dark pixel statistics of quasar absorption spectra. Using 21CMMC, a Markov chain Monte Carlo Epoch of Reionization analysis code, we explore the probability distribution of 21 cm power spectra consistent with this constraint on the neutral fraction. We present 99 per cent confidence upper limits of $Delta^2(k) < 10$ to $20 {rm mK}^2$ over a range of $k$ from 0.5 to $2.0 h{rm Mpc}^{-1}$, with the exact limit dependent on the sampled $k$ mode. This limit can be used as a null test for 21 cm experiments: a detection of power at $z=5.9$ in excess of this value is highly suggestive of residual foreground contamination or other systematic errors affecting the analysis.
The ARCADE2 and LWA1 experiments have claimed an excess over the Cosmic Microwave Background (CMB) at low radio frequencies. If the cosmological high-redshift contribution to this radio background is between 0.1% and 22% of the CMB at 1.42 GHz, it could explain the tentative EDGES Low-Band detection of the anomalously deep absorption in the 21-cm signal of neutral hydrogen. We use the upper limit on the 21-cm signal from the Epoch of Reionization ($z=9.1$) based on 141 hours of observations with LOFAR to evaluate the contribution of the high redshift Universe to the detected radio background. Marginalizing over astrophysical properties of star-forming halos, we find (at 95% C.L.) that the cosmological radio background can be at most 9.6% of the CMB at 1.42 GHz. This limit rules out strong contribution of the high-redshift Universe to the ARCADE2 and LWA1 measurements. Even though LOFAR places limit on the extra radio background, excess of $0.1-9.6$% over the CMB (at 1.42 GHz) is still allowed and could explain the EDGES Low-Band detection. We also constrain the thermal and ionization state of the gas at $z = 9.1$ and put limits on the properties of the first star-forming objects. We find that, in agreement with the limits from EDGES High-Band data, LOFAR data constrain scenarios with inefficient X-ray sources and cases where the Universe was ionized by stars in massive halos only.
We present the first limits on the Epoch of Reionization (EoR) 21-cm HI power spectra, in the redshift range $z=7.9-10.6$, using the Low-Frequency Array (LOFAR) High-Band Antenna (HBA). In total 13,h of data were used from observations centred on the North Celestial Pole (NCP). After subtraction of the sky model and the noise bias, we detect a non-zero $Delta^2_{rm I} = (56 pm 13 {rm mK})^2$ (1-$sigma$) excess variance and a best 2-$sigma$ upper limit of $Delta^2_{rm 21} < (79.6 {rm mK})^2$ at $k=0.053$$h$cMpc$^{-1}$ in the range $z=$9.6-10.6. The excess variance decreases when optimizing the smoothness of the direction- and frequency-dependent gain calibration, and with increasing the completeness of the sky model. It is likely caused by (i) residual side-lobe noise on calibration baselines, (ii) leverage due to non-linear effects, (iii) noise and ionosphere-induced gain errors, or a combination thereof. Further analyses of the excess variance will be discussed in forthcoming publications.
We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionisation (EoR). A Kernel Density Estimator (KDE) is introduced for measuring the spatial temperature fluctuation power spectrum from the EoR. The KDE estimates the underlying probability distribution function of fluctuations as a function of spatial scale, and contains different systematic biases and errors to the typical approach to estimating the fluctuation power spectrum. Extraction of histograms of visibilities allows moments analysis to be used to discriminate foregrounds from 21 cm signal and thermal noise. We use the information available in the histograms, along with the statistical dis-similarity of foregrounds from two independent observing fields, to robustly separate foregrounds from cosmological signal, while making no assumptions about the Gaussianity of the signal. Using two independent observing fields to robustly discriminate signal from foregrounds is crucial for the analysis presented in this paper. We apply the techniques to 13 hours of Murchison Widefield Array (MWA) EoR data over two observing fields. We compare the output to that obtained with a comparative power spectrum estimation method, and demonstrate the reduced foreground contamination using this approach. Using the second moment obtained directly from the KDE distribution functions yields a factor of 2-3 improvement in power for k < 0.3hMpc^{-1} compared with a matched delay space power estimator, while weighting data by additional statistics does not offer significant improvement beyond that available for thermal noise-only weights.
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