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nd into several frequency bins to capture the variation in sensitivity and velocity resolution (which is in the range 7.8\,km\,s$^{-1}$ at 711.5\,MHz to 5.5\,km\,s$^{-1}$ at 1015.5\,MHz). \begin{figure} \centering \includegraphics[width=0.475\textwidth]{z
dist.pdf} \caption{The distribution of CENSORS sources (\citealt{Brookes:2008}) brighter than 10\,mJy beyond a given redshift $z$. The red line denotes the cumulative distribution calculated from the parametric model of \citet{deZotti:2010}.}\label{f
igure:zdist} \end{figure} In order to simulate a realistic survey of the southern sky we select all radio sources south of $\delta = +10\degr$ from catalogues of the National Radio Astronomy Observatory Very Large Array Sky Survey (NVSS, $\nu = 1.4$\,GHz,
$S_{\rm src} \gtrsim 2.5$\,mJy; \citealt{Condon:1998}), the Sydney University Molonglo SkySurvey ($\nu = 843$\,MHz, $S_{\rm src} \gtrsim 10$\,mJy; \citealt{Mauch:2003}) and the second epoch Molonglo Galactic Plane Survey ($\nu = 843$\,MHz, $S_{\rm src} \g
trsim 10$\,mJy; \citealt{Murphy:2007}). The source flux densities, used to calculate the optical depth limit in \autoref{equation:optical_depth_limit}, are estimated at the centre of each frequency bin by extrapolating from the catalogue values and assumin
g a canonical spectral index of $\alpha = -0.7$. In \autoref{figure:nsources_flux}, we show the resulting cumulative distribution of radio sources in our sample as a function of flux density across the band. \begin{figure} \centering \includegraphics[widt
h=0.475\textwidth]{nsources_tau.pdf} \caption{The number of sources in our simulated ASKAP survey with a 21\,cm opacity sensitivity greater than or equal to $\tau_{5\sigma}$, as defined by \autoref{equation:optical_depth_limit}. The grey region enclo
ses opacity sensitivities for the 711.5 - 1011.5\,MHz band. Random samples for the line FWHM and covering factor were drawn from the distributions shown in \autoref{figure:width_dist} and \autoref{figure:covfact_dist}.}\label{figure:nsources_tau} \
end{figure} For any given sight-line, the redshift interval over which absorption may be detected is dependent upon the distance to the continuum source. The lack of accurate spectroscopic redshift measurements for most radio sources over the sky necess
itates the use of a statistical approach based on a model for the source redshift distribution. We therefore apply a statistical weighting to each comoving path element $\delta{X}(z)$ such that the expected number of absorber detections is now given by \be
gin{equation}\label{equation:weighted_sum_number} \mu = \iint{f(N_{\rm HI},X)\,\mathcal{F}_{\rm src}(z^{\prime} \geq z)\,\mathrm{d}X\,\mathrm{d}N_{\rm HI}}, \end{equation} where \begin{equation} \mathcal{F}_{\rm src}(z^{\prime} \geq z) = {\int_{z}^{\
infty} \mathcal{N}_{\rm src}(z^{\prime})\mathrm{d}z^{\prime}\over\int_{0}^{\infty}\mathcal{N}_{\rm src} (z^{\prime})\mathrm{d}z^{\prime}}, \end{equation} and $\mathcal{N}_{\rm src}(z)$ is the number of radio sources as a function of redshift. To estimate $
\mathcal{N}_{\rm src}(z)$ we use the Combined EIS-NVSS Survey Of Radio Sources (CENSORS; \citealt{Brookes:2008}), which forms a complete sample of radio sources brighter than 7.2\,mJy at 1.4\,GHz with spectroscopic redshifts out to cosmological distances.
In \autoref{figure:zdist} we show the distribution of CENSORS sources brighter than 10\,mJy beyond a given redshift $z$, and the corresponding analytical function derived from the model fit of \citet{deZotti:2010}, given by \begin{equation} \mathcal{N}_{
\rm src}(z) \approx 1.29 + 32.37z - 32.89z^{2} + 11.13z^{3} - 1.25z^{4}, \end{equation} which we use in our analysis. For the redshifts spanned by our simulated ASKAP survey, the fraction of background sources evolves from 87\,per\,cent at $z = 0.4$ to 53\
,per\,cent at $z = 1.0$. We assume that this redshift distribution applies to any sight-line irrespective of the continuum flux density. However, this assumption is only true if the source population in the target sample evolves such that the effect of di
stance is nullified by an increase in luminosity. Given this criterion, and the sensitivity of our simulated survey, we limit our sample to sources with flux densities between 10 and 1000\,mJy, which are dominated by the rapidly evolving population of high
-excitation radio galaxies and quasars (e.g. \citealt{Jackson:1999, Best:2012, Best:2014, Pracy:2016}) and for which the redshift distribution is known to be almost independent of flux density (e.g. \citealt{Condon:1984, Condon:1998}). In \autoref{figure:n
sources_tau}, we show the number of sources from this sub-sample as a function of opacity sensitivity [as defined by \autoref{equation:optical_depth_limit}], drawing random samples of the line FWHM and covering factor from the distributions shown in \autor
ef{figure:width_dist} and \autoref{figure:covfact_dist}. There are approximately 190\,000 sightlines with sufficient sensitivity to detect absorption of optical depth greater than $\tau_{5\sigma} \approx 1.0$ and 25\,000 sensitive to optical depths greater
than $\tau_{5\sigma} \approx 0.1$. Since this distribution converges at optical depth sensitivities greater than $\tau_{5\sigma} \approx 5$, the population of sources fainter than 10\,mJy, which are excluded from our simulated ASKAP survey, would not sign
ificantly contribute to further detections of absorption. Similarly, while sources brighter than 1\,Jy are good probes of low-column-density \mbox{H\,{\sc i}} gas, they do not constitute a sufficiently large enough population to significantly affect the to
tal number of absorber detections expected in the survey and can also be safely excluded. Based on these assumptions, we can estimate the number of absorbers we would expect to detect in our survey with ASKAP as a function of spin temperature. In \autoref
{figure:ndetections_nhi}, we show the expected detection yield as a cumulative function of column density. We show results for two scenarios where the spin temperature is fixed at a single value of either 100 or 1000\,K, and the line FWHM and covering fact
ors are drawn from the random distributions shown in \autoref{figure:width_dist} and \autoref{figure:covfact_dist}. We find that for both these cases the expected number of detections is not sensitive to column densities below the DLA definition of $N_{\rm
HI} = 2\times 10^{20}$\,cm$^{-2}$. We also show in \autoref{figure:ndetections_total} the expected total detection yield (integrated over all \mbox{H\,{\sc i}} column densities) as a function of a single spin temperature $T_\mathrm{spin}$ and line FWHM $\
Delta{v}_\mathrm{50}$. We find that for typical spin temperatures of a few hundred kelvin (consistent with the typical fraction of CNM observed in the local Universe) and a line FWHM of approximately $20$\,km\,s$^{-1}$, a wide-field 21\,cm survey with ASKA
P is expected to yield $\sim 1000$ detections. However, even moderate evolution to a higher spin temperature in the DLA population should see significant reduction in the detection yield from this survey. \section{Inferring the average spin temperature}
\label{section:spin_temp} \begin{figure} \centering \includegraphics[width=0.475\textwidth]{ndetections_nhi.pdf} \caption{The expected number of absorber detections (as a cumulative function of column density) in our simulated ASKAP survey. We show tw
o scenarios for a single spin temperature $T_{\rm spin} = 100$ and $1000$\,K, where we have drawn random samples for the line FWHM and covering factor from the distributions shown in \autoref{figure:width_dist} and \autoref{figure:covfact_dist}. In
both cases we find that the expected number of detections is not sensitive to column densities below $N_{\rm HI} = 2 \times 10^{20}$\,cm$^{-2}$, indicating that such a survey will only be sensitive to DLA systems.}\label{figure:ndetections_nhi} \end
{figure} We cannot directly measure the spin temperatures of individual systems without additional data from either 21\,cm emission or Lyman-$\alpha$ absorption. However, from \autoref{figure:ndetections_total} it is evident that the total number of abso
rbing systems expected to be detected with a reasonably large 21\,cm survey is strongly dependent on the assumed value for the spin temperature. Therefore, by comparing the actual survey yield with that expected from the known \mbox{H\,{\sc i}} distributio
n, we can infer the average spin temperature of the atomic gas within the DLA population for a given redshift interval. Assuming that the total number of detections follows a Poisson distribution, the probability of detecting $\mathcal{N}$ intervening abs
orbing systems is given by \begin{equation} p(\mathcal{N}|\overline{\mu}) = {\overline{\mu}^{\mathcal{N}} \over \mathcal{N}!} \mathrm{e}^{-\overline{\mu}}, \end{equation} where $\overline{\mu}$ is the expected total number of detections given by the in
tegral \begin{equation} \overline{\mu} = \iiint{\mu(T_{\rm spin},\Delta{v}_{50},c_{\rm f})\rho(T_{\rm spin},\Delta{v}_{50},c_{\rm f})\mathrm{d}T_{\rm spin}\mathrm{d}\Delta{v}_{50}\mathrm{d}c_{\rm f}}, \end{equation} and $\rho$ is the distribution of syst
ems as a function of spin temperature, line FWHM and covering factor. We assume that all three of these variables are independent\footnote{In the case where thermal broadening contributes significantly to the velocity dispersion, and the spin temperatu
re is dominated by collisional excitation, the assumption that these are independent may no longer hold. However, given that collisional excitation dominates in the CNM, where $T_{\rm spin} \sim 100\,\mathrm{K}$, the velocity dispersion would have
to satisfy $\Delta{v}_{50} \ll 10$\,km\,s$^{-1}$ (c.f. the distribution shown in \autoref{figure:width_dist}).} so that $\rho$ factorizes into functions of each. We then marginalise over the covering factor and line width distributions shown in \autoref{
figure:width_dist} and \autoref{figure:covfact_dist} so that the expression for $\overline{\mu}$ reduces to \begin{equation}\label{equation:harmonic_spin_temp} \overline{\mu} = \int{\mu(T_{\rm spin})\rho(T_{\rm spin})\mathrm{d}T_{\rm spin}} = \mu(\overli
ne{T}_{\rm spin}), \end{equation} where $\overline{T}_{\rm spin}$ is the harmonic mean of the unknown spin temperature distribution, weighted by column density. This is analogous to the spin temperature inferred from the detection of absorption in a single
intervening galaxy averaged over several gaseous components at different temperatures (e.g. \citealt{Carilli:1996}). \begin{figure} \centering \includegraphics[width=0.475\textwidth]{ndetections_total.pdf} \caption{The expected total number of detections
in our simulated ASKAP survey, as a function of a single spin temperature ($T_{\rm spin}$) and line FWHM ($\Delta{v}_{50}$). The vertical dotted lines enclose the velocity resolution across the observed frequency band. We draw random samples for
the covering factor from a uniform distribution between 0 and 1 (as shown in \autoref{figure:covfact_dist}). The contours are truncated at $\mu < 1$ for clarity.}\label{figure:ndetections_total} \end{figure} In the event of the survey yielding $\ma
thcal{N}$ detections, we can calculate the posterior probability density of $\overline{T}_{\rm spin}$ using the following relationship between conditional probabilities \begin{equation} p(\overline{T}_{\rm spin}|\mathcal{N}) = {p(\mathcal{N}|\overline{
T}_{\rm spin})p(\overline{T}_{\rm spin})\over p(\mathcal{N})}, \end{equation} where $p(\overline{T}_{\rm spin})$ is our prior probability density for $\overline{T}_{\rm spin}$ and $p(\mathcal{N})$ is the marginal probability of the number of detectio
ns, which can be treated as a normalizing constant. The minimally informative Jeffreys prior for the mean value $\mu$ of a Poisson distribution is $1/\sqrt{\mu}$ (\citealt{Jeffreys:1946})\footnote{A suitable alternative choice for the prior is the standa
rd scale-invariant form $1/\mu$ (e.g. \citealt{Jeffreys:1961, Novick:1965, Villegas:1977}). While we find that our choice of non-informative prior has negligible effect on the spin temperature posterior for the full \mbox{H\,{\sc i}} absorption sur
vey, as one would expect this choice becomes more important for smaller surveys. For the early-science 1000\,deg$^{2}$ survey discussed in \autoref{section:tspin_results} we find that the difference in these two priors produces a $\sim 2$ to 20\,per\
,cent effect in the posterior. However, in all cases considered this change is smaller than the 68.3\,per\,cent credible interval spanned by the posterior.}. From \autoref{equation:harmonic_spin_temp} it therefore follows that a suitable form for the
non-informative spin temperature prior is $p(\overline{T}_{\rm spin}) = 1/\sqrt{\overline{\mu}}$, so that \begin{equation}\label{equation:tspin_prob} p(\overline{T}_{\rm spin}|\mathcal{N}) = C^{-1}\,{\overline{\mu}^{(\mathcal{N}-1/2)} \over \mathcal{N}!
} \mathrm{e}^{-\overline{\mu}}, \end{equation} where the distribution is normalised to unit total probability by evaluating the integral \begin{equation} C = \int{{\overline{\mu}^{(\mathcal{N}-1/2)} \over \mathcal{N}!} \mathrm{e}^{-\overline{\mu}}}\,\ma
thrm{d}\overline{T}_{\rm spin}. \end{equation} The probabilistic relationship given by \autoref{equation:tspin_prob} and the expected detection yield derived in \autoref{section:all_sky_survey} can be used as a frame-work for inferring the harmonic-mean s
pin temperature using the results of any homogeneous 21-cm survey. We have assumed that we can accurately distinguish intervening absorbing systems from those associated with the host galaxy of the radio source. However, any 21-cm survey will be accompanie
d by follow-up observations, at optical and sub-mm wavelengths, which will aid identification. Furthermore, future implementation of probabilistic techniques to either use photometric redshift information or distinguish between line profiles should provide
further disambiguation. Of course we have not yet accounted for any error in our estimate of $\overline{\mu}$, which will increase our uncertainty in $\overline{T}_\mathrm{spin}$. In the following section we discuss these possible sources of error and th
eir effect on the result. \section{Sources of error}\label{section:errors} Our estimate of the expected number of 21\,cm absorbers is dependent upon several distributions describing the properties of the foreground absorbing gas and the background source
distribution. For future large-scale 21\,cm surveys, the accuracy to which we can infer the harmonic mean of the spin temperature distribution will eventually be limited by the accuracy to which we can measure these other distributions. In this section, w
e describe these errors and their propagation through to the estimate of $\overline{T}_\mathrm{spin}$, summarizing our results in \autoref{table:tspin_uncertainties}. \subsection{The covering factor}\label{section:covering_factor} \subsubsection{Deviatio
n from a uniform distribution between 0 and 1} The fraction $c_{\rm f}$ by which the foreground gas subtends the background radiation source is difficult to measure directly and is thereby a significant source of error for 21\,cm absorption surveys. In th
is work, we have assumed a uniform distribution for $c_{\rm f}$, taking random values between 0 and 1. In \autoref{section:expected_number}, we tested this assumption by comparing it with the distribution of flux density core fractions in a sample of 37 qu
asars, used by \cite{Kanekar:2014a} as a proxy for the covering factor. By carrying out a two-tailed KS test, we found some evidence (at the 0.05 level) that this quasar sample was inconsistent with our assumption of a uniform distribution between 0 and 1.
Noticeably there seems to be an under-representation of quasars in the Kanekar et al. sample with estimated $c_{\rm f} \lesssim 0.2$. In the low optical depth limit, the detection rate is dependent on the ratio of spin temperature to covering factor, in w
hich case a fractional deviation in $c_{\rm f}$ will propagate as an equal fractional deviation in $\overline{T}_\mathrm{spin}$. Based on the difference seen in the covering factor distribution of the Kanekar et al. sample and the uniform distribution, we
assume that the spin temperature can deviate by as much as $\pm$10\,per\,cent. \subsubsection{Evolution with redshift} We also consider that the covering factor distribution may evolve with redshift, which would mimic a perceived evolution in the average
spin temperature. Such an effect was proposed by \cite{Curran:2006b} and \cite{Curran:2012b}, who claimed that the relative change in angular-scale behaviour of absorbers and radio sources between low- and high-redshift samples could explain the apparent
evolution of the spin temperature found by \cite{Kanekar:2003b}. To test for this effect in their larger DLA sample, \cite{Kanekar:2014a} considered a sub-sample at redshifts greater than $z = 1$, for which the relative evolution of the absorber and source
angular sizes should be minimal. While the significance of their result was reduced by removing the lower redshift absorbers from their sample, they still found a difference at $3.5\,\sigma$ significance between spin temperature distributions in the two D
LA sub-samples separated by a median redshift of $z = 2.683$. Future surveys with ASKAP and the other SKA pathfinders will search for \mbox{H\,{\sc i}} absorption at intermediate redshifts ($z \sim 1$), where the relative evolution of the absorber and sou
rce angular sizes is expected to be more significant than for the higher redshift DLA sample considered by \cite{Kanekar:2014a}. We therefore consider the potential effect of this cosmological evolution on the inferred value of $\overline{T}_\mathrm{spin}$
. We approximate the covering factor using the following model of \cite{Curran:2006b} \begin{equation}\label{equation:covering_factor} c_{f} \approx \begin{cases} \left({\theta_{\rm abs}\over \theta_{\rm src}}\right)^{2}, & \text{if}\ \theta_{\rm abs}
< \theta_{\rm src}, \\ 1, & \text{otherwise}, \end{cases} \end{equation} where $\theta_{\rm abs}$ and $\theta_{\rm src}$ are the angular sizes of the absorber and background source, respectively. Under the small-angle approximation $\theta_{\rm abs} \app
rox {d_{\rm abs}/D_{\rm abs}}$ and $\theta_{\rm abs} \approx {d_{\rm src}/D_{\rm src}}$, where $d_{\rm abs}$ and $D_{\rm abs}$ are the linear size and angular diameter distance of the absorber, and likewise $d_{\rm src}$ and $D_{\rm src}$ are the l
inear size and angular diameter distance of the background source. Assuming that the ratio $d_{\rm abs}/d_{\rm src}$ is randomly distributed and independent of redshift, any evolution in the covering factor is therefore dominated by relative changes in the
angular diameter distances. We calculate the expected angular diameter distance ratio at a redshift $z$ by \begin{equation} \left\langle{D_{\rm abs}\over D_{\rm src}}\right\rangle_{z} = D_{\rm abs}(z){\int_{z}^{\infty} \mathcal{N}_{\rm src}(z^{\prime})D
_{\rm src}(z^{\prime})^{-1}\mathrm{d}z^{\prime}\over\int_{z}^{\infty}\mathcal{N}_{\rm src} (z^{\prime})\mathrm{d}z^{\prime}}, \end{equation} which, for the source redshift distribution model given by \cite{deZotti:2010}, evolves from 0.7 at $z = 0.4$ to 1.
0 at $z = 1.0$ (see \autoref{figure:dang_ratio}). We note that this is consistent with the behaviour measured by \cite{Curran:2012b} for the total sample of DLAs observed at 21\,cm wavelengths. By applying this as a correction to the otherwise uniformly d
istributed covering factor (using \autoref{equation:covering_factor}), we find that the inferred value of $\overline{T}_{\rm spin}$ systematically increases by approximately 30 per\,cent. \begin{figure} \centering \includegraphics[width=0.475\textwidth]{d
ang_ratio.pdf} \caption{The expected redshift behaviour of $D_{\rm abs}/D_{\rm src}$ based on the \citet{deZotti:2010} model for the radio source redshift distribution.}\label{figure:dang_ratio} \end{figure} \subsection{The $\bmath{N_{\rm HI}}$ freque
ncy distribution} \subsubsection{Uncertainty in the measurement of $f(N_{\rm HI},X)$} We assume that $f(N_{\rm HI}, X)$ is relatively well understood as a function of redshift by interpolating between model gamma functions fitted to the distributions at
$z = 0$ and $3$. However, these distributions were measured from finite samples of galaxies, which of course have associated uncertainties that need to be considered. In the case of the data presented by \cite{Zwaan:2005} and \cite{Noterdaeme:2009}, both h
ave typical measurement uncertainties in $f(N_{\rm HI}, X)$ of approximately 10\,per\,cent over the range of column densities for which our simulated ASKAP survey is sensitive (see \autoref{figure:ndetections_nhi}). This will propagate as a 10\,per\,cent f
ractional error in the expected number of absorber detections, and contribute a similar percentage uncertainty in the inferred average spin temperature. \subsubsection{Correcting for 21\,cm self-absorption} In the local Universe, \cite{Braun:2012} showed
that self-absorption from opaque \mbox{H\,{\sc i}} clouds identified in high-resolution images of the Local Group galaxies M31, M33 and the Large Magellanic Cloud may necessitate a correction to the local atomic mass density of up to 30\,per\,cent. Althou
gh it is not yet clear whether this small sample of Local Group galaxies is representative of the low-redshift population, it is useful to understand how this effect might propagate through to our average spin temperature measurement. We therefore replace
the gamma-function parametrization of the local $f(N_{\rm HI})$ given by \cite{Zwaan:2005} with the non-parametric values given in table\,2 of \cite{Braun:2012}, and recalculate $\overline{T}_{\rm spin}$. For an all-sky survey with the full 36-antenna AS
KAP we find that $\overline{T}_{\rm spin}$ increases by $\sim$30 for 100 detections and $\sim$10\,per\,cent for 1000 detections. Note that the correction increases for low numbers of detections, which are dominated by the highest column density systems. \
subsubsection{Dust obscuration bias in optically-selected DLAs} At higher redshifts, it is possible that the number density of optically-selected DLAs could be significantly underestimated as a result of dust obscuration of the background quasar (\citealt
{Ostriker:1984}). This would cause a reduction in the $f(\mbox{H\,{\sc i}}, X)$ measured from optical surveys, thereby significantly underestimating the expected number of intervening 21\,cm absorbers at high redshifts. The issue is further compounded by t
he expectation that the highest column density DLAs ($N_{\rm HI} \gtrsim 10^{21}$\,cm$^{-2}$), for which future wide-field 21\,cm surveys are most sensitive (see \autoref{figure:ndetections_nhi}), may contain more dust than their less-dense counterparts.
This conclusion was supported by early analyses of the existing quasar surveys at that time (e.g. \citealt{Fall:1993}), which indicated that up to 70\,per\,cent of quasars could be missing from optical surveys through the effect of dust obscuration, albeit
with large uncertainties. However, subsequent optical and infrared observations of radio-selected quasars (e.g. \citealt{Ellison:2001}; \citealt*{Ellison:2005}; \citealt{Jorgenson:2006}), which are free of the potential selection biases associated with th
ese optical surveys, found that the severity of this issue was substantially over-estimated and that there was minimal evidence in support of a correlation between the presence of DLAs and dust reddening. Furthermore, the \mbox{H\,{\sc i}} column density f
requency distribution measured by \cite{Jorgenson:2006} was found to be consistent with the optically-determined gamma-function parametrization of \cite{Prochaska:2005}, with no evidence of DLA systems missing from the SDSS sample at a sensitivity of $N_{\
rm HI} \lesssim 5 \times 10^{21}$\,cm$^{-2}$. Although radio-selected surveys of quasars are free of the selection biases associated with optical surveys, they do typically suffer from smaller sample sizes and are therefore less sensitive to the rarer DLAs
with the highest column densities. Another approach is to directly test whether optically-selected quasars with intervening DLAs, selected from the SDSS sample, are systematically more dust reddened than a control sample of non-DLA quasars. Comparisons i
n the literature are based on several different colour indicators, which include the spectral index (e.g. \citealt{Murphy:2004,Murphy:2016}), spectral stacking (e.g. \citealt{Frank:2010, Khare:2012}) and direct photometry (e.g. \citealt*{Vladilo:2008}; \ci
tealt{Fukugita:2015}). The current status of these efforts is summarized by \citet{Murphy:2016}, showing broad support for a missing DLA population at the level of $\sim$5\,per\,cent but highlighting that tension still exists between different dust measure
ments. No substantial evidence has yet been found to support a correlation between the dust reddening and \mbox{H\,{\sc i}} column density in these optically selected DLA surveys (e.g. \citealt{Vladilo:2008, Khare:2012, Murphy:2016}). In an attempt to rec
oncile the differences and myriad biases associated with these techniques, \cite{Pontzen:2009} carried out a statistically-robust meta-analysis of the available optical and radio data, using a Bayesian parameter estimation approach to model the dust as a f
unction of column density and metallicity. They found that the expected fraction of DLAs missing from optical surveys is 7\,per\,cent, with fewer than 28\,per\,cent missing at 3\,$\sigma$ confidence. Based on this body of work we therefore assume that appr
oximately 10\,per\,cent of DLAs are missing from the SDSS sample of \cite{Noterdaeme:2009} and consider the affect on our estimate of $\overline{T}_{\rm spin}$. We further assume that there is no dependance on column density, an assumption which is support
ed by the aforementioned observational data for the range of column densities to which our 21\,cm survey is sensitive. We find that increasing the high-redshift column density frequency distribution by 10\,per\,cent introduces a systematic increase of appr
oximately 3\,per\,cent in the expected number of detections for the redshifts covered by our ASKAP surveys. We note that this error will increase significantly for 21\,cm surveys at higher redshifts where the optically derived $f(\mbox{H\,{\sc i}}, X)$ dom
inates the calculation of the expected detection rate. \subsection{The radio source background} As described in \autoref{section:all_sky_survey}, we weight the comoving path-length for each sight-line by a statistical redshift distribution in order to ac
count for evolution in the radio source background. We use the parametric model of \cite{deZotti:2010}, which is derived from fitting the measured redshifts of \cite{Brookes:2008} for CENSORS sources brighter than 10\,mJy, and assume that this applies to a
ll sources in the range 10 - 1000\,mJy. In \autoref{figure:zdist}, we show the cumulative distribution of sources located behind a given redshift and the associated measurement uncertainty given by the errorbars. For the intermediate redshifts covered by t
he ASKAP survey, the fractional uncertainty in this distribution increases from $\sigma_{\mathcal{F}_{\rm src}}/\mathcal{F}_{\rm src} \approx 3.5$ to 8\,per\,cent between $z = 0.4$ and 1.0, which propagates through to a similar fractional uncertainty i
n $\overline{T}_{\rm spin}$. However, for higher redshifts this fractional uncertainty increases rapidly at $z > 2$, to more than 50\,per\,cent at $z = 3$, reflecting the paucity of optical spectroscopic data for the high-redshift radio source population.
Understanding how the radio source population is distributed at lower flux densities and at higher redshifts is therefore a concern for the future 21\,cm absorption surveys undertaken with the SKA mid- and low-frequency telescopes (see \citealt{Kanekar:200
4} and \citealt*{Morganti:2015} for reviews). \begin{table} \begin{threeparttable} \caption{An account of errors in our estimate of $\overline{T}_{\rm spin}$ due to the accuracy to which we can determine the expected number of absorber
detections.}\label{table:tspin_uncertainties} \begin{tabular}{l@{\hspace{0.05in}}l@{\hspace{0.05in}}l@{\hspace{0.05in}}l@{\hspace{0.05in}}l} \hline & Source of error & $\mathrm{err}(\overline{T}_{\rm spin})$ & Refs. \\ & & [per\,cent] &
\\ \hline Covering factor & Distribution uncertainty & $\pm10$ & $a$ \\ Covering factor & Systematic evolution & +30 & $a$, $b$\\ $f(N_{\rm HI}, X)$ & Measurement uncertainty & $\pm10$ & $c, d$\\ Low-$z$ $f(N_{\rm HI}, X)$ & Systemati
c self-absorption & $+(10-30)$ & $e$ \\ High-$z$ $f(N_{\rm HI}, X)$ & Systematic dust-obscuration & $+3$ & $f$, $g$ \\ $\mathcal{F}_{\rm src}(z^{\prime} \geq z)$ & Measurement uncertainty & $\pm 5$ & $h$, $i$ \\ \hline \end{tabular} \be
gin{tablenotes} \item[] References: $^{a}${\citet{Kanekar:2014a}}, $^{b}${\citet{Curran:2012b}}, $^{c}${\citet{Zwaan:2005}}, $^{d}${\citet{Noterdaeme:2009}} , $^{e}${\citet{Braun:2012}}, $^{f}${\citet{Pontzen:2009}}, $^{g}${\citet{Murphy
:2016}}, $^{h}${\citet{Brookes:2008}}, $^{i}${\citet{deZotti:2010}}. \end{tablenotes} \end{threeparttable} \end{table} \section{Expected results for future 21-cm absorption surveys}\label{section:tspin_results} \begin{figure} \centering \includ
egraphics[width=0.475\textwidth]{tspin_prob.pdf} \caption{The posterior probability density of the average spin temperature, as a function of absorber detection yield ($\mathcal{N}$). We show results for our simulated all-southern-sky survey with 2-h
per pointing using the full 36-antenna ASKAP (top panel) and a smaller 1000\,deg$^{2}$ survey with 12-h per pointing and 12 antennas of ASKAP (bottom panel). The dashed curves show the cumulative effect of the systematic errors discussed in \autor
ef{section:errors}. $\overline{\mathcal{F}}_{\rm CNM}$ is the average CNM fraction assuming a simple two-phase neutral ISM with $T_{\rm spin,CNM} = 100$\,K and $T_{\rm spin,WNM} = 1800$\,K (\citealt{Liszt:2001}).}\label{figure:tspin_prob} \end{figure
} In the top panel of \autoref{figure:tspin_prob} we show the results of applying our method for inferring $\overline{T}_{\rm spin}$ to the simulated all-southern-sky \mbox{H\,{\sc i}} absorption survey with ASKAP described in \autoref{section:all_sky_sur
vey}. We account for the uncertainties in the expected detection rate $\overline{\mu}$, discussed in \autoref{section:errors}, by using a Monte Carlo approach and marginalizing over many realizations. A yield of 1000 absorbers from such a survey would impl
y an average spin temperature of $\overline{T}_\mathrm{spin} = 127^{+14}_{-14}\,(193^{+23}_{-23})$\,K\footnote{We give the 68.3\,per\,cent interval about the median value measured from the posterior distributions shown in \autoref{figure:tspin_prob}.},
where values in parentheses denote the alternative posterior probability resulting from the systematic errors discussed in \autoref{section:errors}. This scenario would indicate that a large fraction of the atomic gas in DLAs at these intermediate redshif
ts is in the classical stable CNM phase. Conversely, a yield of only 100 detections would imply that $\overline{T}_\mathrm{spin} = 679^{+64}_{-65}\,(1184^{+116}_{-120})$\,K, indicating that less than 10\,per\,cent of the atomic gas is in the CNM and that t
he bulk of the neutral gas in galaxies is significantly different at intermediate redshifts compared with the local Universe. We also consider the effect of reducing the sky area and array size, which is relevant for planned early science surveys with ASK
AP and other SKA pathfinder telescopes. In the bottom panel of \autoref{figure:tspin_prob}, we show the spin temperatures inferred when observing a random 1000\,deg$^{2}$ field for 12\,h per pointing, between $z_{\rm HI} = 0.4$ and $1.0$, using a 12-antenn
a version of ASKAP. We find that detection yields of 30 and 3 from such a survey would give inferred spin temperatures of $\overline{T}_{\rm spin} =134^{+23}_{-27}\,(209^{+40}_{-47})$ and $848^{+270}_{-430}\,(1535^{+513}_{-837})$\,K, respectively. The sign
ificant reduction in telescope sensitivity and sky-area, compensated by the increase in integration time per pointing planned for early-science, results in a factor of 30 decrease in the expected number of detections and therefore an increase in the sample
variance and uncertainty in $\overline{T}_{\rm spin}$. However, this result demonstrates that we expect to be able to distinguish between the limiting cases of CNM-rich or deficient DLA populations even during the early-science phases of the SKA pathfinde
rs. For example 30 detections with the early ASKAP survey rules out an average spin temperature of 1000\,K at high probability. \section{Conclusions} We have demonstrated a statistical method for measuring the average spin temperature of the neutral ISM
in distant galaxies, using the expected detection yields from future wide-field 21\,cm absorption surveys. The spin temperature is a crucial property of the ISM that can be used to determine the fraction of the cold ($T_{\rm k} \sim 100$\,K) and dense ($n
\sim 100$\,cm$^{-2}$) atomic gas that provides sites for the future formation of cold molecular gas clouds and star formation. Recent 21\,cm surveys for \mbox{H\,{\sc i}} absorption in \mbox{Mg\,{\sc ii}} absorbers and DLAs towards distant quasars have yie
lded some evidence of an evolution in the average spin temperature that might reveal a decrease in the fraction of cold dense atomic gas at high redshift (e.g. \citealt{Gupta:2009, Kanekar:2014a}). By combining recent specifications for ASKAP, with availa
ble information for the population of background radio sources, we show that strong statistical constraints (approximately $\pm10$\,per\,cent) in the average spin temperature can be achieved by carrying out a shallow 2-h per pointing survey of the southern
sky between redshifts of $z = 0.4$ and $1.0$. However, we find that the accuracy to which we can measure the average spin temperature is ultimately limited by the accuracy to which we can measure the distribution of the covering factor, the $N_{\rm HI}$ f
requency distribution function and the evolution of the radio source population as a function of redshift. By improving our understanding of these distributions we will be able to leverage the order-of-magnitude increases in sensitivity and redshift covera
ge of the future SKA telescope, allowing us to measure the evolution of the average spin temperature to much higher redshifts. \section*{Acknowledgements} We thank Robert Allison, Elaine Sadler and Michael Pracy for useful discussions, and the anonymous
referee for providing comments that helped improve this paper. JRA acknowledges support from a Bolton Fellowship. We have made use of \texttt{Astropy}, a community-developed core \texttt{Python} package for astronomy (\citealt{Astropy:2013}); NASA's Astro
physics Data System Bibliographic Services; and the VizieR catalogue acces
s tool, operated at CDS, Strasbourg, France. \bibliographystyle{mnras}
\section{Introduction} Given $\rho>0$, we consider the problem \begin{equation}\label{eq:main_prob_U} \begin{cases} -\Delta U + \lambda U = |U|^{p-1}U & \text{in }\Omega,\smallskip\\ \int_\Omega U^2\,dx = \rho, \quad U=0 & \text{on }\partial\Omega, \end
{cases} \end{equation} where $\Omega\subset{\mathbb{R}}^N$ is a Lipschitz, bounded domain, $1<p<2^*-1$, $\rho>0$ is a fixed parameter, and both $U\in H^1_0(\Omega)$ and $\lambda\in{\mathbb{R}}$ are unknown. More precisely, we investigate conditions on $p$
and $\rho$ (and also $\Omega$) for the solvability of the problem. The main interest in \eqref{eq:main_prob_U} relies on the investigation of standing wave solutions for the nonlinear Schr\"odinger equation \[ i\frac{\partial \Phi}{\partial t}+\Delta \Phi
+ |\Phi|^{p-1}\Phi=0,\qquad (t,x)\in {\mathbb{R}}\times \Omega \] with Dirichlet boundary conditions on $\partial\Omega$. This equation appears in several different physical models, both in the case $\Omega={\mathbb{R}}^N$ \cite{MR2002047}, and on bounded
domains \cite{MR1837207}. In particular, the latter case appears in nonlinear optics and in the theory of Bose-Einstein condensation, also as a limiting case of the equation on ${\mathbb{R}}^N$ with confining potential. When searching for solutions having
the wave function $\Phi$ factorized as $\Phi(x,t)=e^{i\lambda t} U(x)$, one obtains that the real valued function $U$ must solve \begin{equation}\label{eq:NLS} -\Delta U + \lambda U = |U|^{p-1}U ,\qquad U\in H^1_0(\Omega), \end{equation} and two points of
view are available. The first possibility is to assign the chemical potential $\lambda\in{\mathbb{R}}$, and search for solutions of \eqref{eq:NLS} as critical points of the related action functional. The literature concerning this approach is huge and we d
o not even make an attempt to summarize it here. On the contrary, we focus on the second possibility, which consists in considering $\lambda$ as part of the unknown and prescribing the mass (or charge) $\|U\|_{L^2(\Omega)}^2$ as a natural additional condi
tion. Up to our knowledge, the only previous paper dealing with this case, in bounded domains, is \cite{MR3318740}, which we describe below. The problem of searching for normalized solutions in ${\mathbb{R}}^N$, with non-homogeneous nonlinearities, is more
investigated \cite{MR3009665,MR1430506}, even though the methods used there can not be easily extended to bounded domains, where dilations are not allowed. Very recently, also the case of partial confinement has been considered \cite{BeBoJeVi_2016}. Solu
tions of \eqref{eq:main_prob_U} can be identified with critical points of the associated energy functional \[ \mathcal{E}(U) = \frac12\int_\Omega|\nabla U|^2\,dx - \frac{1}{p+1} \int_\Omega|U|^{p+1}\,dx \] restricted to the mass constraint \[ {\mathcal{M}
}_\rho=\{U\in H_0^1(\Omega) : \|U\|_{L^2(\Omega)}=\rho\}, \] with $\lambda$ playing the role of a Lagrange multiplier. A cricial role in the discussion of the above problem is played by the Gagliardo-Nirenberg inequality: for any $\Omega$ and for any $v\i
n H^1_0(\Omega)$, \begin{equation} \label{sobest} \|v\|^{p+1}_{L^{p+1}(\Omega)} \leq C_{N,p} \| \nabla v \|_{L^2(\Omega)}^{N(p-1)/2} \| v \|_{L^2(\Omega)} ^{(p+1)-N(p-1)/2}, \end{equation} the equality holding only when $\Omega={\mathbb{R}}^N$ and $v=Z_{N,
p}$, the positive solution of $-\Delta Z + Z = Z^{p}$ (which is unique up to translations \cite{MR969899}). Accordingly, the exponent $p$ can be classified in relation with the so called \emph{$L^2$-critical exponent} $1+4/N$ (throughout all the paper, $p$
will be always Sobolev-subcritical and its criticality will be understood in the $L^2$ sense). Indeed we have that ${\mathcal{E}}$ is bounded below and coercive on ${\mathcal{M}}_\rho$ if and only if either $p$ is subcritical, or it is critical and $\rho$
is sufficiently small. The recent paper \cite{MR3318740} deals with problem \eqref{eq:main_prob_U} in the case of the spherical domain $\Omega = B_1$, when searching for positive solutions $U$. In particular, it is shown that the solvability of \eqref{eq
:main_prob_U} is strongly influenced by the exponent $p$, indeed: \begin{itemize} \item in the subcritical case $1<p<1+4/N$, \eqref{eq:main_prob_U} admits a unique positive solution for every $\rho>0$; \item if $p=1+4/N$ then \eqref{eq:main_prob_U} admi
ts a unique positive solution for \[ 0<\rho<\rho^*=\left(\frac{p+1}{2C_{N,p}}\right)^{N/2}=\|Z_{N,p}\|^2_{L^2({\mathbb{R}}^N)}, \] and no positive solutions for $\rho\geq\rho^*$; \item finally, in the supercritical regime $1+4/N<p<2^*-1$, \eqref{eq:m
ain_prob_U} admits positive solutions if and only if $0<\rho\leq\rho^*$ (the threshold $\rho^*$ depending on $p$), and such solutions are at least two for $\rho<\rho^*$. \end{itemize} In this paper we carry on such analysis, dealing with a general domai
n $\Omega$ and with solutions which are not necessarily positive. More precisely, let us recall that for any $U$ solving \eqref{eq:main_prob_U} for some $\lambda$, it is well-defined the Morse index \[ m(U) = \max\left\{k : \begin{array}{l} \exists V\subse
t H^1_0(\Omega),\,\dim(V)= k:\forall v\in V\setminus\{0\}\smallskip\\ \displaystyle\int_\Omega |\nabla v|^2 + \lambda v^2 - p|U|^{p-1}v^2\,dx<0 \end{array} \right\}\in{\mathbb{N}}. \] Then, if $\Omega=B_1$, it is well known that a solution $U$ of \eqref{eq
:main_prob_U} is positive if and only if $m(U)=1$. Under this perspective, the results in \cite{MR3318740} can be read in terms of Morse index one--solutions, rather than positive ones: introducing the sets of admissible masses \[ {\mathfrak{A}}_k ={\mathf
rak{A}}_k(p,\Omega) := \left\{\rho>0 : \begin{array}{l} \eqref{eq:main_prob_U} \text{ admits a solution $U$ (for some $\lambda$)}\\ \text{having Morse index }m(U)\leq k \end{array} \right\}, \] then \cite{MR3318740} implies that ${\mathfrak{A}}_1(p,B_1)$ i
s a bounded interval if and only if $p$ is critical or supercritical, while ${\mathfrak{A}}_1(p,B_1)={\mathbb{R}}^+$ in the subcritical case. On the contrary, when considering general domains and higher Morse index, the situation may become much more compl
icated. We collect some examples in the following remark. \begin{remark}\label{rem:specialdomains} In the case of a symmetric domain, one can use any solution as a building block to construct other solutions with a more complex behavior, obtaining the so-c
alled necklace solitary waves. Such kind of solutions are constructed in \cite{MR3426917}, even though in such paper the focus is on stability, rather than on normalization conditions. For instance, by scaling argument, any Dirichlet solution of $-\Delta U
+ \lambda U = |U|^{p-1}U$ in a rectangle $R=\prod_{i=1}^N(a_i,b_i)$ can be scaled to a solution of $-\Delta U + k^2\lambda U = |U|^{p-1}U$ in $R/k$, $k\in{\mathbb{N}}_+$, and then $k^N$ copies of it can be juxtaposed, with alternating sign. In this way on
e obtains a new solution on $R$ having $k^{4/(p-1)}$ times the mass of the starting one, and eventually solutions in $R$ with arbitrarily high mass (but with higher Morse index) can be constructed even in the critical and supercritical case. An analogous c
onstruction can be performed in the disk, using solutions in circular sectors as building blocks, even though in this case explicit bounds on the mass obtained are more delicate. Also, instead of symmetric domains, singular perturbed ones can be considered
, such as dumbbell domains \cite{MR949628}: for instance, using \cite[Theorem 3.5]{MR2997381}, one can show that for any $k$, there exists a domain $\Omega$, which is close in a suitable sense to the disjoint union of $k$ domains, such that \eqref{eq:main_
prob_U} has a \emph{positive} solution on $\Omega$ with Morse index $k$ and $\rho=\rho_k\to+\infty$ as $k\to+\infty$. This kind of results justifies the choice of classifying the solutions in terms of their Morse index, rather than in terms of their nodal
properties. \end{remark} Motivated by the previous remark, the first question we address in this paper concerns the boundedness of ${\mathfrak{A}}_k$. We provide the following complete classification. \begin{theorem}\label{thm:bbd_index} For every $\Omega
\subset{\mathbb{R}}^N$ bounded $C^1$ domain, $k\ge1$, $1<p<2^*-1$, \[ \sup{\mathfrak{A}}_k(p,\Omega) < +\infty \qquad\iff\qquad p \ge 1+\frac{4}{N}. \] \end{theorem} The proof of such result, which is outlined in Section \ref{sec:blow-up}, is obtained by a
detailed blow-up analysis of sequences of solutions with bounded Morse index, via suitable a priori pointwise estimates (see \cite{MR2063399}). In this respect, the regularity assumption on $\partial\Omega$ simplifies the treatment of possible concentrati
on phenomena towards the boundary. The argument, which holds for solutions which possibly change sign, is inspired by \cite{MR2825606}, where the case of positive solutions is treated. Once Theorem \ref{thm:bbd_index} is established, in case $p\geq 1 + 4/
N$ two questions arise, namely: \begin{enumerate} \item is it possible to provide lower bounds for $\sup{\mathfrak{A}}_k$? Is it true that $\sup{\mathfrak{A}}_k$ is strictly increasing in $k$, or, at least, that $\sup{\mathfrak{A}}_k > \sup{\mathfrak{A}}_
1$ for some $k$? \item is \eqref{eq:main_prob_U} solvable for every $\rho\in(0,\sup{\mathfrak{A}}_k)$, or at least can we characterize some subinterval of solvability? \end{enumerate} It is clear that both issues can be addressed by characterizing values
of $\rho$ for which existence (and multiplicity) of solutions with bounded Morse index can be guaranteed. To this aim, it can be useful to restate problem \eqref{eq:main_prob_U} as \begin{equation}\label{eq:main_prob_u} \begin{cases} -\Delta u + \lambda u
= \mu|u|^{p-1}u & \text{in }\Omega,\\ \int_\Omega u^2\,dx = 1, \quad u=0 & \text{on }\partial\Omega, \end{cases} \qquad\text{where}\quad \begin{cases} U=\sqrt{\rho} u\\ \mu = \rho^{(p-1)/2}, \end{cases} \end{equation} where now $\mu>0$ is prescribed. Sin
ce \begin{equation} \label{Emu} \text{both } \mathcal{E}_{\mu}(u) := \frac{1}{2}\int_{\Omega}|\nabla u|^2- \frac{\mu}{p+1}\int_{\Omega}| u|^{p+1} \qquad \text{and }{\mathcal{M}}={\mathcal{M}}_1=\{u : \|u\|_{L^2(\Omega)}=1\} \end{equation} are invariant und
er the ${\mathbb{Z}}_2$-action of the involution $u\mapsto -u$, solutions of \eqref{eq:main_prob_u} can be found via min-max principles in the framework of index theories (see e.g. \cite[Ch. II.5]{St_2008}). Notice that in the supercritical case ${\mathcal
{E}}_\mu$ is not bounded from below on ${\mathcal{M}}$. Following \cite{MR3318740}, it can be convenient to parameterize solutions to \eqref{eq:main_prob_u} with respect to the $H^1_0$-norm, therefore we introduce the sets \begin{equation}\label{eq:defBU}
\mathcal{B}_\alpha:=\left\{u\in {\mathcal{M}}:\,\int_\Omega |\nabla u|^2\,dx<\alpha\right\},\quad\quad \mathcal{U}_\alpha:=\left\{u\in {\mathcal{M}}:\,\int_\Omega |\nabla u|^2\,dx=\alpha\right\}. \end{equation} Introducing the first Dirichlet eigenvalue o
f $-\Delta$ in $H^1_0(\Omega)$, $\lambda_1(\Omega)$, we have that the sets above are non-empty whenever $\alpha> \lambda_1(\Omega)$. Since we are interested in critical points having Morse index bounded from above, following \cite{MR968487,MR954951,MR99126
4} we introduce the following notion of genus. \begin{definition}\label{def:genus} Let $A\subset H^1_0(\Omega)$ be a closed set, symmetric with respect to the origin (i.e. $-A=A$). We define the \emph{genus} $\gamma$ of a $A$ as \[ \gamma(A) := \sup\{m : \
exists h \in C({\mathbb{S}}^{m-1};A),\, h(-u)=-h(u)\}. \] Furthermore, we define \[ \Sigma_{\alpha}=\{A\subset \overline{\mathcal{B}}_\alpha: A\text{ is closed and }-A=A\}, \qquad \Sigma^{(k)}_{\alpha}=\{A\in \Sigma_{\alpha} : \gamma(A)\ge k\}, \] \end{def
inition} We remark that this notion of genus is different from the classical one of \emph{Krasnoselskii genus}, which is well suited for estimates of the Morse index from below, rather than above. Nonetheless, $\gamma$ shares with the Krasnoselskii genus m
ost of the main properties of an index \cite{MR0163310,MR0065910}. In particular, by the Borsuk-Ulam Theorem, any set $A$ homeomorphic to the sphere ${\mathbb{S}}^{m-1} := \partial B_1 \subset {\mathbb{R}}^m$ has genus $\gamma(A) = m$. Furthermore, we show
in Section \ref{sec:2const} that $\Sigma^{(k)}_{\alpha}$ is not empty, provided $\alpha>\lambda_k(\Omega)$ (the $k$-th Dirichlet eigenvalue of $-\Delta$ in $H^1_0(\Omega)$). Equipped with this notion of genus we provide two different variational principl
es for solutions of \eqref{eq:main_prob_u} (and thus of \eqref{eq:main_prob_U}). The first one is based on a variational problem with \emph{two constraints}, which was exploited as the main tool in proving the results in \cite{MR3318740}. \begin{theorem}\l
abel{thm:genus_2constr} Let $k\geq1$ and $\alpha>\lambda_{k}(\Omega)$. Then \begin{equation} \label{maxmin} M_{\alpha,\,k}:= \sup_{A\in\Sigma^{(k)}_{\alpha}}\inf_{u\in A}\int_{\Omega}|u|^{p+1} \end{equation} is achieved on ${\mathcal{U}}_\alpha$, and there
exists a critical point $u_\alpha\in {\mathcal{M}}$ such that, for some $\lambda_\alpha\in{\mathbb{R}}$ and $\mu_\alpha>0$, \begin{equation} \label{lagreq} \int_\Omega|\nabla u_\alpha|^2 = \alpha\qquad\text{and}\qquad -\Delta u_\alpha+\lambda_\alpha\,u_\a
lpha=\mu_\alpha |u_\alpha|^{p-1}u_\alpha\quad \text{in }\Omega. \end{equation} \end{theorem} As a matter of fact, the results in \cite{MR3318740} were obtained by a detailed analysis of the map $\alpha \mapsto \mu_\alpha$ in the case $k=1$, i.e. when deali
ng with \[ M_{\alpha,1} = \max\left\{\|u\|_{L^{p+1}}^{p+1} : \|u\|_{L^2}^2=1,\,\|\nabla u\|_{L^2}^2=\alpha \right\}. \] In the present paper we do not investigate the properties of the map $\alpha \mapsto \mu_\alpha$ for general $k$, but we rather prefer
to exploit the characterization of $M_{\alpha,k}$ in connection with a second variational principle, which deals with only \emph{one constraint}. \begin{theorem}\label{thm:genus_1constr} Let $1+{N}/{4}\leq p<2^*-1$. There exists a sequence $(\hat \mu_k)_k$
(depending on $\Omega$ and $p$) such that, for every $k\geq 1$ and $0<\mu<\hat \mu_k$, the value \begin{equation} \label{infsuplev} c_k:= \inf_{A\in\Sigma^{(k)}_{\alpha}} \sup_{A}{\mathcal{E}}_\mu, \end{equation} is achieved in $\mathcal{B}_\alpha$, for a
suitable $\alpha>\lambda_{k}(\Omega)$. Furthermore there exists a critical point $u_\mu\in {\mathcal{M}}$ such that, for some $\lambda_\mu\in{\mathbb{R}}$, \[ -\Delta u_\mu+\lambda_\mu\,u_\mu=\mu |u_\mu|^{p-1}u_\mu\quad \text{in }\Omega, \] $\|\nabla u\|_
{L^2}^2<\alpha$, and $m(u_\mu)\le k$. \end{theorem} \begin{remark} Of course, if $p<1+4/N$, the above theorem holds with $\hat\mu_k=+\infty$ for every $k$. \end{remark} \begin{corollary} Let $\hat \rho_k := \hat \mu_k^{2/(p-1)}$. Then \[ (0,\hat\rho_k) \su
bset {\mathfrak{A}}_k. \] \end{corollary} The link between Theorem \ref{thm:genus_2constr} and Theorem \ref{thm:genus_1constr} is that we can provide explicit estimates of $\hat \mu_k$ (and hence of $\hat\rho_k$) in terms of the map $\alpha\mapsto M_{\alph
a,k}$ (see Section \ref{sec:1const}). We stress that the above results hold for any Lipschitz $\Omega$. As a first consequence, this allows to extend the existence result in \cite{MR3318740} to non-radial domains. \begin{theorem}\label{thm:intro_GS} For e