Galaxy formation and evolution

Abstract:

Living Labs are increasingly used in European research and innovation programmes as collaborative environments for experimentation and stakeholder participation. While prior research has examined their participatory and governance features, less is known about their structural role in configuring entrepreneurial ecosystems. This paper examines whether EU-funded Living Lab consortia operate as deliberately designed ecosystem architectures and whether the transition from Horizon 2020 to Horizon Europe is associated with changes in actor diversity, firm and SME embeddedness, and formal coordination. Drawing on CORDIS metadata for 350 projects explicitly labelled as Living Labs, the study constructs project-level indicators of actor diversity, entrepreneurial embeddedness, private-sector coordination, and geographic scope. The observed Horizon Europe sample contains more Living-Lab-labelled projects than Horizon 2020, although Horizon Europe is ongoing and the count should be interpreted as observed-to-date label use rather than final programme expansion. Descriptively, Horizon Europe projects show higher actor diversity, wider geographic breadth, lower firm share, and lower private-sector coordination. In regression models, the actor-diversity difference is positive but marginal, the adjusted firm-share difference is not statistically distinguishable from zero, and the decline in private-sector coordination remains significant. Because private-sector coordination is a proxy for formal entrepreneurial orchestration rather than a direct measure of entrepreneurial influence, the evidence is associational and should be interpreted cautiously. The paper contributes to entrepreneurship and innovation management research by suggesting that policy-designed ecosystems may face a governance tension between ecosystem inclusiveness and formal entrepreneurial agency.

Abstract:

ABSTRACT Understanding how galaxies populate and grow within dark matter haloes is essential for linking the observed evolution of galaxies to the hierarchical growth of structure. We present a galaxy clustering analysis using optical and near-infrared data from the UltraVISTA and VIDEO surveys covering 9.3 deg$^2$ across the COSMOS, XMM-LSS, and ECDF-S fields, $\sim 5\times$ larger than previous comparable studies, providing sufficient volume to determine the halo occupation of the most massive galaxies to $z\sim 4$. We measure the angular two-point correlation function for stellar-mass-selected galaxies over $0.25\lt z\lt 4$ and by combining the three fields, we reduce the cosmic variance by a factor of $\sim 2$ compared to the individual fields. The stellar-to-halo mass relation peaks at a halo mass of $M_{h}\approx 10^{12}$ M$_{\odot }$ and is a maximum at $z\sim 1$. For the most massive galaxies, the peak halo mass ($M_{h}^{\rm peak}$) increases from z = 1 to z ~ 0, while the peak stellar mass in such haloes remains approximately constant, indicating that at $z\lt 1$ massive galaxy formation becomes less efficient. We also find a steady increase in the satellite fraction since $z\sim 1$, from which we infer that massive haloes continue to grow hierarchically while their central galaxies experience suppressed stellar-mass growth. We suggest this is due to the central massive galaxies having their growth controlled by feedback from active galactic nuclei, likely from low-power stochastic radio emission.

Abstract:

ABSTRACT Determining the relationship between star formation rate (SFR) and the radio luminosity ($L_{1.4}$) is critical if we are to trace the star formation history of the Universe dust-agnostically using current and future radio facilities. However, until now, such work has relied on potentially biased binary classifications of sources to remove contaminating active galactic nuclei (AGNs). We present a new, statistically driven methodology for deriving the SFR–$L_{1.4}$ relation, removing the need for problematic cuts. We use a Bayesian hierarchical mixture model fit to the radio-detected sources in the deep MIGHTEE COSMOS DR1 catalogue, incorporating the full SFR posterior probability distributions generated by state-of-the-art spectral energy distribution fitting code GRAHSP. This allows us to probabilistically determine a mean SFR–$L_{1.4}$ relation for the SF-dominated galaxies, whilst accounting for changing fractions of SF dominated sources across redshift, radio luminosity, and stellar mass ranges. We find that the SFR–radio luminosity correlation exhibits a significant dependence on redshift, but a stellar mass dependence that is weaker than previous studies. Our resultant SFR–radio correlation is $\log _{10}(\text{SFR}/{\rm M}_{\odot }\, \text{yr}^{-1}) = 0.790\times (\log _{10}(L_{1.4}/\text{W {}Hz}^{-1})-23) + 1.244 \times (1+z)^{0.122} -0.033 \times (\log _{10}(M_*/{\rm M}_{\odot })-10)$, with an intrinsic scatter of 0.178 dex. We show that this redshift evolution could be explained by a moderate evolution in the radio spectral index of SF galaxies. We attribute the lack of observed strong dependence on stellar mass, compared to recent studies, to the novel statistical approach that does not rely on cuts to remove AGNs.

Abstract:

Abstract Radio galaxies play a significant role in galaxy evolution through feedback mechanisms, making it important to characterize the environments in which they reside. We measure the cross-correlation between the positions of radio sources in the MIGHTEE survey with cosmic microwave background lensing measurements from the Atacama Cosmology Telescope over 20 deg2 to flux densities S1.4 GHz > 40 μJy, detecting the signal at ∼4σ significance. By combining this with auto-correlation measurements of low- and high-redshift radio samples, we constrain the redshift evolution of the galaxy bias parameter, b(z). Fitting different models for the redshift evolution of the bias, we find that both a model inversely proportional to the linear growth factor, $b(z)=(1.63^{+0.19}_{-0.22})/D(z)$, and a model where bias grows linearly with redshift, $b(z)=(0.49^{+0.44}_{-0.32})+(1.62^{+0.37}_{-0.51})z$, provide comparably good fits to the data, with the current measurements unable to distinguish between them. Using a radio luminosity function, we estimate the fraction of sources that are active galactic nuclei (AGNs) or star-forming galaxies (SFGs) as a function of redshift, and model the individual contributions of AGNs and SFGs to the total bias. This approach allows us to measure the bias of AGNs and SFGs without individual source classifications. Though no single model is favoured significantly, the best-fitting model gives $b_{\rm AGN}(z) = (2.60^{+0.65}_{-0.91})/D(z)$ compared to $b_{\rm SFG}(z) = (0.52^{+0.47}_{-0.34})/D(z)$. Incorporating SFG bias measurements from previous work as a prior tightens these constraints to $b_{\rm AGN}(z) = (1.96^{+0.37}_{-0.40})/D(z)$ and $b_{\rm SFG}(z) = (0.90^{+0.06}_{-0.06})/D(z)$.