Diverse Metallicities in Protoclusters at z about 3.4 detected by Deep Learning

We present spectroscopic follow-up observations with Subaru/MOIRCS of four protocluster candidate regions identified by the deep-learning model PCFNet. In three candidate regions, we confirm four protoclusters at z = 3.316, 3.403, 3.408 and 3.425, exhibiting galaxy density peaks over five times the uniform distribution. The detection rate of confirmed members aligns with PCFNet's predictions, underscoring its effectiveness. Analysis of spectral energy distributions (SEDs), incorporating up to ten photometric bands (uu*grizyJHK), reveals that protocluster members lie on the star-formation main sequence. The masses of the most massive halos in the protoclusters are estimated from the most massive stellar mass of the member galaxies, yielding M halo/M=12.4 - 12.8, which are consistent with those at this redshift predicted by cosmological simulations and are comparable to those of the progenitors of typical local clusters (M halo z=0 about10 14M). Using the Voronoi Tessellation Monte Carlo technique based on the probability of protocluster membership from PCFNet, we find that our protoclusters exhibit a significantly higher SFRD than the cosmic SFRD at z about3.4. Based on the [Oiii]/H β emission line ratio, two protoclusters show marginally (1.4 - 2σ) higher average metallicities than the field, while the other protoclusters are statistically consistent with the field. These diverse metallicities highlight the environmental impact within protoclusters detected by PCFNet, likely reflecting the complex opposing interplay between metal-rich gas recycling and metal-poor gas inflow, which may depend on the surrounding environment of each protocluster. This work demonstrates PCFNet's capability to unveil diverse samples of high-redshift protoclusters, paving the way for a more comprehensive understanding of their role in galaxy evolution.