English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We use the panchromatic SED-fitting code Prospector to measure the galaxylogM$^*$-logSFR relationship (the `star-forming sequence') across $0.2 < z <3.0$ using the COSMOS-2015 and 3D-HST UV-IR photometric catalogs. Wedemonstrate that the chosen method of identifying star-forming galaxiesintroduces a systematic uncertainty in the inferred normalization and width ofthe star-forming sequence, peaking for massive galaxies at $\sim 0.5$ dex and$\sim0.2$ dex respectively. To avoid this systematic, we instead parameterizethe density of the full galaxy population in the logM$^*$-logSFR-redshift planeusing a flexible neural network known as a normalizing flow. The resultingstar-forming sequence has a low-mass slope near unity and a much flatter slopeat higher masses, with a normalization $0.2-0.5$ dex lower than typicalinferences in the literature. We show this difference is due to thesophistication of the Prospector stellar populations modeling: thenonparametric star formation histories naturally produce higher masses whilethe combination of individualized metallicity, dust, and star formation historyconstraints produce lower star formation rates than typical UV+IR formulae. Weintroduce a simple formalism to understand the difference between SFRs inferredfrom spectral energy distribution fitting and standard template-basedapproaches such as UV+IR SFRs. Finally, we demonstrate the inferredstar-forming sequence is consistent with predictions from theoretical models ofgalaxy formation, resolving a long-standing $\sim0.2-0.5$ dex offset withobservations at $0.5<z<3$. The fully trained normalizing flow including anonparametric description of $\rho(\log{\rm M}^*,\log{\rm SFR},z)$ is madeavailable online to facilitate straightforward comparisons with future work.

A New Census of the 0.2< z <3.0 Universe, Part II: The Star-Forming Sequence