AstroNuc 2026 will be held on March 10-13, 2026 at the University of Arizona, Tucson, Arizona, USA. 

The workshop will bring together observers, theorists and experimentalists working in nuclear astrophysics. Our goal is to discuss advancements in stellar and explosive nucleosynthesis, including their role in enriching galaxies with heavy elements, leveraging insights from recent time domain astronomy initiatives. 

JWST and LSST have begun releasing remarkable new data on transients, making an understanding of the nuclear processes in their final stages essential for accurate interpretation. Complementing these efforts, SDSS-V is delivering all-sky spectroscopic observations that provide critical insights into chemical enrichment and evolution. In the coming years, gravitational-wave detections of compact object mergers with LVK and Cosmic Explorer are expected to shed light on the formation of heavy elements and the rate of key nuclear reactions in stars, which will be further constrained in new laboratory measurements. At the same time, the growing use of machine learning in both data analysis and simulations, which is manifested in new institutes like SkAI and CosmicAI, and a growing number of publications, is opening new avenues for nuclear astrophysics research. Together, these recent and anticipated advances are transforming our ability to study nucleosynthesis in stars and stellar explosions.

We will review the current state of the field and explore opportunities for new collaborations, building a bridge across the different communities. Through a combination of presentations, hands-on introductory sessions, and discussions, we will identify the most pressing open questions, highlight key issues such as nuclear reaction rate uncertainties and computational challenges, and develop strategies to address them from a multidisciplinary perspective, with a particular focus on the use of machine learning approaches.

Amongst the topics of interest are: stellar nucleosynthesis, explosive nucleosynthesis,  stellar archeology, chemical evolution, machine learning applications, time domain astronomy, reaction rates measurements, mass measurements, r-process, s-process, i-process, core collapse supernovae, type 1a supernovae, and more...