- David Shih (Rutgers University)
- Tilman Plehn
To obtain information on the still unknown sources of ultra-high-energy cosmic rays (UHECRs), a combined fit of the observed energy spectrum and depths of the shower maximum can be used, which constrains characteristic parameters of the sources. During propagation from the sources to Earth, UHECRs can experience numerous stochastic processes such that no explicit inverse function, which would...
I describe a new machine learning algorithm, Via Machinae, to identify cold stellar streams in data from the Gaia telescope. Via Machinae is based on ANODE, a general method that uses conditional density estimation and sideband interpolation to detect local overdensities in the data in a model agnostic way. By applying ANODE to the positions, proper motions, and photometry of stars observed by...
I will give a very brief (and incomplete) review on quantum machine learning techniques and focus then on novel quantum computing approaches for the task of finding a solution to an optimisation problem. I will then give explicit examples how quantum machine learning techniques can be used for classification tasks and to calculate solutions to nonperturbative problems in quantum field theory.