22 citations · 71 across the 7 of their papers we have counts for
7 papers
Search for Dark Photons between 16.96--19.52 eV with the HAYSTAC Experiment
Xiran Bai, A. Droster, J. Echevers +21
We report dark photon results from HAYSTAC Phase II using data from previously reported axion searches. Additionally, we present an analysis of an unpublished dataset covering a re…
Rydberg-atom-based single-photon detection for haloscope axion searches
Eleanor Graham, Sumita Ghosh, Yuqi Zhu +8
We propose a Rydberg-atom-based single-photon detector for signal readout in dark matter haloscope experiments between 40 eV and 200 eV (10 GHz and 50 GHz). At these frequenc…
On the use of dielectric elements in axion searches with microwave resonant cavities
Xiran Bai, Michael J. Jewell, Steve K. Lamoreaux +2
This study explores the primary effects of dielectric materials in a resonant cavity-based search for axion dark matter. While dielectrics prove beneficial in numerous cases, their…
New Results from HAYSTAC's Phase II Operation with a Squeezed State Receiver
HAYSTAC Collaboration, M. J. Jewell, A. F. Leder +26
A search for dark matter axions with masses has been performed using the HAYSTAC experiment's squeezed state receiver to achieve sub-quantum limited noise. This rep…
An improved synthetic signal injection routine for the Haloscope At Yale Sensitive To Axion Cold dark matter (HAYSTAC)
Yuqi Zhu, M. J. Jewell, Claire Laffan +6
Microwave cavity haloscopes are among the most sensitive direct detection experiments searching for dark matter axions via their coupling to photons. When the power of the expected…
The design of the Ali CMB Polarization Telescope receiver
Maria Salatino, Jason E. Austermann, Keith L. Thompson +72
Ali CMB Polarization Telescope (AliCPT-1) is the first CMB degree-scale polarimeter to be deployed on the Tibetan plateau at 5,250m above sea level. AliCPT-1 is a 90/150 GHz 72 cm…
Inpainting Galactic Foreground Intensity and Polarization maps using Convolutional Neural Network
Giuseppe Puglisi, Xiran Bai
Deep convolutional neural networks have been a popular tool for image generation and restoration. The performance of these networks is related to the capability of learning realist…