PAUS originated in the context of the PAU Project, funded, in 2007, by the Consolider Ingenio 2010 Program of the (at the time) Spanish Ministry of Research and Innovation. The PAU project was approved in 2007 and ended in 2014. Its main deliverable was the PAUCam camera, built by 5 of the 7 groups that were originally in the Consolider Project, namely from CIEMAT and IFT (in Madrid), and from IEEC, PIC and IFAE (in Barcelona). These groups also developed the large amount of software needed for the control of PAUCam and for the data processing from their production at the Telescope to their analysis at the labs [3,4]. The same groups also collaborate closely in other projects, notably in DES, DESI and EUCLID, described elsewhere in this report.
PAUCam operates as a Visitor’s Instrument at the prime focus of the William Herschel Telescope (WHT) in the Canary Island of La Palma. Starting in 2016 other groups have joined the PAUS Collaboration, namely from Durham University, Plymouth University and University College of London in the UK, from Leiden Observatory in the Netherlands, from ETH in Switzerland, and from Bonn University in Germany. A group from Tsinghua University in Beijing, China, joined in 2021. The observing nights are granted from the Isaac Newton Group of Telescopes (ING), a Consortium of the United Kingdom, the Netherlands and Spain, that operates several telescopes at the La Palma site, the WHT among them. The proposals for observation periods are submitted twice per year to the TACs (Time Allocation Committees) in those three countries, that advise the ING Management.
Since first light in 2015 until the end of 2019, PAUS has observed for about 215 nights with high efficiency (only 8.9 effective nights lost), but unfortunately with very bad weather conditions, particularly in the fall and winter. For that reason the effective number of good observing nights has only been half of the above, namely 101 nights of good data. PAUS has chosen to observe in fields where redshift data is available from other observations, either photometric or spectroscopic. These include the COSMOS field [5], containing over one million galaxies, collected from several telescopes (in satellites and ground-based), with a coverage of 2 square degrees in the equatorial region, and the W1, W2, W3, W4 fields of the CFHTLS [6]. The COSMOS field has been completely covered by PAUS while the CFHTLS fields are not yet completed. In terms of square degrees we do not quote detailed numbers, as they depend on the particular analysis being pursued and also vary depending on the observation strategies. A rough number is 0.7 square degrees per good night of observation.
During the two years 2020 and 2021 no data has been taken, due to ongoing work in the WHT telescope needed to accommodate the future WEAVE spectrometer, and also to the occurrence of two major disruptions in 2021, the Covid-19 pandemic and the eruption of the Cumbre Vieja volcano in the south of the La Palma island. Future running of PAUCam will be possible after the installation of WEAVE, but detailed plans are not yet developed.
In addition to the 13 PAUS publications in previous years, 4 new papers have been published in 2023 and are listed below. Papers 1 and 4 explore various methods to calculate and improve the photo-z determination made possible by the narrow-band filters available in PAUS, both in the PAUS data alone or in combination with other projects, such as Euclid. Paper 4 deals with the detection of galaxy-pairs in the PAUS data, which will be publicly available.
The method to select the pairs makes use of the PAUS narrow filters and was applied to the total sample of galaxies provided by PAUS and to a subset with high-quality redshift estimates. Finally, the most relevant result we achieved was determining the mean mass for several subsets of galaxy pairs selected according to their total luminosity, colour and redshift, using galaxy-galaxy lensing estimates. Finally, paper 2 explains in detail the software packages developed for the data reduction in the whole PAUS project, and it is invaluable to understand the data reduction algorithms.
PUBLICATIONS