Search for: All records

We present ALMA band 6 images of the 12CO, 13CO, and C18O J = 2-1 line emissions for the circumstellar disc around HD 169142, at ∼8 au spatial resolution. We resolve a central gas-depleted cavity, along with two independent near-symmetric ring-like structures in line emission: a well-defined inner gas ring [∼25 au] and a second relatively fainter and diffuse outer gas ring [∼65 au]. We identify a localized super-Keplerian feature or vertical flow with a magnitude of ∼75 ms−1 in the 12CO map. This feature has the shape of an arc that spans azimuthally across a position angle range of −60° to 45° and radially in between the B1[26au] and B2[59au] dust rings. Through reconstruction of the gas surface density profile, we find that the magnitude of the background perturbations by the pressure support and self-gravity terms are not significant enough to account for the kinematic excess. If of planetary origin, the relative depletion in the gas-density profile would suggest a 1 MJ planet. In contrast, the central cavity displays relatively smooth kinematics, suggesting either a low-mass companion and/or a binary orbit with a minimal vertical velocity component.

The Breakthrough Listen Initiative is conducting a program using multiple telescopes around the world to search for “technosignatures”: artificial transmitters of extraterrestrial origin from beyond our solar system. The Very Energetic Radiation Imaging Telescope Array System (VERITAS) Collaboration joined this program in 2018 and provides the capability to search for one particular technosignature: optical pulses of a few nanoseconds in duration detectable over interstellar distances. We report here on the analysis and results of dedicated VERITAS observations of Breakthrough Listen targets conducted in 2019 and 2020 and of archival VERITAS data collected since 2012. Thirty hours of dedicated observations of 136 targets and 249 archival observations of 140 targets were analyzed and did not reveal any signals consistent with a technosignature. The results are used to place limits on the fraction of stars hosting transmitting civilizations. We also discuss the minimum pulse sensitivity of our observations and present VERITAS observations of CALIOP: a space-based pulsed laser on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations. The detection of these pulses with VERITAS, using the analysis techniques developed for our technosignature search, allows a test of our analysis efficiency and serves as an important proof of principle.

The direct search for dark matter in the form of weakly interacting massive particles (WIMP) is performed by detecting nuclear recoils produced in a target material from the WIMP elastic scattering. The experimental identification of the direction of the WIMP-induced nuclear recoils is a crucial asset in this field, as it enables unmistakable modulation signatures for dark matter. The Recoil Directionality (ReD) experiment was designed to probe for such directional sensitivity in argon dual-phase time projection chambers (TPC), that are widely considered for current and future direct dark matter searches. The TPC of ReD was irradiated with neutrons at the INFN Laboratori Nazionali del Sud. Data were taken with nuclear recoils of known directions and kinetic energy of 72 keV, which is within the range of interest for WIMP-induced signals in argon. The direction-dependent liquid argon charge recombination model by Cataudella et al. was adopted and a likelihood statistical analysis was performed, which gave no indications of significant dependence of the detector response to the recoil direction. The aspect ratioRof the initial ionization cloud is$$R < 1.072$$$R<1.072$with 90 % confidence level.

We present a novel approach for the search of dark matter in the DarkSide-50 experiment, relying on Bayesian Networks. This method incorporates the detector response model into the likelihood function, explicitly maintaining the connection with the quantity of interest. No assumptions about the linearity of the problem or the shape of the probability distribution functions are required, and there is no need to morph signal and background spectra as a function of nuisance parameters. By expressing the problem in terms of Bayesian Networks, we have developed an inference algorithm based on a Markov Chain Monte Carlo to calculate the posterior probability. A clever description of the detector response model in terms of parametric matrices allows us to study the impact of systematic variations of any parameter on the final results. Our approach not only provides the desired information on the parameter of interest, but also potential constraints on the response model. Our results are consistent with recent published analyses and further refine the parameters of the detector response model.