The Deep Convolutional Neural Networks (DCNNs) have been a popular tool for image generation and restoration. In this work, we applied DCNNs to the problem of inpainting non-Gaussian astrophysical ...signal, in the context of Galactic diffuse emissions at the millimetric and submillimetric regimes, specifically Synchrotron and Thermal Dust emissions. Both signals are affected by contamination at small angular scales due to extragalactic radio sources (the former) and dusty star-forming galaxies (the latter). We compare the performance of the standard diffusive inpainting with that of two novel methodologies relying on DCNNs, namely Generative Adversarial Networks and Deep-Prior. We show that the methods based on the DCNNs are able to reproduce the statistical properties of the ground-truth signal more consistently with a higher confidence level. The Python Inpainter for Cosmological and AStrophysical SOurces (PICASSO) is a package encoding a suite of inpainting methods described in this work and has been made publicly available at http://giuspugl.github.io/picasso/.
Ali CMB Polarization Telescope (AliCPT) is the first Cosmic Microwave Background (CMB) polarimeter with a large focal plane camera to be deployed in the Northern Hemisphere, in the Tibetan Plateau. ...Here we present the design of a dichroic (90/150 GHz) focal plane camera capable of hosting up to 32,376 Transition-Edge Sensor (TES) bolometers operating from a base temperature of 280 mK. Detectors are fabricated as monolithic arrays of 1,704 feedhorn-coupled and polarization-sensitive TES bolometers that are packaged in independent modules and read out with a microwave multiplexing architecture. A custom RFSoC-based system manages the multiplexing readout. Prototype AliCPT pixels have been fabricated and characterized, demonstrating passband performance within 2.5% of design and cross-polarization systematic sensitivity <inline-formula><tex-math notation="LaTeX">\leq</tex-math></inline-formula>2%.
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 realistic features from a ...large dataset. In this work, we applied the problem of inpainting non-Gaussian signal, in the context of Galactic diffuse emissions at the millimetric and sub-millimetric regimes, specifically Synchrotron and Thermal Dust emission. Both of them are affected by contamination at small angular scales due to extra-galactic radio sources (the former) and to dusty star-forming galaxies (the latter). We consider the performances of a nearest-neighbors inpainting technique and compare it with two novels methodologies relying on generative Neural Networks. We show that the generative network is able to reproduce the statistical properties of the ground truth signal more consistently with high confidence level. The Python Inpainter for Cosmological and AStrophysical SOurces (PICASSO) is a package encoding a suite of inpainting methods described in this work and has been made publicly available.
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 incorporation may ...lead to less-than-optimal performance, especially for the lowest TM mode. Additionally, the stronger confinement of the electric field inside the dielectrics can exacerbate mode mixings, in particular for higher-order modes. Case studies have been carried out using a combination of analytical solutions and numerical simulations. The findings indicate dielectric cavities employing the \(\text{TM}_{010}\) mode experience a significant reduction in sensitivity when compared to a similar search conducted in a cavity at equivalent frequency using no dielectrics.
We propose a Rydberg-atom-based single-photon detector for signal readout in dark matter haloscope experiments between 40 \({\mu}\)eV and 200 \({\mu}\)eV (10 GHz and 50 GHz). At these frequencies, ...standard haloscope readout using linear amplifiers is limited by quantum measurement noise, which can be avoided by using a single-photon detector. Our single-photon detection scheme can offer scan rate enhancements up to a factor of \(10^4\) over traditional linear amplifier readout, and is compatible with many different haloscope cavities. We identify multiple haloscope designs that could use our Rydberg-atom-based single-photon detector to search for QCD axions with masses above 40 \({\mu}\)eV (10 GHz), currently a minimally explored parameter space.
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