Tuesdays 10:30 - 11:30 | Fridays 11:30 - 12:30
Showing votes from 2016-02-02 11:30 to 2016-02-05 12:30 | Next meeting is Friday May 8th, 11:30 am.
When ultralight axion dark matter encounters a static magnetic field, it sources an effective electric current that follows the magnetic field lines and oscillates at the axion Compton frequency. We propose a new experiment to detect this axion effective current. In the presence of axion dark matter, a large toroidal magnet will act like an oscillating current ring, whose induced magnetic flux can be measured by an external pickup loop inductively coupled to a SQUID magnetometer. We consider both resonant and broadband readout circuits and show that a broadband approach has advantages at small axion masses. We estimate the reach of this design, taking into account the irreducible sources of noise, and demonstrate potential sensitivity to axion dark matter with masses in the range of 10^{-13} eV to 10^{-6} eV, particularly the QCD axion with a GUT-scale decay constant.
Over the past few decades, an anomalous 511 keV gamma-ray line has been observed from the centre of the Milky Way. Dark matter (DM) in the form of light (< 10 MeV) WIMPs annihilating into electron-positron pairs has been one of the leading hypotheses of the observed emission. Here we show that this explanation is ruled out by the latest cosmological data, suggesting an astrophysical or more exotic DM source of the signal.
One of the main obstacles for extracting the Cosmic Microwave Background (CMB) from mm/submm observations is the pollution from the main Galactic components: synchrotron, free-free and thermal dust emission. The feasibility of using simple neural networks to extract CMB has been demonstrated on both temperature and polarization data obtained by the WMAP satellite. The main goal of this paper is to demonstrate the feasibility of neural networks for extracting the CMB signal from the Planck polarization data with high precision. Both auto-correlation and cross-correlation power spectra within a mask covering about 63 percent of the sky have been used together with a 'high pass filter' in order to minimize the influence of the remaining systematic errors in the Planck Q and U maps. Using the Planck 2015 released polarization maps, a BB power spectrum have been extracted by \textit{Multilayer Perceptron} neural networks. This spectrum contains a bright feature with signal to noise ratios $\simeq$ 4.5 within 200 $\leq$ l $\leq$ 250. The spectrum is significantly brighter than the BICEP2 2015 spectrum, with a spectral behaviour quite different from the 'canonical' models (weak lensing plus B-modes spectra with different tensor to scalar ratios). The feasibility of the neural network to remove the residual systematics from the available Planck polarization data to a high level has been demonstrated.
The decay rates of quasistable states in quantum field theories are usually calculated using instanton methods. Standard derivations of these methods rely in a crucial way upon deformations and analytic continuations of the physical potential, and on the saddle point approximation. While the resulting procedure can be checked against other semi-classical approaches in some one-dimensional cases, it is challenging to trace the role of the relevant physical scales, and any intuitive handle on the precision of the approximations involved are at best obscure. In this paper, we use a physical definition of the tunneling probability to derive a formula for the decay rate in both quantum mechanics and quantum field theory directly from the Minkowski path integral, without reference to unphysical deformations of the potential. There are numerous benefits to this approach, from non-perturbative applications to precision calculations and aesthetic simplicity.