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LISA Cosmology Working Group(Bartolo, N. et al), & Figueroa, D. G. (2022). Probing anisotropies of the Stochastic Gravitational Wave Background with LISA. J. Cosmol. Astropart. Phys., 11, 009–65pp.
Abstract: We investigate the sensitivity of the Laser Interferometer Space Antenna (LISA) to the anisotropies of the Stochastic Gravitational Wave Background (SGWB). We first discuss the main astrophysical and cosmological sources of SGWB which are characterized by anisotropies in the GW energy density, and we build a Signal-to-Noise estimator to quantify the sensitivity of LISA to different multipoles. We then perform a Fisher matrix analysis of the prospects of detectability of anisotropic features with LISA for individual multipoles, focusing on a SGWB with a power-law frequency profile. We compute the noise angular spectrum taking into account the specific scan strategy of the LISA detector. We analyze the case of the kinematic dipole and quadrupole generated by Doppler boosting an isotropic SGWB. We find that beta Omega(GW) similar to 2 x 10(-11) is required to observe a dipolar signal with LISA. The detector response to the quadrupole has a factor similar to 10(3) beta relative to that of the dipole. The characterization of the anisotropies, both from a theoretical perspective and from a map-making point of view, allows us to extract information that can be used to understand the origin of the SGWB, and to discriminate among distinct superimposed SGWB sources.
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Herrero-Garcia, J., Patrick, R., & Scaffidi, A. (2022). A semi-supervised approach to dark matter searches in direct detection data with machine learning. J. Cosmol. Astropart. Phys., 02, 039–19pp.
Abstract: The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.
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Reid, B. A., Verde, L., Jimenez, R., & Mena, O. (2010). Robust neutrino constraints by combining low redshift observations with the CMB. J. Cosmol. Astropart. Phys., 01(1), 003–21pp.
Abstract: We illustrate how recently improved low-redshift cosmological measurements can tighten constraints on neutrino properties. In particular we examine the impact of the assumed cosmological model on the constraints. We first consider the new HST H-0 = 74.2 +/- 3.6 measurement by Riess et al. (2009) and the sigma(8)(Omega(m)/0.25)(0.41) = 0.832 +/- 0.033 constraint from Rozo et al. (2009) derived from the SDSS maxBCG Cluster Catalog. In a ACDM model and when combined with WMAP5 constraints, these low-redshift measurements constrain Sigma m(v) < 0.4 eV at the 95% confidence level. This bound does not relax when allowing for the running of the spectral index or for primordial tensor perturbations. When adding also Supernovae and BAO constraints, we obtain a 95% upper limit of Sigma m(v) < 0.3eV. We test the sensitivity of the neutrino mass constraint to the assumed expansion history by both allowing a dark energy equation of state parameter w not equal -1 and by studying a model with coupling between dark energy and dark matter, which allows for variation in w, Omega(k), and dark coupling strength xi. When combining CMB, H-0 and the SDSS LRG halo power spectrum from Reid et al. 2009, we find that in this very general model, Sigma m(v) < 0.51 eV with 95% confidence. If we allow the number of relativistic species N-rel to vary in a ACDM model with Sigma m(v) = 0, we find N-rel = 3.76(-0.68)(+0.63)(+1.38 -1.21) for the 68% and 95% confidence intervals. We also report prior-independent constraints, which are in excellent agreement with the Bayesian constraints.
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Bertone, G., Cerdeño, D. G., Fornasa, M., Ruiz de Austri, R., Strege, C., & Trotta, R. (2012). Global fits of the cMSSM including the first LHC and XENON100 data. J. Cosmol. Astropart. Phys., 01(1), 015–23pp.
Abstract: We present updated global fits of the constrained Minimal Supersymmetric Standard Model (cMSSM), including the most recent constraints from the ATLAS and CMS detectors at the LHC, as well as the most recent results of the XENON100 experiment. Our robust analysis takes into account both astrophysical and hadronic uncertainties that enter in the calculation of the rate of WIMP-induced recoils in direct detection experiment. We study the consequences for neutralino Dark Matter, and show that current direct detection data already allow to robustly rule out the so-called Focus Point region, therefore demonstrating the importance of particle astrophysics experiments in constraining extensions of the Standard Model of Particle Physics. We also observe an increased compatibility between results obtained from a Bayesian and a Frequentist statistical perspective. We find that upcoming ton-scale direct detection experiments will probe essentially the entire currently favoured region (at the 99% level), almost independently of the statistical approach used. Prospects for indirect detection of the cMSSM are further reduced.
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Bertone, G., Cumberbatch, D., Ruiz de Austri, R., & Trotta, R. (2012). Dark Matter searches: the nightmare scenario. J. Cosmol. Astropart. Phys., 01(1), 004–24pp.
Abstract: The unfortunate case where the Large Hadron Collider (LHC) fails to discover physics Beyond the Standard Model (BSM) is sometimes referred to as the “Nightmare scenario” of particle physics. We study the consequences of this hypothetical scenario for Dark Matter (DM), in the framework of the constrained Minimal Supersymmetric Standard Model (cMSSM). We evaluate the surviving regions of the cMSSM parameter space after null searches at the LHC, using several different LHC configurations, and study the consequences for DM searches with ton-scale direct detectors and the IceCube neutrino telescope. We demonstrate that ton-scale direct detection experiments will be able to conclusively probe the cMSSM parameter space that would survive null searches at the LHC with 100 fb(-1) of integrated luminosity at 14TeV. We also demonstrate that IceCube (80 strings plus DeepCore) will be able to probe as much as similar or equal to 17% of the currently favoured parameter space after 5 years of observation.
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