arXiv subjects

Roberto Trotta

Publications and source records attributed to Roberto Trotta.

At least 73 records · Page 4Linked to original sources

arXiv2011

Quantifying the tension between the Higgs mass and (g-2)_mu in the CMSSM

Supersymmetry has been often invoqued as the new physics that might reconcile the experimental muon magnetic anomaly, a_mu, with the theoretical prediction (basing the computation of the hadronic contribution on e^+ e^- data). However, in the context of the CMSSM, the required supersymmetric contributions (which grow with decreasing supersymmetric masses) are in potential tension with a possibly large Higgs mass (which requires large stop masses). In the limit of very large m_h supersymmetry gets decoupled, and the CMSSM must show the same discrepancy as the SM with a_mu . But it is much less clear for which size of m_h does the tension start to be unbearable. In this paper, we quantify this tension with the help of Bayesian techniques. We find that for m_h > 125 GeV the maximum level of discrepancy given current data (~ 3.3 sigma) is already achieved. Requiring less than 3 sigma discrepancy, implies m_h < 120 GeV. For a larger Higgs mass we should give up either the CMSSM model or the computation of a_mu based on e^+ e^-; or accept living with such inconsistency.

hep-ph↗

arXiv2011

Complementarity of Dark Matter Direct Detection Targets

We investigate the reconstruction capabilities of Dark Matter mass and spin-independent cross-section from future ton-scale direct detection experiments using germanium, xenon or argon as targets. Adopting realistic values for the exposure, energy threshold and resolution of Dark Matter experiments which will come online within 5 to 10 years, the degree of complementarity between different targets is quantified. We investigate how the uncertainty in the astrophysical parameters controlling the local Dark Matter density and velocity distribution affects the reconstruction. For a 50 GeV WIMP, astrophysical uncertainties degrade the accuracy in the mass reconstruction by up to a factor of $\sim 4$ for xenon and germanium, compared to the case when astrophysical quantities are fixed. However, combination of argon, germanium and xenon data increases the constraining power by a factor of $\sim 2$ compared to germanium or xenon alone. We show that future direct detection experiments can achieve self-calibration of some astrophysical parameters, and they will be able to constrain the WIMP mass with only very weak external astrophysical constraints.

astro-ph.CO↗

arXiv2011

Statistical Challenges of Global SUSY Fits

We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorithmic difficulties of obtaining accurate profile likelihood estimates.

hep-ph↗

arXiv2011

Hunting Down the Best Model of Inflation with Bayesian Evidence

We present the first calculation of the Bayesian evidence for different prototypical single field inflationary scenarios, including representative classes of small field and large field models. This approach allows us to compare inflationary models in a well-defined statistical way and to determine the current "best model of inflation". The calculation is performed numerically by interfacing the inflationary code FieldInf with MultiNest. We find that small field models are currently preferred, while large field models having a self-interacting potential of power p>4 are strongly disfavoured. The class of small field models as a whole has posterior odds of approximately 3:1 when compared with the large field class. The methodology and results presented in this article are an additional step toward the construction of a full numerical pipeline to constrain the physics of the early Universe with astrophysical observations. More accurate data (such as the Planck data) and the techniques introduced here should allow us to identify conclusively the best inflationary model.

astro-ph.CO↗

arXiv2010

Global fits of the Minimal Universal Extra Dimensions scenario

In theories with Universal Extra-Dimensions (UED), the gamma_1 particle, first excited state of the hypercharge gauge boson, provides an excellent Dark Matter (DM) candidate. Here we use a modified version of the SuperBayeS code to perform a Bayesian analysis of the minimal UED scenario, in order to assess its detectability at accelerators and with DM experiments. We derive in particular the most probable range of mass and scattering cross sections off nucleons, keeping into account cosmological and electroweak precision constraints. The consequences for the detectability of the gamma_1 with direct and indirect experiments are dramatic. The spin-independent cross section probability distribution peaks at ~ 10^{-11} pb, i.e. below the sensitivity of ton-scale experiments. The spin-dependent cross-section drives the predicted neutrino flux from the center of the Sun below the reach of present and upcoming experiments. The only strategy that remains open appears to be direct detection with ton-scale experiments sensitive to spin-dependent cross-sections. On the other hand, the LHC with 1 1/fb of data should be able to probe the current best-fit UED parameters.

hep-ph↗

arXiv2010

Identification of Dark Matter particles with LHC and direct detection data

Dark matter (DM) is currently searched for with a variety of detection strategies. Accelerator searches are particularly promising, but even if Weakly Interacting Massive Particles (WIMPs) are found at the Large Hadron Collider (LHC), it will be difficult to prove that they constitute the bulk of the DM in the Universe. We show that a significantly better reconstruction of the DM properties can be obtained with a combined analysis of LHC and direct detection (DD) data, by making a simple Ansatz on the WIMP local density, i.e. by assuming that the local density scales with the cosmological relic abundance. We demonstrate this method in an explicit example in the context of a 24-parameter supersymmetric model, with a neutralino LSP in the stau co-annihilation region. Our results show that future ton-scale DD experiments will allow to break degeneracies in the SUSY parameter space and achieve a significantly better reconstruction of the neutralino composition and its relic density than with LHC data alone.

hep-ph↗

arXiv2009

Reconstructing WIMP Properties in Direct Detection Experiments Including Galactic Dark Matter Distribution Uncertainties

We present a new method for determining Weakly Interacting Massive Particle (WIMP) properties in future tonne scale direct detection experiments which accounts for uncertainties in the Milky Way (MW) smooth dark matter distribution. Using synthetic data on the kinematics of MW halo stars matching present samples from the Sloan Digital Sky Survey, complemented by local escape velocity constraints, we demonstrate that the local dark matter density can be constrained to approximately 20% accuracy. For low mass WIMPs, we find that a factor of two error in the assumed local dark matter density leads to a severely biased reconstruction of the WIMP spin-independent cross section that is incorrect at the 15-sigma level. We show that this bias may be overcome by marginalizing over parameters that describe the MW potential, and use this formalism to project the accuracy attainable on WIMP properties in future 1 tonne Xenon detectors. Our method can be readily applied to different detector technologies and extended to more detailed MW halo models.

astro-ph.HE↗

arXiv2009

The Virtues of Frugality - Why cosmological observers should release their data slowly

Cosmologists will soon be in a unique position. Observational noise will gradually be replaced by cosmic variance as the dominant source of uncertainty in an increasing number of observations. We reflect on the ramifications for the discovery and verification of new models. If there are features in the full data set that call for a new model, there will be no subsequent observations to test that model's predictions. We give specific examples of the problem by discussing the pitfalls of model discovery by prior adjustment in the context of dark energy models and inflationary theories. We show how the gradual release of data can mitigate this difficulty, allowing anomalies to be identified, and new models to be proposed and tested. We advocate that observers plan for the frugal release of data from future cosmic variance limited observations.

astro-ph.CO↗

arXiv2009

Indirect Dark Matter Detection from Dwarf Satellites: Joint Expectations from Astrophysics and Supersymmetry

We present a general methodology for determining the gamma-ray flux from annihilation of dark matter particles in Milky Way satellite galaxies, focusing on two promising satellites as examples: Segue 1 and Draco. We use the SuperBayeS code to explore the best-fitting regions of the Constrained Minimal Supersymmetric Standard Model (CMSSM) parameter space, and an independent MCMC analysis of the dark matter halo properties of the satellites using published radial velocities. We present a formalism for determining the boost from halo substructure in these galaxies and show that its value depends strongly on the extrapolation of the concentration-mass (c(M)) relation for CDM subhalos down to the minimum possible mass. We show that the preferred region for this minimum halo mass within the CMSSM with neutralino dark matter is ~10^-9-10^-6 solar masses. For the boost model where the observed power-law c(M) relation is extrapolated down to the minimum halo mass we find average boosts of about 20, while the Bullock et al (2001) c(M) model results in boosts of order unity. We estimate that for the power-law c(M) boost model and photon energies greater than a GeV, the Fermi space-telescope has about 20% chance of detecting a dark matter annihilation signal from Draco with signal-to-noise greater than 3 after about 5 years of observation.

astro-ph.HE↗

arXiv2009

How flat can you get? A model comparison perspective on the curvature of the Universe

The question of determining the spatial geometry of the Universe is of greater relevance than ever, as precision cosmology promises to verify inflationary predictions about the curvature of the Universe. We revisit the question of what can be learnt about the spatial geometry of the Universe from the perspective of a three-way Bayesian model comparison. We show that, given current data, the probability that the Universe is spatially infinite lies between 67% and 98%, depending on the choice of priors. For the strongest prior choice, we find odds of order 50:1 (200:1) in favour of a flat Universe when compared with a closed (open) model. We also report a robust, prior-independent lower limit to the number of Hubble spheres in the Universe, N_U > 5 (at 99% confidence). We forecast the accuracy with which future CMB and BAO observations will be able to constrain curvature, finding that a cosmic variance limited CMB experiment together with an SKA-like BAO observation will constrain curvature with a precision of about sigma ~ 4.5x10^{-4}. We demonstrate that the risk of 'model confusion' (i.e., wrongly favouring a flat Universe in the presence of curvature) is much larger than might be assumed from parameter errors forecasts for future probes. We argue that a 5-sigma detection threshold guarantees a confusion- and ambiguity-free model selection. Together with inflationary arguments, this implies that the geometry of the Universe is not knowable if the value of the curvature parameter is below |Omega_curvature| ~ 10^{-4}, a bound one order of magnitude larger than the size of curvature perturbations, ~ 10^{-5}. [abridged]

astro-ph.CO↗

arXiv2008

Introducing doubt in Bayesian model comparison

There are things we know, things we know we don't know, and then there are things we don't know we don't know. In this paper we address the latter two issues in a Bayesian framework, introducing the notion of doubt to quantify the degree of (dis)belief in a model given observational data in the absence of explicit alternative models. We demonstrate how a properly calibrated doubt can lead to model discovery when the true model is unknown.

physics.data-an↗

arXiv2008

On prospects for dark matter indirect detection in the Constrained MSSM

In the framework of the Constrained MSSM we derive the most probable ranges of the diffuse gamma radiation flux from the direction of the Galactic center and of the positron flux from the Galactic halo due to neutralino dark matter annihilation. We find that, for a given halo model, and assuming flat priors, the 68% probability range of the integrated gamma-ray flux spans about one order of magnitude, while the 95% probability range can be much larger and extend over four orders of magnitude (even exceeding five for a tiny region at small neutralino mass). The detectability of the signal by GLAST depending primarily on the cuspiness of the halo profile. The positron flux, on the other hand, appears to be too small to be detectable by PAMELA, unless the boost factor is at least of order ten and/or the halo profile is extremely cuspy. We also briefly discuss the sensitivity of our results to the choice of priors.

astro-ph↗

arXiv2008

Bayes in the sky: Bayesian inference and model selection in cosmology

The application of Bayesian methods in cosmology and astrophysics has flourished over the past decade, spurred by data sets of increasing size and complexity. In many respects, Bayesian methods have proven to be vastly superior to more traditional statistical tools, offering the advantage of higher efficiency and of a consistent conceptual basis for dealing with the problem of induction in the presence of uncertainty. This trend is likely to continue in the future, when the way we collect, manipulate and analyse observations and compare them with theoretical models will assume an even more central role in cosmology. This review is an introduction to Bayesian methods in cosmology and astrophysics and recent results in the field. I first present Bayesian probability theory and its conceptual underpinnings, Bayes' Theorem and the role of priors. I discuss the problem of parameter inference and its general solution, along with numerical techniques such as Monte Carlo Markov Chain methods. I then review the theory and application of Bayesian model comparison, discussing the notions of Bayesian evidence and effective model complexity, and how to compute and interpret those quantities. Recent developments in cosmological parameter extraction and Bayesian cosmological model building are summarized, highlighting the challenges that lie ahead.

astro-ph↗

arXiv2007

On the detectability of the CMSSM light Higgs boson at the Tevatron

We examine the prospects of detecting the light Higgs h^0 of the Constrained MSSM at the Tevatron. To this end we explore the CMSSM parameter space with μ>0, using a Markov Chain Monte Carlo technique, and apply all relevant collider and cosmological constraints including their uncertainties, as well as those of the Standard Model parameters. Taking 50 GeV < m_{1/2}, m_0 < 4 TeV, |A_0| < 7 TeV and 2 < tan(beta) < 62 as flat priors and using the formalism of Bayesian statistics we find that the 68% posterior probability region for the h^0 mass lies between 115.4 GeV and 120.4 GeV. Otherwise, h^0 is very similar to the Standard Model Higgs boson. Nevertheless, we point out some enhancements in its couplings to bottom and tau pairs, ranging from a few per cent in most of the CMSSM parameter space, up to several per cent in the favored region of tan(beta)\sim 50 and the pseudoscalar Higgs mass of m_A\lsim 1 TeV. We also find that the other Higgs bosons are typically heavier, although not necessarily much heavier. For values of the h^0 mass within the 95% probability range as determined by our analysis, a 95% CL exclusion limit can be set with about 2/fb of integrated luminosity per experiment, or else with 4/fb (12/fb) a 3 sigma evidence (5 sigma discovery) will be guaranteed. We also emphasize that the alternative statistical measure of the mean quality-of-fit favors a somewhat lower Higgs mass range; this implies even more optimistic prospects for the CMSSM light Higgs search than the more conservative Bayesian approach. In conclusion, for the above CMSSM parameter ranges, especially m_0, either some evidence will be found at the Tevatron for the light Higgs boson or, at a high confidence level, the CMSSM will be ruled out.

hep-ph↗

arXiv2007

Implications for the Constrained MSSM from a new prediction for b to s gamma

We re-examine the properties of the Constrained MSSM in light of updated constraints, paying particular attention to the impact of the recent substantial shift in the Standard Model prediction for BR(B to X_s gamma). With the help of a Markov Chain Monte Carlo scanning technique, we vary all relevant parameters simultaneously and derive Bayesian posterior probability maps. We find that the case of μ>0 remains favored, and that for μ<0 it is considerably more difficult to find a good global fit to current constraints. In both cases we find a strong preference for a focus point region. This leads to improved prospects for detecting neutralino dark matter in direct searches, while superpartner searches at the LHC become more problematic, especially when μ<0. In contrast, prospects for exploring the whole mass range of the lightest Higgs boson at the Tevatron and the LHC remain very good, which should, along with dark matter searches, allow one to gain access to the otherwise experimentally challenging focus point region. An alternative measure of the mean quality-of-fit which we also employ implies that present data are not yet constraining enough to draw more definite conclusions. We also comment on the dependence of our results on the choice of priors and on some other assumptions.

hep-ph↗

arXiv2007

Monolithic or hierarchical star formation? A new statistical analysis

We consider an analytic model of cosmic star formation which incorporates supernova feedback, gas accretion and enriched outflows, reproducing the history of cosmic star formation, metallicity, supernovae type II rates and the fraction of baryons allocated to structures. We present a new statistical treatment of the available observational data on the star formation rate and metallicity that accounts for the presence of possible systematics. We then employ a Bayesian Markov Chain Monte Carlo method to compare the predictions of our model with observations and derive constraints on the 7 free parameters of the model. We find that the dust correction scheme one chooses to adopt for the star formation data is critical in determining which scenario is favoured between a hierarchical star formation model, where star formation is prolonged by accretion, infall and merging, and a monolithic scenario, where star formation is rapid and efficient. We distinguish between these modes by defining a characteristic minimum mass, M > 10^{11} M_solar, in our fiducial model, for early type galaxies where star formation occurs efficiently. Our results indicate that the hierarchical star formation model can achieve better agreement with the data, but that this requires a high efficiency of supernova-driven outflows. In a monolithic model, our analysis points to the need for a mechanism that drives metal-poor winds, perhaps in the form of supermassive black hole-induced outflows. Furthermore, the relative absence of star formation beyond z ~ 5 in the monolithic scenario requires an alternative mechanism to dwarf galaxies for reionizing the universe at z ~ 11, as required by observations of the microwave background. While the monolithic scenario is less favoured in terms of its quality-of-fit, it cannot yet be excluded.

astro-ph↗

arXiv2007

Bayesian Calibrated Significance Levels Applied to the Spectral Tilt and Hemispherical Asymmetry

Bayesian model selection provides a formal method of determining the level of support for new parameters in a model. However, if there is not a specific enough underlying physical motivation for the new parameters it can be hard to assign them meaningful priors, an essential ingredient of Bayesian model selection. Here we look at methods maximizing the prior so as to work out what is the maximum support the data could give for the new parameters. If the maximum support is not high enough then one can confidently conclude that the new parameters are unnecessary without needing to worry that some other prior may make them significant. We discuss a computationally efficient means of doing this which involves mapping p-values onto upper bounds of the Bayes factor (or odds) for the new parameters. A p-value of 0.05 ($1.96σ$) corresponds to odds less than or equal to 5:2 which is below the `weak' support at best threshold. A p-value of 0.0003 ($3.6σ$) corresponds to odds of less than or equal to 150:1 which is the `strong' support at best threshold. Applying this method we find that the odds on the scalar spectral index being different from one are 49:1 at best. We also find that the odds that there is primordial hemispherical asymmetry in the cosmic microwave background are 9:1 at best.

astro-ph↗

arXiv2007

Applications of Bayesian model selection to cosmological parameters

Bayesian model selection is a tool to decide whether the introduction of a new parameter is warranted by data. I argue that the usual sampling statistic significance tests for a null hypothesis can be misleading, since they do not take into account the information gained through the data, when updating the prior distribution to the posterior. On the contrary, Bayesian model selection offers a quantitative implementation of Occam's razor. I introduce the Savage-Dickey density ratio, a computationally quick method to determine the Bayes factor of two nested models and hence perform model selection. As an illustration, I consider three key parameters for our understanding of the cosmological concordance model. By using WMAP 3-year data complemented by other cosmological measurements, I show that a non-scale invariant spectral index of perturbations is favoured for any sensible choice of prior. It is also found that a flat Universe is favoured with odds of 29:1 over non--flat models, and that there is strong evidence against a CDM isocurvature component to the initial conditions which is totally (anti)correlated with the adiabatic mode (odds of about 2000:1), but that this is strongly dependent on the prior adopted. These results are contrasted with the analysis of WMAP 1-year data, which were not informative enough to allow a conclusion as to the status of the spectral index. In a companion paper, a new technique to forecast the Bayes factor of a future observation is presented.

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