Abstract: We investigate the reconstruction capabilities of the 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 similar to 4 for xenon and germanium, compared to the case when astrophysical quantities are fixed. However, the combination of argon, germanium, and xenon data increases the constraining power by a factor of similar to 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.

Abstract: We examine the extent to which it is possible to realize the NMSSM “ideal Higgs” models espoused in several papers by Gunion et al. in the context of partially universal GUT scale boundary conditions. To this end we use the powerful methodology of nested sampling. We pay particular attention to whether ideal-Higgs-like points not only pass LEP constraints but are also acceptable in terms of the numerous constraints now available, including those from the Tevatron and B-factory data, (g – 2)(mu) and the relic density Omega h(2). In general for this particular methodology and range of parameters chosen, very few points corresponding to said previous studies were found, and those that were found were at best 2 sigma away from the preferred relic density value. Instead, there exist a class of points, which combine a mostly singlet-like Higgs with a mostly singlino-like neutralino coannihilating with the lightest stau, that are able to effectively pass all implemented constraints in the region 80 < m(h) < 100. It seems that the spin-independent direct detection cross section acts as a key discriminator between ideal Higgs points and the hard to detect singlino-like points.

Abstract: The "mu from nu'' supersymmetric standard model (mu nu SSM) cures the μproblem and concurrently reproduces measured neutrino data by using a set of usual right-handed neutrino superfields. Recently, the LHC has revealed the first scalar boson which naturally makes it tempting to test μnu SSM in the light of this new discovery. We show that this new scalar, while decaying to a pair of unstable long-lived neutralinos, can lead to a distinct signal with nonprompt multileptons. With concomitant collider analysis we show that this signal provides an intriguing signature of the model, pronounced with light neutralinos. Evidence of this signal is well envisaged with sophisticated displaced vertex analysis, which deserves experimental attention.

Abstract: Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events like Monte Carlo generators. We study three processes: a simple two-body decay, the processes e(+)e(-)-> Z -> l(+)l(-) and pp -> tt<mml:mo><overbar></mml:mover> including the decay of the top quarks and a simulation of the detector response. By buffering density information of encoded Monte Carlo events given the encoder of a Variational Autoencoder we are able to construct a prior for the sampling of new events from the decoder that yields distributions that are in very good agreement with real Monte Carlo events and are generated several orders of magnitude faster. Applications of this work include generic density estimation and sampling, targeted event generation via a principal component analysis of encoded ground truth data, anomaly detection and more efficient importance sampling, e.g., for the phase space integration of matrix elements in quantum field theories. Here, the authors report buffered-density variational autoencoders for the generation of physical events. This method is computationally less expensive over other traditional methods and beyond accelerating the data generation process, it can help to steer the generation and to detect anomalies.

Abstract: We explore the implications of LHC and cold dark matter searches for supersymmetric particle mass spectra in two different grand unified models with left-right symmetry, SO(10) and SU(4)(c) x SU(2)(L) x SU(2)(R) (4-2-2). We identify characteristic differences between the two scenarios, which imply distinct correlations between experimental measurements and the particular structure of the GUT group. The gauge structure of 4-2-2 enhances significantly the allowed parameter space as compared to SO(10), giving rise to a variety of coannihilation scenarios compatible with the LHC data, LSP dark matter and the ongoing muon g-2 experiment.