Revisiting the Galactic Double Neutron Star merger and LIGO detection rates

We revisit the merger rate for Galactic double neutron star (DNS) systems in light of recent observational insight into the longitudinal and latitudinal beam shape of the relativistic DNS PSR J1906$+$0746. Due to its young age and its relativistic orbit, the pulsar contributes significantly to the estimate of the joint Galactic merger rate. We follow previous analyses by modelling the underlying pulsar population of nine merging DNS systems and study the impact and resulting uncertainties when replacing simplifying assumptions made in the past with actual knowledge of the beam shape, its extent and the viewing geometry. We find that the individual contribution of PSR J1906$+$0746 increases to $R = 6^{+28}_{-5}$ Myr$^{-1}$ although the values is still consistent with previous estimates given the uncertainties. We also compute contributions to the merger rates from the other DNS systems by applying a generic beam shape derived from that of PSR J1906+0746, evaluating the impact of previous assumptions. We derive a joint Galactic DNS merger rate of $R^{rm{gen}}_{rm{MW}} = 32^{+19}_{-9}$Myr$^{-1}$, leading to a LIGO detection rate of ${R}^{rm{gen}}_{rm{LIGO}} = 3.5^{+2.1}_{-1.0}$Myr$^{-1}$ (90% conf. limit), considering the upcoming O3 sensitivity of LIGO. As these values are in good agreement with previous estimates, we conclude that the method of estimating the DNS merger and LIGO detection rates via the study of the radio pulsar DNS population is less prone to systematic uncertainties than previously thought.

Constraining dark matter annihilation with cosmic ray antiprotons using neural networks

The interpretation of data from indirect detection experiments searching for dark matter annihilations requires computationally expensive simulations of cosmic-ray propagation. In this work we present a new method based on Recurrent Neural Networks that significantly accelerates simulations of secondary and dark matter Galactic cosmic ray antiprotons while achieving excellent accuracy. This approach allows for an efficient profiling or marginalisation over the nuisance parameters of a cosmic ray propagation model in order to perform parameter scans for a wide range of dark matter models. We identify importance sampling as particularly suitable for ensuring that the network is only evaluated in well-trained parameter regions. We present resulting constraints using the most recent AMS-02 antiproton data on several models of Weakly Interacting Massive Particles. The fully trained networks are released as DarkRayNet together with this work and achieve a speed-up of the runtime by at least two orders of magnitude compared to conventional approaches.

Autoencoders for unsupervised anomaly detection in high energy physics

Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for model-independent new physics searches. We scrutinize the usage of autoencoders for unsupervised anomaly detection based on reconstruction loss to show their capabilities, but also their limitations. As a particle physics benchmark scenario, we study the tagging of top jet images in a background of QCD jet images. Although we reproduce the positive results from the literature, we show that the standard autoencoder setup cannot be considered as a model-independent anomaly tagger by inverting the task: due to the sparsity and the specific structure of the jet images, the autoencoder fails to tag QCD jets if it is trained on top jets even in a semi-supervised setup. Since the same autoencoder architecture can be a good tagger for a specific example of an anomaly and a bad tagger for a different example, we suggest improved performance measures for the task of model-independent anomaly detection. We also improve the capability of the autoencoder to learn non-trivial features of the jet images, such that it is able to achieve both top jet tagging and the inverse task of QCD jet tagging with the same setup. However, we want to stress that a truly model-independent and powerful autoencoder-based unsupervised jet tagger still needs to be developed.

On the beam properties of radio pulsars with interpulse emission

In the canonical picture of pulsars, radio emission arises from a narrow cone centered on the stars magnetic axis but many basic details remain unclear. We use high-quality polarization data taken with the Parkes radio telescope to constrain the geometry and emission heights of pulsars showing interpulse emission, and include the possibility that emission heights in the main and interpulse may be different. We show that emission heights are low in the centre of the beam, typically less than 3% of the light cylinder radius. The emission beams are under-filled in longitude, with an average profile width only 60% of the maximal beam width and there is a strong preference for the visible emission to be located on the trailing part of the beam. We show substantial evidence that the emission heights are larger at the beam edges than in the beam centre. There is some indication that a fan-like emission beam explains the data better than conal structures. Finally, there is a strong correlation between handedness of circular polarization in the main and interpulse profiles which implies that the hand of circular polarization is determined by the hemisphere of the visible emission.

Strongly interacting dark sectors in the early Universe and at the LHC through a simplified portal

We study the cosmology and LHC phenomenology of a consistent strongly interacting dark sector coupled to Standard Model particles through a generic vector mediator. We lay out the requirements for the model to be cosmologically viable, identify annihilations into dark vector mesons as the dominant dark matter freeze-out process and discuss bounds from direct detection. At the LHC the model predicts dark showers, which can give rise to semi-visible jets or displaced vertices. Existing searches for di-jet resonances and for missing energy mostly probe the parameter regions where prompt decays are expected and constrain our model despite not being optimised for dark showers. We also estimate the sensitivity of dedicated analyses for semi-visible jets and emphasize the complementarity of different search strategies.

NNLL-fast: predictions for coloured supersymmetric particle production at the LHC with threshold and Coulomb resummation

We present state-of-the art predictions for the production of supersymmetric squarks and gluinos at the Large Hadron Collider (LHC), including soft-gluon resummation up to next-to-next-to-leading logarithmic (NNLL) accuracy, the resummation of Coulomb corrections and the contribution from bound states. The NNLL corrections enhance the cross-section predictions and reduce the scale uncertainty to a level of 5-10%. The NNLL resummed cross-section predictions can be obtained from the computer code NNLL-fast, which also provides the scale uncertainty and the pdf and alpha_s error.

Pulsars as probes of gravity and fundamental physics

Radio-loud neutron stars known as pulsars allow a wide range of experimental tests for fundamental physics, ranging from the study of super-dense matter to tests of general relativity and its alternatives. As a result, pulsars provide strong-field tests of gravity, they allow for the direct detection of gravitational waves in a pulsar timing array, and they promise the future study of black hole properties. This contribution gives an overview of the on-going experiments and recent results.

A Quantitative Test of the No-Hair Theorem with Sgr A* using stars, pulsars, and the Event Horizon Telescope

The black hole in the center of the Milky Way, Sgr A*, has the largest mass-to-distance ratio among all known black holes in the Universe. This property makes Sgr A* the optimal target for testing the gravitational no-hair theorem. In the near future, major developments in instrumentation will provide the tools for high-precision studies of its spacetime via observations of relativistic effects in stellar orbits, in the timing of pulsars, and in horizon-scale images of its accretion flow. We explore here the prospect of measuring the properties of the black-hole spacetime using all these three types of observations. We show that the correlated uncertainties in the measurements of the black-hole spin and quadrupole moment using the orbits of stars and pulsars are nearly orthogonal to those obtained from measuring the shape and size of the shadow the black hole casts on the surrounding emission. Combining these three types of observations will, therefore, allow us to assess and quantify systematic biases and uncertainties in each measurement and lead to a highly accurate, quantitative test of the gravitational no-hair theorem.

NLO+NLL squark and gluino production cross-sections with threshold-improved parton distributions

We present updated predictions for the cross-sections for pair production of squarks and gluinos at the LHC Run II. First of all, we update the calculations based on NLO+NLL partonic cross-sections by using the NNPDF3.0NLO global analysis. This study includes a full characterization of theoretical uncertainties from higher orders, PDFs and the strong coupling. Then, we explore the implications for this calculation of the recent NNPDF3.0 PDFs with NLO+NLL threshold resummation. We find that the shift in the results induced by the threshold-improved PDFs is within the total theory uncertainty band of the calculation based on NLO PDFs. However, we also observe that the central values of the cross-sections are modified both in a qualitative and a quantitative way, illustrating the relevance and impact of using threshold-improved PDFs together with resummed partonic cross-sections. The updated NLO+NLL cross-sections based on NNPDF3.0NLO are publicly available in the NLL-fast format, and should be an important ingredient for the interpretation of the searches for supersymmetric particles at Run II.

Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5_aMC@NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties.