B physics has played a prominent role in investigations of new physics effects at low-energies. Presently, the largest discrepancy between a standard model prediction and experimental measurements appears in the branching ratio of the charged current mediated B$\rightarrow${}$\tau${}$\nu${}\ifmmode\bar\else\textasciimacron\fi{}$\tau${} decay, where the large $\tau${} mass lifts the helicity suppression arising in leptonic B decays. Less significant systematic deviations are also observed in the semileptonic B$\rightarrow${}D(*)$\tau${}$\nu${}\ifmmode\bar\else\textasciimacron\fi{}$\tau${} rates. Because of the rich spin structure of the final state, the decay mode B$\rightarrow${}D*$\tau${}$\nu${}\ifmmode\bar\else\textasciimacron\fi{}$\tau${} offers a number of tests of such possible standard model deviations. We investigate the most general set of lowest dimensional effective operators leading to helicity suppressed modifications of b$\rightarrow${}c (semi)leptonic transitions. We explore such contributions to the B$\rightarrow${}D*$\tau${}$\nu${}\ifmmode\bar\else\textasciimacron\fi{}$\tau${} decay amplitudes by determining the differential decay rate, longitudinal D* polarization fraction, D*-$\tau${} opening angle asymmetry and the $\tau${} helicity asymmetry. We identify the size of possible new physics contributions to these observables constrained by the present B$\rightarrow${}D(*)$\tau${}$\nu${}\ifmmode\bar\else\textasciimacron\fi{}$\tau${} rate measurements and find significant modifications are still possible in all of them. In particular, the opening angle asymmetry can be shifted by almost 30%, relative to the standard model prediction, while the $\tau${} helicity asymmetry can still deviate by as much as 80%.

We confront the indications of lepton flavor universality (LFU) violation observed in semi-tauonic B meson decays with new physics (NP) searches using high pT tau leptons at the LHC. Using effective field theory arguments we correlate possible non-standard contributions to semi-tauonic charged currents with the τ+τ− signature at high energy hadron colliders. Several representative standard model extensions put forward to explain the anomaly are examined in detail: (i) weak triplet of color-neutral vector resonances, (ii) second Higgs doublet and (iii) scalar or (iv) vector leptoquark. We find that, in general, τ+τ− searches pose a serious challenge to NP explanations of the LFU anomaly. Recasting existing 8 TeV and 13 TeV LHC analyses, stringent limits are set on all considered simplified models. Future projections of the τ+τ− constraints as well as caveats in interpreting them within more elaborate models are also discussed

Present measurements of $b\to c\tau \nu$ and $b\to u\tau \nu$ transitions differ from the standard model predictions of lepton flavor universality by almost $4\sigma$. We examine new physics interpretations of this anomaly. An effective field theory analysis shows that minimal flavor violating models are not preferred as an explanation, but are also not yet excluded. Allowing for general flavor violation, right-right vector and right-left scalar quark currents are identified as viable candidates. We discuss explicit examples of two Higgs doublet models, leptoquarks as well as quark and lepton compositeness. Finally, implications for LHC searches and future measurements at the (super-)$B$ factories are presented.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

During 2011 the LHCb experiment at CERN collected 1.0 fb−1 of [equation] ppcollisions. Due to the large heavy quark production cross-sections, these data provide unprecedented samples of heavy...