Related papers: Preserving physically important variables in optim…
We compute the fully differential rate for the Higgs-boson decay $h\to Z\ell^+\ell^-$, with $Z\to\ell^{'+}\ell^{'-}$. For these processes we assume the most general matrix elements within an effective Lagrangian framework. The electroweak…
We propose a method for learning dynamical systems from high-dimensional empirical data that combines variational autoencoders and (spatio-)temporal attention within a framework designed to enforce certain scientifically-motivated…
We consider the complete set of observables for collider searches for indirect effects of new heavy physics. They consist of $SU(3)_{\rm C}\times U(1)_{\rm EM}$ invariant interaction terms/operators that parameterize deviations from the…
We present up-to-date constraints on a generic Higgs parameter space. An accurate assessment of these exclusions must take into account statistical, and potentially signal, fluctuations in the data currently taken at the LHC. For this, we…
The determination of the Higgs self-coupling is a key target for future colliders, in particular through di-Higgs production at $e^+e^-$ Linear Colliders with $\sqrt{s} > 450$\,GeV, e.g.\ ILC, C3 or CLIC. This contribution will discuss the…
One of the challenges of collider physics is to unambiguously associate detector based objects with the corresponding elementary physics objects. A particular example is the association of calorimeter-based objects such as "jets",…
We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequentially observed multivariate count data, improving previously proposed models by not only mining deep hierarchical latent structure from the data, but also capturing…
Particle physics classification often assumes flat geometry, ignoring the curved statistical structure of collision data. We present a geometric framework for Vector Boson Fusion Higgs classification that combines physics-inspired…
We develop an algorithm based on an interaction network to identify high-transverse-momentum Higgs bosons decaying to bottom quark-antiquark pairs and distinguish them from ordinary jets that reflect the configurations of quarks and gluons…
We study mono-Higgs signatures emerging in an illustrative new physics scenario involving Standard Model Higgs boson decays to bottom quark pairs using Hybrid Deep Neural Networks. We use a Multi-Layer Perceptron to analyze the kinematic…
The FAIR Universe HiggsML Uncertainty Challenge focused on measuring the physical properties of elementary particles with imperfect simulators. Participants were required to compute and report confidence intervals for a parameter of…
Differential measurements of particle collisions or decays can provide stringent constraints on physics beyond the Standard Model of particle physics. In particular, the distributions of the kinematical and angular variables that…
Most work on supervised learning research has focused on marginal predictions. In decision problems, joint predictive distributions are essential for good performance. Previous work has developed methods for assessing low-order predictive…
A search for Higgs boson production in association with a pair of top quarks ($t\bar{t}H$) is performed, where the Higgs boson decays to $b\bar{b}$, and both top quarks decay hadronically. The data used correspond to an integrated…
Identifying the dynamical state variables of a system from high-dimensional observations is a central problem across physical sciences. The challenge is that the state variables are not directly observable and must be inferred from raw…
Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. In case of repeated observations of time series for several experimental units, it is often the case that some of the…
We describe a technique to learn the underlying structure of collider events directly from the data, without having a particular theoretical model in mind. It allows to infer aspects of the theoretical model that may have given rise to this…
We introduce an optimization technique to discriminate signal and background in any phenomeno- logical study based on the cut and count-based method. The core ideas behind this technique are the introduction of a ranking scheme that can…
We estimate the accuracy with which the coefficient of the CP even dimension six operators involving Higgs and two vector bosons (HVV) can be measured at linear $e^+ e^-$ colliders. Using the optimal observables method for the kinematic…
We analyse the production of a Higgs boson in association with a Z boson at hadron colliders in the Standard Model and some simple extensions. We show how multi-jet merging algorithms at leading and next-to-leading order for the…