Determination of nonuniversal supergravity models at the Large Hadron Collider

We examine a well motivated non-universal supergravity model where the Higgs boson masses are not unified with the other scalars at the grand unified scale at the LHC. The dark matter content can easily be satisfied in this model by having a larger Higgsino component in the lightest neutralino. Typical final states in such a scenario at the LHC involve W bosons. We develop a bi-event subtraction technique to remove a huge combinatorial background to identify W -> jj decays. This is also a key technique to reconstruct supersymmetric particle masses in order to determine the model parameters. With the model parameters, we find that the dark matter content of the universe can be determined in agreement with existing experimental results.Comment: 19 pages, 8 figures, corrected figures for visibility, additional background and systematic uncertainties estimated, references added and correcte

Introducing Symmetries to Black Box Meta Reinforcement Learning

Meta reinforcement learning (RL) attempts to discover new RL algorithms automatically from environment interaction. In so-called black-box approaches, the policy and the learning algorithm are jointly represented by a single neural network. These methods are very flexible, but they tend to underperform compared to human-engineered RL algorithms in terms of generalisation to new, unseen environments. In this paper, we explore the role of symmetries in meta-generalisation. We show that a recent successful meta RL approach that meta-learns an objective for backpropagation-based learning exhibits certain symmetries (specifically the reuse of the learning rule, and invariance to input and output permutations) that are not present in typical black-box meta RL systems. We hypothesise that these symmetries can play an important role in meta-generalisation. Building off recent work in black-box supervised meta learning, we develop a black-box meta RL system that exhibits these same symmetries. We show through careful experimentation that incorporating these symmetries can lead to algorithms with a greater ability to generalise to unseen action & observation spaces, tasks, and environments

Syk kinases are required for spinal commissural axon repulsion at the midline via the ephrin/Eph pathway

International audienceIn the hematopoietic system, Syk family tyrosine kinases are essential components of immunoreceptor ITAM-based signaling. While there is increasing data indicating the involvement of immunoreceptors in neural functions, the contribution of Syk kinases remains obscure. Previously, we identified phosphorylated forms of Syk kinases in specialized populations of migrating neurons or projecting axons. Moreover, we identified ephrin/Eph as guidance molecules utilizing the ITAM-bearing CD3zeta (Cd247) and associated Syk kinases for the growth cone collapse response induced in vitro. Here, we show that in the developing spinal cord, Syk is phosphorylated in navigating commissural axons. By analyzing axon trajectories in open-book preparations of Syk[−/−] ; Zap70[−/−] mouse embryos, we show that Syk kinases are dispensable for attraction towards the midline but confer growth cone responsiveness to repulsive signals that expel commissural axons from the midline. Known to serve a repulsive function at the midline, ephrin B3/EphB2 are obvious candidates for driving the Syk-dependent repulsive response. Indeed, Syk kinases were found to be required for ephrin B3-induced growth cone collapse in cultured commissural neurons. In fragments of commissural neuron-enriched tissues, Syk is in a constitutively phosphorylated state and ephrin B3 decreased its level of phosphorylation. Direct pharmacological inhibition of Syk kinase activity was sufficient to induce growth cone collapse. In conclusion, Syk kinases act as a molecular switch of growth cone adhesive and repulsive responses