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Nicolò Foppiani

Publications and source records attributed to Nicolò Foppiani.

5 recordsLinked to original sources

Testing Explanations of Short Baseline Neutrino Anomalies

The experimental observation of neutrino oscillations profoundly impacted the physics of neutrinos, from being well understood theoretically to requiring new physics beyond the standard model of particle physics. Indeed, the mystery of neutrino masses implies the presence of new particles never observed before, often called sterile neutrinos, as they would not undergo standard weak interactions. And while neutrino oscillation measurements entered the precision era, reaching percent-level precision, many experimental results show significant discrepancies with the standard model, at baselines much shorter than typical oscillation baselines, like LSND, MiniBooNE, gallium experiments, and reactor antineutrino measurements. These short baseline anomalies could be explained by the addition of a light sterile neutrino, with mass in the $1-10~\text{eV}$ range, however, in strong tension with many null experimental observations. Other explanations that rely on sterile neutrinos with masses in the $1-500~\text{MeV}$ could resolve the tension. Here we test both classes of models. On the one hand, we look for datasets collected at a short baseline which can constrain heavy sterile neutrino models. We find that the minimal model is fully constrained, but several extensions of this model could weaken the current constraint and be tested with current and future datasets. On the other hand, we test the presence of neutrino oscillations at short baselines, induced by a light sterile state, with the data collected by the MicroBooNE experiment, a liquid argon time projection chamber specifically designed to resolve the details of each neutrino interaction. We report null results from both analyses, further constraining the space of possible explanations for the short baseline anomalies. If new physics lies behind the short baseline anomaly puzzle, it is definitely not described by a simple model.

hep-ex

Efficiently Exploring Multi-Dimensional Parameter Spaces Beyond the Standard Model

We propose a method to ease the challenges of exploring multi-dimensional parameter spaces in beyond-the-Standard Model theories. We evaluate the model likelihood for any choice of parameters by sampling the theory parameters intelligently and building a Kernel Density Estimator. By reducing the number of expensive Monte-Carlo simulations, this method provides a more efficient way to test complex theories. We illustrate our technique to set new limits on a short-lived heavy neutrino $N$, proposed as an explanation of anomalies in neutrino experiments. Using a search for lepton pairs in the T2K near detector, we find exclusion limits on the model parameters in a vast region of parameter space, fully exploiting the advantages of our new method. With a single Monte Carlo simulation, we obtain the differential event rate for arbitrary choices of model parameters, allowing us to cast limits on any slice of the model parameter space. We conclude that $N$ particles with lifetimes greater than $c τ^0 \gtrsim 3~$cm are excluded by T2K data. We also derive model-independent constraints in terms of the total rate, lifetime, and $N$ mass and provide an approximated analytical formula. This method can be applied in other branches of physics to explore the landscape of theory parameters efficiently.

hep-ph

Heavy neutral leptons below the kaon mass at hodoscopic detectors

Heavy neutral leptons ($N$) below the kaon mass are severely constrained by cosmology and lab-based searches for their decays in flight. If $N$ interacts via an additional force, $N\toνe^+e^-$ decays are enhanced and cosmological limits can be avoided. We show that the T2K and MicroBooNE neutrino experiments provide the best limits on the mixing of $N$ with muon-neutrinos, outperforming past-generation experiments, previously thought to dominate. We constrain models with electromagnetically-decaying and long-lived $N$, such as in a transition-magnetic-moment portal and in a leptophilic axion-like particle portal, invoked to explain the MiniBooNE excess. By considering these models as representative examples, our results show that explanations of the MiniBooNE excess that involve $e^+e^-$ pairs from long-lived particles are in tension with T2K, PS191, and MicroBooNE data. Similarly, these searches also constrain MiniBooNE explanations based on single photons due to the associated $e^+e^-$ decay mode via a virtual photon.

hep-ph

Do explanations increase the effectiveness of AI-crowd generated fake news warnings?

Social media platforms are increasingly deploying complex interventions to help users detect false news. Labeling false news using techniques that combine crowd-sourcing with artificial intelligence (AI) offers a promising way to inform users about potentially low-quality information without censoring content, but also can be hard for users to understand. In this study, we examine how users respond in their sharing intentions to information they are provided about a hypothetical human-AI hybrid system. We ask i) if these warnings increase discernment in social media sharing intentions and ii) if explaining how the labeling system works can boost the effectiveness of the warnings. To do so, we conduct a study ($N=1473$ Americans) in which participants indicated their likelihood of sharing content. Participants were randomly assigned to a control, a treatment where false content was labeled, or a treatment where the warning labels came with an explanation of how they were generated. We find clear evidence that both treatments increase sharing discernment, and directional evidence that explanations increase the warnings' effectiveness. Interestingly, we do not find that the explanations increase self-reported trust in the warning labels, although we do find some evidence that participants found the warnings with the explanations to be more informative. Together, these results have important implications for designing and deploying transparent misinformation warning labels, and AI-mediated systems more broadly.

cs.HC

Search for a Low Energy Excess in MicroBooNE

MicroBooNE (the Micro Booster Neutrino Experiment) is a liquid argon time-projection chamber (TPC) experiment designed for short-baseline neutrino physics, currently running at Fermilab. It aims to address the anomalous excess of low-energy events observed by the MiniBooNE experiment. Recent progress towards the search for the low-energy events have brought to develop fully automated event selection algorithm to identify charged-current electron neutrino event candidates with no pions and at least one proton in the final state ($ν_e~\text{CC} 0π\text{N}p$) using the Pandora multi-algorithm pattern recognition. Several cross checks and sidebands have been studied so far to validate the analysis.

hep-ex