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G.F.Giudice
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Review of prospects for discovery of new physics signals at LEP2. The areas covered include SUSY, exotic fermions, BESS models, leptoquarks, virtual effects and CP violating observables.
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SND@LHC is an approved experiment equipped to detect scattering of neutrinos produced in the far-forward direction at the LHC, and aimed to measure their properties. In addition, the detector has a potential to search for new feebly interacting particles (FIPs) that may be produced in proton-proton collisions. In this paper, we discuss FIPs signatures at SND@LHC considering two classes of particles: stable FIPs that may be detected via their scattering, and unstable FIPs that decay inside the detector. We estimate the sensitivity of SND@LHC to probe scattering of leptophobic dark matter, and to detect decays of neutrino, scalar, and vector portal particles. Finally, we also compare and qualitatively analyze the potential of SND@LHC and FASER/FASER{ u} experiments for these searches.
The high energy programme of the HERA collider ended in March 2007. During the whole HERA programme, a combined total integrated luminosity of 1 fb$^{-1}$ was collected by the H1 and ZEUS experiments. In this context, an overview of the most recent results of both experiments concerning searches for new physics is presented. The topics covered are searches for contact interactions, leptoquarks and excited leptons, as well as studies of the isolated lepton and multi-lepton topologies, and a general signature based search.
This paper reviews the most recent results on searches for physics beyond the Standard Model at Tevatron. Both the collider experiments: CDF and DO are performing a large variety of searches such as searches for scalar top and scalar bottom particles, search for new gauge bosons, search for long-lived massive particles and general searches for new particles decaying into dijets. The results, summarized here, are a selection of what obtained recently by both the collaborations using the Run II data, collected so far.
Given the cost, both financial and even more importantly in terms of human effort, in building High Energy Physics accelerators and detectors and running them, it is important to use good statistical techniques in analysing data. Some of the statistical issues that arise in searches for New Physics are discussed briefly. They include topics such as: Should we insist on the 5 sigma criterion for discovery claims? The probability of A, given B, is not the same as the probability of B, given A. The meaning of p-values. What is Wilks Theorem and when does it not apply? How should we deal with the `Look Elsewhere Effect? Dealing with systematics such as background parametrisation. Coverage: What is it and does my method have the correct coverage? The use of p0 versus p1 plots.
We propose a new scientific application of unsupervised learning techniques to boost our ability to search for new phenomena in data, by detecting discrepancies between two datasets. These could be, for example, a simulated standard-model background, and an observed dataset containing a potential hidden signal of New Physics. We build a statistical test upon a test statistic which measures deviations between two samples, using a Nearest Neighbors approach to estimate the local ratio of the density of points. The test is model-independent and non-parametric, requiring no knowledge of the shape of the underlying distributions, and it does not bin the data, thus retaining full information from the multidimensional feature space. As a proof-of-concept, we apply our method to synthetic Gaussian data, and to a simulated dark matter signal at the Large Hadron Collider. Even in the case where the background can not be simulated accurately enough to claim discovery, the technique is a powerful tool to identify regions of interest for further study.
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