Lepton flavour violating slepton decays to test type-I and II seesaw at the LHC

Searches at the LHC of lepton flavour violation (LFV) in slepton decays can indirectly test both type-I and II seesaw mechanisms. Assuming universal flavour-blind boundary conditions, LFV in the neutrino sector is related to LFV in the slepton sector by means of the renormalization group equations. Ratios of LFV slepton decay rates result to be a very effective way to extract the imprint left by the neutrino sector. Some neutrino scenarios within the type-I seesaw mechanism are studied. Moreover, for both type-I and II seesaw mechanisms, a scan over the minimal supergravity parameter space is performed to estimate how large LFV slepton decay rates can be, while respecting current low-energy constraints.Comment: 4 pages; to appear in the proceedings of the 17th International Conference on Supersymmetry and the Unification of Fundamental Interactions (SUSY09), Boston (MA), USA, 5-10 Jun 200

CP Studies and Non-Standard Higgs Physics

There are many possibilities for new physics beyond the Standard Model that feature non-standard Higgs sectors. These may introduce new sources of CP violation, and there may be mixing between multiple Higgs bosons or other new scalar bosons. Alternatively, the Higgs may be a composite state, or there may even be no Higgs at all. These non-standard Higgs scenarios have important implications for collider physics as well as for cosmology, and understanding their phenomenology is essential for a full comprehension of electroweak symmetry breaking. This report discusses the most relevant theories which go beyond the Standard Model and its minimal, CP-conserving supersymmetric extension: two-Higgs-doublet models and minimal supersymmetric models with CP violation, supersymmetric models with an extra singlet, models with extra gauge groups or Higgs triplets, Little Higgs models, models in extra dimensions, and models with technicolour or other new strong dynamics. For each of these scenarios, this report presents an introduction to the phenomenology, followed by contributions on more detailed theoretical aspects and studies of possible experimental signatures at the LHC and other colliders.Comment: Report of the CPNSH workshop, May 2004 - Dec 2005, 542 pages. The complete report as well as its individual chapters are also available from http://kraml.home.cern.ch/kraml/cpnsh/report.htm

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Minimal lepton flavour structures lead to non-maximal 2-3 mixing

24 pages, 10 figuresInternational audiencePresent data prefer a large but non-maximal 2-3 mixing in the lepton sector. We argue that this value, in connection with $\sin\theta_{13}\simeq 0.15$, is the generic outcome of minimal flavour structures. We present a few different incarnations of this statement, in terms of lepton mass matrices depending on a small number of parameters, that can be justified by discrete flavour symmetries. We also propose a general procedure to study the correlation between $\theta_{23}$, the absolute scale and ordering of the neutrino masses, and the leptonic CP-violating phases

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed with the goal of researching and training large language models as a values-driven undertaking, putting issues of ethics, harm, and governance in the foreground. This paper documents the data creation and curation efforts undertaken by BigScience to assemble the Responsible Open-science Open-collaboration Text Sources (ROOTS) corpus, a 1.6TB dataset spanning 59 languages that was used to train the 176-billion-parameter BigScience Large Open-science Open-access Multilingual (BLOOM) language model. We further release a large initial subset of the corpus and analyses thereof, and hope to empower large-scale monolingual and multilingual modeling projects with both the data and the processing tools, as well as stimulate research around this large multilingual corpus

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

International audienceAs language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed with the goal of researching and training large language models as a values-driven undertaking, putting issues of ethics, harm, and governance in the foreground. This paper documents the data creation and curation efforts undertaken by BigScience to assemble the Responsible Open-science Open-collaboration Text Sources (ROOTS) corpus, a 1.6TB dataset spanning 59 languages that was used to train the 176-billion-parameter BigScience Large Open-science Open-access Multilingual (BLOOM) language model. We further release a large initial subset of the corpus and analyses thereof, and hope to empower large-scale monolingual and multilingual modeling projects with both the data and the processing tools, as well as stimulate research around this large multilingual corpus