Observational and Physical Classification of Supernovae

This chapter describes the current classification scheme of supernovae (SNe). This scheme has evolved over many decades and now includes numerous SN Types and sub-types. Many of these are universally recognized, while there are controversies regarding the definitions, membership and even the names of some sub-classes; we will try to review here the commonly-used nomenclature, noting the main variants when possible. SN Types are defined according to observational properties; mostly visible-light spectra near maximum light, as well as according to their photometric properties. However, a long-term goal of SN classification is to associate observationally-defined classes with specific physical explosive phenomena. We show here that this aspiration is now finally coming to fruition, and we establish the SN classification scheme upon direct observational evidence connecting SN groups with specific progenitor stars. Observationally, the broad class of Type II SNe contains objects showing strong spectroscopic signatures of hydrogen, while objects lacking such signatures are of Type I, which is further divided to numerous subclasses. Recently a class of super-luminous SNe (SLSNe, typically 10 times more luminous than standard events) has been identified, and it is discussed. We end this chapter by briefly describing a proposed alternative classification scheme that is inspired by the stellar classification system. This system presents our emerging physical understanding of SN explosions, while clearly separating robust observational properties from physical inferences that can be debated. This new system is quantitative, and naturally deals with events distributed along a continuum, rather than being strictly divided into discrete classes. Thus, it may be more suitable to the coming era where SN numbers will quickly expand from a few thousands to millions of events.Comment: Extended final draft of a chapter in the "SN Handbook". Comments most welcom

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

KC 4.1: Rural heritage and urban-rural linkages in the ICOMOS SDGs Policy Guidance

This Knowledge Café aims to provide a discussion platform to contribute to the drafting of a new ICOMOS SDGs Policy Guidance, from the perspective of rural heritage, landscapes and rural-urban linkages. While 50%-plus of global populations are urban dwellers, we tend to forget that the other half dwell in rural places. One of the 7 Priority Actions of the ICOMOS SDGs Working Group in 2018 is the preparation of a consolidated policy statement, as an effective tool for advocacy and communication to wider society and the development world. Based on the need to boost the role of cultural heritage in sustainable development processes, this would be a robust Policy Guidance document, serving to improve the recognition of the role of cultural heritage protection, particularly as defined by SDG 11.4 and the New Urban Agenda. The ICOMOS SDGs Working Group aims to launch this document at the 10th World Urban Forum in 2020 and at the High-Level Political Forum in 2021. The new Policy Guidance aims to emphasize “heritage as a resource, a strategic opportunity”, using the framework of the 3 dimensions of sustainability, economic, social, environmental, and propose adding the 4th dimension of ‘culture’ through an appropriate approach. The document should be based on solid scientific expertise sourced from ICOMOS membership. The Symposium on Rural Heritage: Landscapes and Beyond is a prime opportunity to involve some of this membership, ensuring a diverse and inclusive range of expertise in heritage informs the Policy Guidance. Rural heritage and landscapes, including rural-urban linkages, have great relevance for the intersection of cultural heritage and sustainable development, touching on many SDGs and issues raised in the New Urban Agenda, not to mention the Historic Urban Landscape Recommendation. To cite some examples of this inter-connectedness, the “inter-related categories of continuity and change” addressed during the Symposium, provide the following links: - under ‘Rural Culture’ to SDG 11.4 (change management for tangible rural heritage), SDG 1.5, 2.4, 11.5, 11.b, 13.1 (risk of loss of intangible rural traditions/ practices), SDG 8.9, SDG 12.b (rural cultural tourism), SDG 16.7, 16.a, 17.9, 17.15, 17.17 (identity of people and places); - under ‘Rural economics’ to SDG 1 (poverty eradication), SDG2 (food security), SDG3 (rural agricultural heritage), SDG 8 (improvement of markets and opportunities for rural traditional tools, techniques and rural heritage tourism), SDG 8 (infrastructure, services to small enterprises), SDG 11 (spatial form, territorial policies); - under ‘Rural Environment’ to SDG 6 (water), 13 and 15 (desertification, climate-induced severe weather events, biodiversity, forest management); and - under ‘Rural Society’ to SDG 1 (poverty alleviation) SDG 2 (agriculture), SDG 3.8, 3.c (health services), SDG 16, 17 (bottom-up governance). - Some case studies from ‘Moroccan Rural Heritage’ can be proposed during the session from participants who may have relevant knowledge, to demonstrate these links. The Knowledge Café will feature two speakers, Ege Yildirim and Patricia O’Donnell, giving the conceptual framework of the session, followed by Ilaria Rosetti presenting the method of open discussion, whereby breakout groups (e.g. 3-4 groups of 5-6) can discuss the links of rural heritage issues to the various 17 Goals and Targets under them, concluding with short reporting from each group, to be compiled and disseminated later by the conveners