Projet : SNSPEC PROGRAMME BLANC EDITION 2012 DOCUMENT SCIENTIFIQUE

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1 Important Ce document ne doit pas dépasser 30 pages, dans la mise en page et la typographie fournies par l ANR. Ce point constitue un critère de recevabilité de la proposition de projet. Les propositions de projet ne satisfaisant pas aux critères de recevabilité ne seront pas évaluées. Acronyme / Acronym Titre du projet Proposal title SNspec Phénoménologie et modélisation spectrophotométrique des supernovae de type Ia pour la cosmologie Type Ia supernova spectrophotometric phenomenology and modeling for cosmology. Comité d évaluation/evaluation Committee Type de recherche / Type of research Coopération OUI internationale (si applicable) / International cooperation (if applicable) Aide totale demandée / Grant requested Simi 5 : Physique subatomique et théories associées, astrophysique, astronomie et planétologie x Recherche Fondamentale / Basic Research Recherche Industrielle / Industrial Research Développement Expérimental / Experimental Development x NON Durée du projet / Projet duration 36 mois ANR-GUI-AAP-05 Doc Scientifique 2012 V1 1/30

2 1. RÉSUME DE LA PROPOSITION DE PROJET / EXECUTIVE SUMMARY CONTEXTE, POSITIONNEMENT ET OBJECTIFS DE LA PROPOSITION / CONTEXT, POSITION AND OBJECTIVES OF THE PROPOSAL Contexte et enjeux économiques et sociétaux / Context, social and economic issues Positionnement du projet / Position of the project État de l'art / State of the art Objectifs et caractère ambitieux/novateur du projet / Objectives, originality and novelty of the project PROGRAMME SCIENTIFIQUE ET TECHNIQUE, ORGANISATION DU PROJET / SCIENTIFIC AND TECHNICAL PROGRAMME, PROJECT ORGANISATION Programme scientifique et structuration du projet / Scientific programme, project structure Management du projet / Project management Description des travaux par tâche / Description by task Tâche 1 / Task 1 : Phenomenological analysis Tâche 2 / Task 2 : Supernovae modelling and extinction Tâche 3 / Task 3 : SN spectrophotometric dataset and algorithm dissemination in community Calendrier des tâches, livrables et jalons / Tasks schedule, deliverables and milestones STRATÉGIE DE VALORISATION, DE PROTECTION ET D EXPLOITATION DES RÉSULTATS / DISSEMINATION AND EXPLOITATION OF RESULTS. INTELLECTUAL PROPERTY DESCRIPTION DU PARTENARIAT / CONSORTIUM DESCRIPTION Description, adéquation et complémentarité des partenaires / Partners description & relevance, complementarity Partenaire 1/Partner 1 : LPC Partenaire 2/Partner 2 : CPPM Partenaire 3/Partner 3 : IPNL Partenaire 4/Partner 4 : LPNHE Qualification du coordinateur du projet / Qualification of the project coordinator Qualification, rôle et implication des participants / Qualification and contribution of each partner JUSTIFICATION SCIENTIFIQUE DES MOYENS DEMANDÉS / SCIENTIFIC JUSTIFICATION OF REQUESTED RESSOURCES Partenaire 1 / Partner 1 : LPC Partenaire 2 / Partner 2 : CPPM Partenaire 3 / Partner 3 : IPNL Partenaire 4 / Partner 4 : LPNHE RÉFÉRENCES BIBLIOGRAPHIQUES / REFERENCES RÉSUME DE LA PROPOSITION DE PROJET / EXECUTIVE SUMMARY Type Ia supernovae observations led to the astonishing discovery in 1998 that the Universe's expansion was accelerating, and not decelerating as it was thought at the end of the XXth century. This result brought a revolution in our whole understanding of the Universe, and was awarded the Nobel Prize for physics in Since these pioneering results, a large observation program was set up, in order first to confirm the phenomenon, which was done in 2006, then to determine what could be the nature of the Dark Energy which is responsible for the acceleration. A definite answer to this issue is expected by the so-called 4 th generation programs which will start around Yet employing ANR-GUI-AAP-05 Doc Scientifique 2012 V1 2/30

3 supernovae as standard candles to track the Universe's expansion relies on the assumption that supernovae explosions in the early universe are similar to the more recent ones. This is not fully the case, and part of the standardization game is to design the best possible corrections : this goes through a deep understanding of parameters driving the explosion luminosity. In this context, a novel observation technique was designed by a collaboration between Saul Perlmutter, one of the Nobel Prize laureates, and the French teams forming this proposal (SNFactory) : the spectrophotometry of variable objects. It collected over the course of 5 years an unique dataset that contains all the DNA code of the supernovae in the extended visible spectral range. The quality of the dataset has been thoroughly validated by reproducing the known results of the standard photometric techniques. They are now ready to reveal all their mysteries and to push further the limits of the knowledge. The aim of the SNspec project is to deliver an analysis platform for Type Ia supernovae in addition to a set of novel scientific results important both for the astrophysical understanding of SNe Ia and for cosmology. The added value of such a platform is that it can be used as a reference to develop 4th generation photometric surveys. The scientific results expected will provide an empirical parametrization of the flux emitted during a supernova explosion,and constraints for the physical forward-modeling approach, while the analysis platform will help setting the requirements of purely photometric surveys as well as their need for complementary observations: The state of the art suggest that some hidden variables are driving the luminosity, and that they should be taken into account in order to avoid experimental bias. These variables have been hinted at by direct spectroscopic analysis or by host galaxy studies, but it is too early to tell if a purely photometric approach can be sensitive enough to measure them with the accuracy needed for precision cosmology. In order to acheive these goals, a thorough empirical analysis of the time series of 192 supernovae, which amounts to more than 3000 spectra in total, will be conducted. It will determine the number and the impact of parameters driving the explosion luminosity, and wether or not there exists subclasses of Type Ia supernovae which would contaminate the regular sample. In a second step, the influence of those parameters will be propagated to a full model of the flux received, with a complete study of the so-called color law: Type Ia supernovae are one of the rare probes that can provide information of the nature of dust in galaxies at cosmological distances. Finally, the model will be compared and validated with data from other sources, employing the analysis platform developed for the project, and the conclusions will be disseminated to the scientific community, the institutional decision-makers and the general audience. 2. CONTEXTE, POSITIONNEMENT ET OBJECTIFS DE LA PROPOSITION / CONTEXT, POSITION AND OBJECTIVES OF THE PROPOSAL 2.1. CONTEXTE ET ENJEUX ÉCONOMIQUES ET SOCIÉTAUX / CONTEXT, SOCIAL AND ECONOMIC ISSUES Type Ia supernovæ (SNe Ia) have proven to be excellent standard candles directly usable for cosmological measurements: the physics of their explosion constrains the natural variation of their luminosity at peak magnitude with a raw 0.4 magnitude dispersion (B band), and they are luminous enough to be observed up to a redshift of z~1.4 with the current technological means at our disposal. These two features made it possible to measure the expansion of the universe from the local Hubble flow up to cosmological distances, which lead to the unexpected discovery in 1998 by two independent teams that the expansion of the universe is accelerating, and not decelerating as expected (Riess et al and Perlmutter et al. 1999). This discovery has been rewarded by the Nobel prize award for physics in ANR-GUI-AAP-05 Doc Scientifique 2012 V1 3/30

4 Yet the interpretation of the accelerated expansion leads to open questions (see e.g. Copeland 2006): introducing a cosmological constant in the Einstein equation leads to a discrepancy of many orders of magnitude with the vacuum energy density predicted by particle physics that can so far only be solved by fine tuning. Other interpretations have been suggested: instead of adding a cosmological constant to Einstein equations, one can interpret the extra term as an energy arising from a new field. Scalar field models such as Quintessence arise from this scenario. Ad-hoc modification of the gravitation have also been proposed the so-called f(r) theories in order to explain the accelerated expansion of the universe. Last, it has also been shown that averaging the inhomogeneities of the universe could lead to a modified Robertson-Walker equation with a repulsive term: this is the back-reaction. Nevertheless, the order of magnitude of this effect has yet to be constrained. All these interpretations lead to an effective equation of state of the dark energy p=w(z) ρ that can be probed experimentally: any departure from w=-1 would be the indication of new physics beyond a plain cosmological constant. The aim of the second-generation supernovae projects was to confirm the acceleration of the universe and to provide the first constraints on w. This went through an increase of both supernovæ statistics, and a better scheme to reduce their intrinsic dispersion using empirical standardization methods. The recent compilations uses as many as 16 sources of supernovæ (Amanullah 2010), with a total of 557 objects retained in the final analysis. Some data sets, on the other hand, display a remarkable homogeneity: the SNLS collaboration probed the high redshift range (0.2<z<1.0), with repeated photometric observations of degree field with the MEGACAM camera mounted on the CFHT telescope. Their 3-year dataset contains 121 supernovae light-curves and resulted in the most precise determination of the w parameter to date (w=-1.06±0.07; Sullivan 2011), still compatible with a cosmological constant. The intermediate redshift range (0.04<z<0.42) has been covered by the SDSS survey, which has published 103 supernova light curves so far. As they share some calibrators with SNLS, a joint light-curve analysis is onging and should lead to improved results in a near future. The partners LPNHE and CPPM of this proposal are members of the SNLS collaboration and have a wide experience in using type Ia supernovæ as cosmological probes. While current ongoing third generation projects like Palomar Transient Factory (PTF) or Dark Energy Survey (DES) will continue to increase the number of supernovæ for the next decade, both in the nearby and the large redshift ranges, France is currently involved in fourth generation projects, like LSST and EUCLID. Both will provide complementary data at the horizon of the 2020 decade: LSST uses a 6-filter wide-field ground-based camera on a dedicated telescop, while EUCLID is a wide-field ESO space mission with visible and infrared filters. The coordinated observation of ~ SNe by these two instruments would provide cosmological constraints both competitive and complementary with other cosmological probes such as Baryon Accoustic Oscillations or Weak Lensing. However a substantial part of the uncertainty budget would still be dominated by the systematic errors that this proposal will help to reduce significantly POSITIONNEMENT DU PROJET / POSITION OF THE PROJECT Type Ia supernovæ, acting as cosmological standard candles, can be gathered in their so-called Hubble diagram, a direct visualisation of the expansion history of the Universe. For that matter, one needs simultaneous measurements of their redshifts (the scale of the universe) and their distances (the age of the universe). The redshift is usually obtained by a spectroscopic observation of the SN Ia galactic host with very good accuracy. It is therefore the distance estimation, directly related to the luminosity of the standard candles, that drives the accuracy of the cosmological measurement. In the second generation experiment using the so-called rolling search mode, the luminosity of the supernovae is measured through repeated wide-field multi-filter observations of the same portion of the sky allowing both for efficient SN Ia detection and good sampling of their light curves, critical to their standardization. The typing of the SNe Ia candidate is done in parallel by observing a spectrum ANR-GUI-AAP-05 Doc Scientifique 2012 V1 4/30

5 near maximum light if possible. A light-curve fit is then performed on the multi-epoch photometric data, and empirical corrections are applied in order to improve the distance estimator. While this traditional method relies heavily on wide-field photometry, the most popular standardization schemes like MLCS2k2, SALT2 or SIFTO heavily rely on underlying supernovae spectral templates in order to reproduce the flux observed in wide bands. However, they lack an homogeneous spectrophotometric training set sampling the natural diversity of SNe Ia. SN2011fe spectral timeserie as observed by SNFactory The purpose of the Nearby Supernova Factory (SNfactory, Aldering 2002, Copin 2006) was to acquire spectrophotometric time-series of a hundreds of nearby SNe Ia in the Hubble flow, targeting 0.03<z<0.08 which has been proved to be optimal to anchor the Hubble diagram at low redshift. This international collaboration was formed in 2001, and the SuperNova Integral Field Spectrograph ANR-GUI-AAP-05 Doc Scientifique 2012 V1 5/30

6 (SNIFS), dedicated to the spectrophotometry of variable objects was built and installed in 2004 on the bent Cassegrain port of the UH 88 inch telescope at Mauna Kea. 192 SNIa were followed from 2004 to 2009 with more than 6 epochs per supernova and an average of 15 epochs per object, with a cadence of 2-3 days and a median first spectrum 4 days prior maximum light, amounting for a total of more than 3000 spectra. The spectral coverage goes from 3200 to Å with two spectroscopic channels having a spectral resolution of 4.4 to 6 Å. The overall spectrophotometric accuracy was assessed both by the observation of established flux standard stars in various conditions and by direct comparison of supernova synthetic light-curve to photometric measurement from external photometric surveys such as CfA. It amounts to 0.05 mag for SNe, with 0.03 mag coming from the spectrophotometric calibration procedure, and the rest coming from a combination of galactic subtraction residuals and low-flux uncertainties. Such a data set is unprecedented and constitute an unique tool to study how supernovae variabilities affect their use as standard candles. The scientific program allowed by such a spectrophotometric SN Ia time serie set is multiple: The statistical sample of 192 supernovæ in the Hubble flow will improve the data set available for light-curve based cosmological fits. Even if future photometric programs have the potential to outnumber this sample, it is currently the biggest homogeneous sample in its redshift range. The spectrophotometric data can be fed to any custom synthetic photometric-like filters, allowing to compute K-correction free Hubble diagrams. It can also provide underlying reference templates for K-correction computation at any redshift, without resorting to a specific model by providing a correct match to an object in our database. Empirical models are trained using calibrated photometric data in addition to poorly calibrated spectra. Having access to spectrophotometric data greatly simplifies the procedure, and SNfactory data set is a unique opportunity in this respect. Even without improvement in the standardization scheme, a model trained on our data would be a major reference. Spectral indicators and other spectral metrics derived from our high signal-to-noise spectra will provide a thorough reference for variability studies beyond the traditional technique. As nearby and further away supernovæ might not sample the same parameter-space due to evolution effects, spectral indicators should provide some useful handles to constrain those and to control the induced biases. Having access to the host galaxy in photometry and spectroscopy, supernova properties will be correlated to their hosts. This opens the door to study the luminosity and global properties breakdown with respect to the host category, bringing an answer to a currently much debated topic. Finally, the availability of calibrated spectra covering a wide range of phases and wavelength will allow to constrain supernovae explosion models and help to understand SN Ia physics. Based upon their renowned expertise of the integral field spectrography original technology, the responsibilities of the French groups in SNfactory were to build the SNIFS, which is a joint INSU- IN2P3 realization, and to write the whole chain of the data reduction, from CCD processing to the spectrophotometric calibration and host subtraction. This time-consuming investment was necessary to produce and understand the spectral data, which now have to be analyzed and released. French group interests are in the scope of next-generation experiments: the current spectrophotometric data set is sufficient to address systematic issues in order to improve the efficiency of SNe Ia used as cosmological standard candles. This goes through designing and releasing the best possible standardization scheme. ANR funding will in this respect help to maintain the French leadership in the supernova usage for cosmology, both for current and future surveys. ANR-GUI-AAP-05 Doc Scientifique 2012 V1 6/30

7 2.3. ÉTAT DE L'ART / STATE OF THE ART Despite the successful use of SNIa in cosmology, the physical mechanism beyond their explosions remains largely unknown. Even is the nature of the progenitor is still discussed, and while the presence of a compact C/O white dwarf is admitted, there are still two mechanisms which are believed to lead to an explosion. The first one, the single degenerate (SD) scenario supposes that the degenerate core accretes matter from a companion, either a star in the main sequence or a red giant which. Nearing the Chandrasekhar mass, the mostly admitted scenario considers a run-away thermonuclear burnout start as a deflagration flame, which is believed to turn out as a detonation due to the turbulent mixing of hot and unburned material. While popular, as it describes reasonably well the overall spectral properties of the object, and the relative homogeneity of the explosions, this scenario suffers some shortcomings. One would expect the signature of the companion ejecta in the early phases, but there are only two observations of hydrogen lines in early spectra (one being from SNfactory, Aldering et al. 2006) showing this material. One would also expect to detect the companion of the exploding star, either from HST reference images taken before the explosion or from historical explosions, but no firm conclusions could be drawn. This model has also competitors in the single degenerate class of models, such as the double-detonation model. The other channel, the double degenerate scenario (DD), supposes the coalescence of two white dwarfs. This scenario which was not the one preferred by the community for a few decades was brought back recently to the attention by several evidences, one of the most striking being the observation of super-chandrasekhar explosions, which cannot be explained by the single degenerate scenario. One of these events was observed and thoroughfully analyzed by SNfactory (Scalzo et al. 2010, Childress et al. 2011). The existence of this double-degenerate scenario is also supported by the reconstruction of the delayed time distribution of SNIa (Maoz 2010), which best fit supposes a mix of SD and DD channels. The explosions numerical simulations despite constant progresses still lack the discriminant power to distinguish both scenarios when directly fitting the whole spectral energy density, even if a reasonable agreement can be locally found at some phases: there is a constant ongoing effort to match observational spectra such as SNfactory observations of SN2001fe to models (Röpke et al, in prep.). But more important than a single match for a given explosion model, the supernovae diversity should be explained by the explosion mechanism. The total amount of Nickel-56 mass produced during the explosion is the main driver for the object luminosity, and its variability can be attributed to the details of the initial state of the white dwarf, the specifics of turbulent deflagration and environmental effects: for instance it is known that active star-forming galaxies produce more luminous supernovae (Sullivan 2010). Beyond this primer variability, one would expect to see metallicity effects affecting the explosion. Another source of variability is expected to be the angle of view of an asymmetric explosion: this asymetry can arise indeed from the initial ignition point in double-detonation models or the convection due to the carbon flash in delayed detonation models (Maeda et al. 2010) or the initial broken symmetry in a double degenerate merger. From an observational point of view, the study of the spectral variability will provide constraints to the global class of allowed model: for instance, observations of unburnt carbon signatures by the SNfactory (Thomas et al. 2007, Thomas et al. 2011) are consistent with the delayed detonation model. Beyond the diversity inside a class of models which will manifest as a continuum in some parameter space, the existence of unusual objects led to attempt empirical sub-classification. Branch et al. (2006) proposed to use the equivalent width of Si II 5972 Å and Si II 6355 Å to provide a classification in four types: the luminous shallow-silicon, the core-normals, the underluminous cools and the broad lines. While the classification scheme varies depending on the authors, there is no clear answer wether ANR-GUI-AAP-05 Doc Scientifique 2012 V1 7/30

8 there is a continuum between the subclasses or it they belong to distinct physical conditions, as suggested by the reddening measurements of Wang et al. (2009). As far as the cosmological use of SNIa is concerned, the presence of different concurrent channels to produce the explosion, the existence of subclasses or even the secondary variabilities are widely ignored: the widely-used models such as SALT2 (Guy 2007) suppose that there are two main sources of variability, described empirically as the light-curve stretch (the slower-brighter relation) and the color (the brighter-bluer relation). While the first one describes a variability intrinsic to the object properties probably linked to the 56-Nickel mass, the second one is believed to be a mix of intrinsic effects and the reddening by dust in the host galaxy. Quantitatively, numbers obtained by SNfactory using this calibration scheme show that the uncorrected dispersion of SNIa luminosity in B at peak brightness is 0.4 mag, most of it coming from the color dispersion, and the global dispersion obtained after correction reaches 0.15 mag, which is the same as was obtained by dedicated photometric programs like SNLS (Guy et al. 2010), proving that SNfactory data while using a novel technique meets the standards needed for cosmology. The spectral data contains much more information than a few broad band light-curve and the idea to link luminosity to spectral properties was first explored by Nugent (1995), who derived two spectral indicators, one relevant to the Silicon line ratio, the other for flux ratios in the Ca H&K UV region and showed a tentative correlation to the supernova properties. More recently, attention was brought to the Si II 4131 Å line by Arsenijevic et al. (2008) and with the SNfactory data, Chotard et al. (2011) showed that it can be used as efficiently as the stretch to standardize supernovae. Other indicators were studied, in particular in the UV part: Bongard et al. (2006) refined the definition of Nugent's calcium ratio, Walker et al. (2010) studied the spectral variability in this region and our Chotard et al. (2011) study showed that the Ca II H&K equivalent width traces a novel spectral variability, uncorrelated to stretch. Another way to handle spectral data was to blindly search which flux ratios in narrow bands would minimize the Hubble residuals (Bailey 2009) and the best-found ratio in SNfactory data gave an RMS of mag. Blondin (2011) confirmed with the limited sample of CfA data that this flux ratio improves the scatter RMS by 10% with respect to traditional technique, and that including some equivalent width in addition to SALT2 parameter may improve the distance estimation. Trying to get down to the better standardization, Foley (2011) used instead the Si II 6355 Å line velocity to improve the standardization down to an RMS of 0.13 mag. As shown by these few highlighted examples, this field is subject to an active research. The other component of the standardization is the color law: there is a long standing issue since 1998 whether this comes from extinction by dust, or represents some intrinsic luminosity fluctuations or circumstellar dust (Goobar 2008). Indeed, the cosmological fit using SALT2-like models where color is interpreted as dust effects leads to a total to selective extinction ratio around 2, where the Milky Way value is 3.1. Wang et al. (2009) argued that the value may depend on the considered subclass of supernovae, and Kessler (2009) showed that the reconstructed value is increased by adding a color dispersion. In Chotard et al. (2011) we demonstrated that a Cardelli-like extinction law as well as a Milky Way value is recovered when both the proper correction by two intrinsic variations is included, and the dispersion due to remaining variability is correctly handled. These first results were obtained when considering only spectra near maximum light, and two spectral features. It needs now to be generalized OBJECTIFS ET CARACTÈRE AMBITIEUX/NOVATEUR DU PROJET / OBJECTIVES, ORIGINALITY AND NOVELTY OF THE PROJECT The availability of SNIa spectrophotometric time series of unprecedented quality will allow us to address thoroughfully the issue of supernovae standardization for cosmological analyses, and to ANR-GUI-AAP-05 Doc Scientifique 2012 V1 8/30

9 provide the recipes for the analysis of next generation surveys. While being spectroscopic, the data will allow us to study the detail of object spectral variabilities, and while being spectrophotometric, we will be able to relate them to the luminosity of the object as if it were measured by broad-band photometry employing integration in synthetic filters. The goal of the project is thus to provide the community with a comprehensive study of supernovae variabilities, and use it in order to build the best possible supernova templates, that can be then used inside a light-curve fitter or as benchmarks for explosion models. In order to do so, some questions needs to be addressed. First, how many intrinsic parameters are needed to describe the object variability? We know that there are at least two independent intrinsic variables measured by Si II 4131 Å and Ca II H&K line width at maximum light. As pointed by some authors, the Si II 6355 Å velocity may also be an indicator related to luminosity properties. Host galaxy properties may also give a handle on the supernovae standardization. Beyond these, a generalization to all available indicators at all phases is possible, and would provide a definite answer to the number of parameters needed, as well as the best observational mix: for instance, it is not known if the complete analysis of a spectrum at maximum light is sufficient to predict the whole spectral light-curve at all phases, or if some targeted observations at other phases would bring relevant information for standardization. It also not known whether dedicated spectroscopic observations of host galaxies once the supernova has faint will help the standardization. This has a direct impact on observational strategy for future surveys. Once the number of relevant variabilities will have been studied, a coherent picture will emerge in order to constrain explosion models: yet the state of the art doesn't allow a forward modelling approach. Also, the metric defined by the major indicators will allow to study the presence of subclasses of SNIa, and more important if the extreme objects can be described as distribution tails of otherwise continuous conditions, or if they clusterize to form separate subclasses. In the latter case, specific rejection criteria should be applied in order to avoid sample contamination for cosmological analysis. Finally, with an homogeneous set of supernovae, the list of relevant spectral indicators driving the luminosity independently from reddening by the host dust, it will be possible to derive the color or the extinction law of SNIa and to build a set of spectral templates. These templates, the training code to derive them and the fitter using them to reproduce either the spectral time series or a set of photometric light-curve will be the major deliverable of the project. Other deliverables will include the set of interpolation algorithm which transform a set of discrete measurement at given phases to a full 2D brane of flux versus wavelength versus time. Lastly, the whole data set will be released, as well as the code to compute the derived data out of it. The main benchmark used for the standardization will be the residuals to the Hubble diagram, as well as other metrics such as the residual spectral flux dispersion in order to quantify the left-over variabilities. For the color law, a specific metric will be the stability with respect to the phase selection: in case the color is due to galactic dust, a stable behaviour is expected, where any evolution with phase would suggest an intrinsic component. Finally, the comparison of the model to photometric data will be made possible by the release of our code. ANR-GUI-AAP-05 Doc Scientifique 2012 V1 9/30

10 3. PROGRAMME SCIENTIFIQUE ET TECHNIQUE, ORGANISATION DU PROJET / SCIENTIFIC AND TECHNICAL PROGRAMME, PROJECT ORGANISATION 3.1. PROGRAMME SCIENTIFIQUE ET STRUCTURATION DU PROJET / SCIENTIFIC PROGRAMME, PROJECT STRUCTURE The main technical of the project is to deliver a set of tools useful for cosmological data analysis. The final product is a comprehensive supernova analyzer platform which will take as an input a set of measurement of a SNIa, both photometric and/or spectroscopic, and deliver the derived information such as feature measurements, light-curve parameters, best-template approximation, and subclassification. This product is identified as being developed and made available to the community by Task 3 (Data release). Project breakdown structure The developments needed in order to deliver such a product can be divided in two tasks: Task 1 (Phenomenological analysis) is devoted to the empirical analysis of spectrophotometric data in order to provide a relevant set of phenomenological classification tools. This is a crucial R&D task needed to answer the questions of how to best describe and measure SNe Ia spectral variability. This includes finding the relevant spectral indicators as well as using them to sort SNe Ia in sub-classes, taking into account the host galaxy information. ANR-GUI-AAP-05 Doc Scientifique 2012 V1 10/30

11 Task 2 (Supernova modelling) is devoted to the delivery and the analysis of templates in the flux,time,wavelength space. It will provide to Task 1 the interpolated data needed to derive spectral analysis at an arbitrary phase. In return, Task 1 will provide this task with an empirical estimate of the number of intrinsic parameters and more generally a scale of the total variability of the supernova population. One of the key part of the task will be to transform these inputs into a model including and answering the reddening law issue on supernovae. The deliverable will be either a light-curve fitter or a distance fitter, depending on the findings whether the color law can be interpreted as an extinction law or not. An obvious connection of the templates with supernovae physical modeling will help to constrain explosion models, which in turn can inform on the spectral variabilities to be looked at in Task 1. Most of the members of the present project are also involved in the SNfactory collaboration, which will provide the input data for the analysis as delivered by the data reduction task of the SNfactory, where the members of the present project played a major role. The ANR funding will thus help to capitalize the investment of the French teams, who have the best knowledge of the spectrophotometric data. Employing the yet proprietary spectrophotometric data of the SNfactory, the activities of the current project will have to be developed in connection with the SNfactory analysis team, which is only weakly structured. Some of the tasks for this project may receive external help from other SNfactory members, and the task coordinators are open to such help, but there is yet no formal agreement from other SNfactory members to provide deliverables useful in the framework if this project. As a spin-off, ANR funding may thus bring some momentum on the whole SNfactory analysis effort, due to its structuring effect. The present proposal is however self-contained, covers a broader scope than the sole SNfactory data analysis, and the asked for resources are sufficient to accomplish the scientific program MANAGEMENT DU PROJET / PROJECT MANAGEMENT The project management will be held by a board of four representative identified people (E. Gangler, Y. Copin, S. Bongard and D. Fouchez), one per institution. Each member of the project management is also a task or subtask coordinator, for the efficiency of the decision-making. All these people have a long collaboration history as they are members of the relatively small French supernovae science community since a decade, and have the same long-term science goal of making the SNIa the best possible standard candle. The management task (Task 0) will be coordinated by E. Gangler. Its goal is to follow the advancement of the project, to ensure the resources allocation corresponds to the needs, to track down, discuss and solve the issues, and to ensure the promotion of the project via an active participation to international conferences and scientific publications as well as outreach activities. It will be also responsible for the project administration and reporting to the financing agency. The management board will meet once per month either in person or by remote conferencing to monitor progresses and discuss issues specific to this Task 0. Day-by-day work will be self-organized within each sub-task. For sub-tasks shared by more than one partner, the coordination will be made by remote means whenever possible, and dedicated working session meetings will be organized by the participants depending on the needs. Some working sessions may be held in another countries when the subject meets the local competence of other SNfactory members or international experts in the field. Each week, a videoconferencing slot shared with the SNfactory people will be setup, where sub-tasks may present progresses reports or discuss projectwide issues relevant for the sub-task. Each task of the project will uses this slot to make a complete scientific progress report at least once every two monthes, in addition to partial progresses reports made on an at-will basis. ANR-GUI-AAP-05 Doc Scientifique 2012 V1 11/30

12 In addition, a complete project review is scheduled twice a year, and will be organized whenever possible in sync with SNfactory project reviews. This review is expected to be held in turn in the different home institutions of the participants, which implies abroad trips. The risk analysis linked to the management Task 0 yield to a low risk profile: involved partners have a strong will to collaborate in an international competitive environment. The relation to SNfactory will be handled by the partners representatives, 3 of them being members of the SNfactory institutional board, thus ensuring a high degree of cooperation between the two projects. The risk linked to the opening of postdoctoral positions is also under control: while being an open and equal opportunity recruitment procedure, many good candidates are already known to be able to fill-in the temporary positions offered by the current project. Finally, there is a risk linked to the natural evolution of the research teams: beyond the commitment of the partners, the size of the involved teams in the current proposal may grow due to institutional or temporary recruitment, this risk will be addressed by requesting to ANR a physical reallocation of resources between the partners of the project to better balance the overall efficiency, after a dedicated project review DESCRIPTION DES TRAVAUX PAR TÂCHE / DESCRIPTION BY TASK TÂCHE 1 / TASK 1 : PHENOMENOLOGICAL ANALYSIS Coord. E. Gangler It is obvious that the type Ia SN diversity is a key point when using supernovae as cosmological standard candles, but it has also strong implications in the understanding of supernova astrophysics. One question about subclassification is the existence of discontinuous classes or the possible continuous path from one subclass to to other. These questions will be addressed employing spectral indicators describing localized measurements of physical interest on the spectra, which reduce the number of degree of freedom under scrutiny, but also from global template building. There are also evidences that that host galactic properties such as Hubble type, star formation, metallicity, and mass are correlated to supernovae properties, yet it is unknown if this correlation can be tracked by spectral indicators alone, or if they bring additional information. The phenomenological analysis will rely on the various empirical relations than can be derived between these derived quantities and global lightcurve properties in order to provide the relevant inputs for model building. Objectives: Derive spectral indicators at all phases Derive host properties Determine the relevant parameters for supernovae variability and probe the existence of subclasses. Sub-task 1.1: Spectral indicator derivation Responsible: Postdoc 1 (to be hired by the project) Participants: LPC Program: Step 1: The spectral indicator will be derived first on spectra at the phase of their observation. An automatic derivation procedure, based on an existing prototype for spectra at maximum, will be developed, allowing for phase-dependent characterization of the features. At Milestone 1, a first set of indicators at different phases computed on the latest version of the data release will be made available to Task 1.3 and Task 2.2. Step 2: employing the spectral 3D model developed by Task 2.1, the indicators will be computed at any arbitrary phase, and their time derivative will be made available. The ANR-GUI-AAP-05 Doc Scientifique 2012 V1 12/30

13 definition of features will be improved in order to be relevant for the peculiar subclasses, or to better follow spectral modifications induced by non-linear physical processes. A model-free generalization of the feature definitions will also be attempted. At Milestone 2, the final code to derive indicators will be completed, and the set of all indicators considered in the analysis will be made available to all other tasks (1.3, 2.2, 2.3, 3.1) depending on spectral indicators. Step 3: maintenance. As the spectral templates will be refined by task 2.2, the phase interpolation will be improved, and the code regularly rerun (for Milestone 3 and final Milestone 4) in order to provide the most accurate measurement. The final set of indicator will be published. Deliverables : Algorithm to compute spectral indicators at any phase Set of indicators computed at some relevant phases for the SNFactory set. Methods: A spectral smoother based on optimal function approximation theorems will be employed in order to improve the S/N of the spectra for determining feature boundaries. It will be interfaced with a MC estimation of errors and an automatic derivation of spectral variance and adjacent bins covariance in order to provide the indicators measurement variance. The relevant features will be defined employing first literature indications, then with a modelindependent approach by characterizing the statistical significance and frequency of peaks or troughs in the spectral data. Risk : The model-dependent extraction of spectral indicators is based on a prototype that provide already success rate of 99% in order to determine the feature boundaries. Generalizing this prototype should be straightforward. The model-independent approach to define boundaries is a new technology to analyze spectra. It may not bring more information than the conventional approach, or need a longer development than the allocated schedule. It is however not mandatory for the final success of the project. In case there are delays in the postdoc hiring, other LPC members will act as a backup on this task. Provided the postdoc is eventually hired, this shall not delay the project. Sub-task 1.2: Host properties Responsible: M. Rigault Participants: IPNL Program: The determination of the host properties is weakly linked to the main program, employing another set of input data. They need to be available at Milestone 2, in order to be correlated to spectral indicators (Task 1.3), and for the analysis of the reddening law (Task 2.2). They will be released inside the scheme of task 3.1. Comparison between local (in physical SN neighborhood) and mean host properties, and between host properties and other supernova properties will be analyzed and published. Deliverables: Hosts morphological type, mass, global and local metallicities and star formation rate Method: Host local properties will be determined by the analysis of the spectral data inside the spectrograph field of view after proper subtraction of the supernova signal. The galactic ANR-GUI-AAP-05 Doc Scientifique 2012 V1 13/30

14 emission lines and background spectra will allow to determine the metallicity or the SFR. Mean host properties are already available to the collaboration from the work of a former PhD student (M. Childress), and will be published soon. Risk: The derivation of the local host properties has started with M. Rigault PhD thesis in 2010, and current status of his work suggests there are no significant risks associated to this task. Sub-task 1.3: Variabilities and subclassing Resp D. Fouchez Participants : CPPM, LPC Program: Step 1 : when a first set of spectral indicators will be released at Milestone 1, they will be used in order to have a first study on variability in a reduced parameter space, and to deliver at Milestone 2 first conclusions on subclasses and relevant parameters useful for the modeling task 2.2 Step 2 : Once the final set of indicator and host quantities will be released at Milestone 2, the full analysis will be carried, employing spectral indicators (LPC participation) or from direct spectral comparisons employing task 2.1 methodology (CPPM participation). The final conclusions on variabilities should be released to be used by the modeler at Milestone 3, and published for the end of the project. Deliverables: Set of variables that should enter the template model, and degree of expected non-linearity. Algorithm to asses the probability for an object to belong a subclass. Method: Use of multi-dimensional analysis like kernel PCA, or known unsupervised clustering algorithms will help to hierarchize the relevant parameters, and to establish empirical relations and subclasses. The spectral comparisons will use the advanced metrics defined by task 2.1. Risk: The identification of the most important variables is a guaranteed success, preliminary results show that a few intrinsic variables may be sufficient Statistical sample may prove to be limited to establish the existence of some subclasses, which may amount to only 1 representative. This however would be a striking result, and corresponding objects flagged for the rest of the analysis. The full analysis may encounter unexpected developments, due to the yet unknown nature of the studied object. This would result on a delay for the scientific publication, however this task is handled mostly by permanent staff, who may still work on the publication after the project funding stops. CPPM forsees to hire a PhD student on this task which would help to mitigate this risk TÂCHE 2 / TASK 2 : SUPERNOVAE MODELLING AND EXTINCTION Coord.: S. Bongard At a time where type Ia supernovae have proven to be a solid cosmological probes, the unsolved mystery of the nature of their progenitor has been called one of the big scientific embarrassment of the moment. This rhetorical form should not hide the tremendous progress that 3D hydro-dynamic ANR-GUI-AAP-05 Doc Scientifique 2012 V1 14/30

15 simulations have made during the past decade. If the exact nature of type Ia progenitors is still hotly debated, models are now at a point where they can simulate from first principle realistic light curves and even spectra. While light curves have been used to probe the total amount of radioactive nickel produced in the first stages of the explosion and spectral features to constrain the intermediate mass elements produces in the later stages, such approaches are now coming to a limit. In this context, spectro-photometric time series allow to probe simultaneously the full structure of the ejecta, and are the ideal Roseta stone to decipher the intricacies of type Ia physics. This is exciting not only because of its astrophysical implications, but because a better understanding of SNe Ia progenitors is crucial to constrain the potential bias that an evolution of the progenitor system with redshift could cause in deriving the cosmological parameters with type Ia supernovae. In a similar way, the use of flux calibrated time series of spectra opens the possibility to disentangle between the supernovae intrinsic, time dependent, behavior and the extinction caused by dust. A first step in this direction has been presented in Chotard et al Considering its success while only using one epoch of the SuperNova factory dataset, it opens promising prospectives on what can be achieve once the full dataset will be used at its fullest. Objectives: Separate the dust extinction from the intrinsic behavior of SNe Ia. Constrain explosion models and progenitors Subtask 2.1: Supernovae 3D model Responsible: C. Balland Participants : CPPM, LPNHE Program: Step 1 (LPNHE): The framework needed to consider SNe Ia as landscapes in the (flux, wavelenght, time) 3D space from descrete measurements at given times will be developped and delivered at Milestone 1 as an interpolator to task 1.1, and as a function basis for template development to task 2.2. Step 2: Implementation of a framework allowing to compare models to the observed SNe Ia (LPNHE), and to compare supernovae one to another (CPPM), employing the the true potential of spectro-photometric time series instead of a set of numbers (color,stretch) and one spectrum. Results will be delivered to tasks 1.3 and 2.3 at Milestone 2. Deliverables Algorithm to build a mathematical 3D spectro-photomatric model out of discrete measurements, acting as a phase interpolator. Method for meaningful comparison between objects and with models. Methods Advanced numerical techniques will be used to represent the SNe Ia as 3D objects in the (flux, wavelength, time) landscape like for example NURBS (Non-Uniform Rational Basis Spline) or Gaussian processes. Using new techniques would allow us to provide a mathematical model taking full advantage of the time coverage and wavelength resolution of the SNfactory, while taking into account observational error accurately. Statistical techniques beyond the use of L2 norm will be used to measure distances between data and model, and provide insight on which tensions and agreements are the most meaningful, and provide more discriminating power. Risk ANR-GUI-AAP-05 Doc Scientifique 2012 V1 15/30

16 The mathematical representation of SNe Ia as objects in the 3D (flux, wavelength, time) landscape is a guaranteed success. Even with existing proven techniques like splines, a useful mathematical representation could be implemented. Developing new metrics to measure the distance between models and data: The risk is small, considering that for all practical purposes a weighted chi-square can already be used with profit. The small risk involved here is in the development of a pertinent weighting scheme. This risk is mitigated by the statistical expertise developed in the laboratories involved, as well as by the strong ties with SNe Ia modeling some of the members of this current proposal have. All exploration of new techniques are here considered as a bonus. Subtask 2.2 Reddening law and template building Responsible: Postdoc 2 (to be hired by the project) Participants: LPNHE, LPC Program Step 1 (LPNHE): reddening law study. With spectral indicators derived by task 1.1 and the parametrization from task 2.1, a framework to study the reddening law at all phases will be setup: while SNe Ia intrinsic behavior is time dependent, dust in the line of sight is usually too far from the explosion to be impacted. This coupled with spectral features that trace the intrinsic behavior of the supernovae, generalizing for example what has been done in Chotard et al is a very powerful mean of separating the intrinsic behavior from the dust extinction. At Milestone 2, the framework should be ready to take into account the findings on intrinsic variability (task 1.3). Step 2: template building. Once the key variables are identified, a full supernova template will be derived, including the variability induced by intrinsic parameters variations, and by color (LPNHE). The effect of remaining dispersion to the model will be scrutinized and a conclusion made about the best way to derive cosmological distances: employing a direct distance fitter, or a two-step approach like in SALT2 (LPC). The templates will be ready for Milestone 3. Step 3: any-data fitter (LPNHE). As future generation surveys won't necessarily have supplementary spectrophotometric data to compute the intrinsic parameters, a dedicated study is needed to know wether they can be derived from light-curve fits or if complementary observations are needed. LPC has special interest to complete a case study in the framework of LSST data, and forsees to hire a PhD position who will partially work on this issue. The algorithm will be integrated to the package release (Task 3.2). Deliverables Reddening law model, and spectral templates matching intrinsic measured properties Supernova fitter for cosmology. Methods The reddening law model will be derived employing numerical high-dimensionality chisquare fitting and restricted maximum likelihood formalism. A specific break-through is expected from the high spectral resolution of the spectrophotometric data. Risk The expertise in developing SNe Ia templates accumulated in the contributing labs, especially in Paris where SALT2 was developed and in LPC with reddening studies mitigates the risk inherent to the development of new algorithm ANR-GUI-AAP-05 Doc Scientifique 2012 V1 16/30

17 Reddening law: Considering the much larger volume of information contained in time series, and considering that Chotard et al already had some success in this direction simply using spectra at maximum, the main risk here is not to be able to deliver because of a man power issue. This risk is addressed in the core of this proposal since one of the postdoc position we ask for will be set in priority on this task. Subtask 2.3 Data driven analysis of explosion models Responsible: S. Bongard. Participant: LPNHE Program Data driven analysis of explosion models : While explosion models have made tremendous progress in describing SNe Ia explosions, they are still not able to discriminate between progenitors system. On the other hand, using the host of information made available by the simulation to understand where models are the most realistic but also where they show the most tension with the data in a similar way to what was done in Bongard et al. (2008) is expected to yield strong constraints on the explosion models. Task 2.1 will provide will provide the metric needed to compare models to data; at Milestone 2, the major outcome from variability study and at Milestone 3 the resulting impact on spectrophotometric evolution will act as the main drivers of this analysis. Deliverables Data driven set of physical constraints to models Methods We will develop code and visualisation techniques to take advantage of all the secondary information provided by full 3D time dependent supernova spectral synthesis (opacity maps, ionization fractions, temperature structure, etc) Risk The proof of concept of this approach has been made in Bongard et al. (2008). The main risk in delivering constraints is due to the vastness of the problem, and is thus again a manpower issue. This is mitigated by the fact that there is already a PhD student working on this topic. Moreover, a postdoc taking over the crucial issue of the reddening law would free up an important fraction of the time of one of the staff scientists who would then take this task as his first priority TÂCHE 3 / TASK 3 : SN SPECTROPHOTOMETRIC DATASET AND ALGORITHM DISSEMINATION IN COMMUNITY Coord.: Y. Copin Participants: IPNL Supernova cosmology has been historically based on broad-band photometry at maximum, and rolling search observational paradigm combining detection and photometric follow-up has been used in multiple surveys, generating large photometric datasets (e.g. SNLS, SDSS, CSP). As a consequence, the interpretation effort and standardization methods have focused mainly on the SN light-curves: heterogeneous samples have been uniformized (e.g. Union and Constitution samples), and light-curve standardization tools have been developed (e.g. SALTs, MLCSs, SNooPy, etc.). A contrario, there is a drastic lack of consistent and homogeneous spectro-photometric datasets, specially in the time-domain (even though one should mention the historical SUpernova SPECTrum database), which in turn has severely limited the studies and cosmological use of the potentially richer SN spectrophotometry. ANR-GUI-AAP-05 Doc Scientifique 2012 V1 17/30

18 With the advent of new large-scale homogeneous spectral datasets (e.g. from SDSS or PTF), including purely spectro-photometric ones (such as SNfactory s), and the development of dedicated algorithms as mentioned in the other tasks of this proposal this situation is about to improve significantly, if the community is granted an easy access to these observations and tools. Objectives Disseminate homogeneous spectro-photometric datasets in community (starting with SNfactory sample), around max and other phases Develop and distribute new spectral analysis methods, including the time domain Subtask 3.1: Homogeneous access to spectro-photometric public datasets Resp.: N. Giraud Participants: IPNL Program Build a general framework for online and offline access to structured spectro-photometric homogenized samples, including complex queries on all accessible SN-related properties (phases, Hubble residuals, light-curve parameters, spectral indicators, host properties, etc.) For Milestone 2 : Import SNfactory dataset to this framework, as well as derived quantities like spectral indicator as a way to distribute the SNf sample to the collaboration and the community, and as an incentive for others to import external samples Deliverables Centralized web-accessible database and visualization tools Framework for local (offline) access to selected (sub)samples Publication of the SNfactory main spectrophotometric and auxiliary datasets Methods Modern DB-interfaces and visualization tools, decentralized browser-based clients. Given physical proximity and historical collaboration, the online database could naturally be hosted by the Computer Center (CC) of IN2P3 Risk The deliverable for this subtask is a general framework: we will offer the community flexible tools to manage and import their own datasets, but we don t plan to support external samples per se. This approach relies on sufficiently large adoption by the community. In any case, the SNfactory collaboration will use the tools, and this should act as a good incentive for others to step in and join the effort. The SNfactory dataset distribution policy is under the sole responsability of the SNfactory Collaboration Board. This policy risk will be handled by the three participants to this proposal (S. Bongard, Y. Copin, C. Tao) which are also members of this Board. Subtask 3.2: SN-dedicated spectro-photometric analysis packages Resp.: Y. Copin Participants: IPNL, LPNHE Program Centralize, package and distribute the algorithms developed in the frame of this proposal (see other tasks), potentially including ANR-GUI-AAP-05 Doc Scientifique 2012 V1 18/30

19 Classical spectral indicators Reddening law (determination and dereddening) Phase interpolation and other statistical tools (clustering, Gaussian processes) Visualization & data-mining tools Deliverables Centralized software distribution for SN spectro-photometric studies Methods Lightweight, easy-to-use, easy-to-install software, based on largely accepted datafile formats (e.g. FITS), high-level languages (e.g. Python through the new AstroPy effort) and distribution channels (e.g. distributed revision control systems) Risk The peculiar algorithm development risks are mentioned in their associated tasks The 4 participant labs already have a strong tradition in collaborative code development for the SNfactory data-production, thus mitigating the integration and interface risk CALENDRIER DES TÂCHES, LIVRABLES ET JALONS / TASKS SCHEDULE, DELIVERABLES AND MILESTONES Project deliverables summary : Task Deliverable Due (in month) Responsible 0 Mid-term review 18 E. Gangler/ LPC 0 Final review and reporting 36 E. Gangler/ LPC 1.1 Indicator prototype algorithm 6 Postdoc 1 / LPC ANR-GUI-AAP-05 Doc Scientifique 2012 V1 19/30