
Chania, Greece, May 24-27, 2016
The conference was held in the impressive historic building of the Grand Arsenal, built by the Venetians in the 1600s. The building, which has been fully renovated and currently houses the Center of Mediterranean Architecture, includes a modern amphitheater of 150 people capacity, with all the required amenities, including modern audiovisual equipment and wifi connection.
Awards
The 2016 prize (an iPad) for best poster was awarded to Thibault Kuntzer (EPFL) for his poster on Stellar classification from single-band imaging using machine learning.
Programme
The abstract book and the final program are available here: abstract_book-Cosmo21_V2.3
The emphasis of the conference is on advances and methodological challenges in cosmology, and new results derived from advanced data analysis and modeling methods. Cosmology is entering a new area which will require processing of huge data sets, and measurements at the sub-percent level of accuracy in order to answer fundamental cosmological questions such as the nature of dark matter, dark energy and gravity. As ever, statistics will inevitably play a fundamental role in understanding the new generation of data, but with additional challenges of ever-increasing datasets and large parameter spaces.
Topics
- Cosmic microwave background: non-Gaussianity, component separation methods.
- Weak lensing: galaxy shape measurements, projected mass density map reconstruction, three-dimensional mapping of the dark matter, high order statistics, Euclid, LSST.
- Large-scale structure
- High redshift supernovae.
- Mapping high-z 21-cm radiation
- Lyman-alpha forest
- Astronomical discovery from overwhelmingly large datasets: BOSS, EUCLID, PAU, LAMOST, LOFAR, SKA, LSST and others.
- Statistical methods used in astronomical data analysis (including new developments coming from fertile cross-interactions in astrostatistics). A preliminary list of these methods is included below:
- Bayesian methods, evidence, model selection.
- Multivariate classification and clustering.
- Sparsity: wavelets, compressive sampling, 2D and 3D data representations.
- Machine learning for large multivariate datasets: Kernel regression, Support Vector Machine, neural networks, supervised learning.
There will be several sessions during the conference. Each session will have at least one keynote speaker, and half of the talks will be contributed talks. The cross-disciplinary nature of the symposium is reflected in the inclusion of speakers from the statistics community in the suggested list.
KEYNOTE SPEAKERS
|
Shirley Ho, Carnegie Mellon University, US - Large Scale Structures |
Alexie Leauthaud, University of Tokyo, Japan - Weak Lensing |
David Spergel, Princeton University, US - Cosmic Microwave Background |
Roberto Trotta, Imperial College, London, UK - Bayesian Methodology |
Pierre Vandergheynst, EPFL University, CH - Data & Graphs |
INVITED SPEAKERS
|
Tania Regimbau, Nice Observatory, FR - Gravitational Waves |
Alice Pisani, CPPM, Aix-Marseille Univ., FR - Large Scale Structures, Voids |
Benjamin Joachimi, UCL, UK - Large Scale Structures |
Valeria Pettorino, Univ of Heidelberg, GER - CMB, modified gravity |
Yabebal Fantaye, Univ of Rome, IT - CMB lensing |
COSMO21 PROGRAM
Tuesday - May 24th, 2016 |
Session 1: Cosmology and Statistical Information I |
Chair: Jean-Luc Starck |
14:00 | 14:20 | Vassilis Charmandaris | Welcome |
14:20 | 15:00 | David Spergel, Keynote | WFIRST and the next generation of Surveys |
15:00 | 15:30 | Valeria Pettorino Invited | Dark Energy and Modified Gravity after Planck |
15:30 | 15:50 | Caitlin Adams | Beating cosmic variance in the low - redshift universe |
15:50 | 16:10 | Adam Amara | Information from Cosmology Experiments |
16:10 | 16:40 | Coffee Break | |
Session 2: Gravitational Waves | |||
Chair: Roberto Trotta | |||
16:40 | 17:20 | Tania Regimbeau , Invited | Observation of Gravitational Waves from a Binary Black Hole Merger |
Poster Session |
17:20 | 19:00 | Posters Session | |
19:00 | 20:30 | Cocktail |
Wednesday - May 25th, 2016 | |||
Session 3: Bayesian Methods | |||
Chair: Alan Heavens | |||
09:00 | 09:40 | Roberto Trotta, Keynote | Bayesian Hierarchical Models in Cosmology |
09:40 | 10:00 | Cong Ma | Application of Bayesian Graphs to Type Ia Supernova Data Analysis and Compression |
10:00 | 10:20 | Hikmatali Shariff | BAHAMAS: new SNIa analysis reveals inconsistencies with standard cosmologyf |
10:20 | 10:40 | Kaisey Mandel | Hierarchical Bayesian Models for Type Ia Supernova Intrinsic Variations and Host Galaxy Dust |
10:40 | 11:10 | Coffee Break | |
Session 4: Cosmology and Statistical Information II | |||
Chair: Adam Amara | |||
11:10 | 12:40 | Benjamin Joachimi, Invited | Small errors for big surveys |
11:40 | 12:00 | Didier Fraix-Burnet | Multivariate classification of galaxies: which observables? |
12:00 | 12:20 | Andriy Olenko | On Minkowski functionals of random fields |
12:20 | 12:40 | Steven Murray | Accounting for Eddington bias in observed mass functions using hierarchical Bayesian likelihoods |
12:40 | 14:00 | Lunch Break | |
Session 5: Survey & Statistics | |||
Chair: David Spergel | |||
14:0 | 14:40 | Shirley Ho, Keynote | Digging in the Large Scale Structure of the Universe |
14:40 | 15:00 | Mark Neyrinck | Sliced correlations: revealing density- dependent clustering, and the correlation function’s statistical issues |
15:00 | 15:20 | Jelena Aleksic | Digging Deeper in Imaging Surveys |
15:20 | 15:40 | L. Raul Abramo | Fourier analysis of multi-tracer cosmological surveys |
15:40 | 16:00 | Vicent Martinez | Joint constraints on galaxy bias and sigma8 through the N-pdf of the galaxy number density |
16:00 | 16:20 | Valeria Amaro | |
16:20 | 16:50 | Coffee Break | |
Session 6: Machine Learning I | |||
Chair: Emile E. O. Ishida | |||
16:50 | 17:10 | Boris Leistedt | Accurate photometric redshifts with no or shallow spectroscopic training data |
17:10 | 17:30 | Alex Malz | Cosmological Inference Using Photometric Redshift Probability Distribution Functions |
17:30 | 17:50 | Carlo Enrico Petrillo | Selection of strong gravitational lenses with convolutional neural networks |
20:30 | 00:00 | Conference Dinner |
POSTER PRESENTATIONS
See also the COSMO21 best poster prize web page
P# | Presenter | Poster Title | |
1 | Amon | Alexandra | Testing Einstein's gravity with the gravitational slip statistic on cosmological scales |
2 | Berlind | Andreas | Accurate Modeling of Galaxy Clustering on Small Scales through Data Simulation |
3 | Ballardini | Mario | Constraints on Induced Gravity: reproducing the cosmic acceleration with a scalar-tensor model |
4 | Ballardini | Mario | Probing violations of slow-roll inflation with future galaxy surveys |
5 | Baxter | Eric | Joint Measurement of Lensing-Galaxy Correlations Using South Pole Telescope and Dark Energy Survey Data |
6 | Beck | Robert | Automated classification of emission line galaxies using machine learning methods |
7 | Beck | Robert | Photo-z-SQL: Integrated On-demand Photo-z Services in a Database |
8 | Bird | Simeon | Minimally Parametric Power Spectra from BOSS Lyman-alpha data |
9 | Bunn | Emory F | Polarization predictions for cosmological models with broken statistical isotropy |
10 | Caro | Fernando | Morphological classification of galaxies using deep learning |
11 | Carucci | Isabella P. | Exploiting the 21cm power spectrum: forecasts for SKA on the warm dark matter and cross-correlation with the Lyman-alpha forest flux. |
12 | Chan | Jennifer Y. H. | Cosmological polarised radiative transfer and diagnostics of large-scale magnetic field structures |
13 | Chan | Jennifer Y. H. | Second-generation curvelets on the sphere for efficient representation of elongated structure |
14 | de Souza | Rafael S. | Beyond Gaussian: An overview of Bayesian Generalized Linear Models for Astronomers |
15 | Demchenko | Vasiliy | A Test of Spherical Evolution of Cosmic Voids in Λ-CDM |
16 | Dupac | Xavier | The Planck Legacy Archive for cosmology |
17 | Ebrahimpour | Leyla S. | Bayesian parametric and non-parametric characterisation of relations between galaxy cluster properties |
18 | Farrens | Samuel | PSF Deconvolution For Future Weak Lensing Surveys |
19 | Giblin | Benjamin | Results from the first 450 sq. degrees of the Kilo Degree Survey |
20 | Gizani | Nectaria | Using diffuse radio emission in clusters of galaxies to probe the cosmic web, cosmic rays and dark matter |
21 | Godłowski | Wlodzimierz | New method of investigation of the alignment of galaxies in clusters |
22 | Han | Bo | A Divide and Conquer Approach Applied for Photometric Redshift Estimation |
23 | Jamal | Sara | zBayes : Bayesian approach for the spectroscopic redshift estimation |
24 | Kovács | András | Dark Energy illuminated by cosmic voids in the DES footprint |
25 | Kovács | András | Cosmic troublemakers: the Cold Spot, the Eridanus Supervoid, and the Great Walls |
26 | Kuntzer | Thibault | Stellar classification from single-band imaging using machine learning |
27 | Lablanche | Pierre-Yves | A MCMC method for supernova classification |
28 | Lei | Ya-Juan | Spectral analysis of the SUZAKU data of GX 9+9 |
29 | Leistedt | Boris | 3D weak lensing with spin wavelets on the ball |
30 | Long | James | Near Field Cosmology with RR Lyrae Variable Stars |
31 | Mak | Daisy | New measurement of CIB power spectra from Planck HFI maps |
32 | Niemiec | Anna | Halo mass measurements of satellite galaxies in CFHT Stripe82 and CFHTLenS |
33 | Nunez | Carolina | Photometric Selection of a Massive Galaxy Catalog with z≥ 0.55 |
34 | Peel | Austin | Cosmological constraints from peak counts in a Euclid-like simulation |
35 | Petrakis | Manolis | Non-Stationary Covariance Functions for the Interpolation of Irregularly Sampled Data Sets |
35 | Petrillo | Carlo Enrico | Selection of strong gravitational lenses with convolutional neural networks. |
36 | Pignata | Giuliano | Supernovae photometric typing for the SUDARE survey |
37 | Pratley | Luke | The Influence of Convolutional Gridding on Sparse Image Reconstruction for Radio Interferometry |
38 | Racz | Gabor | An n-body simulation to estimate the effects of inhomogeneities on the expansion of the Universe |
39 | Rémy | Joseph | Automated colour-based deblending of the Hubble Frontier Fields |
40 | Renneby | Malin | The galaxy-halo relation through a lens of cosmological rescaling |
41 | Rogers | Keir | Spin-SILC: CMB polarisation component separation with spin directional wavelets |
42 | Ruppin | Florian | Multi-probe analysis of high resolution observations of galaxy clusters by the NIKA camera |
43 | Sánchez Gil | M. Carmen | Hierarchical Bayesian approach for estimating physical properties in spiral galaxies |
44 | Schmit | Claude | 3D Statistical Analysis of the Cosmic 21cm Signal |
45 | Schmitt | Alain | AMAZED : Algorithm for Massive Automated Z Evaluation and Determination |
46 | Schuhmann | Robert L. | Gaussianisation for Bayesian posterior distributions and model comparison in cosmology |
47 | Smailagic | Marijana | A Model for Evolution of Lyα Blobs Number Density at z~ 1-6.6 |
48 | Sulis | Sophia | Statistical analysis of an extrasolar planet detection approach based on hydrodynamical simulations |
49 | Tarrío | Paula | A matched filter approach for the joint detection of galaxy clusters in X-ray and SZ surveys |
50 | Tihhonova | Olga | Mapping the Mass Along the Line of Sight of Multiply Lensed Quasars |
51 | Umiltà | Caterina | Pushing further component separation and improving Planck cosmological results |
52 | Yu | Yu | Kriging Interpolating Cosmic Velocity Field |
53 | Zhang | Yanxia | The Influence of Sample Selection on Photometric Redshift Accuracy |