Notes and discussions
Anze Slosar
Notes:
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Surveys interacting with S4: live on k-plane
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Taxonomy of surveys:
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Cross-correlation: overlap in k modes
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Proj: no redshift specificity
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Spectro: full 3D, xcorr with CMB only small slice, high SN
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Foregrounded: no kpar, 21cm, do not overlap with CMB lensing (projected)
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Redshift specificity helps a lot - 3x2pt, CMB lensing
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Higher order stats: allow you to combine things that don’t necessarily overlap on k plane
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Field reconstructions to recover lost k modes, e.g. 21cm, reconstruct initial modes
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CMB: lensing (complete, sample-variance cancelation), tSZ/kSZ, ISW, moving lens, patchy reionization - xcorr with 21cm
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Combine kSZ ML: Hotinli et al.
Questions:
Utkarsh Giri
Notes:
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kSZ: CMB photon scattering by moving electrons
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Sec. anisotropy prop to velocity and electron density
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Fixed realization of vr produces non-vanishing correlation between deltag and T -> reconstruct velocity mode
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Vr probes large scale cosmological modes, on large scales: cosmological fields linearly related, on large scales - vr reconstruction noise smaller than GC shot noise
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Application: fNL, sample variance cancelation due to additional tracers
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Use vr as additional tracer -> strong fNL constraints
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Question: rely on linear noise models, nonlinearities?
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Use sims to investigate noise assumptions: 2-3 times larger noise for reconstructions due to nonlinear noises (similar to CMB lensing biases) N1, N3/2
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Noises can be captured analytically
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Use sims to check SVC -
Questions:
Blake: is it obvious why the N3/2 bias is a lot bigger than the N1? (Sorry if I missed this.)
Manu: How important is accurate modeling of N32?
Colin: what sets the scale at which N3/2 peaks?
David Alonso
Notes:
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Projected tracers, e.g. LSST, tracers of matter fluctuations
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Focus on CMB lensing and WL, GC
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tSZ tomography: cross-correlate tSZ with clustering - constrain gas pressure / mass bias
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Cluster mass calibration - high-z clusters
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Tomography: reconstruct redshift dependence, Nx2pt
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Use tomography to constrain growth - break bias - growth degeneracy with CMB lensing
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Growth reconstruction: check probe consistency, consistency with LCDM
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Two data sets: DECALS, KiDS / DES / Planck
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Decouple growth from background - growth spline with nodes
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S8(z): data comb gives evidence of lower growth at 0.2<z<0.6 -> driven by shear
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Need CMB lensing for high-z
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LCDM good fit with lower S8
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Systematics:
Questions:
Alex Krolewski
Notes:
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Improve on CMB lensing auto with GC - growth of structure, brings in galaxy bias -> need all probes
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Related to S8 tension
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Use CMB lensing as xcheck of optical lensing
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Pick galaxy sample with high S/N
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High z - overlap with lensing kernel
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Angular coverage
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WISE: infrared galaxy survey: all-sky, gals with old stellar pops can be easier to detect in WISE
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Three galaxy samples: blue, red, green z~0.6 - z~1.5
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Need to remove stars using GAIA - contamination left 1%
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Redshift distribution: no photoz - > do cross-correlation redshifts with specs, measure n(z) and bias evolution, so just include measured relations in theory
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Theory: linear + HO bias (dominated by linear modes), allows fix cosmo & HO bias
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Tests on mocks, calibration of scales used, lmax~250-300
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Redshift uncertainty: run sep. chains for all nz realizations -> full shape marg.
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Results: samples consistent, 2.6sigma tension with Planck in S8
Questions:
David A.: Can you say a bit more about the N(z) marginalization using clustering redshifts? E.g. do you need to worry about the fact that the measurements allow for negative values?
Blake: If I recall right, DES obtained the same S8-only constraint but did not report tension with Planck when considering the full posterior. Could you remind me how you obtained the 2.6sigma tension number and could a similar effect operate here?
Yan-Chuan Cai
Notes:
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ISW and CMB lensing around substructures
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ISW and CMB lensing: Sourced by same late-time grav potential
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ISW: probe of accelerated expansion - time-varying potentials
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Photons in voids: cold-spot in CMB, photons in clusters: hot spot
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Usually: cross-correlations between primary CMB and LSS tracers (e.g. lensing)
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Why superstructures?
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Look at generalization of cluster cosmology, peak counts, etc.
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Beyond 2pt
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Beyond GR - different behaviour in high/low density regions
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Granett et al., 2008: amplitude of stacked CMB temperature high compared to LCDM expectation
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Question: what is the cause for this?
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Repeat analysis using DESI legacy survey
Questions:
Jia: why is there no lack of signal for void (but it is there for clusters..)? I.e.why “lensing is low” is not impacting void? Answer: could be related to photo-z bias, or something physical (e.g. neutrino free-streaming) but no definitive answer.
David A.: there was a recent paper measuring a negative ISW from voids at very high redshifts from QSOs. Do you have any thoughts on that? (this one)
Yan-Chuan Cai: Yes. I think the statistical significance isn’t very high,less than 3sigma I think, similar to many other analyses. It would be great to have more volume to beat down the variance.
Leander Thiele
Notes:
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NNs to map N-bodies to baryons: CNN / DeepSet
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Predict baryonic fields from DM only - baryons local, i.e. use local ML approach
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Usage:
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CNN:
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DM -> pe, ne
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Use CNN on 3D field, redshift zero
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Semianalytic models
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Main problem: sparsity, only small fraction of volume is interesting, overcome by biasing training sample using zoom-ins
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Electron pressure spans large dynamic range (input trafos, semi-analytic model)
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Small scales well fit, large scales better than models, projection improves performance
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DeepSet:
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Concentrate on massive halos -> no transl symmetry
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CNNs not best approach: spend lot of resource on empty regions, poor interpretability
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Idea: can we use simulations representation to train NN? - DeepSet VAE
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Restricted architecture improves on existing models
Questions:
Jia Liu
Notes:
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Why sims? Test pipelines, systematics, astrophysics, covariance, modeling
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Why correlated? CMB foregrounds and LSS, not super useful for survey systematics because will be uncorrelated, but extragalactic, astrophysics syst will show up differently, input to train ML models
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Typical CMB sims: 2D, gravity only, CMB observables painted -> Sehgal, Stein
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Typical LSS sims: 2/3D, more cosmo, hydro/gravity only, curved/flat, smaller boxes
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Correlated sims need to accommodate both worlds
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current : run by experts in both areas
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Yuuki Omori: MultiDark Planck 2
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Roadmap:
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Basis: gravity-only sims
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Then send off to experts and paint on CMB / LSS observables
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Coordination!
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How to get gravity-only sims: fast full-sky lightcone (e.g. COLA, FastPM)
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Challenges: computing, storage, requirements, maintenance, personnel
Questions:
Dongwon ‘DW’ Han
Notes:
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Need correlated sims: high-res, multi-frequency, need NG info
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Computationally expensive -> use DL
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mmDL: CMB kappa -> NG kappa, kSZ, tSZ, CIB, radio + lensed TUQ
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Network:
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Results:
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Reproduce source counts, power spectra, cross-correlations, bispectra, trispectra (CMB lensing biases)
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Network can recover correlations between large and small scales even though trained on small patches
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Variance in sims comparable to Knox
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Sims available publicly
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Allow mass-production of independent full-sky realizations
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Fast: forward-modeling
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Future:
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Fixed cosmology - CAMELS?
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Missing associated catalog - extension to create catalogs
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Can we use network to learn optimal summary stats?
Questions: