Notes and discussions

Anze Slosar

Notes:

• Surveys interacting with S4: live on k-plane

• Taxonomy of surveys: 

  • projected tracers (CMB lensing, WL, GC): low k_perp, no k_par 

  • Spec surveys: all plane

  • Foregrounded: no kpar

• Cross-correlation: overlap in k modes

• Proj: no redshift specificity

• Spectro: full 3D, xcorr with CMB only small slice, high SN

• Foregrounded: no kpar, 21cm, do not overlap with CMB lensing (projected)

• Redshift specificity helps a lot - 3x2pt, CMB lensing

• Higher order stats: allow you to combine things that don’t necessarily overlap on k plane

• Field reconstructions to recover lost k modes, e.g. 21cm, reconstruct initial modes

• CMB: lensing (complete, sample-variance cancelation), tSZ/kSZ, ISW, moving lens, patchy reionization - xcorr with 21cm

• Combine kSZ ML: Hotinli et al.

Questions:

• Most promising avenue for CMB x 21cm?
  → Probably tidal reconstruction or lensing reconstruction

Utkarsh Giri

Notes:

• kSZ: CMB photon scattering by moving electrons

• Sec. anisotropy prop to velocity and electron density

• Fixed realization of vr produces non-vanishing correlation between deltag and T -> reconstruct velocity mode

• Vr probes large scale cosmological modes, on large scales: cosmological fields linearly related, on large scales - vr reconstruction noise smaller than GC shot noise

• Application: fNL, sample variance cancelation due to additional tracers

• Use vr as additional tracer -> strong fNL constraints

• Question: rely on linear noise models, nonlinearities?

• 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

• Noises can be captured analytically

• 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:

• Projected tracers, e.g. LSST, tracers of matter fluctuations

• Focus on CMB lensing and WL, GC

• tSZ tomography: cross-correlate tSZ with clustering - constrain gas pressure / mass bias

• Cluster mass calibration - high-z clusters

• Tomography: reconstruct redshift dependence, Nx2pt

• Use tomography to constrain growth - break bias - growth degeneracy with CMB lensing

• Growth reconstruction: check probe consistency, consistency with LCDM

  • Two data sets: DECALS, KiDS / DES / Planck

  • Decouple growth from background - growth spline with nodes

  • S8(z): data comb gives evidence of lower growth at 0.2<z<0.6 -> driven by shear

  • Need CMB lensing for high-z

  • LCDM good fit with lower S8

• Systematics:

  • Photoz uncertainties: analytic marg, self-calib, CMB x less sensitive

  • Shear calibration:

  • Galaxy bias: hybrid EFT

Questions:

Alex Krolewski

Notes:

• Improve on CMB lensing auto with GC - growth of structure, brings in galaxy bias -> need all probes

• Related to S8 tension

• Use CMB lensing as xcheck of optical lensing

• Pick galaxy sample with high S/N

  • High z - overlap with lensing kernel

  • Angular coverage

  • WISE: infrared galaxy survey: all-sky, gals with old stellar pops can be easier to detect in WISE

• Three galaxy samples: blue, red, green z~0.6 - z~1.5

• Need to remove stars using GAIA - contamination left 1%

• Redshift distribution: no photoz - > do cross-correlation redshifts with specs, measure n(z) and bias evolution, so just include measured relations in theory

• Theory: linear + HO bias (dominated by linear modes), allows fix cosmo & HO bias

• Tests on mocks, calibration of scales used, lmax~250-300

• Redshift uncertainty: run sep. chains for all nz realizations -> full shape marg.

• 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:

• ISW and CMB lensing around substructures

• ISW and CMB lensing: Sourced by same late-time grav potential 

• ISW: probe of accelerated expansion - time-varying potentials

• Photons in voids: cold-spot in CMB, photons in clusters: hot spot

• Usually: cross-correlations between primary CMB and LSS tracers (e.g. lensing)

  • Joint measurements of GC, CMB lensing, ISW

• Why superstructures?

  • Look at generalization of cluster cosmology, peak counts, etc.

  • Beyond 2pt

  • Beyond GR - different behaviour in high/low density regions

  • Granett et al., 2008: amplitude of stacked CMB temperature high compared to LCDM expectation

  • Question: what is the cause for this?

• Repeat analysis using DESI legacy survey 

  • reduce sample variance

  • No detection for temperature imprints from supervoids 

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:

• NNs to map N-bodies to baryons: CNN / DeepSet

• Predict baryonic fields from DM only - baryons local, i.e. use local ML approach

• Usage:

  • Rapidly generate sims

  • Interpret trained model and learn about astro

• CNN:

  • DM -> pe, ne

  • Use CNN on 3D field, redshift zero

  • Semianalytic models

  • Main problem: sparsity, only small fraction of volume is interesting, overcome by biasing training sample using zoom-ins

  • Electron pressure spans large dynamic range (input trafos, semi-analytic model)

  • Small scales well fit, large scales better than models, projection improves performance

• DeepSet:

  • Concentrate on massive halos -> no transl symmetry

  • CNNs not best approach: spend lot of resource on empty regions, poor interpretability

  • Idea: can we use simulations representation to train NN? - DeepSet VAE

  • Restricted architecture improves on existing models

Questions:

• Interpolate between baryonic feedback models? Train on one sim and then do transfer learning on other sim

Jia Liu

Notes:

• Why sims? Test pipelines, systematics, astrophysics, covariance, modeling

• 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

• Typical CMB sims: 2D, gravity only, CMB observables painted -> Sehgal, Stein

• Typical LSS sims: 2/3D, more cosmo, hydro/gravity only, curved/flat, smaller boxes

• Correlated sims need to accommodate both worlds

• current : run by experts in both areas

• Yuuki Omori: MultiDark Planck 2

• Roadmap:

  • Basis: gravity-only sims

  • Then send off to experts and paint on CMB / LSS observables

  • Coordination!

  • How to get gravity-only sims: fast full-sky lightcone (e.g. COLA, FastPM)

  • Challenges: computing, storage, requirements, maintenance, personnel

Questions:

Dongwon ‘DW’ Han

Notes:

• Need correlated sims: high-res, multi-frequency, need NG info

• Computationally expensive -> use DL

• mmDL: CMB kappa -> NG kappa, kSZ, tSZ, CIB, radio + lensed TUQ

• Network:

  • Data augmentation, not enough sims

  • Conversion / prediction

  • NG restoration step

• Results:

  • Reproduce source counts, power spectra, cross-correlations, bispectra, trispectra (CMB lensing biases)

  • Network can recover correlations between large and small scales even though trained on small patches

  • Variance in sims comparable to Knox

• Sims available publicly

• Allow mass-production of independent full-sky realizations

• Fast: forward-modeling

• Future:

  • Fixed cosmology - CAMELS?

  • Missing associated catalog - extension to create catalogs

  • Can we use network to learn optimal summary stats?

Questions: