opacity to Lyman- radiation Sarah Bosman University College London - - PowerPoint PPT Presentation

opacity to lyman radiation
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opacity to Lyman- radiation Sarah Bosman University College London - - PowerPoint PPT Presentation

Update on the pathchiness of IGM opacity to Lyman- radiation Sarah Bosman University College London George Becker, Martin Haehnelt, Xiaohui Fan, Yoshiki Matsuoka (SHELLQs collaboration ), Sophie Reed (DES-VHS collaboration), Linhua Jiang


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SLIDE 1

Update on the pathchiness of IGM

  • pacity to Lyman-α radiation

Sarah Bosman University College London

George Becker, Martin Haehnelt, Xiaohui Fan, Yoshiki Matsuoka (SHELLQs collaboration ), Sophie Reed (DES-VHS collaboration), Linhua Jiang (SDSS collaboration)

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SLIDE 2

Probing Reionisation using Lyman-α transmission towards AGN

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 3

Probing Reionisation using Lyman-α transmission towards AGN

Fan+06

Full Gunn-Peterson absorption kicks in at z=5.9 Universe is at least 99.9% ionized at z<5.9 in a global-averaged sense

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 4

Probing Reionisation using Lyman-α transmission towards AGN

Credit: George Becker

Becker+15 discovers extremely opaque line of sight spanning z=5.5 – 5.85 : Intrinsic ∆ at the same redshift much larger than expected from density fluctuations alone!

𝜐eff

𝜐eff = − ln ( < 𝑮 >50 𝑑Mpc ℎ−1 )

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 5

Three families of models proposed:

Rare bright sources contribute significantly: AGN, largest galaxies e.g. Chardin+15, 17 Differential timing

  • f Re⁰ due to temperature

fluctuations: high ρ regions ionize, cool down and recombine first e.g. D’Aloisio+15; Keating+17 Varying mean free path

  • f Re⁰ photons due to

fluctuations of the UV background e.g. Davies & Furlanetto 16

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 6

Our objective: improve measurements of

▪ Dramatic increase in number of lines of sight: 62 (96) up from 33

  • > Grasp on cosmic variance, error bars

▪ Consistent measurement of across all lines of sight ▪ Push to z=6.1 ▪ Test biases in a statistical sample (e.g. length of proximity zone, data quality, bin size) 𝜐eff

𝜐eff

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 7

The catalogue: 62 QSOs at z>5.7

SHELLQs 4 DES-VHS 18 SDSS 13 archival 13 previous studies 19 new 3

Origin

X-Shooter 9 FOCAS 4 GMOS 3 ESI 21 HIRES 5 EFOSC 6 MMT 13 MagE 1 LBT-MODS 1

Spectrograph

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 8

Measurement technique

▪ Normalize spectrum by power-law fit to continuum ▪ = – ln (<F>) over fixed comoving window – usually 50 cMpc ℎ−1 ▪ Excludes quasar proximity zone, BALs and DLAs ▪ Two bounds depending on treatment of non-detections: take = – ln (2 ε) “real flux just below detection threshold” and = ∞ “real F = 0”

𝜐eff 𝜐eff 𝜐eff

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 9

Results

▪ Normalize spectrum by power-law fit to

We confirm the huge spread in Lyman-α opacities Opaque ‘tail’ already exists at z=5.2 !! First bounds at z=6.0

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 10

Consistency with previous work

▪ Normalize spectrum by power-law fit to

Our sample contains all quasars from previous B15 study: can check we get the same results All distributions agree with both Fan+06 and Becker+15 within 1σ measured via bootstrap (sub)sampling

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 11

Systematics: proximity zone

▪ Normalize spectrum by power-law fit to

Stacks of quasars in redshift bins + individual inspection Choose λ = 1178Å as fixed end of proximity zone

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 12

Systematics: binning size

▪ Normalize spectrum by power-law fit to

Repeat using l = 10, 30, 50, 70 cMpc ℎ−1 l = 10 cMpc ℎ−1 picks up individual peaks and troughs l > 30 cMpc 𝒊−𝟐 necessary

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 13

Systematics: data quality

▪ Normalize spectrum by power-law fit to

Pick SILVER and GOLD samples

  • f objects with SNR > 5.3 and

SNR > 11.2 (matching previous studies) Only few spectrographs can detect > 4 !

𝜐eff

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 14

Comparison with numerical models

Rare bright sources contribute significantly: Lines of sight from Chardin+17 Differential timing

  • f Re⁰ due to temperature

fluctuations: Lines of sight from Keating+17 ‘Null hypothesis’ with constant UV background: Lines of sight from the Sherwood simulation Bolton+17

The global emissivity in all of these is tuned to match the mean flux !!

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 15

Comparison with numerical models

Rare bright sources contribute significantly: Lines of sight from Chardin+15 Differential timing

  • f Re⁰ due to temperature

fluctuations: Lines of sight from Keating+17 Models don’t work Rare sources model does the best but still mismatches

  • bservations

More models being developed…

All of these are tuned to match the mean flux !!

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 16

Comparison with numerical models

SARAH BOSMAN SAKURA CLAW 2018

Models don’t work Mean opacity is a ‘forced match’ to simulations Spread or skewness is the issue

1 7

17

1 7

17

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SLIDE 17

Conclusions

▪ Improved measurements of Lyman-α

▪ Opaque tail still exists are z = 5.2 … which is a problem ▪ First bounds at z = 6.1

▪ Discrepancy with numerical models persists / gets worse when considering non- detection bounds ▪ A rare-sources-only (toy) model provides the only decent fit to the data so far…

▪ Future: better radiative transfer, self-shielding… ▪ Implications for observing high-z LAEs ?

𝜐eff

Thank you!

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SLIDE 18

The catalog

𝜐eff

SARAH BOSMAN SAKURA CLAW 2018

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SLIDE 19

UKIDS 4% PANSTARRS 35% DES-VHS 8% SHELLQs 14% VIKING 4% CFHQS 9% SDSS 23%

  • ther

3%

z > 5.7

SARAH BOSMAN SAKURA CLAW 2018