Fast Radio Burst Dispersion Measures & Rotation Measures

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Keith Vanderlinde; NASA Fast Radio Burst Dispersion Measures & Rotation Measures Bryan Gaensler! (University of Toronto)!! with Tony Piro, Klaus Dolag,! Anthony Walters,! Amanda Weltman, Yin-Zhe Ma,! Manisha Caleb, Emily Petroff. Takuya Akahori, Dongsu Ryu!!

Dispersion Measure and Rotation Measure DM ν delay = 0.41 seconds pc cm 3 100 MHz DM = " 0 n %"! n $! RM = 0.812 # e & B $! dl $ $ e ' dl % $ ' pc cm -3 " cm -3 # %" µg& # & rad m -2 B # cm 3 = 1.232 (RM / rad m-2 ) &# pc & L/pc %" pc % (DM / pc cm -3 ) µg 0 L/pc Manchester et al. (1996) Philipp Kronberg / Physics Today 2 ΔΘ = RM λ 2 Manchester et al. (1996)

Possible DM & RM Contributions Milky Way disk (Oppermann et al. 2015; Yao et al. 2016) Milky Way halo (Dolag, Gaensler et al. 2015) Host galaxy (Xu & Han 2015; Yang et al. 2016, 2017) Local environment (Connor+ 2016; Lyuitkov+ 2016; Piro 2016, 2017) Intergalactic medium (IGM) (McQuinn 2014; Dolag, Gaensler et al. 2015; Akahori, Ryu & Gaensler 2016) Cosmological expansion (Zhou et al. 2014; Gao et al. 2014) Swinburne Astronomy Productions Gemini Observatory/AURA/NSF/NRC

DM & RM of Supernova Ejecta Piro (2016)

Stellar Winds Bubble Nebula, aka NGC 7635 (ESA/Hubble)

Progenitor Winds: SN 1987A ESA/Hubble ESO / L. Calçada

Progenitor Winds: SN 1979C Montes et al. (2000)

Progenitor Winds: 1E 1048.1-5937 ATCA (21cm H I) + Chandra (Gaensler et al. 2005)

Supernova Remnants SNR G296.5+10.0 (Harvey-Smth, Gaensler et al. 2010)

Stellar Wind Structure Unshocked wind: nr () = Mo 2 rrv3m 4 H Draine (2010)

Stellar Wind Structure Unshocked wind: Br ()~ B * S R r X S V V * rot 3 X J. Jokipii, University of Arizona

Swept Up RM and DM (I) Shocked ejecta (Piro 2016): DM SNR 3fionMej () t t 2 () t. ( V 2 1/ 2 3fionMej = 2 RMSNR = 0 81 4re Bt rev) 2 t 4rVSNRmH 4rVSNRmH - - 2 Uniform ambient medium (un-ionised) :. DM ( t) = nv 0 SNR R 3 t RM ( t) = 0 14 SNR SNR n0b0 V SNR a S t DR X Stellar wind: RM SNR a + 2 Mo -1 DM SNR( t) = S X a + 1 4 rv V m t 3 SNR H 1 1 V BRMo () t 0. 81 rot * * = # 2 2 a + &S X ( 1 a) V 4rV VSNRm + 3 3 a = H D R R. 12 1 t -2 Piro (2016); Piro & Gaensler, in preparation

Swept Up RM and DM (II) Piro & Gaensler, in preparation

Swept Up RM and DM (III) Uniform ambient medium : negligble Shocked SNR ejecta: (Piro 2016; Piro & Burke-Spolaor 2017) DM RM SNR SNR Mej fion VSNR t ()~ t 100 S XS XT 4 Y S X M9 01. 10 km/s 10 yr -2-2 Mej fion VSNR t ()~ t 400 S XS XT 4 Y S X M9 01. 10 km/s 10 yr -1-2 pc cm Stellar wind (normalised by parameters for a red supergiant): -3 rad m -2 DM SNR Mo V3 VSNR t ()~ t 10 T 10-5 -1 YS X T 4 Y S X M9 yr 30 km/s 10 km/s 10 yr -1-1 -1 pc cm -3 RM ()~ t 3 10 SNR # 4 B R Mo * * Vrot/ V3 V3 VSNR S XS X t 500 G 300 R T -5-1 YT YS X T 4 Y S X 9 10 M9 yr 0. 1 30 km/s 10 km/s 10 yr -1-2 -2 Evolution of DM & RM for repeating FRBs: overall + detailed diagnostic? rad m -2 Piro & Gaensler, in preparation

Magneticum Pathfinder Simulation Very large cosmological simulation (896h -3 Mpc 3 ) (Dolag et al. 2014) - cosmic web and halos (but not disks) - supernova heating, winds, ionisation, AGN growth, chemical evolution - medium-resolution simulation for overall volume - high-resolution simulation for galaxies & halos Dolag, Gaensler, Beck and Beck (2014) Klaus Dolag T (colour) and n (intensity) at z = 0 DM out to z = 2

DM Distribution: Random Dolag, Gaensler, et al., in preparation

DM Distribution: Traces Stars Dolag, Gaensler, et al., in preparation

DM Distribution: Stellar Populations Metal poor Young Dolag, Gaensler, et al., in preparation

Energy Distribution (I) p(e) E β, fluence > F detect β = 0.0 β = 0.5 β = 1.0 β = 1.5 β = 2.0 z eff = 0.90 Dolag, Gaensler, et al., in preparation

Energy Distribution (II) p(e) E β, fluence > F detect β = 0.0 β = 0.5 β = 1.0 β = 1.5 β = 2.0 z eff = 0.96 Dolag, Gaensler, et al., in preparation

Energy Distribution (III) p(e) E β, fluence > F detect β = 0.0 β = 0.5 β = 1.0 β = 1.5 β = 2.0 z eff = 1.04 Dolag, Gaensler, et al., in preparation

Energy Distribution (V) p(e) E β, fluence > F detect β Dolag, Gaensler, et al., in preparation z

RM Contribution: Host Halo Beck et al. (2013)

RM vs DM (z = 1.74) FRB 110523 FRB 160102 Disk contribution: 15 μg RM obs (rad m -2 ) 100 FRB 150807 FRB 150418 HALO ONLY 10 100 1000 DM obs (pc cm -3 ) Dolag, Gaensler et al. (in preparation)

RM vs DM (z = 1.74) FRB 110523 FRB 160102 RM obs (rad m -2 ) 100 FRB 150807 FRB 150418 HALO + IGM 10 100 1000 DM obs (pc cm -3 ) Dolag, Gaensler et al. (in preparation)

RM vs DM vs Redshift z = 1.74 z = 1.49 z = 1.05 z = 0.73 z = 0.49 z = 0.30 Dolag, Gaensler et al. (in preparation)

Faraday Rotation of the IGM B IGM is discriminant between competing models of cosmic magnetism B < = 1 0. 81 DM RM Three issues for RM of IGM RM : - Main DM source depends on z (WHIM at low z ; voids at high z) - Main source of RM: hot cluster gas - DM and RM have different redshift dependencies Magnetic fields [ng] Modified equation: (Akahori, Ryu & Gaensler 2016) 100 10 1 ALL T57 TS0 B B < < 1 1 + z = 0. 81 f 1 = 0. 81 DM RM WHIM DM, WHIM DM RM B,IGM 1 2 3 4 5 6 1+z B < = 1 1 + z 0. 81 f WHIM DM, WHIM DM RM Akahori, Ryu & BMG (2016)

Summary & Future Work DM and RM from progenitor wind could be significant, should evolve with time - to do: full simulations, realistic wind models Joint statistics of DM and RM will become increasingly important probe - to do: properly incorporate host contribution, simulate fluence distributions FRB DMs may be sensitive to cosmology beyond flat ΛCDM - to do: sophisticated modelling of host galaxies and uncertainties - full joint constraints from FRBs with CMB, SNe, BAOs, IM, WL, RSD CAASTRO CAASTRO Gao et al. (2014)