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Testing GR with GW polarizations Maximiliano Isi LIGO Laboratory, California Institute of Technology July 12, 2017 @ Amaldi12 LIGO-G1701301 using LIGO and Virgo

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Testing GR with GW polarizations

Maximiliano Isi

LIGO Laboratory, California Institute of Technology

July 12, 2017 @ Amaldi12

LIGO-G1701301

using LIGO and Virgo

LIGO-G1701301Max Isi - Amaldi 2017 2

Testing GR with GWs

dispersion

agreement with NR

self-consistency

not about polarizations!there are currently no model-independent

measurements of GW polarizations

we have already learned a lot from transients:

LIGO-G1701301Max Isi - Amaldi 2017 3

it is important to probe GW polarizations

we can do so with current detectors

using long-lived signals

[tl;dr]

[too long ; didn’t read]

LIGO-G1701301Max Isi - Amaldi 2017 4

x

y

z

x

x

y

z

y

z

y

x

y

plus

cross

vector x

vector y

breathing

longitudinal

LIGO-G1701301Max Isi - Amaldi 2017

Theory + x x y b l

General Relativity

GR in noncompactified 4/6D Minkowski

Einstein-Æther

5D Kaluza-Klein

Randall-Sundrum braneworld

Dvali-Gabadadze-Porrati braneworld

Brans-Dicke

f(R) gravity

Bimetric theory

Four-Vector Gravity

allowed / depends / forbiddenNishizawa et al., Phys. Rev. D 79, 082002 (2009) [except G4v & Einstein-Æther].

5

LIGO-G1701301Max Isi - Amaldi 2017 6

motivation

GR makes unequivocal prediction that only + & x should propagate

polarizations are go/no-go test, so let’s check!

LIGO-G1701301Max Isi - Amaldi 2017

breathing

longitudinal

plus

cross

vector x

vector y

7

LIGO-G1701301Max Isi - Amaldi 2017

antenna pattern for cross polarization

8

detector

source

*

LIGO-G1701301Max Isi - Amaldi 2017 9

persistent signals

antenna patterns leave imprint in

persistent signals characteristic of

each polarization

continuous-wavesstochastic background

LIGO-G1701301Max Isi - Amaldi 2017 10

new bayesian analyses

detect long GWs of any polarization(from known pulsars, or a stochastic background)

distinguish between GR and non-GR

limit amplitude of scalar/vector modes

}model selection

➜ parameterestimation

Isi et al. (2017) [arXiv:1703.07530]

Callister et al. (2017) [arXiv:1704.08373]

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

NASA / CXC / SAO

11

crab pulsar

one of ~200 known pulsars potentially in LIGO’s band

continuous waves

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

12

�(t) ⇡ 2⇡ ⇥ (2frot

)+ doppler and other timing corrections

h(t) = h01

2

�1 + cos

2 ◆�F+(t) cos�(t) + h0 cos ◆ F⇥(t) sin�(t)

h0

, overall strength; ◆, inclination; F (t), antenna pattern; frot

, rotational frequency

simple form, in general relativity:

continuous wavescoherent, monochromatic, well-localized

in a generic metric theory of gravity:

p 2 {+, ⇥, x, y, s}

h(t) =X

p

Fp(t)ap cos(�(t) + �p)

polarization amplitude

phase offset

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

tensor

vector scalar

polarization

antenna pattern

amplitude modulationover a sidereal day

Crab pulsar LIGO H1

13

time (h) time (h)

Crab pulsar LIGO H1

Crab pulsar LIGO H1

time (h)

ante

nn

a r

espon

se

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]signal vs noise

14

10�28 10�27 10�26 10�25

hGR

0

101

102

103

104

lnO

m N

Any

GR

tensor injections

odds(detection statistic)

Crab H1L1V1 1yr advanced design

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

15

10�28 10�27 10�26 10�25

hG4V

0

101

102

103

104

lnO

m N

Any

GR

vector injections

odds(detection statistic)

vector

Crab H1L1V1 1yr advanced design

signal vs noise

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

16

10�28 10�27 10�26 10�25

hGR

10�28

10�27

10�26

10�25

10�24h

b

0

101

103

105

lnBG

RN

scalar-tensor injections

scalaramplitude

signal

noise

Crab H1L1V1 1yr advanced design

gr signal vs noise

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

17

10�28 10�27 10�26 10�25

hGR

10�28

10�27

10�26

10�25

10�24h

b

0

101

103

105

lnO

S N

scalar-tensor injections

scalaramplitude

Crab H1L1V1 1yr advanced design signal

noise

any signal vs noise

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

18

10�28 10�27 10�26 10�25

hGR

10�28

10�27

10�26

10�25

10�24h

b

0

102

104

lnO

nG

RG

R

scalar-tensor injections

scalaramplitude

not GR

GR

Crab H1L1V1 1yr advanced design

non-gr vs gr

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

19

102 103

fGW (Hz)

10�27

10�26

10�25

h95

%b

Results

ASD

102 103

10�24

10�23

pS

n(1

/pH

z)

scalar upper limits

sensitivity projections for

design aLIGO + Virgo

(each point represents one pulsar)

LIGO-G1701301Max Isi - Amaldi 2017

CW[arXiv:1703.07530]

20

vector upper limits

102 103

fGW (Hz)

10�27

10�26

10�25

h95

%v

Results

ASD

102 103 10�24

10�23

pS

n(1

/pH

z)

hv

⌘�h2

x

+ h2

y

�1/2

sensitivity projections for

design aLIGO + Virgo

(each point represents one pulsar)

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

21

stochastic backgroundincoherent superposition of myriad unresolvable sources

SNR (top) and 90%-confidence upper-limits (bottom) from radiometer stochastic background search

[Abbott et al., PRL 118, 121102 (2017)]

see Andrew Mata’s overview talk on Friday!

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

22

measure correlated strain power in two detectors

incoherent, broadband, all-sky

in a generic metric theory of gravity:

p 2 {+, ⇥, x, y, s}polarization amplitude

spectral index(“slope”)

stochastic background

with the canonical GW energy density usually parametrized by

⌦(f) = ⌦0 (f/f0)↵

overlap-reductionfunction

Dh̃⇤1(f)h̃

⇤2(f

0)E=

3H20

20⇡2�(f � f 0)|f |�3

X

p

⌦p0

✓f

f0

◆↵p

�p(f)

Dh̃⇤1(f)h̃

⇤2(f

0)E=

3H20

20⇡2�(f � f 0)|f |�3⌦(f)�(f)

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]stochastic background

0 50 100 150 200 250 300 350 400

f (Hz)

�1.0

�0.8

�0.6

�0.4

�0.2

0.0

0.2

0.4

0.6

�(f

)

Hanford-Livingston

Tensor

Vector

Scalar

0 50 100 150 200 250 300 350 400

f (Hz)

�0.25

�0.20

�0.15

�0.10

�0.05

0.00

0.05

0.10

0.15

0.20

�(f

)

Livingston-Virgo

Tensor

Vector

Scalar

overlap reduction functions encode effect of time-of-flight and differences between polarizations

23

�(f) =5

8⇡

X

p

Z

skydn̂ ei2⇡fn̂·�~x/cF p

1 (n̂)Fp

2 (n̂)

sky location

detector separation

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

10�10 10�9 10�8

Tensor ⌦0

0

20

40

60

80

100ln

Osi

gn

signal vs noisetensor injections

odds(detection statistic)

24

(spec. index 2/3)

H1L1 3yr advanced design

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

10�10 10�9 10�8

Vector ⌦0

0

20

40

60

80

100ln

Osi

gn

signal vs noisevector injections

odds(detection statistic)

25

(spec. index 2/3)

H1L1 3yr advanced design

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

10�10 10�9 10�8

Scalar ⌦0

0

20

40

60

80

100ln

Osi

gn

signal vs noisescalar injections

odds(detection statistic)

26

H1L1 3yr advanced design

(spec. index 2/3)

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

�10.5 �10.0 �9.5 �9.0 �8.5 �8.0

Tensor log ⌦T0

�10.5

�10.0

�9.5

�9.0

�8.5

�8.0

�7.5Sca

lar

log

⌦S 0

�3

0

3

10

30

507090

lnO

sig

n

scalar-tensor injections

scalaramplitude

signal

noise

H1L1V1 3yr advanced design

27

(spec. index 2/3)

non-gr vs gr

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

�10.5 �10.0 �9.5 �9.0 �8.5 �8.0

Tensor log ⌦T0

�10.5

�10.0

�9.5

�9.0

�8.5

�8.0

�7.5Sca

lar

log

⌦S 0

�3

0

3

10

30

507090

lnO

ngr

gr

scalaramplitude

not GR

GR

H1L1V1 3yr advanced design

28

(spec. index 2/3)

scalar-tensor injections

non-gr vs gr

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

29

3yr sensitivity projections for design aLIGO + Virgo

�13�12�11�10�9 �8 �7 �6

log ⌦T0

log ⌦T0 = �11.71+1.02

�0.83

�13�12�11�10�9 �8 �7 �6

log ⌦V0

log ⌦V0 = �11.63+1.11

�0.90

�13�12�11�10�9 �8 �7 �6

log ⌦S0

log ⌦S0 = �11.69+1.02

�0.84

�8�6�4�2 0 2 4 6 8↵T

↵T = �0.40+2.49�2.50

�8�6�4�2 0 2 4 6 8↵V

↵V = 0.17+2.38�2.69

�8�6�4�2 0 2 4 6 8↵S

↵S = �0.37+2.48�2.55

tensor vector scalar

amplitudes

tensor vector scalar

slopes

log⌦

S0 < �10.0log⌦

V0 < �9.9log⌦

T0 < �10.1

projected 95%-credible amplitude upper limits

gray histograms are LIGO-only results, dashed lines mark priors

parameter estimation

SB

LIGO-G1701301Max Isi - Amaldi 2017

[arXiv:1704.08373]

�13�12�11�10�9 �8 �7 �6

log ⌦T0

log ⌦T0 = �8.73+0.15

�0.22

�13�12�11�10�9 �8 �7 �6

log ⌦V0

log ⌦V0 = �11.22+1.46

�1.20

�13�12�11�10�9 �8 �7 �6

log ⌦S0

log ⌦S0 = �8.70+0.18

�0.33

�8�6�4�2 0 2 4 6 8↵T

↵T = 0.88+0.88�0.77

�8�6�4�2 0 2 4 6 8↵V

↵V = �0.26+2.03�2.53

�8�6�4�2 0 2 4 6 8↵S

↵S = 0.60+0.78�0.51

tensor vector scalar

amplitudes

tensor vector scalar

slopes

30

3yr scalar-tensor signal with design aLIGO + Virgo

gray histograms are LIGO-only results, dashed lines mark priors

Virgo does not increase sensitivity but helps

break degeneracy between scalar and vector

parameter estimation

LIGO-G1701301Max Isi - Amaldi 2017

we are now able to detect persistent signals of any

polarization content in a model-independent way

we can directly measure polarization content and

quantify agreement with GR

this will allow us to explore a new side of gravity!

conclusion

31

[arXiv:1703.07530] | [arXiv:1704.08373]

thank you!