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Strongly lensed gravitational waves as the probes to test the cosmic distance duality relation

Hai-Nan Lin Department of Physics, Chongqing University, Chongqing 401331, China    Xin Li Department of Physics, Chongqing University, Chongqing 401331, China    Li Tang [email protected] Department of Math and Physics, Mianyang Normal University, Mianyang 621000, China Department of Physics, Chongqing University, Chongqing 401331, China
Abstract

The cosmic distance relation (DDR) associates the angular diameters distance (DAD_{A}) and luminosity distance (DLD_{L}) by a simple formula, i.e., DL=(1+z)2DAD_{L}=(1+z)^{2}D_{A}. The strongly lensed gravitational waves (GWs) provide a unique way to measure DAD_{A} and DLD_{L} simultaneously to the GW source, hence can be used as probes to test DDR. In this paper, we prospect the use of strongly lensed GW events from the future Einstein Telescope to test DDR. We write the possible deviation of DDR as (1+z)2DA/DL=η(z)(1+z)^{2}D_{A}/D_{L}=\eta(z), and consider two different parametrizations of η(z)\eta(z), namely, η1(z)=1+η0z\eta_{1}(z)=1+\eta_{0}z and η2(z)=1+η0z/(1+z)\eta_{2}(z)=1+\eta_{0}z/(1+z). Numerical simulations show that, with about 100 strongly lensed GW events observed by ET, the parameter η0\eta_{0} can be constrained at 1.3%1.3\% and 3%3\% levels for the first and second parametrizations, respectively.

gravitational waves – gravitational lensing – cosmology
preprint: AIP/123-QED

I Introduction

In astronomy and cosmology we often require to measure the distance to a celestial body in the sky far away from us. However, due to the accelerating expansion of the universe, there is no unique way to define distance. Among several definitions of distance, the luminosity distance (DLD_{L}) and angular diameter distance (DAD_{A}) are widely used. The definition of luminosity distance is based on the fact that the measured bolometric flux from a spherically symmetric radiating body is inversely proportional to the square of distance to the radiating source. The angular diameter distance, on the other hand, is defined as the ratio of transverse linear size to angular size of a celestial body. In the standard cosmology, the spacetime is governed by Einstein’s general relativity, and these two distances are correlated by Etherington’s distance duality relation (DDR), i.e., DL(z)=(1+z)2DA(z)D_{L}(z)=(1+z)^{2}D_{A}(z) Etherington:1933 ; Etherington:2007 . The validity of DDR requires that photons propagate along null geodesics and the number of photons is conserved Ellis:1971 ; Ellis:2007 . The violation of DDR may be caused by e.g. the extinction of photon by intergalactic dust Corasaniti:2016 , the coupling of photon with other particles Bassett:2003vu , the variation of fundamental constants Ellis:2013 , and so on. DDR is a fundamental relation in the standard cosmological model, hence testing its validity is of great importance.

Several methods have been proposed to test DDR, see e.g. Refs.Holanda:2010vb ; Piorkowska:2011nhd ; Li:2011mdk ; Yang:2013coa ; Liang:2013yst ; Costa:2015lja ; Holanda:2016msr ; Liao:2016uzb ; Ma:2016bjt ; Holanda:2016zpz ; Li:2018 ; Hu:2018yah ; Lin:2018mdj ; Liao:2019xug . In order to test DDR, one needs to independently measure both DLD_{L} and DAD_{A} at the same redshift zz. The measurement of luminosity distance is relatively easy. For example, as the standard candles, type-Ia supernovae (SNe Ia) provide an excellent tool to measure DLD_{L} up to redshift z2.3z\sim 2.3 Scolnic:2017caz . According to the luminosity-period relation of Cepheid variables, we can also measure DLD_{L}, but to a relatively lower redshift. Besides, the gravitational waves (GWs) can be used as the standard sirens to measure DLD_{L} Abbott:2016ajs ; Abbott:2017lpn . There are also several methods to measure the angular diameter distance. One of the most precise way to measure DAD_{A} is using the standard ruler baryonic acoustic oscillations (BAO), which can be measured up to redshift z2.34z\sim 2.34 Delubac:2015 , comparable to the furthest SNe Ia detected at present. We can also measure DAD_{A} from the Sunyaev-Zel’dovich effect of galaxy clusters Filippis:2005 ; Bonamente:2006ct and the angular size of ultra-compact radio sources Jackson:2006bg , but the uncertainty is much larger than BAO. In addition, strong gravitational lensing systems can provide information of angular diameter distance Liao:2016uzb ; Liao:2019xug . However, in the ordinary quasar lensing systems where only two images are seen, only the ratio of distances between lens to source and between observer to source can be obtained, unless the time delay between two images can be observed to break the degeneracy.

One shortcoming of the above methods is that DAD_{A} and DLD_{L} are measured from different sources at different redshifts, hence couldn’t be directly used to test DDR. To solve this problem, we can first apply some special techniques such as interpolations Liang:2013yst and Gaussian processes Lin:2018mdj to reconstruct the DLzD_{L}-z relation, then DLD_{L} can be calculated at any redshift we want. In addition, we can also use the nearest neighbourhood method Holanda:2010vb to pick up DLD_{L} and DAD_{A} that are measured at approximately equal redshifts. After these procedures, DLD_{L} and DAD_{A} can be compared at the same redshift. However, the above methods have not considered the fact that DLD_{L} and DAD_{A} are usually measured at different sky directions. If DDR really holds, this is not a problem. However, if there is any violation of DDR, e.g. caused by photo extinction by intergalactic dust, then the measured DLD_{L} may depend on the sky direction, since different line-of-sight directions may have different environments. Therefore, it is unreasonable to test DDR using DAD_{A} and DLD_{L} measured at different sky directions. The most ideal way to avoid this problem is to measure DAD_{A} and DLD_{L} from the same source. But this is not trivial, since it is difficult to find a source who can play the roles of standard candle and standard ruler simultaneously.

In a recent paper Lin:2020mdh , we proposed a new method to measure DLD_{L} and DAD_{A} simultaneously from the strongly lensed GW events. We have shown that, if the image positions of GW source and the relative time delay between different images can be observed simultaneously, and if the redshifts of lens and source can be measured independently, then we can extract DLD_{L} and DAD_{A} to the GW source. Therefore, the strongly lensed GWs provide a unique way to measure the luminosity distance and angular distance simultaneously to the same source, thus can be used to test DDR. A rough estimate shows that, with 100\sim 100 such events, DDR can be constrained at several percentage level. The third generation ground-based GW detectors such as the Einstein Telescope (ET) is expected to observe hundreds of strongly lensed GW events in the future Biesiada:2014kwa ; Ding:2015uha . Therefore, it is meaningful to prospect the accuracy of the future GW observations in constraining DDR. In this paper, based on the designed sensitivity of ET, we will use numerical simulation to investigate the ability of strongly lensed GW events in constraining DDR.

The rest of this paper is arranged as follows: In section II, we introduce the method of how to measure angular diameter distance and luminosity distance simultaneously from the strongly lensed GW events. In section III, based on the sensitivity of ET, we use Monte Carlo simulations to investigate the accuracy of using strongly lensed GW events to constrain DDR. Finally, discussion and conclusions are given in section IV.

II Methodology

II.1 Measure DAD_{A} from strong lensing

Suppose a GW burst is strongly lensed by a foreground galaxy. For simplicity we assumed that the lens galaxy is spherically symmetric. Specifically, we take the singular isothermal sphere (SIS) model as an example. With this configuration, we will see two images at opposite sides of the lens position. The Einstein radius θE=|θ1θ2|/2\theta_{E}=|\theta_{1}-\theta_{2}|/2 is given by Mollerach:2002

θE=4πσSIS2DA(zl,zs)c2DA(zs),\theta_{E}=\frac{4\pi\sigma_{\rm SIS}^{2}D_{A}(z_{l},z_{s})}{c^{2}D_{A}(z_{s})}, (1)

where σSIS\sigma_{\rm SIS} is the velocity dispersion of the lens galaxy, θ1\theta_{1} and θ2\theta_{2} are the image positions with respect to the lens galaxy, DA(zs)D_{A}(z_{s}) and DA(zl,zs)D_{A}(z_{l},z_{s}) are the angular diameter distances from the observer to source and from the lens to source, respectively. Inverting equation (1) we can obtain the distance ratio

RADA(zl,zs)DA(zs)=c2θE4πσSIS2.R_{A}\equiv\frac{D_{A}(z_{l},z_{s})}{D_{A}(z_{s})}=\frac{c^{2}\theta_{E}}{4\pi\sigma_{\rm SIS}^{2}}. (2)

If the angular resolution of the GW detector is high enough such that the angular positions of the two images (θ1\theta_{1} and θ2\theta_{2}) can be well localized, and if the velocity dispersion of the lens galaxy can be measured independently, then the distance ratio RAR_{A} can be calculated according to equation (2).

Different images propagate along different paths and feel different gravitational potentials, so have different time consumptions when arriving to the detector. The time delay between two images is given by Mollerach:2002

Δt=(1+zl)DΔtcΔϕ,\Delta t=(1+z_{l})\frac{D_{\Delta t}}{c}\Delta\phi, (3)

where

DΔtDA(zl)DA(zs)DA(zl,zs)=c1+zlΔtΔϕD_{\Delta t}\equiv\frac{D_{A}(z_{l})D_{A}(z_{s})}{D_{A}(z_{l},z_{s})}=\frac{c}{1+z_{l}}\frac{\Delta t}{\Delta\phi} (4)

is the time-delay distance, and

Δϕ=(θ1β)22Ψ(θ1)(θ2β)22+Ψ(θ2)\Delta\phi=\frac{(\theta_{1}-\beta)^{2}}{2}-\Psi(\theta_{1})-\frac{(\theta_{2}-\beta)^{2}}{2}+\Psi(\theta_{2}) (5)

is the Fermat potential difference between two paths, Ψ(θ)\Psi(\theta) is the rescaled projected gravitational potential of the lens galaxy. For the singular isothermal spherical lens, Ψ(θ)=θE|θ|\Psi(\theta)=\theta_{E}|\theta|. If the gravitational potential of the lens galaxy can be measured from photometric and spectroscopic observations, and if the time delay between two images can be recorded, then we can calculate the time-delay distance DΔtD_{\Delta t} according to equation (4), given that the spectroscopic redshift of the lens galaxy is precisely known.

In a spatially flat universe, the comoving distance is related to the angular diameter distance by r(zs)=(1+zs)DA(zs)r(z_{s})=(1+z_{s})D_{A}(z_{s}), r(zl)=(1+zl)DA(zl)r(z_{l})=(1+z_{l})D_{A}(z_{l}), r(zl,zs)=(1+zs)DA(zl,zs)r(z_{l},z_{s})=(1+z_{s})D_{A}(z_{l},z_{s}), where the comoving distance from lens to source is simply given by r(zl,zs)=r(zs)r(zl)r(z_{l},z_{s})=r(z_{s})-r(z_{l}). Therefore, the angular diameter distance from lens to source can be written as

DA(zl,zs)=DA(zs)1+zl1+zsDA(zl).D_{A}(z_{l},z_{s})=D_{A}(z_{s})-\frac{1+z_{l}}{1+z_{s}}D_{A}(z_{l}). (6)

From equations (2)(4)(6) we can uniquely solve for DA(zs)D_{A}(z_{s}), which reads

DA(zs)=1+zl1+zsRADΔt1RA,D_{A}(z_{s})=\frac{1+z_{l}}{1+z_{s}}\frac{R_{A}D_{\Delta t}}{1-R_{A}}, (7)

where RAR_{A} and DΔtD_{\Delta t} are given by equations (2) and (4), respectively. Assuming that RAR_{A} and DΔtD_{\Delta t} are uncorrelated, we can obtain the uncertainty on DA(zs)D_{A}(z_{s}) using the standard error propagating formulae,

δDA(zs)DA(zs)=(δRARA(1RA))2+(δDΔtDΔt)2,\frac{\delta D_{A}(z_{s})}{D_{A}(z_{s})}=\sqrt{\left(\frac{\delta R_{A}}{R_{A}(1-R_{A})}\right)^{2}+\left(\frac{\delta D_{\Delta t}}{D_{\Delta t}}\right)^{2}}, (8)

where the uncertainty on RAR_{A} propagates from the uncertainties on θE\theta_{E} and σSIS\sigma_{\rm SIS},

δRARA=(δθEθE)2+4(δσSISσSIS)2,\frac{\delta R_{A}}{R_{A}}=\sqrt{\left(\frac{\delta\theta_{E}}{\theta_{E}}\right)^{2}+4\left(\frac{\delta\sigma_{\rm SIS}}{\sigma_{\rm SIS}}\right)^{2}}, (9)

and the uncertainty on DΔtD_{\Delta t} propagates from the uncertainties on Δt\Delta t and Δϕ\Delta\phi,

δDΔtDΔt=(δΔtΔt)2+(δΔϕΔϕ)2.\frac{\delta D_{\Delta t}}{D_{\Delta t}}=\sqrt{\left(\frac{\delta\Delta t}{\Delta t}\right)^{2}+\left(\frac{\delta\Delta\phi}{\Delta\phi}\right)^{2}}. (10)

If the physical quantities (zlz_{l}, zsz_{s}, Δt\Delta t, Δϕ\Delta\phi, θE\theta_{E}, σSIS\sigma_{\rm SIS}) are measured, DA(zs)D_{A}(z_{s}) and its uncertainty can be obtained from equations (7)–(10).

II.2 Measure DLD_{L} from GW signals

As the standard sirens, GWs provide an excellent tool to measure the luminosity distance. The self-calibrating property of GWs makes the measurement of DLD_{L} being independent of any other cosmological probes, and also independent of cosmological model. According to general relativity, GW has two polarization states, which are written as h+(t)h_{+}(t) and h×(t)h_{\times}(t). GW detectors based on the interferometers such as ET measure the change of difference of two optical paths caused by the spacetime fluctuation when GW signals pass. The response of GW detectors on GW signals depends on the spacetime strain, which is the linear combination of two polarization states,

h(t)=F+(θ,φ,ψ)h+(t)+F×(θ,φ,ψ)h×(t),h(t)=F_{+}(\theta,\varphi,\psi)h_{+}(t)+F_{\times}(\theta,\varphi,\psi)h_{\times}(t), (11)

where the beam-pattern functions F+(θ,φ,ψ)F_{+}(\theta,\varphi,\psi) and F×(θ,φ,ψ)F_{\times}(\theta,\varphi,\psi) not only depend on the configuration of detector, but also depend on the position of GW source on the sky (θ,φ)(\theta,\varphi) and the polarization angle ψ\psi.

The Einstein Telescope (ET) ET is a third generation ground-based GW detector under designed. It consists of three interferometer arms of 10 kilometers length, arranged along three sides of an equilateral triangle, respectively. ET is sensitive in the frequency range 11041-10^{4} Hz, and it is expected to be able to detect GW signals produced by the coalescence of compact binary system up to redshift z5z\sim 5. The beam-pattern functions for ET are given as Zhao:2011

F+(1)(θ,φ,ψ)\displaystyle F_{+}^{(1)}(\theta,\varphi,\psi) =\displaystyle= 32[12(1+cos2θ)cos2φcos2ψ\displaystyle\frac{\sqrt{3}}{2}\Big{[}\frac{1}{2}(1+\cos^{2}\theta)\cos 2\varphi\cos 2\psi
cosθsin2φsin2ψ],\displaystyle-\cos\theta\sin 2\varphi\sin 2\psi\Big{]},
F×(1)(θ,φ,ψ)\displaystyle F_{\times}^{(1)}(\theta,\varphi,\psi) =\displaystyle= 32[12(1+cos2θ)cos2φsin2ψ\displaystyle\frac{\sqrt{3}}{2}\Big{[}\frac{1}{2}(1+\cos^{2}\theta)\cos 2\varphi\sin 2\psi
+cosθsin2φcos2ψ],\displaystyle+\cos\theta\sin 2\varphi\cos 2\psi\Big{]},
F+,×(2)(θ,φ,ψ)\displaystyle F_{+,\times}^{(2)}(\theta,\varphi,\psi) =\displaystyle= F+,×(1)(θ,φ+2π/3,ψ),\displaystyle F_{+,\times}^{(1)}(\theta,\varphi+2\pi/3,\psi),
F+,×(3)(θ,φ,ψ)\displaystyle F_{+,\times}^{(3)}(\theta,\varphi,\psi) =\displaystyle= F+,×(1)(θ,φ+4π/3,ψ).\displaystyle F_{+,\times}^{(1)}(\theta,\varphi+4\pi/3,\psi). (12)

In this paper, we only consider the GW signals produced by the coalescence of compact binary systems (e.g. NS-NS binary and NS-BH binary). In signal processing of GWs, it is convenient to work in the Fourier space. Using the post-Newtonian and stationary phase approximation, the spacetime strain h(t)h(t) can be written in the the Fourier space by Zhao:2011 ; Sathyaprakash:2009

(f)=𝒜f7/6exp[i(2πft0π/4+2ψ(f/2)φ(2,0))],\mathcal{H}(f)=\mathcal{A}f^{-7/6}\exp[i(2\pi ft_{0}-\pi/4+2\psi(f/2)-\varphi_{(2,0)})], (13)

where

𝒜\displaystyle\mathcal{A} =\displaystyle= 1DLF+2(1+cos2ι)2+4F×2cos2ι\displaystyle\frac{1}{D_{L}}\sqrt{F_{+}^{2}(1+\cos^{2}\iota)^{2}+4F_{\times}^{2}\cos^{2}\iota} (14)
×5π96π7/6c5/6,\displaystyle\times\sqrt{\frac{5\pi}{96}}\pi^{-7/6}\mathcal{M}_{c}^{5/6},

is the Fourier amplitude, ι\iota is the inclination of the binary’s orbital plane, DLD_{L} is the luminosity distance from the GW source to the detector, c=Mη3/5\mathcal{M}_{c}=M\eta^{3/5} is the chirp mass, M=m1+m2M=m_{1}+m_{2} is the total mass, η=m1m2/M2\eta=m_{1}m_{2}/M^{2} is the symmetric mass ratio, m1m_{1} and m2m_{2} are the component masses of the binary in comoving frame. For a GW source at redshift zz, c\mathcal{M}_{c} in equation (14) should be interpreted as the chirp mass in observer frame, which is related to the chirp mass in comoving frame by c,obs=(1+z)c,com\mathcal{M}_{c,{\rm obs}}=(1+z)\mathcal{M}_{c,{\rm com}} Krolak:1987 . The exponential term on the right-hand-side of equation (13) represents the phase of GW strain, whose explicit form can be found in Ref.Sathyaprakash:2009 , but it is unimportant in our study.

The signal-to-noise ratio (SNR) of a GW signal is given by the square root of the inner product of the spacetime strain in Fourier space, namely Sathyaprakash:2009

ρi=,,\rho_{i}=\sqrt{\langle\mathcal{H},\mathcal{H}\rangle}, (15)

where the inner product is defined as

a,b=4flowerfuppera~(f)b~(f)+a~(f)b~(f)2dfSh(f),\langle a,b\rangle=4\int_{f_{\rm lower}}^{f_{\rm upper}}\frac{\tilde{a}(f)\tilde{b}^{*}(f)+\tilde{a}^{*}(f)\tilde{b}(f)}{2}\frac{df}{S_{h}(f)}, (16)

where a~\tilde{a} and aa^{*} represent the Fourier transformation and complex conjugation of aa, respectively, Sh(f)S_{h}(f) is the one-side noise power spectral density (PSD) characterizing the sensitivity of the detector on spacetime strain, flowerf_{\rm lower} and fupperf_{\rm upper} are the lower and upper cutoffs of the frequency. The PSD for ET is given by Mishra:2010lfdk ; Cai:2017aea

Sh(f)\displaystyle S_{h}(f) =\displaystyle= 1050(2.39×1027x15.64+0.349x2.145\displaystyle 10^{-50}(2.39\times 10^{-27}x^{-15.64}+0.349x^{-2.145} (17)
+1.76x0.12+0.409x1.1)2Hz1.\displaystyle+1.76x^{-0.12}+0.409x^{1.1})^{2}~{}{\rm Hz}^{-1}.

Following Ref.Zhao:2011 , we assume flower=1f_{\rm lower}=1 Hz and fupper=2fLSOf_{\rm upper}=2f_{\rm LSO}, where fLSO=1/(63/22πMobs)f_{\rm LSO}=1/(6^{3/2}2\pi M_{\rm obs}) is the orbit frequency at the last stable orbit, Mobs=(1+z)(m1+m2)M_{\rm obs}=(1+z)(m_{1}+m_{2}) is the total mass in observer frame. If NN independent detectors form a network and detect the same GW source simultaneously, the combined SNR is given by

ρ=[i=1Nρi2]1/2.\rho=\left[\sum_{i=1}^{N}\rho_{i}^{2}\right]^{1/2}. (18)

For ET, three arms interfere with each other in pairs, which is equivalent to three independent detectors, thus N=3N=3. Generally, if ρ8\rho\geq 8 we can claim to detect a GW signal.

By matching the GW signals to GW templates we can obtain the luminosity distance to GW source, as well as other parameters. Due to the degeneracy between the luminosity distance DLD_{L} and inclination angle ι\iota, the uncertainty on DLD_{L} may be very large. However, if the GW event is accompanied by a short gamma-ray burst (GRB, which is expected in the coalescence of NS-NS binary and NS-BH binary), then due to the beaming of GRB outflow we can assume that the inclination angle is small, hence the degeneracy breaks. In this case the uncertainty on DLD_{L} can be estimated as Sathyaprakash:2009xt ; Cai:2017sby

δDLGW=2DLρ.\delta D_{L}^{\rm GW}=\frac{2D_{L}}{\rho}. (19)

For GW source at high redshift, there is an additional uncertainty arising from weak lensing effect caused by the intergalactic medium along the line-of-sight. This uncertainty is assume to be proportional to redshift, i.e. δDLlens/DL=0.05z\delta D_{L}^{\rm lens}/D_{L}=0.05z Zhao:2011 . Therefore, the total error on DLD_{L} is given by

δDL=(2DLρ)2+(0.05zDL)2.\delta D_{L}=\sqrt{\left(\frac{2D_{L}}{\rho}\right)^{2}+(0.05zD_{L})^{2}}\,. (20)

At low redshift (z1z\lesssim 1), the uncertainty caused by weak lensing is negligible. However, ET can detect GW signals at redshift z5z\gtrsim 5. At such high redshift, the uncertainty caused by weak lensing is comparable to the uncertainty caused by detector itself.

II.3 test the DDR

If a GW signal is strongly lensed by a foreground galaxy, we can simultaneously measure the angular diameter distance and luminosity distance to the GW source. The angular diameter distance can be measured from strongly lensing effect according to section II.1, and the luminosity distance can be measured from the GW signals according to section II.2.

One should pay specific attention that, due to the magnification effect of lensing, the luminosity distance measured from the strongly lensed GW signals is not the true distance. From equation (14) we know that the luminosity distance DLD_{L} is inversely proportional to the amplitude of GW signal, while the latter is magnified by the lensing effect by a factor of μ±\sqrt{\mu_{\pm}} Wang:1996 . For the singular isothermal spherical lens, the magnification factor can be calculated as μ±=1±θE/β\mu_{\pm}=1\pm\theta_{E}/\beta, where β\beta is the actual position of the source, and “±\pm” represent the first and second images, respectively. The actual position of the source β\beta can be determined through deep photometric imaging, β/θE=(F+F)/(F++F)\beta/\theta_{E}=(F_{+}-F_{-})/(F_{+}+F_{-}), where F±F_{\pm} are the photometric flux of two images. If the magnification factor is measured from photometric observations, we can obtain the true distance DLtrue=μ±DLobsD_{L}^{\rm true}=\sqrt{\mu_{\pm}}D_{L}^{\rm obs}. The uncertainty of μ±\mu_{\pm} will propagate to DLD_{L}. Therefore, the total uncertainty on DL(zs)D_{L}(z_{s}) is given by Lin:2020mdh

δDLtotalDL=(2ρ)2+(0.05zs)2+14(δμ±μ±)2.\frac{\delta D_{L}^{\rm total}}{D_{L}}=\sqrt{\left(\frac{2}{\rho}\right)^{2}+(0.05z_{s})^{2}+\frac{1}{4}\left(\frac{\delta\mu_{\pm}}{\mu_{\pm}}\right)^{2}}. (21)

Having DAD_{A} and DLD_{L} measured, we can use them to test DDR. We write the possible deviation of DDR as

(1+z)2DADL=η(z).\frac{(1+z)^{2}D_{A}}{D_{L}}=\eta(z). (22)

Specifically, we consider two different parametrizations of η(z)\eta(z), namely, η1(z)=1+η0z\eta_{1}(z)=1+\eta_{0}z and η2(z)=1+η0z/(1+z)\eta_{2}(z)=1+\eta_{0}z/(1+z). The parameter η0\eta_{0} represents the amplitude of deviation from the standard DDR. If η0=0\eta_{0}=0, the standard DDR holds. By fitting the measured DAD_{A} and DLD_{L} to equation (22), η0\eta_{0} can be constrained. The best-fitting η0\eta_{0} can be obtained by maximizing the following likelihood,

i=1N12πσtotalexp[((1+z)2DAη(z)DLσtotal)2],\mathcal{L}\propto\prod_{i=1}^{N}\frac{1}{\sqrt{2\pi}\sigma_{\rm total}}\exp\left[-\left(\frac{(1+z)^{2}D_{A}-\eta(z)D_{L}}{\sigma_{\rm total}}\right)^{2}\right], (23)

where

σtotal=(1+z)4(δDA)2+η2(z)(δDL)2,\sigma_{\rm total}=\sqrt{(1+z)^{4}(\delta D_{A})^{2}+\eta^{2}(z)(\delta D_{L})^{2}}, (24)

and the product runs over all the data points.

III Monte Carlo simulations

In this section, based on the designed sensitivity of ET, we will use Monte Carlo simulations to investigate the precision of strongly lensed GWs in constraining DDR. The fiducial cosmological model is chosen to be the flat Λ\LambdaCDM model, with parameters Ωm=0.3\Omega_{m}=0.3 and H0=70kms1Mpc1H_{0}=70~{}{\rm km~{}s}^{-1}~{}{\rm Mpc}^{-1}. The luminosity distance in the fiducial cosmological model is given by

D¯L=(1+z)cH00zdzΩm(1+z)3+1Ωm.\bar{D}_{L}=(1+z)\frac{c}{H_{0}}\int_{0}^{z}\frac{dz}{\sqrt{\Omega_{m}(1+z)^{3}+1-\Omega_{m}}}. (25)

We only consider the GWs produced by the coalescence of NS-NS and NS-BH binaries. BH-BH binaries are not considered, because according to most theoretical models the coalescence of BH-BH binary has no electromagnetic counterparts, although some exotic models predict that it may also be accompanied by electromagnetic counterparts Zhang:2016rli ; Fraschetti:2016bpm ; Perna:2016jqh . The redshift distribution and event rate of GWs depend on the stellar evolution model. Ref.Biesiada:2014kwa has calculated in detail the redshift distribution and event rate of the strongly lensed inspiral double compact objects (including NS-NS, NS-BH and BH-BH binaries) in different scenarios. Based on the initial configuration of ET, the excepted redshift distribution of the strongly lensed NS-NS and NS-BH events in the standard evolution scenario is plotted in Figure 1.

Refer to caption
Figure 1: The redshift distribution of strongly lensed GW sources. The lines are reproduced from Ref.Biesiada:2014kwa , but are renormalized such that the area under each line is unity.

The probability density function (pdf) of a GW event at redshift zsz_{s} being lensed by a foreground galaxy at redshift zlz_{l} (zl<zs)(z_{l}<z_{s}) is given by Biesiada:2014kwa

P(zl|zs)=Cr~2(zl,zs)r~2(0,zl)r~2(0,zs)E(zl),P(z_{l}|z_{s})=C\frac{\tilde{r}^{2}(z_{l},z_{s})\tilde{r}^{2}(0,z_{l})}{\tilde{r}^{2}(0,z_{s})E(z_{l})}, (26)

where E(z)=Ωm(1+z)3+1ΩmE(z)=\sqrt{\Omega_{m}(1+z)^{3}+1-\Omega_{m}} is the dimensionless Hubble parameter, CC is a normalization constant, and

r~(z1,z2)=z1z21E(z)𝑑z\tilde{r}(z_{1},z_{2})=\int_{z_{1}}^{z_{2}}\frac{1}{E(z)}dz (27)

is the dimensionless comoving distance from z1z_{1} to z2z_{2}. For a given GW source at redshift zsz_{s}, the redshift of the lens galaxy zlz_{l} is randomly sampled according to the pdf given in equation (26). We assume that zsz_{s} and zlz_{l} can be measured spectroscopically, so the uncertainty is negligible.

The velocity dispersion of the lens galaxy is assumed to follow the modified Schechter function Choi:2007

n(σ)dσ=n0(σσ)αexp[(σσ)β]dσσ,n(\sigma)d\sigma=n_{0}\left(\frac{\sigma}{\sigma_{*}}\right)^{\alpha}\exp\left[-\left(\frac{\sigma}{\sigma_{*}}\right)^{\beta}\right]\frac{d\sigma}{\sigma}, (28)

where n0n_{0} is a normalization constant, σ=161kms1\sigma_{*}=161~{}{\rm km~{}s}^{-1}, α=2.32\alpha=2.32 and β=2.67\beta=2.67. We set a lower limit on the velocity dispersion, i.e., σlower=70kms1\sigma_{\rm lower}=70~{}{\rm km~{}s}^{-1}. The observational accuracy of velocity dispersion may strongly affect the accuracy of DAD_{A}. According to the presently available quasar lensing systems compiled in Ref.Cao:2015qja , the measured uncertainty of velocity dispersion is about 10%10\%. With the progress of observational technique, it is not impossible to reduce the uncertainty to less than 5%5\% in the near future Cao:2019kgn .

To determine DAD_{A}, it is necessary to precisely measure the Fermat potential difference Δϕ\Delta\phi, the Einstein angle θE\theta_{E}, and the time delay between two images Δt\Delta t. Benefitting from the fact that GW signals do not suffer from the bright AGN contamination from the lens galaxy, the measured accuracy of Δϕ\Delta\phi can be improved to 0.6%\sim 0.6\% in the lensed GW system, while the uncertainty in the lensed quasar systems is approximately larger by a factor of five Liao:2017ioi . The accuracy of θE\theta_{E} is expected to be at 1%\sim 1\% level in the future LSST survey Cao:2019kgn . Thanks to the transient property of GW events, the arrival time of GW signals can be accurately recorded, so the uncertainty on time delay is negligible.

To correctly determine DLD_{L}, we should precisely measure the magnification factor μ±\mu_{\pm} from photometric observations. In general, μ±\mu_{\pm} can be determined by measuring the photo flux of two images as described in section II.3. The measurement of image flux, however, may be highly uncertain due to the photometric contamination from the foreground lensing galaxy. Here we follow Ref.Cao:2019kgn and assume a 20%\sim 20\% uncertainty on μ±\mu_{\pm}.

The masses of the neutron star and of the black hole are assumed to be uniformly distributed in the range mNSU(1,2)Mm_{NS}\in U(1,2)M_{\odot} and mBHU(3,10)Mm_{BH}\in U(3,10)M_{\odot}, respectively Cao:2019kgn . In addition, we assume that the GW sources are uniformly distributed in the sky, i.e., θU(0,π)\theta\in U(0,\pi), φU(0,2π)\varphi\in U(0,2\pi). The occurrence rate of lensed NS-NS and NS-BH events depends on the stellar evolution scenarios. Numerical simulations show that the NS-BH event rate is in general larger than the NS-NS event rate Biesiada:2014kwa . In our simulations, we assume that the ratio of NS-NS event rate and NS-BH event rate is 1:51:5.

Based on the discussions above, we assume that the measured accuracy for parameters (σ,θE,Δϕ,μ±\sigma,\theta_{E},\Delta\phi,\mu_{\pm}) is (5%,1%,0.6%,20%5\%,1\%,0.6\%,20\%), respectively. With this setup, we can now simulate the strongly lensed GW events following the steps bellow:

  1. 1.

    Randomly sample parameters (zs,zl,σ,m1,m2,θ,φ)(z_{s},z_{l},\sigma,m_{1},m_{2},\theta,\varphi) according to the pdf of each parameter described above.

  2. 2.

    Calculate the SNR of GW signal based on the simulated parameters according to section II.2. If SNR>16{\rm SNR}>16, continue; else go back to step 1.

  3. 3.

    Calculate DAD_{A} and δDA\delta D_{A} at redshift zsz_{s} according to section II.1. If δDA/DA<30%\delta D_{A}/D_{A}<30\%, continue; else go back to step 1.

  4. 4.

    Calculate the fiducial luminosity distance D¯L\bar{D}_{L} at redshift zsz_{s} according to equation (25), and the uncertainty δDL\delta D_{L} according to equation (21).

  5. 5.

    Sample DLD_{L} from the Gaussian distribution DLG(D¯L,δDL)D_{L}\sim G(\bar{D}_{L},\delta D_{L}).

  6. 6.

    Save the parameter set (zs,DA,δDA,DL,δDL)(z_{s},D_{A},\delta D_{A},D_{L},\delta D_{L}) as an effective GW event; go back to step 1 until we obtain NN events.

Some notes on the simulation procedures. In step 2, we require that the SNR of GW signal is at least SNR16{\rm SNR}\gtrsim 16, compared to the usual criterion SNR8{\rm SNR}\gtrsim 8. For a GW events with SNR8{\rm SNR}\approx 8, the uncertainty on DLD_{L} from GW signal itself is about 25%. If the errors from weak lensing and magnification factor are included, the total uncertainty on DLD_{L} is 30%\sim 30\% for an event at zs=2z_{s}=2, which is unacceptably large. If we require SNR>16{\rm SNR}>16, the uncertainty can be reduced down to 20%20\%. In step 3, we only retain the GW events whose accuracy on DAD_{A} are better than 30%30\%. From equation (8) we can see that the error on DAD_{A} mainly comes from the error on RAR_{A}, while the latter is at the order of 10%10\%. The error on DAD_{A} is larger than the error on RAR_{A} by a factor of 1/(1RA)1/(1-R_{A}). If RAR_{A} is close to unity (this happens when zlzsz_{l}\ll z_{s}), the error on DAD_{A} may be very large.

A representative simulating result of 100 strongly lensed events is plotted in Figure 2. Panel (a) and panel (b) show the histogram of zsz_{s} and zlz_{l}, respectively. Panel (c) and panel (d) show the angular diameter distance and luminosity distance versus redshift zsz_{s}, respectively. The red lines are the theoretical curves of the fiducial Λ\LambdaCDM model. The redshift distributions of GW source and lens galaxy peak at about 1.6 and 0.6, respectively. The uncertainty on DLD_{L} increases with redshift because of the increasing error caused by the weak lensing effect at high redshift.

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Refer to caption
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Figure 2: A representative simulating result of 100 strongly lensed events. (a) The redshift distribution of zsz_{s}. (b) The redshift distribution of zlz_{l}. (c) The angular diameter distance. (d) The luminosity distance. The red lines are the theoretical curves of the fiducial Λ\LambdaCDM model.

Using the simulated GW events, DDR can be strictly constrained. The posterior pdf of η0\eta_{0} constrained from 100 simulated GW events is plotted in Figure 3. With 100 strongly lensed GW events, the parameter η0\eta_{0} can be constrained at 1.3%\sim 1.3\% and 3%\sim 3\% levels for the first and second parametrizations, respectively. The simulating results imply that strongly lensed GW events are very promising in constraining DDR as the construction of ET in the future.

Refer to caption
Figure 3: The posterior pdf of η0\eta_{0} constrained by 100 strongly lensed GW events.

IV Discussion and conclusions

In this paper, we have investigate the possibility of using strongly lensed GW event to constrain DDR. The strongly lensed GW events provide a unique way to measure angular diameter distance and luminosity distance to the GW source simultaneously, thus can be directly used to test DDR. This method is independent of cosmological model, except the assumption that the universe is spatially flat. Monte Carlo simulations shows that with about 100 such events, DDR can be constrained at 1.3%\sim 1.3\% and 3%\sim 3\% level for the first and second parametrizations, respectively. In comparison, using the combination of SNe, galaxy clusters and BAO data, DDR is constrained at 12%\sim 12\% and 22%\sim 22\% level for the first and second parametrizations, respectively Lin:2018mdj . Using the combination of SNe and ultra-compact radio sources, DDR is constrained at 5%\sim 5\% and 16%\sim 16\% level for the first and second parametrizations, respectively Li:2018 . Ref.Liao:2019xug have used the combined data of GWs and strongly lensed quasar systems to constrain DDR, and the constraining accuracy is comparable to our results. Note that the method we proposed here is completely different from that in Ref.Liao:2019xug . In Ref.Liao:2019xug , the strongly lensed quasars provide DAD_{A}, and GW events provide DLD_{L}. So DAD_{A} and DLD_{L} are still measured from different source at different redshift. While the method we proposed here measures DAD_{A} and DLD_{L} from the same GW source.

The biggest challenge to put the method into practise is how to identify the strongly lensed GW events. The angular separation between two images of a typical strong lensing system is of the order of arc seconds. It seems extremely difficult to reach such high angular resolution in the near future. Zhao & Wen Zhao:2018cbb found that even for a network of three or four third generation GW detectors, the localization accuracy is about several arc degrees. This accuracy is far from enough to separate the images, but it is enough to identify the host galaxy. If two GW signals with the same observed strains (up to a normalization constant) come from the same host galaxy, and if the relative time delay is consistent with theoretical prediction, then these two signals can be treated as two images of a strongly lensed GW event. If we further assume that GW and electromagnetic wave travel along the same null-geodesic, the image separation between two GW signals can be obtained through photometric observations, which can be easily realized with the present technique.

The method proposed here needs independent measurement of redshift of source and lens. The third general GW detector ET is expected to be able to record several hundreds strongly lensed GW events during its lifetime Biesiada:2014kwa . Unfortunately, most of the events are produced by the coalescence of BH-BH binaries, which is in general has no electromagnetic counterparts. Without electromagnetic counterparts, it is difficult to identify the host galaxy of GW sources, hence it is impossible to measure the spectroscopic redshift. This prevents the direct use of these events to test DDR. However, if the GW event can be precisely localized, it is possible to infer the redshift of GW source statistically Chen:2017rfc ; Mukherjee:2020hyn . Of course, this will introduce additional uncertainty.

Acknowledgements.
This work has been supported by the National Natural Science Fund of China under grant Nos. 11603005, 11775038 and 11947406.

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