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Register a new userGravitationally Lensed Gamma-Ray Bursts as Probes of Dark Compact Objects
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G.F. Marani
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If dark matter in the form of compact objects comprises a large fraction of the mass of the universe, then gravitational lensing effects on gamma-ray bursts are expected. We utilize BATSE and Ulysses data to search for lenses of different mass ranges, which cause lensing in the milli, pico, and femto regimes. Null results are used to set weak limits on the cosmological abundance of compact objects in mass ranges from 10$^{-16}$ to 10$^{-9}$ $M_{odot} $. A stronger limit is found for a much discussed $Omega = 0.15$ universe dominated by black holes of masses $sim 10^{6.5} M_{odot}$, which is ruled out at the $sim$ 90% confidence level.
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We review recent results on the high-redshift universe and the cosmic evolution obtained using Gamma Ray Bursts (GRBs) as tracers of high-redshift galaxies. Most of the results come from photometric and spectroscopic observations of GRB host galaxies once the afterglow has faded away but also from the analysis of the GRB afterglow line of sight as revealed by absorptions in their optical spectrum.
Since the launch of the highly successful and ongoing Swift mission, the field of gamma-ray bursts (GRBs) has undergone a revolution. The arcsecond GRB localizations available within just a few minutes of the GRB alert has signified the continual sampling of the GRB evolution through the prompt to afterglow phases revealing unexpected flaring and plateau phases, the first detection of a kilonova coincident with a short GRB, and the identification of samples of low-luminosity, ultra-long, and highly dust extinguished GRBs. The increased numbers of GRB afterglows, GRB-supernova detections, redshifts, and host galaxy associations has greatly improved our understanding of what produces and powers these immense, cosmological explosions. Nevertheless, more high quality data often also reveal greater complexity. In this review, I summarize some of the milestones made in GRB research during the Swift era, and how previous widely accepted theoretical models have had to adapt to accommodate the new wealth of observational data.
Compact dark matter has been efficiently constrained in the M <~ 10 M_sun mass range by null searches for microlensing of stars in nearby galaxies. Here we propose to probe the mass range M >~ 10 M_sun by seeking echoes in gamma-ray-burst light curves induced by strong lensing. We show that strong gravitational lensing of gamma ray bursts (GRBs) by massive compact halo objects (MACHOs) generates superimposed GRB images with a characteristic time delay of >~ 1 ms for M >~ 10 M_sun. Using dedicated simulations to capture the relevant phenomenology of the GRB prompt emission, we calculate the signal-to-noise ratio required to detect GRB lensing events as a function of the flux ratio and time delay between the lensed images. We then analyze existing data from the Fermi/GBM and Swift/BAT instruments to assess their constraining power on the compact dark matter fraction f_DM. We find that this data is noise limited, and therefore localization-based masking of background photons is a key ingredient. Future observatories with better sensitivity will be able to probe down to the f_ DM >~ 1% level across the 10 M_sun <~ M <~ 1000 M_sun mass range.
LambdaCDM, for the currently preferred cosmological density Omega_0 and cosmological constant Omega_Lambda, predicts that the Universe expansion decelerates from early times to redshift z~0.9 and accelerates at later times. On the contrary, the cosmological model based on conformal gravity predicts that the cosmic expansion has always been accelerating. To distinguish between these two very different cosmologies, we resort to gamma-ray bursts (GRBs), which have been suggested to probe the Universe expansion history at z>1, where identified type Ia supernovae (SNe) are rare. We use the full Bayesian approach to infer the cosmological parameters and the additional parameters required to describe the GRB data available in the literature. For the first time, we use GRBs as cosmological probes without any prior information from other data. In addition, when we combine the GRB samples with SNe, our approach neatly avoids all the inconsistencies of most numerous previous methods that are plagued by the so-called circularity problem. In fact, when analyzed properly, current data are consistent with distance moduli of GRBs and SNe that can respectively be, in a variant of conformal gravity, ~15 and ~3 magnitudes fainter than in LambdaCDM. Our results indicate that the currently available SN and GRB samples are accommodated equally well by both LambdaCDM and conformal gravity and do not exclude a continuous accelerated expansion. We conclude that GRBs are currently far from being effective cosmological probes, as they are unable to distinguish between these two very different expansion histories.
Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, Refsdal, and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of such objects can deliver measurements of the lensing time delays, which are the difference in arrival times for the separate images. These measurements provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Over the next decade, accurate time delay measurements will be needed for the tens to hundreds of lensed SNe to be found by wide-field time-domain surveys such as LSST and WFIRST. We have developed an open source software package for simulations and time delay measurements of multiply-imaged SNe, including an improved characterization of the uncertainty caused by microlensing. We describe simulations using the package that suggest a before-peak detection of the leading image enables a more accurate and precise time delay measurement (by ~1 and ~2 days, respectively), when compared to an after-peak detection. We also conclude that fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data, but that employing a Gaussian Process Regression (GPR) technique is sufficient for determining the uncertainty due to microlensing.
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