arXiv subjects

U. Sawangwit

Publications and source records attributed to U. Sawangwit.

At least 19 recordsLinked to original sources

arXiv2026

GOTO identification and broadband modelling of the counterpart to the SVOM GRB 250818B

Rapid localisation and follow-up of gamma-ray bursts (GRBs) increasingly rely on low-latency triggers from new missions coupled to wide-field robotic optical facilities. We present the discovery and multi-wavelength follow-up of GRB 250818B, detected by the Space Variable Objects Monitor (SVOM) and localised optically by the Gravitational-wave Optical Transient Observer (GOTO). We compile and homogenise X-ray, optical/NIR, and radio data to build broadband light curves and spectral energy distributions. The afterglow is unusually luminous for a nominal short GRB, lying on the bright end of the short-GRB population in X-rays and optical and among the most luminous high-redshift short-GRB afterglows in the radio. MeerKAT detects the source at 3.1 GHz, while ALMA provides deep higher-frequency limits. Keck/LRIS spectroscopy shows continuum and metal absorption (Fe II, Mg II, Mg I), giving $z=1.216$. Synchrotron forward-shock modelling favours a constant-density medium and strongly prefers refreshed (energy-injection) emission, well described by a two-component jet with $E_{K,iso} \sim 4\times10^{52}$ erg, $n_0 \sim 3.6$ cm$^{-3}$, $\theta_j \simeq 0.10$ rad ($\sim 5.7$ deg), and $p \simeq 1.64$. The host association is ambiguous: the nearest LS DR10 galaxy candidate ($r_{AB} \sim 24.7$) is offset by $\sim 4$ arcsec ($\sim 34$ kpc) with chance-alignment probability $P_{cc} \sim 0.2$, and current imaging does not exclude a fainter, near-coincident host. SED fitting of the candidate host suggests a low-mass galaxy. GRB 250818B highlights the power of rapid wide-field counterpart identification in the SVOM era, while host-association uncertainty can still limit offset-based interpretation.

astro-ph.HE↗

arXiv2024

$\textit{Kilonova Seekers}$: the GOTO project for real-time citizen science in time-domain astrophysics

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for machine learning classifiers are crucial to make the most of this torrent of discovery -- with citizen science approaches proving effective at meeting these requirements. In this paper, we describe the creation of and the initial results from the $\textit{Kilonova Seekers}$ citizen science project, built to find transient phenomena from the GOTO telescopes in near real-time. $\textit{Kilonova Seekers}$ launched in July 2023 and received over 600,000 classifications from approximately 2,000 volunteers over the course of the LIGO-Virgo-KAGRA O4a observing run. During this time, the project has yielded 20 discoveries, generated a `gold-standard' training set of 17,682 detections for augmenting deep-learned classifiers, and measured the performance and biases of Zooniverse volunteers on real-bogus classification. This project will continue throughout the lifetime of GOTO, pushing candidates at ever-greater cadence, and directly facilitate the next-generation classification algorithms currently in development.

astro-ph.IM↗

arXiv2023

Eclipse timing variations in the WD+dM eclipsing binary RR Cae

We present the binary model and the eclipse timing variations of the eclipsing binary RR Cae, which consists of a white dwarf eclipsed by an M-type dwarf companion. The multi-wavelength optical photometry from the Transiting Exoplanet Survey Satellite (TESS), the 0.6-m PROMPT-8 telescope, and the 0.7-m Thai Robotic Telescope at Spring Brook Observatory, combined with archive H-alpha radial velocities from the Very Large Telescope (VLT) are analysed. From the data, the physical parameters of the system are obtained along with 430 new times of minima. The TESS light curves in 2018 and 2020 show out-of-eclipse variations, which might be caused by a large spot on the secondary component. The light travel time effect models due to the gravitational interaction of one or two circumbinary objects are adopted to fit the cyclic variations in the RR Cae's O-C curve. The fitting solution of the O-C curve with one circumbinary object model shows a periodic variation with a period of $16.6\pm0.2$ yr and an amplitude of $14\pm1$ s, which can be caused by a planet with a minimum mass of $3.4\pm0.2$ M$_{Jup}$. When we consider the model with two circumbinary objects, the O-C curve shows cyclic variations with periods of $15.0\pm0.5$ yr and $39\pm5$ yr and amplitudes of $12\pm1$ s and $20\pm5$ s, respectively, corresponding to minimum masses of $3.0\pm0.3$ M$_{Jup}$ and $2.7\pm0.7$ M$_{Jup}$.

astro-ph.EP↗

arXiv2022

Self-Supervised Clustering on Image-Subtracted Data with Deep-Embedded Self-Organizing Map

Developing an effective automatic classifier to separate genuine sources from artifacts is essential for transient follow-ups in wide-field optical surveys. The identification of transient detections from the subtraction artifacts after the image differencing process is a key step in such classifiers, known as real-bogus classification problem. We apply a self-supervised machine learning model, the deep-embedded self-organizing map (DESOM) to this "real-bogus" classification problem. DESOM combines an autoencoder and a self-organizing map to perform clustering in order to distinguish between real and bogus detections, based on their dimensionality-reduced representations. We use 32x32 normalized detection thumbnails as the input of DESOM. We demonstrate different model training approaches, and find that our best DESOM classifier shows a missed detection rate of 6.6% with a false positive rate of 1.5%. DESOM offers a more nuanced way to fine-tune the decision boundary identifying likely real detections when used in combination with other types of classifiers, for example built on neural networks or decision trees. We also discuss other potential usages of DESOM and its limitations.

cs.CV↗

arXiv2022

CTA Sensitivity on TeV scale Dark Matter Models with Complementary Limits from Direct Detection

With ever increasing pressure from collider physics and direct detection experiments, particle physics models of TeV scale dark matter are gaining more attention. In this work, we consider two realizations of the class of scalar portal dark matter scenarios -- the inverse seesaw model and the inert doublet model. Observations by the Cherenkov Telescope Array (CTA) of very-high-energy $γ$ rays from dark matter annihilation in the context of these models are simulated for the Draco and Sculptor dwarf spheroidal galaxies, and later analyzed using ctools. We study the potential of CTA for the 5$σ$ detection of a dark matter annihilation signal. In the absence of a signal, we also derive the 2$σ$ upper limits on the annihilation cross-section. We compare our projected CTA sensitivity against the projected sensitivity of the next generation of direct detection experiment, i.e. XENONnT. Although the limits from CTA are significantly improved compared with the previous generations of $γ$-ray experiments, they are still $\sim2$ orders of magnitude above the thermal relic cross-section for the considered targets. In the case of the inverse seesaw model, the constraint from the future direct detection experiment XENONnT is much weaker than the CTA sensitivity, whereas for the inert doublet model, XENONnT gives a bound an order of magnitude stronger compared to the CTA limits.

astro-ph.HE↗

arXiv2021

The study of active geomagnetic shielding coils system for JUNO

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator (LS) detector for neutrino mass ordering and other neutrino physics research. The detector uses large-size $20$ inches photomultiplier tubes to detect photons from a liquid scintillator. The large PMTs are sensitive and easily affected such that the detection efficiency loses about 60$\%$ under the geomagnetic field intensity ($\sim$500 mG). It has a significantly negative effect on the detector performance, and a compensation system is necessary for geomagnetic field shielding. As permalloys are easily rusted in water, a better way for the geomagnetic shielding is to apply an active compensation coils system. The simulations show that a set of 32 circular coils can meet the experiment requirement. The residual magnetic field is less than 0.05 G in the Central Detector Photomultiplier Tube (CD-PMT) region (38.5-39.5 m in diameter). A prototype coil system with a 1.2 m was built to validate the simulation and the design. The measured data of prototype and simulation results are consistent with each other, and geomagnetic field intensity is effectively reduced by coils, verifying the shielding coils system design for JUNO. This study is expected to provide practical guidance for the PMT magnetic field shielding for future large-scale detector designs.

physics.ins-det↗

arXiv2021

The Gravitational-wave Optical Transient Observer (GOTO): prototype performance and prospects for transient science

The Gravitational-wave Optical Transient Observer (GOTO) is an array of wide-field optical telescopes, designed to exploit new discoveries from the next generation of gravitational wave detectors (LIGO, Virgo, KAGRA), study rapidly evolving transients, and exploit multi-messenger opportunities arising from neutrino and very high energy gamma-ray triggers. In addition to a rapid response mode, the array will also perform a sensitive, all-sky transient survey with few day cadence. The facility features a novel, modular design with multiple 40-cm wide-field reflectors on a single mount. In June 2017 the GOTO collaboration deployed the initial project prototype, with 4 telescope units, at the Roque de los Muchachos Observatory (ORM), La Palma, Canary Islands. Here we describe the deployment, commissioning, and performance of the prototype hardware, and discuss the impact of these findings on the final GOTO design. We also offer an initial assessment of the science prospects for the full GOTO facility that employs 32 telescope units across two sites.

astro-ph.IM↗

arXiv2021

Searching For Fermi GRB Optical Counterparts With The Prototype Gravitational-Wave Optical Transient Observer (GOTO)

The typical detection rate of $\sim1$ gamma-ray burst (GRB) per day by the \emph{Fermi} Gamma-ray Burst Monitor (GBM) provides a valuable opportunity to further our understanding of GRB physics. However, the large uncertainty of the \emph{Fermi} localization typically prevents rapid identification of multi-wavelength counterparts. We report the follow-up of 93 \emph{Fermi} GRBs with the Gravitational-wave Optical Transient Observer (GOTO) prototype on La Palma. We selected 53 events (based on favourable observing conditions) for detailed analysis, and to demonstrate our strategy of searching for optical counterparts. We apply a filtering process consisting of both automated and manual steps to 60\,085 candidates initially, rejecting all but 29, arising from 15 events. With $\approx3$ GRB afterglows expected to be detectable with GOTO from our sample, most of the candidates are unlikely to be related to the GRBs. Since we did not have multiple observations for those candidates, we cannot confidently confirm the association between the transients and the GRBs. Our results show that GOTO can effectively search for GRB optical counterparts thanks to its large field of view of $\approx40$ square degrees and its depth of $\approx20$ mag. We also detail several methods to improve our overall performance for future follow-up programs of \emph{Fermi} GRBs.

astro-ph.HE↗

arXiv2021

Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream. A problem that arises in real-world applications of learning algorithms for classification is imbalanced data, where a class of objects within the data is underrepresented, leading to a bias for over-represented classes in the ML and DL classifiers. We present a recurrent neural network (RNN) classifier that takes in photometric time-series data and additional contextual information (such as distance to nearby galaxies and on-sky position) to produce real-time classification of objects observed by the Gravitational-wave Optical Transient Observer (GOTO), and use an algorithm-level approach for handling imbalance with a focal loss function. The classifier is able to achieve an Area Under the Curve (AUC) score of 0.972 when using all available photometric observations to classify variable stars, supernovae, and active galactic nuclei. The RNN architecture allows us to classify incomplete light curves, and measure how performance improves as more observations are included. We also investigate the role that contextual information plays in producing reliable object classification.

astro-ph.IM↗

arXiv2021

Processing GOTO data with the Rubin Observatory LSST Science Pipelines II: Forced Photometry and light curves

We have adapted the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Science Pipelines to process data from the Gravitational-Wave Optical Transient Observer (GOTO) prototype. In this paper, we describe how we used the Rubin Observatory LSST Science Pipelines to conduct forced photometry measurements on nightly GOTO data. By comparing the photometry measurements of sources taken on multiple nights, we find that the precision of our photometry is typically better than 20~mmag for sources brighter than 16 mag. We also compare our photometry measurements against colour-corrected PanSTARRS photometry, and find that the two agree to within 10~mmag (1$σ$) for bright (i.e., $\sim14^{\rm th}$~mag) sources to 200~mmag for faint (i.e., $\sim18^{\rm th}$~mag) sources. Additionally, we compare our results to those obtained by GOTO's own in-house pipeline, {\sc gotophoto}, and obtain similar results. Based on repeatability measurements, we measure a $5σ$ L-band survey depth of between 19 and 20 magnitudes, depending on observing conditions. We assess, using repeated observations of non-varying standard SDSS stars, the accuracy of our uncertainties, which we find are typically overestimated by roughly a factor of two for bright sources (i.e., $<15^{\rm th}$~mag), but slightly underestimated (by roughly a factor of 1.25) for fainter sources ($>17^{\rm th}$~mag). Finally, we present lightcurves for a selection of variable sources, and compare them to those obtained with the Zwicky Transient Factory and GAIA. Despite the Rubin Observatory LSST Science Pipelines still undergoing active development, our results show that they are already delivering robust forced photometry measurements from GOTO data.

astro-ph.IM↗

arXiv2021

Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream

Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional neural network that provides nuanced, uncertainty-aware classification of transient candidates in difference imaging, and demonstrate its application to the datastream from the GOTO wide-field optical survey. Not only are candidates assigned a well-calibrated probability of being real, but also an associated confidence that can be used to prioritise human vetting efforts and inform future model optimisation via active learning. To fully realise the potential of this architecture, we present a fully-automated training set generation method which requires no human labelling, incorporating a novel data-driven augmentation method to significantly improve the recovery of faint and nuclear transient sources. We achieve competitive classification accuracy (FPR and FNR both below 1%) compared against classifiers trained with fully human-labelled datasets, whilst being significantly quicker and less labour-intensive to build. This data-driven approach is uniquely scalable to the upcoming challenges and data needs of next-generation transient surveys. We make our data generation and model training codes available to the community.

astro-ph.IM↗

arXiv2020

Processing GOTO data with the Rubin Observatory LSST Science Pipelines I : Production of coadded frames

The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy, however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO), whose primary science objective is the optical follow-up of Gravitational Wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near real-time to fully exploit the time-domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this "off-the-shelf" pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to sub-pixel levels, and that measured L-band photometries are accurate to $\sim50$ mmag at $m_L\sim16$ and $\sim200$ mmag at $m_L\sim18$. These values compare favourably to those obtained using GOTO's primary, in-house pipeline, GOTOPHOTO, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic "obs package" that others can build-upon should they wish to use the LSST Science Pipelines to process data from other facilities.

astro-ph.IM↗

arXiv2020

Searching for Electromagnetic Counterparts to Gravitational-wave Merger Events with the Prototype Gravitational-wave Optical Transient Observer (GOTO-4)

We report the results of optical follow-up observations of 29 gravitational-wave triggers during the first half of the LIGO-Virgo Collaboration (LVC) O3 run with the Gravitational-wave Optical Transient Observer (GOTO) in its prototype 4-telescope configuration (GOTO-4). While no viable electromagnetic counterpart candidate was identified, we estimate our 3D (volumetric) coverage using test light curves of on- and off-axis gamma-ray bursts and kilonovae. In cases where the source region was observable immediately, GOTO-4 was able to respond to a GW alert in less than a minute. The average time of first observation was $8.79$ hours after receiving an alert ($9.90$ hours after trigger). A mean of $732.3$ square degrees were tiled per event, representing on average $45.3$ per cent of the LVC probability map, or $70.3$ per cent of the observable probability. This coverage will further improve as the facility scales up alongside the localisation performance of the evolving gravitational-wave detector network. Even in its 4-telescope prototype configuration, GOTO is capable of detecting AT2017gfo-like kilonovae beyond 200~Mpc in favourable observing conditions. We cannot currently place meaningful electromagnetic limits on the population of distant ($\hat{D}_L = 1.3$~Gpc) binary black hole mergers because our test models are too faint to recover at this distance. However, as GOTO is upgraded towards its full 32-telescope, 2 node (La Palma \& Australia) configuration, it is expected to be sufficiently sensitive to cover the predicted O4 binary neutron star merger volume, and will be able to respond to both northern and southern triggers.

astro-ph.HE↗

arXiv2017

The SUrvey for Pulsars and Extragalactic Radio Bursts II: New FRB discoveries and their follow-up

We report the discovery of four Fast Radio Bursts (FRBs) in the ongoing SUrvey for Pulsars and Extragalactic Radio Bursts (SUPERB) at the Parkes Radio Telescope: FRBs 150610, 151206, 151230 and 160102. Our real-time discoveries have enabled us to conduct extensive, rapid multi-messenger follow-up at 12 major facilities sensitive to radio, optical, X-ray, gamma-ray photons and neutrinos on time scales ranging from an hour to a few months post-burst. No counterparts to the FRBs were found and we provide upper limits on afterglow luminosities. None of the FRBs were seen to repeat. Formal fits to all FRBs show hints of scattering while their intrinsic widths are unresolved in time. FRB 151206 is at low Galactic latitude, FRB 151230 shows a sharp spectral cutoff, and FRB 160102 has the highest dispersion measure (DM = $2596.1\pm0.3$ pc cm$^{-3}$) detected to date. Three of the FRBs have high dispersion measures (DM >$1500$ pc cm$^{-3}$), favouring a scenario where the DM is dominated by contributions from the Intergalactic Medium. The slope of the Parkes FRB source counts distribution with fluences $>2$ Jyms is $α=-2.2^{+0.6}_{-1.2}$ and still consistent with a Euclidean distribution ($α=-3/2$). We also find that the all-sky rate is $1.7^{+1.5}_{-0.9}\times10^3$FRBs/($4π$ sr)/day above $\sim2$ Jyms and there is currently no strong evidence for a latitude-dependent FRB sky-rate.

astro-ph.HE↗

arXiv2017

A polarized fast radio burst at low Galactic latitude

We report on the discovery of a new fast radio burst, FRB 150215, with the Parkes radio telescope on 2015 February 15. The burst was detected in real time with a dispersion measure (DM) of 1105.6$\pm$0.8 pc cm^{-3}, a pulse duration of 2.8^{+1.2}_{-0.5} ms, and a measured peak flux density assuming the burst was at beam center of 0.7^{+0.2}_{-0.1} Jy. The FRB originated at a Galactic longitude and latitude of 24.66^{\circ}, 5.28^{\circ}, 25 degrees away from the Galactic Center. The burst was found to be 43$\pm$5% linearly polarized with a rotation measure (RM) in the range -9 < RM < 12 rad m^{-2} (95% confidence level), consistent with zero. The burst was followed-up with 11 telescopes to search for radio, optical, X-ray, gamma-ray and neutrino emission. Neither transient nor variable emission was found to be associated with the burst and no repeat pulses have been observed in 17.25 hours of observing. The sightline to the burst is close to the Galactic plane and the observed physical properties of FRB 150215 demonstrate the existence of sight lines of anomalously low RM for a given electron column density. The Galactic RM foreground may approach a null value due to magnetic field reversals along the line of sight, a decreased total electron column density from the Milky Way, or some combination of these effects. A lower Galactic DM contribution might explain why this burst was detectable whereas previous searches at low latitude have had lower detection rates than those out of the plane.

astro-ph.HE↗

arXiv2016

The 2QDES Pilot : The luminosity and redshift dependence of quasar clustering

We present a new redshift survey, the 2dF Quasar Dark Energy Survey pilot (2QDESp), which consists of ${\approx}10000$ quasars from ${\approx}150$ deg$^2$ of the southern sky, based on VST-ATLAS imaging and 2dF/AAOmega spectroscopy. Combining our optical photometry with the WISE (W1,W2) bands we can select essentially contamination free quasar samples with $0.8{<}z{<}2.5$ and $g{<}20.5$. At fainter magnitudes, optical UVX selection is still required to reach our $g{\approx}22.5$ limit. Using both these techniques we observed quasar redshifts at sky densities up to $90$ deg$^{-2}$. By comparing 2QDESp with other surveys (SDSS, 2QZ and 2SLAQ) we find that quasar clustering is approximately luminosity independent, with results for all four surveys consistent with a correlation scale of $r_{0}{=}6.1{\pm}0.1 \: h^{-1}$Mpc, despite their decade range in luminosity. We find a significant redshift dependence of clustering, particularly when BOSS data with $r_{0}{=}7.3{\pm}0.1 \: h^{-1}$Mpc are included at $z{\approx}2.4$. All quasars remain consistent with having a single host halo mass of ${\approx}2{\pm}1{\times}10^{12} \: h^{-1}M_\odot$. This result implies that either quasars do not radiate at a fixed fraction of the Eddington luminosity or AGN black hole and dark matter halo masses are weakly correlated. No significant evidence is found to support fainter, X-ray selected quasars at low redshift having larger halo masses as predicted by the `hot halo' mode AGN model of Fanidakis et al. 2013. Finally, although the combined quasar sample reaches an effective volume as large as that of the original SDSS LRG sample, we do not detect the BAO feature in these data.

astro-ph.GA↗

arXiv2013

Testing the WMAP cosmology via Planck radio catalogues

The prime evidence underpinning the standard LCDM cosmological model is the CMB power spectrum as observed by WMAP and other microwave experiments. But Sawangwit & Shanks (2010) have recently shown that the WMAP CMB power spectrum is highly sensitive to the beam profile of the WMAP telescope. Here, we use the source catalogue from the Planck Early Data Release to test further the WMAP beam profiles. We confirm that stacked beam profiles at Q, V and particularly at W appear wider than expected when compared to the Jupiter beam, normalised either directly to the radio source profiles or using Planck fluxes. The same result is also found based on WMAP-CMBfree source catalogues and NVSS sources. The accuracy of our beam profile measurements is supported by analysis of CMB sky simulations. However the beam profiles from WMAP7 at the W band are narrower than previously found in WMAP5 data and the rejection of the WMAP beam is now only at the ~3sigma level. We also find that the WMAP source fluxes demonstrate possible non-linearity with Planck fluxes. But including ground-based and Planck data for the bright Weiland et al (2011) sources may suggest that the discrepancy is a linear offset rather than a non-linearity. Additionally, we find that the stacked Sunyaev-Zel'dovich (SZ) decrements of ~151 galaxy clusters observed by Planck are in agreement with the WMAP data. We find that there is no evidence for a WMAP SZ deficit as has previously been reported. In the particular case of Coma we find evidence for the presence of an ~0.1mK downwards CMB fluctuation. We conclude that beam profile systematics can have significant effects on both the amplitude and position of the acoustic peaks, with potentially important implications for cosmology parameter fitting.

astro-ph.CO↗

arXiv2011

Measuring BAO and non-Gaussianity via QSO clustering

Our goals are (i) to search for BAO and large-scale structure in current QSO survey data and (ii) to use these and simulation/forecast results to assess the science case for a new, >10x larger, QSO survey. We first combine the SDSS, 2QZ and 2SLAQ surveys to form a survey of ~60000 QSOs. We find a hint of a peak in the QSO 2-point correlation function, xi(s), at the same scale (~105h^-1 Mpc) as detected by Eisenstein et al (2005) in their sample of DR5 LRGs but only at low statistical significance. We then compare these data with QSO mock catalogues from the Hubble Volume simulation used by Hoyle et al (2002) and find that both routes give statistical error estimates that are consistent at ~100h^-1 Mpc scales. Mock catalogues are then used to estimate the nominal survey size needed for a 3-4 sigma detection of the BAO peak. We find that a redshift survey of ~250000 z<2.2 QSOs is required over ~3000 deg^2. This is further confirmed by static log-normal simulations where the BAO are clearly detectable in the QSO power spectrum and correlation function. The nominal survey would on its own produce the first detection of, for example, discontinuous dark energy evolution in the so far uncharted 1<z<2.2 redshift range. A survey with ~50% higher QSO sky densities and 50% bigger area will give an ~6sigma BAO detection, leading to an error ~60% of the size of the BOSS error on the dark energy evolution parameter, w_a. Another important aim for a QSO survey is to place new limits on primordial non-Gaussianity at large scales, testing tentative evidence we have found for the evolution of the linear form of the combined QSO xi(s) at z~1.6. Such a QSO survey will also determine the gravitational growth rate at z~1.6 via z-space distortions, allow lensing tomography via QSO magnification bias while also measuring the exact luminosity dependence of small-scale QSO clustering.

astro-ph.CO↗