ABSTRACT Ongoing and future imaging surveys represent significant improvements in depth, area, and seeing compared to current data sets. These improvements offer the opportunity to discover up to ...three orders of magnitude more galaxy-galaxy strong lenses than are currently known. In this work we forecast the number of lenses that will be discoverable in forthcoming surveys and simulate their properties. We generate a population of statistically realistic strong lenses and simulate observations of this population for the Dark Energy Survey (DES), the Large Synoptic Survey Telescope (LSST), and Euclid surveys. We verify our model against the galaxy-scale lens search of the Canada-France-Hawaii Telescope Legacy Survey, predicting 250 discoverable lenses compared to 220 found by Gavazzi et al. The predicted Einstein radius distribution is also remarkably similar to that found by Sonnenfeld et al. For future surveys we find that, assuming Poisson limited lens galaxy subtraction, searches of the DES, LSST, and Euclid data sets should discover 2400, 120000, and 170000 galaxy-galaxy strong lenses, respectively. Finders using blue-minus-red ( ) difference imaging for lens subtraction can discover 1300 and 62000 lenses in DES and LSST. The uncertainties on the model are dominated by the high-redshift source population, which typically gives fractional errors on the discoverable lens number at the level of tens of percent. We find that doubling the signal-to-noise ratio required for a lens to be detectable approximately halves the number of detectable lenses in each survey, indicating the importance of understanding the selection function and the sensitivity of future lens finders in interpreting strong lens statistics. We make our population forecasting and simulated observation codes publicly available so that the selection function of strong lens finders can easily be calibrated.
Spatial Memory in Insect Navigation Collett, Matthew; Chittka, Lars; Collett, Thomas S.
Current biology,
09/2013, Letnik:
23, Številka:
17
Journal Article
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A wide variety of insects use spatial memories in behaviours like holding a position in air or flowing water, in returning to a place of safety, and in foraging. The Hymenoptera, in particular, have ...evolved life-histories requiring reliable spatial memories to support the task of provisioning their young. Behavioural experiments, primarily on social bees and ants, reveal the mechanisms by which these memories are employed for guidance to spatial goals and suggest how the memories, and the processing streams that use them, may be organized. We discuss three types of memory-based guidance which, together, can explain a large part of observed insect spatial behaviour. Two of these, alignment image-matching and positional image-matching, are based on an insect's remembered views of its surroundings: The first uses views to keep to a familiar heading and the second to head towards a familiar place. The third type of guidance is based on a process of path integration by which an insect monitors its distance and direction from its nest through odometric and compass information. To a large degree, these guidance mechanisms appear to involve modular computational systems. We discuss the lack of evidence for cognitive maps in insects, and in particular the evidence against a map based on path integration, in which view-based and path integration memories might be combined. We suggest instead that insects have a collective of separate guidance systems, which cooperate and train each other, and together provide reliable guidance over a range of conditions.
Probing the relative speeds of gravitational waves and light acts as an important test of general relativity and alternative theories of gravity. Measuring the arrival time of gravitational waves ...(GWs) and electromagnetic (EM) counterparts can be used to measure the relative speeds, but only if the intrinsic time lag between emission of the photons and gravitational waves is well understood. Here we suggest a method that does not make such an assumption, using future strongly lensed GW events and EM counterparts; Biesiada et al. J. Cosmol. Astropart. Phys.10 (2014) 080JCAPBP1475-751610.1088/1475-7516/2014/10/080 forecast that 50-100 strongly lensed GW events will be observed each year with the Einstein Telescope. A single strongly lensed GW event would produce robust constraints on c_{GW}/c_{γ} at the 10^{-7} level, if a high-energy EM counterpart is observed within the field of view of an observing γ-ray burst monitor.
We present constraints on the equation of state of dark energy, w, and the total matter density, ΩM, derived from the double-source-plane strong lens SDSSJ0946+1006, the first cosmological ...measurement with a galaxy-scale double-source-plane lens. By modelling the primary lens with an elliptical power-law mass distribution, and including perturbative lensing by the first source, we are able to constrain the cosmological scaling factor in this system to be β−1 = 1.404 ± 0.016, which implies
$\Omega _{\mathrm{M}}= 0.33_{-0.26}^{+0.33}$
for a flat Λ cold dark matter (ΛCDM) cosmology. Combining with a cosmic microwave background prior from Planck, we find w =
$-1.17^{+0.20}_{-0.21}$
assuming a flat wCDM cosmology. This inference shifts the posterior by 1σ and improves the precision by 30 per cent with respect to Planck alone, and demonstrates the utility of combining simple, galaxy-scale multiple-source-plane lenses with other cosmological probes to improve precision and test for residual systematic biases.
Research on central brain areas in Drosophila and other insects is revealing the highly conserved neural circuitries in the central complex that are responsible for course control using visual, ...ideothetic and compass cues 1,2, and in the mushroom bodies that hold long-term visual and olfactory memories 3,4. Interactions between these areas are likely to be particularly important for navigation in which long-term memories determine an insect’s course. Many ants, for example, use long-term visual memories for guidance along routes between their nest and food sites. But the interactions remain a puzzle: both because there are no known direct connections between mushroom body and central complex, and because the output from the mushroom body, where the route memories are probably stored 5, may simply signal whether a sensory input is attractive or aversive 4. Extrapolating from a recent behavioural finding 6, we propose one way that the long-term memories in the mushroom body may be transformed into central complex steering commands. This answer, if correct, may reconcile two apparently conflicting ways of thinking about route following — suggesting how steering along a route can use a feedback controller based on a few prominent features 7, while the route memories themselves are holistic memories of the entire panorama 5. It also suggests how visual navigation is related to (and possibly evolved from) visual targeting and olfactory-based guidance.
Collett et al. propose how long-term memories in the mushroom bodies (mushroom body) are transformed into an insect’s guidance commands: mushroom body output on recognising a stimulus acts as a trigger signal for steering circuitry in the central complex (central complex). The central complex then fixes its current sensory inputs as short-term set-points for feedback control of travel direction.
Insect learning flights and walks Collett, Thomas S.; Zeil, Jochen
Current biology,
09/2018, Letnik:
28, Številka:
17
Journal Article
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Knowledge of where things are in one’s habitual surroundings cannot be encoded genetically and must be acquired in those surroundings. Many ants, bees and wasps forage from a home base and before ...doing so learn where resources are to be found and how to return with them to their nest. A significant component of this navigational learning seems to be the acquisition of panoramic views that insects record close to their nests and resource sites and along the paths between these places. Behavioural evidence indicates that these views are retinotopic, meaning, for instance, that an insect knows that it faces along a familiar route, if the image on its retina matches a view that it had previously recorded, when facing in that direction during route learning.
Many ants, bees and wasps make repeated foraging trips from their nest. In this primer, Collett and Zeil discuss the special learning behaviour that these insects perform in order to become familiar with the visual features of their surroundings when they first leave their nest to pursue a foraging career.
ABSTRACT
We investigate the effect of microlensing on the standardization of strongly lensed Type Ia supernovae (GLSNe Ia). We present predictions for the amount of scatter induced by microlensing ...across a range of plausible strong lens macromodels. We find that lensed images in regions of low convergence, shear and stellar density are standardizable, where the microlensing scatter is ≲ 0.15 mag, comparable to the intrinsic dispersion of a typical SN Ia. These standardizable configurations correspond to asymmetric lenses with an image located far outside the Einstein radius of the lens. Symmetric and small Einstein radius lenses (≲ 0.5 arcsec) are not standardizable. We apply our model to the recently discovered GLSN Ia iPTF16geu and find that the large discrepancy between the observed flux and the macromodel predictions from More et al. cannot be explained by microlensing alone. Using the mock GLSNe Ia catalogue of Goldstein et al., we predict that ∼22 per cent of GLSNe Ia discovered by Large Synoptic Survey Telescope (LSST) will be standardizable, with a median Einstein radius of 0.9 arcsec and a median time delay of 41 d. By breaking the mass-sheet degeneracy the full LSST GLSNe Ia sample will be able to detect systematics in H0 at the 0.5 per cent level.
Inferring cosmological parameters from time-delay strong lenses requires a significant investment of telescope time; it is therefore tempting to focus on the systems with the brightest sources, the ...highest image multiplicities and the widest image separations. We investigate if this selection bias can influence the properties of the lenses studied and the cosmological parameters inferred. Using an ellipsoidal power-law deflector population, we build a sample of double- and quadruple-image systems. Assuming reasonable thresholds on image separation and flux, based on current lens monitoring campaigns, we find that the typical density profile slopes of monitorable lenses are significantly shallower than the input ensemble. From a sample of quads, we find that this selection function can introduce a 3.5 per cent bias on the inferred time-delay distances if the properties of the input ensemble are (incorrectly) used as priors on the lens model. This bias remains at the 2.4 per cent level when high-resolution imaging of the quasar host is used to precisely infer the properties of individual lenses. We also investigate if the lines of sight for monitorable strong lenses are biased. The expectation value for the line-of-sight convergence is increased by 0.009 (0.004) for quads (doubles) implying a 0.9 per cent (0.4 per cent) bias on H sub( 0). We therefore conclude that whilst the properties of typical quasar lenses and their lines of sight do deviate from the global population, the total magnitude of this effect is likely to be a subdominant effect for current analyses, but has the potential to be a major systematic for samples of ~25 or more lenses.
A precise extragalactic test of General Relativity Collett, Thomas E; Oldham, Lindsay J; Smith, Russell J ...
Science (American Association for the Advancement of Science),
06/2018, Letnik:
360, Številka:
6395
Journal Article
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Einstein's theory of gravity, General Relativity, has been precisely tested on Solar System scales, but the long-range nature of gravity is still poorly constrained. The nearby strong gravitational ...lens ESO 325-G004 provides a laboratory to probe the weak-field regime of gravity and measure the spatial curvature generated per unit mass, γ. By reconstructing the observed light profile of the lensed arcs and the observed spatially resolved stellar kinematics with a single self-consistent model, we conclude that γ = 0.97 ± 0.09 at 68% confidence. Our result is consistent with the prediction of 1 from General Relativity and provides a strong extragalactic constraint on the weak-field metric of gravity.