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The performance of tomographic adaptive optics systems is intrinsically linked to the vertical profile of optical turbulence. Firstly, a sufficient number of discrete turbulent layers must be reconstructed to model the true continuous turbulence profile. Secondly over the course of an observation, the profile as seen by the telescope changes and the tomographic reconstructor must be updated. These changes can be due to the unpredictable evolution of turbulent layers on meteorological timescales as short as minutes. Here we investigate the effect of changing atmospheric conditions on the quality of tomographic reconstruction by coupling fast analytical adaptive optics simulation to a large database of 10 691 high resolution turbulence profiles measured over two years by the Stereo-SCIDAR instrument at ESO Paranal, Chile. This work represents the first investigation of these effects with a large, statistically significant sample of turbulence profiles. The statistical nature of the study allows us to assess not only the degradation and variability in tomographic error with a set of system parameters (e.g. number of layers, temporal update period) but also the required parameters to meet some error threshold. In the most challenging conditions where the profile is rapidly changing, these parameters must be far more tightly constrained in order to meet this threshold. By providing estimates of these constraints for a wide range of system geometries as well as the impact of different temporal optimisation strategies we may assist the designers of tomographic AO for the ELT to dimension their systems., Comment: 13 pages, 13 figures. Accepted MNRAS March 2020

For extremely large telescopes, adaptive optics will be required to correct the Earth's turbulent atmosphere. The performance of tomographic adaptive optics is strongly dependent on the vertical distribution (profile) of this turbulence. An important way in which this manifests is the tomographic error, arising from imperfect measurement and reconstruction of the turbulent phase at altitude. Conventionally, a small number of reference profiles are used to obtain this error in simulation however these profiles are not constructed to be representative in terms of tomographic error. It is therefore unknown whether these simulations are providing realistic performance estimates. Here, we employ analytical adaptive optics simulation that drastically reduces computation times to compute tomographic error for 10 691 measurements of the turbulence profile gathered by the Stereo-SCIDAR instrument at ESO Paranal. We assess for the first time the impact of the profile on tomographic error in a statistical manner. We find, in agreement with previous work, that the tomographic error is most directly linked with the distribution of turbulence into discrete, stratified layers. Reference profiles are found to provide mostly higher tomographic error than expected, which we attribute to the fact that these profiles are primarily composed of averages of many measurements resulting in unrealistic, continuous distributions of turbulence. We propose that a representative profile should be defined with respect to a particular system, and that as such simulations with a large statistical sample of profiles must be an important step in the design process., Comment: Accepted MNRAS June 2019

In order to enhance accuracy of astrophysical estimates obtained on Adaptive-optics (AO) images, such as photometry and astrometry, we investigate a new concept to constrain the Point Spread Function (PSF) model called PSF Reconstruction and Identification for Multi-sources characterization Enhancement (PRIME), that handles jointly the science image and the AO control loop data. We present in this paper the concept of PRIME and validate it on Keck II telescope NIRC2 images. We show that by calibrating the PSF model over the scientific image, PSF reconstruction achieves 1\% and 3 mas of accuracy on respectively the Strehl-ratio and the PSF full width at half maximum. We show on NIRC2 binary images that PRIME is sufficiently robust to noise to retain photometry and astrometry precision below 0.005 mag and 100$\mu$as on a $m_H=$ 14 mag object. Finally, we also validate that PRIME performs a PSF calibration on the triple system Gl569BAB which provides a separation of 66.73$\pm 1.02$ and a differential photometry of 0.538$\pm 0.048$, compared to the reference values obtained with the extracted PSF which are 66.76 mas $\pm$ 0.94 and 0.532 mag $\pm$ 0.041.

The European Extremely Large Telescope will see first lights by the end of 2024. With a diameter of almost 40 meters, it will be the biggest optical telescope ever built from the ground. The ELT will open a brand new window in a sensitivity / spatial angular resolution parameter space. To take the full benefit of the scientific potential of this giant, all the instruments will be equipped with Adaptive Optics (AO), providing the sharpest images. This paper provides a quick overview of the AO capabilities of the future instruments to be deployed at the ELT, highlight some of the expected performance and describe a couple of technical challenges that are still to tackle for an optimal scientific use. This paper has been presented at the "Societe Francaise d'Astronomie et Astrophysique" symposium in Bordeaux 2018, it is then naturally biased toward the French contribution for the ELT., Comment: SF2A proceeding

The latest generation of high contrast instruments dedicated to exoplanets and circumstellar disks imaging are equipped with extreme adaptive optics and coronagraphs to reach contrasts of up to 10^--4 at a few tenths of arc-seconds in the near infrared. The resulting image shows faint features, only revealed with this combination, such as the wind driven halo. The wind driven halo is due to the lag between the adaptive optics correction and the turbulence speed over the telescope pupil. However we observe an asymmetry of this wind driven halo that was not expected when the instrument was designed. In this letter, we describe and demonstrate the physical origin of this asymmetry and support our explanation by simulating the asymmetry with an end-to-end approach. From this work, we found out that the observed asymmetry is explained by the interference between the AO-lag error and scintillation effects, mainly originating from the fast jet stream layer located at about 12 km in altitude. Now identified and interpreted, this effect can be taken into account for further design of high contrast imaging simulators, next generation or upgrade of high contrast instruments, predictive control algorithms for adaptive optics or image post-processing techniques.

Knowledge of the atmospheric turbulence in the telescope line-of-sight is crucial for wide-field observations assisted by adaptive optics (AO), for which the Point Spread Function (PSF) becomes strongly elongated due to the anisoplanatism effect. This one must be modelled accurately to extrapolate the PSF anywhere across the Field of view (FOV) and improve the science exploitation. However, anisoplanatism is a function of the Cn2(h) profile, that is not directly accessible from single conjugate AO telemetry. One may rely on external profilers, but recent studies have highlighted more than 10% of discrepancies with AO internal measurements, while we aim better than 1% of accuracy for PSF modelling. To tackle this existing limitation, we present the Focal plane profiling (FPP), as a $C_n^2(h)$ profiling method that relies on post-AO focal plane images. We demonstrate such an approach complies with a 1%-level of accuracy on the $C_n^2(h)$ estimation and establish how this accuracy varies regarding the calibration stars magnitudes and positions in the field. We highlight that photometry and astrometry errors due to PSF mis-modelling reaches respectively 1% and 50{\mu}as using FPP on a Keck baseline, with a preliminary calibration using a star of magnitude H=14 at 20". We also validate this concept using Canadas NRC-Herzberg HENOS testbed images in comparing FPP retrieval with alternative $C_n^2(h)$ measurements on HeNOS. The FPP approach allows to profile the $C_n^2(h)$ using the SCAO systems and improve significantly the PSF characterisation. Such a methodology is also ELT-size compliant and will be extrapolated to tomographic systems in a near future.

The neutron detection system for characterization of emissivity in ITER Tokamak during DD and DT experiments poses serious challenges to the performance of the diagnostic control and data acquisition system (CDAcq). The ongoing design of the ITER Radial Neutron Camera (RNC) diagnostic is composed by 26 lines of sight (LOS) for complete plasma inspection. The CDAcq system aims at meeting the ITER requirements of delivering the measurement of the real-time neutron emissivity profile with time resolution and control cycle time of 10 ms at peak event rate of 2 MEvents/s per LOS. This measurement demands the generation of the neutron spectra for each LOS with neutron/gamma discrimination and pile up rejection. The neutron spectra can be totally processed in the host CPU or it can use the processed data coming from the system FPGA. The number of neutron counts extracted from the spectra is then used to calculate the neutron emissivity profile using an inversion algorithm. Moreover, it is required that the event based raw data acquired is made available to the ITER data network without local data storage for post processing. The data production for the 2 MEvents/s rate can go up to a maximum data throughput of 0.5 GB/s per channel. The evaluation of the use of real-time data compression techniques in RNC is also depicted in another contribution. To meet the demands of the project a CDAcq prototype has been used to design and test a high-performance distributed software architecture taking advantage of multi-core CPU technology capable of coping with the requirements. This submission depicts the design of the real-time architecture, the spectra algorithms (pulse height analysis, neutron/gamma discrimination and pile-up correction) and the inversion algorithm to calculate the emissivity profile. Preliminary tests to evaluate the system performance with synthetic data are presented., Comment: Conference Record - 21st IEEE Real Time Conference, Colonial Williamsburg, USA, 9-15 June 2018

To achieve the aim of the ITER Radial Neutron Camera Diagnostic, the data acquisition prototype must be compliant with a sustained 2 MHz peak event for each channel with 128 samples of 16 bits per event. The data is acquired and processed using an IPFN FPGA Mezzanine Card (FMC-AD2-1600) with 2 digitizer channels of 12-bit resolution and a sampling rate up to 1.6 GSamples/s mounted in a PCIe evaluation board from Xilinx (KC705) installed in the host PC. The acquired data in the event-based data-path is streamed to the host through the PCIe x8 Direct Memory Access (DMA) with a maximum data throughput per channel is 0.5 GB/s of raw data (event base), 1 GB/s per digitizer and up to 1.6 GB/s in continuous mode. The prototype architecture comprises an host PC with two KC705 modules and four channels, producing up to 2 GB/s in event mode and up to 3.2 GB/s in continuous mode. To reduce the produced data throughput from host to ITER databases, the real-time data compression was evaluated using the LZ4 lossless compression algorithm, which provides compression speed up to 400 MB/s per core. This paper presents the architecture, implementation and test of the parallel real-time data compression system running in multiple isolated cores. The average space saving and the performance results for long term acquisitions up to 30 minutes, using different data block size and different number of CPUs, is also presented., Comment: 21st Real Time Conference, June 9th - 15th, Colonial Williamsburg, Virginia, United States

HARMONI is a visible and NIR integral field spectrograph, providing the E-ELT's core spectroscopic capability at first light. HARMONI will work at the diffraction limit of the E-ELT, thanks to a Classical and a Laser Tomographic AO system. In this paper, we present the system choices that have been made for these SCAO and LTAO modules. In particular, we describe the strategy developed for the different Wave-Front Sensors: pyramid for SCAO, the LGSWFS concept, the NGSWFS path, and the truth sensor capabilities. We present first potential implementations. And we asses the first system performance., Comment: SPIE proceeding, 2016

Adaptive optics (AO) restore the angular resolution of ground-based telescopes, but at the cost of delivering a time- and space-varying point spread function (PSF) with a complex shape. PSF knowledge is crucial for breaking existing limits on the measured accuracy of photometry and astrometry in science observations. In this paper, we concentrate our analyses on anisoplanatism signature only onto PSF: for large-field observations (20") with single- conjugated AO, PSFs are strongly elongated due to anisoplanatism that manifests itself as three different terms for Laser-guide star (LGS) systems: angular, focal and tilt. We propose a generalized model that relies on a point-wise decomposition of the phase and encompasses the non-stationarity of LGS systems. We demonstrate it is more accurate and less computationally demanding than existing models: it agrees with end-to-end physical-optics simulations to within 0.1% of PSF measurables, such as Strehl-ratio, FWHM and fraction of variance unexplained.Secondly, we study off-axis PSF modelling is with respect to $C_n^2(h)$ profile (heights and fractional weights). For 10m class telescope, PSF morphology is estimated at 1% level as long as we model the atmosphere with at least 7 layers whose heights and weights are known respectively with 200m and 10% precision. As a verification test we used the Canada's NRC-Herzberg HeNOS testbed data, featuring four lasers. We highlight capability of retrieving off-axis PSF characteristics within 10% of fraction of variance unexplained, which complies with the expected range from the sensitivity analysis. Our new off-axis PSF modelling method lays the ground-work for testing on-sky in the near future.

Canary is the Multi-Object Adaptive Optics (MOAO) pathfinder for the future MOAO-assisted Integral-Field Units (IFU) proposed for Extremely Large Telescopes (ELT). The MOAO concept relies on tomographically reconstructing the turbulence using multiple measurements along different lines of sight. Tomography requires the knowledge of the statistical turbulence parameters, commonly recovered from the system telemetry using a dedicated profiling technique. For demonstration purposes with the MOAO pathfinder Canary , this identification is performed thanks to the Learn & Apply (L&A) algorithm, that consists in model- fitting the covariance matrix of WFS measurements dependent on relevant parameters: $C_n^2(h)$ profile, outer scale profile and system mis-registration. We explore an upgrade of this algorithm, the Learn 3 Steps (L3S) approach, that allows one to dissociate the identification of the altitude layers from the ground in order to mitigate the lack of convergence of the required empirical covariance matrices therefore reducing the required length of data time-series for reaching a given accuracy. For nominal observation conditions, the L3S can reach the same level of tomographic error in using five times less data frames than the L&A approach. The L3S technique has been applied over a large amount of Canary data to characterize the turbu- lence above the William Herschel Telescope (WHT). These data have been acquired the 13th, 15th, 16th, 17th and 18th September 2013 and we find 0.67"/8.9m/3.07m/s of total seeing/outer scale/wind-speed, with 0.552"/9.2m/2.89m/s below 1.5 km and 0.263"/10.3m/5.22m/s between 1.5 and 20 km. We have also de- termined the high altitude layers above 20 km, missed by the tomographic reconstruction on Canary , have a median seeing of 0.187" and have occurred 16% of observation time.

CANARY is the multi-object adaptive optics (MOAO) on-sky pathfinder developed in the perspective of Multi-Object Spectrograph on Extremely Large Telescopes~(ELTs). In 2013, CANARY was operated on-sky at the William Herschel telescope~(WHT), using three off-axis natural guide stars~(NGS) and four off-axis Rayleigh laser guide stars~(LGS), in open-loop, with the on-axis compensated turbulence observed with a H-band imaging camera and a Truth wave-front sensor~(TS) for diagnostic purposes. Our purpose is to establish a reliable and accurate wave-front error breakdown for LGS MOAO. This will enable a comprehensive analysis of \cana on-sky results and provide tools for validating simulations of MOAO systems for ELTs. To evaluate the MOAO performance, we compared the CANARY on-sky results running in MOAO, in Single Conjugated Adaptive Optics~(SCAO) and in Ground Layer Adaptive Optics~(GLAO) modes, over a large set of data acquired in 2013. We provide a statistical study of the seeing. We also evaluated the wave-front error breakdown from both analytic computations, one based on a MOAO system modelling and the other on the measurements from the CANARY TS. We have focussed especially on the tomographic error and we detail its vertical error decomposition~(VED). We show that CANARY obtained 30.1\%, 21.4\% and 17.1\% H-band Strehl ratios in SCAO, MOAO and GLAO respectively, for median seeing conditions with 0.66" of total seeing including 0.59" at the ground. Moreover, we get 99\% of correlation over 4,500 samples, for any AO modes, between two analytic computations of residual phase variance. Based on these variances, we obtain a reasonable Strehl-ratio~(SR) estimation when compared to the measured IR image SR. We evaluate the gain in compensation for the altitude turbulence brought by MOAO when compared to GLAO.

In preparation of future Multi-Object Spectrographs (MOS) whose one of the major role is to provide an extensive statistical studies of high redshifted galaxies surveyed, the demonstrator Canary has been designed to tackle technical challenges related to open-loop Adaptive-Optics (AO) control with jointed Natural Guide Star (NGS) and Laser Guide Star (LGS) tomography. We have developed a Point Spread Function (PSF)-Reconstruction algorithm dedicated to MOAO systems using system telemetry to estimate the PSF potentially anywhere in the observed field, a prerequisite to post- process AO-corrected observations in Integral Field Spectroscopy (IFS). In this paper we show how to handle off-axis data to estimate the PSF using atmospheric tomography and compare it to a classical approach that uses on-axis residual phase from a truth sensor observing a natural bright source. We have reconstructed over 450 on-sky Canary PSFs and we get bias/1-${\sigma}$ standard-deviation (std) of 1.3/4.8 on the H-band Strehl ratio (SR) with 92.3% of correlation between reconstructed and sky SR. On the Full Width at Half Maximum (FWHM), we get respectively 2.94 mas, 19.9 mas and 88.3% for the bias, std and correlation. The reference method achieves 0.4/3.5/95% on the SR and 2.71 mas/14.9 mas/92.5% on the FWHM for the bias/std/correlation.

Aims:To support the computation and evolutionary interpretation of periods associated with the rotational modulation, oscillations, and variability of stars located in the CoRoT fields, we are conducting a spectroscopic survey for stars located in the fields already observed by the satellite. These observations allow us to compute physical and chemical parameters for our stellar sample. Method: Using spectroscopic observations obtained with UVES/VLT and Hydra/Blanco, and based on standard analysis techniques, we computed physical and chemical parameters ($T_{\rm{eff}}$, $\log \,(g)$, $\rm{[Fe/H]}$, $v_{\rm{mic}}$, $v_{\rm{rad}}$, $v \sin \,(i)$, and $A(\rm{Li})$) for a large sample of CoRoT targets. Results: We provide physical and chemical parameters for a sample comprised of 138 CoRoT targets. Our analysis shows the stars in our sample are located in different evolutionary stages, ranging from the main sequence to the red giant branch, and range in spectral type from F to K. The physical and chemical properties for the stellar sample are in agreement with typical values reported for FGK stars. However, we report three stars presenting abnormal lithium behavior in the CoRoT fields. These parameters allow us to properly characterize the intrinsic properties of the stars in these fields. Our results reveal important differences in the distributions of metallicity, $T_{\rm eff}$, and evolutionary status for stars belonging to different CoRoT fields, in agreement with results obtained independently from ground-based photometric surveys. Conclusions: Our spectroscopic catalog, by providing much-needed spectroscopic information for a large sample of CoRoT targets, will be of key importance for the successful accomplishment of several different programs related to the CoRoT mission, thus it will help further boost the scientific return associated with this space mission., Comment: 43 pages, 17 figures, accepted for publication in A&A

Context. Frequency analyses are very important in astronomy today, not least in the ever-growing field of exoplanets, where short-period signals in stellar radial velocity data are investigated. Periodograms are the main (and powerful) tools for this purpose. However, recovering the correct frequencies and assessing the probability of each frequency is not straightforward. Aims. We provide a formalism that is easy to implement in a code, to describe a Bayesian periodogram that includes weights and a constant offset in the data. The relative probability between peaks can be easily calculated with this formalism. We discuss the differences and agreements between the various periodogram formalisms with simulated examples. Methods. We used the Bayesian probability theory to describe the probability that a full sine function (including weights derived from the errors on the data values and a constant offset) with a specific frequency is present in the data. Results. From the expression for our Baysian generalised Lomb-Scargle periodogram (BGLS), we can easily recover the expression for the non-Bayesian version. In the simulated examples we show that this new formalism recovers the underlying periods better than previous versions. A Python-based code is available for the community., Comment: 6 pages, 6 figures, accepted for publication in A&A, code online at https://www.astro.up.pt/exoearths/tools.html

Modern Tokamaks have evolved from the initial axisymmetric circular plasma shape to an elongated axisymmetric plasma shape that improves the energy confinement time and the triple product, which is a generally used figure of merit for the conditions needed for fusion reactor performance. However, the elongated plasma cross section introduces a vertical instability that demands a real-time feedback control loop to stabilize the plasma vertical position and velocity. At the Tokamak \`a Configuration Variable (TCV) in-vessel poloidal field coils driven by fast switching power supplies are used to stabilize highly elongated plasmas. TCV plasma experiments have used a PID algorithm based controller to correct the plasma vertical position. In late 2013 experiments a new optimal real-time controller was tested improving the stability of the plasma. This contribution describes the new optimal real-time controller developed. The choice of the model that describes the plasma response to the actuators is discussed. The high order model that is initially implemented demands the application of a mathematical order reduction and the validation of the new reduced model. The lower order model is used to derive the time optimal control law. A new method for the construction of the switching curves of a bang-bang controller is presented that is based on the state-space trajectories that optimize the time to target of the system. A closed loop controller simulation tool was developed to test different possible algorithms and the results were used to improve the controller parameters. The final control algorithm and its implementation are described and preliminary experimental results are discussed., Comment: Preprint submitted to IEEE Transactions on Nuclear Science