Optical chopping is a step taken to acquire calibrated images for high-contrast instruments such as our SPIDERS pathfinder, the CAL2.0 Gemini Planet Imager 2.0 upgrade, and other future projects. A unique design with smooth, continuous, and slow operation is needed to blink the fringed and unfringed images for dim and bright stars. The Ultra-Low Speed Optical Chopper (ULSOC) must blink between 0.05Hz and 100Hz with noise-free operation, stop in the ‘on’ or ‘off’ position, and have its timing controlled by an external trigger. Silicone dampers are utilized to ensure it is vibration-isolated from other components in the system. The self-calibrating system accepts any chopping wheel between 10-30 blades without the need to reconfigure software and will find its home position on every power-up. The ULSOC communicates serially to start and stop as needed during operation. Long operational periods (during on-sky observations) over a lifetime of at least 10 years, closed-loop stepper-servo control and optical feedback from the chopper wheel guarantees accurate and repeatable velocity and position. Initial prototypes show that smooth and noise-free operation are possible for the desired speed ranges, and vibration is well-managed. Further development this year will lead to a fully functional device to be tested on-sky with our SPIDERS instrument and lead the way to revisions down the road for future projects.
In July of 2020 the Herzberg Astronomy and Astrophysics Research Centre was contracted to provide the Gemini Telescopes Observatory with a facility class Adaptive Optics (AO) Real Time Controller (RTC) suitable to run existing and future Adaptive Optics Systems. This Gemini Adaptive Optics Real-Time Controller (GAO RTC) is using the Herzberg Extensible Adaptive Real-time Toolkit (HEART), a C/Python software framework for constructing RTCs that targets general-purpose CPUs and standard networking hardware. Initially a fully simulated stand-alone RTC will be completed which will be suitable for experimentation in association with end-to-end AO simulation software. Subsequently, it will be reconfigured and extended to support hardware interfaces to the future Gemini North Adaptive Optics (GNAO) facility. This paper will provide an overview of the customization of the HEART design for GNAO, current state of the development, how this system state changes during operation, and how HEART was de-risked.
The Gemini Planet Imager (GPI) is undergoing a number of upgrades as part of the process of moving the instrument from Gemini South to Gemini North. The upgraded instrument (GPI2.0) will include a new Real- Time Controller (RTC) that drives the eXtreme Adaptive Optics (XAO) system, which is composed of a new high-sensitivity Natural Guide Star (NGS) Pyramid Wavefront Sensor (PWFS), and the existing two Deformable Mirrors (DMs) and Tip/Tilt Stage (TTS) at loop rates up to 2 kHz with very low latency. The new RTC is based on the Herzberg Extensible Adaptive Real-time Toolkit (HEART), which is a collection of libraries and other software that can be used to control different types of Adaptive Optics (AO) systems. HEART’s configurability and flexibility lends itself well to GPI2.0 RTC. This paper explores how HEART functionality is used and configured to construct the GPI2.0 RTC.
REVOLT is an experimental testbed that will be used to test novel AO components and AO techniques on sky at the 1.2m telescope of the Dominion Astrophysical Observatory. In its initial configuration that will be tested on-sky in spring 2022, REVOLT will have one deformable mirror, an ALPAO DM 277 and a Shack-Hartmann WFS based on a newly developed 512x512 pixel Near-Infrared Avalanche Photodiode array (Saphira). This testbed will be controlled at frame rates of up to 1 kHz by a Real-Time Controller (RTC) based on HEART1. HEART has gone through extensive testing and benchmarking, but this is the first time it will be tested on-sky. This paper will discuss customization of HEART required by REVOLT for the specified hardware, the issues found and lessons learned, the performance achieved during operations and the upgrades performed on HEART as a result.
This paper will discuss the Gemini Infrared Multi-Object Spectrograph (GIRMOS) with a focus on the design of its facility class Adaptive Optics (AO) Real Time Controller (RTC). The GIRMOS Adaptive Optics Real-Time Controller (GIRMOS RTC) will be developed using the Herzberg Extensible Adaptive Real-time Toolkit (HEART), a C/C++ software framework for constructing RTCs that targets general-purpose CPUs and standard networking hardware. The GIRMOS RTC just finished a successful pre-build phase where the custom parts of GIRMOS were designed and it was shown how the design incorporated HEART’s software modules. The GIRMOS RTC as a Multi-Object implementation of HEART will leverage a decade of design, modelling, and prototyping effort aimed to support the performance and configurability requirements of AO systems, with support for multiple client science instruments. This paper will discuss how HEART can be customized for a Multi-Object AO (MOAO) system.
Herzberg Extensible Adaptive Real-time Toolkit (HEART) is a collection of libraries and other software that can be used to create different types of Adaptive Optics (AO) systems. Pixels can be received from Laser Guide Star (LGS) Wavefront Sensors (WFSs), high-order Natural Guide Star (NGS) WFSs, On-Instrument WFSs (OIWFSs) that are located in the science instruments, and on-detector guide windows (ODGW) from science imagers. These inputs are processed in real-time by HEART to compute commands to configure the deformable mirrors (DMs) and the tip-tilt stage (TTS), as well as offloading information to selected mechanisms in the RTC, in the telescope and in the client instruments. This paper will explore the internal structure of HEART. In particular, the concept of “blocks”, which are reusable software units from which an RTC can be composed, how “pipes” are used to combine blocks in a meaningful manner and ultimately how those pipes can be used to realize many different types of real-time controllers (RTCs) such as SCAO (Single Conjugate AO), Multi-Conjugate AO (MCAO), Multi-Object AO (MOAO), and Ground Layer AO (GLAO). HEART is currently being implemented for use in NFIRAOS (Near Field Infra-Red AO System) for TMT, GNAO (Gemini North Adaptive Optics system), GIRMOS (Gemini Infrared Multi-Object Spectrograph), GPI2.0 (Gemini Planet Imager upgrade) and REVOLT (Research, Experiment and Validation of adaptive Optics with a Legacy Telescope).
Prior statistical knowledge of the turbulence such as turbulence strength, layer altitudes and the outer scale is essential for atmospheric tomography in adaptive-optics (AO). These atmospheric parameters can be estimated from measurements of multiple Shack-Hartmann wave-front sensors (SH-WFSs) by the SLOpe Detection And Ranging (SLODAR). In this paper, we present the statistics of the vertical CN2 and the outer scale L0 at Maunakea in Hawaii estimated from 60 hours telemetry data in total from multiple SH-WFSs of RAVEN, which is an on-sky multi-object AO demonstrator tested on the Subaru telescope. The mean seeing during the RAVEN on-sky observations is 0.475 arcsec, and 55% turbulence is below 1.5 km. The vertical profile of CN2 from the RAVEN SLODAR is consistent with the profiles from CFHT DIMM and MASS, and TMT site characterization.
This paper presents the AO performance we got on-sky with RAVEN, a Multi-Object Adaptive Optics (MOAO) technical and science demonstrator installed and tested at the Subaru telescope. We report Ensquared-Energy (EE) and Full Width at Half Maximum (FWHM) measured from science images on Subaru's IRCS taken during all of the on-sky observing runs. We show these metrics as function of different AO modes and atmospheric conditions for two asterisms of natural guide stars. The performances of the MOAO and Ground-Layer AO (GLAO) modes are between the classical Single-Conjugate AO (SCAO) and seeing-limited modes. We achieve the EE of 30% in H-band with the MOAO correction, which is a science requirement for RAVEN. The MOAO provides sightly better performance than the GLAO mode in both asterisms. One of the reasons which cause this small difference between the MOAO and GLAO modes may be the strong GL contribution. Also, the performance of the MOAO modes is affected by the accuracy of the on-sky turbulence profiling by the SLOpe Detection And Ranging (SLODAR) method.
Raven is a multi-object adaptive optics (MOAO) demonstrator that will be mounted on the NIR Nasmyth platform of the Subaru telescope in May, 2014. Raven can use three open-loop NGS WFSs and an on-axis LGS WFS to control DMs in two separate science pick-off arms. Centroiding in open loop AO systems like Raven is more difficult than in closed loop AO systems because the Shack-Hartmann spots will not be driven to the same spot on a detector. Rather the spots can fall on any combination of pixels because the WFSs need to have sufficient dynamic range to measure the full turbulence. In this paper, we compare correlation and thresholded center of gravity (tCOG) centroiding methods in simulation, with Raven using its calibration unit, and on-sky. Each method has its own advantages. Correlation centroiding is superior to tCOG centroiding for faint NGSs and for extended sources (Raven open loop WFSs do not contain ADCs so spots will become elongated). We expect that correlation centroiding will push the limiting magnitude of Raven NGSs fainter by roughly one magnitude. Correlation centroiding is computationally more intensive, however, and actually will limit Raven’s sampling rate for shorter integrations. Therefore, for bright stars with sufficiently high signal-to-noise, Raven can be run significantly faster and with superior performance using the tCOG method. Here we quantify both the performance and timing differences of these two centroiding methods in simulation, in the lab and on sky using Raven.
This paper discusses static and dynamic tomographic wave-front (WF) reconstructors tailored to Multi-Object Adaptive Optics (MOAO) for Raven, the first MOAO science and technology demonstrator recently installed on an 8m telescope. We show the results of a new minimum mean- square error (MMSE) solution based on spatio-angular (SA) correlation functions, which extends previous work in Correia et al, JOSA-A 20131 to adopt a zonal representation of the wave-front and its associated signals. This solution is outlined for the static reconstruction and then extended for the use of stand-alone temporal prediction and as a prediction model in a pupil plane based Linear Quadratic Gaussian (LQG) algorithm. We have fully tested our algorithms in the lab and compared the results to simulations of the Raven system. These simulations have shown that an increase in limiting magnitude of up to one magnitude can be expected when prediction is implemented and up to two magnitudes when the LQG is used.
Raven is a Multi-Object Adaptive Optics (MOAO) technical and science demonstrator which had its first light at the Subaru telescope on May 13-14, 2014. Raven was built and tested at the University of Victoria AO Lab before shipping to Hawai`i. Raven includes three open loop wavefront sensors (WFSs), a central laser guide star WFS, and two independent science channels feeding light to the Subaru IRCS spectrograph. Raven supports different kinds of AO correction: SCAO, open-loop GLAO and MOAO. The MOAO mode can use different tomographic reconstructors, such as Learn-and-Apply or a model-based reconstructor. This paper presents the latest results obtained in the lab, which are consistent with simulated performance, as well as preliminary on-sky results, including echelle spectra from IRCS. Ensquared energy obtained on sky in 140mas slit is 17%, 30% and 41% for GLAO, MOAO and SCAO respectively. This result confirms that MOAO can provide a level of correction in between GLAO and SCAO, in any direction of the field of regard, regardless of the science target brightness.
Raven is a Multi-Object Adaptive Optics (MOAO) scientific demonstrator which will be used on-sky at the Subaru
observatory. Raven is currently being built at the University of Victoria AO Lab. In this paper, we present an overview
of the final Raven design and then describe lab tests involving prototypes of Raven subsystems. The final design
includes three open loop wavefront sensors (WFSs), a laser guide star WFS and two figure/truth WFSs. Two science
channels, each containing a deformable mirror (DM), feed light to the Subaru IRCS spectrograph. Central to the Raven
MOAO system is a Calibration Unit (CU) which contains multiple sources, a telescope simulator including two rotating
phase screens and a ground layer DM that can be used to calibrate and test Raven. We are working with the Raven CU
and open loop WFSs to test and validate our open loop calibration and alignment techniques.
Raven is a Multi-Object Adaptive Optics (MOAO) technical and scientific demonstrator which will be used on
the Subaru telescope with the IRCS spectrograph. The optical and mechanical designs are finalised and the
system is now being integrated in the lab at UVic. Raven features three open-loop wavefront sensors (WFS)
patrolling a 3.5' field of regard, one on-axis LGS WFS, two science channels each equipped with a pick-off arm,
an 11x11 actuator deformable mirror, a closed-loop WFS for calibration and performance comparison and an
image rotator. This paper presents in detail the optical design and its performance, as well as the mechanical
design.
This article reports the progress made at the University of Victoria AO Lab, regarding the realtime
open-loop control of a 1024-actuator MEMS deformable mirror (DM). The setup is an hybrid
woofer-tweeter/open-loop bench. A tip-tilt mirror and a woofer DM (a 57-actuator CILAS DM)
are driven in closed-loop while a 1024-actuator MEMS DM is utilized on a parallel open-loop
path. Previous work shows that open-loop control providing low residual error (with frozen
Kolmogorov turbulence) can be obtained without the need of DM modelling. A preliminary
methodical calibration of the DM is employed instead. The MEMS electronics were upgraded
to an update rate of 500 Hz and the experiment lays the groundwork for showing how these
performances can also be achieved on the bench with dynamic turbulence (created with custom
hot air turbulence generators). The current status of the experiment and the next milestones
are presented.
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