Monday, June 18, 2018

SPIE conference report

From June 10th to June 15th, the lab team attended the SPIE conference in Austin-Texas to present the latest results it obtained. Here are some pictures and sum ups of the presentations!

Chris (left) and Keira (right) presented the software architecture for HiCAT. This infrastructure enables 24/7 automated calibration, safety checks, and operation.

Rémi (very right) had an overview talk on HiCAT, to show the latest results obtained on the testbed: tests of different coronagraphs, with and without segmentation, also combined with the speckle nulling tool for wavefront control, phasing errors reconstruction with the COFFEE wavefront sensor...

Iva (the quality of the picture does not reflect the quality of her work!) presented an update of the JOST status: results have been obtained on the testbed alignment on both single field and wide field of view, using the LAPD algorithm.

Greg introduced the OPERA wavefront sensor he developed and tested successfully on HiCAT, enabling to reduce the wavefront error from 16nm rms to 3nm rms over a 18mm diameter pupil.

Kathryn described us the APLC design propositions for the different LUVOIR's primary mirror configurations and their combination with wavefront control to improve their efficiency in terms of throughput, inner working angle, etc. Her work is part of the SCDA study.

Kevin also presented his work on the SCDA study. He examined APLCs apodizations with circular symmetric pupil masks and pairs of DMs using a modified MCMC algorithm that allows to probe previously unexamined combinations of pupil apodizations, focal plane mask size, and Lyot stop size. He also explored using this strategy to optimize the APLC for planet yield.

Lucie presented the latest developments of the PASTIS model that enables fast error budgeting for segmented telescopes combined with a coronagraph. PASTIS had already proven its efficiency for one kind of Zernike polynomials present on the segment, it is now working in the multi-Zernike and dynamic cases.

Even if no picture was taken, Marshall introduced the different performance and stability studies and results conducted on the JWST, and Laurent presented the LUVOIR coronagraph instrument.
As a conclusion, the team was glad to present so many results on so many different topics and to learn so much on the other projects happening in parallel in other institutes, industries, or labs!

Monday, June 4, 2018

HiCAT: Johns Hopkins University students' project

JHU ME Senior Design project STScI-E18:

The demanding requirements for HiCAT drive continual innovation. The precise optics work best in a controlled, enclosed chamber. Meanwhile the science team need to be able to open the chamber easily & without causing contamination. The enclosure developed by mechanical engineering students in 2015 was OK but over time problems were found. The sliding panels caused some dust to form due to wear, and they were not as airtight as desired. A team of four mechanical engineering seniors worked on a fresh version during their two semester capstone course. After many prototypes the final version installed has a viton™ rubber seal and magnetic attachment to the frame. It’s only been used for a few weeks but early signs are that it is an improvement over the previous design.

HiCAT with new enclosure panels, May 2018

Remi installs one of the panels

ME Seniors Courtney, Andrew, Andrew & Matthieu would like to thank STScI and our friends at the Makidon lab for a first rate educational experience.

Wednesday, May 2, 2018

In the news!

The Makidon lab is in the news!
The lab is first mentioned in the NASA's Cutting edge journal for Spring 2018, in the article "2020 Decadal Survey Missions: At a glance" pages 4 to 9 focusing, in particular, on our carbon nanotube apodizer for the 37 segment deformable mirror.
Furthermore, the STScI 2017 annual report offers a full section on our latest results (pages 17 to 19), followed with a feature of Christopher Moriarty, the software engineer working on HiCAT (page 20).
These articles show how the lab is involved with future space missions such as the LUVOIR telescope, proposing experimental studies that combine innovative science with the cutting edge technological advancements.

Sunday, April 22, 2018

HiCAT: First demonstration of a coronagraph dark zone in broadband light with a segmented aperture

Recently on HiCAT, we obtained a very first dark hole with a broadband light source, combining a segmented aperture, a coronagraph (Apodized Pupil Lyot Coronagraph or APLC), and wavefront control (the Speckle Nulling method, now running on demand in any configuration). 

Once the full APLC was set, with a segmented aperture (segment gap, central obscuration, and spiders), the experiment had three steps:
- Conducted the Speckle Nulling procedure with our monochromatic light source (638nm) to create a DM command for a dark zone.
- Switched the light source to broadband, loaded the dark zone command, and computed the contrast.
- Switched to another tunable light source, took data at a range of wavelengths from 600nm to 680nm, and computed the contrast at each wavelength.

In the final configuration (see image below), the broadband contrast is 6.3*10^-6 in a 6% bandpass, while the monochromatic contrast is 1.7*10^-6. Please note the superposition of the "natural" circular dark zone of the APLC and of the deeper dark zone (non symmetrical) from the wavefront control. 

Left: image obtained in broadband light, with the full APLC and the speckle nulling procedure, that join effort to improve the contrast on the dark zone. Center: Broadband demo using a tunable laser (not yet fully optimized in this experiment, with minimum contrast about twice higher than our best monochromatic result). Right: HiCAT testbed with three DMs and carbon nanotube APLC apodizer. 

Wednesday, April 4, 2018

HiCAT: first results with the COFFEE wavefront sensor

Last week, Jean-François Sauvage (from the Office National d’Etudes et de Recherches Aérospatiales and the Laboratoire d’Astrophysique de Marseille) has been invited by STScI to come to the Makidon Lab to implement and test the COFFEE wavefront sensor on HiCAT data, with the HiCAT team: his PhD student Lucie Leboulleux, Christopher Moriarty, Keira Brooks, Peter Petrone, and Rémi Soummer.
COFFEE stands for COronagraphic Focal-plane wave-Front Estimation for Exoplanet detection and is a focal plane wavefront sensing method that can, with or without coronagraph, reconstruct the pupil aberrations. It requires two sets of images from the science camera: one with the pupil plane DM being flat, one with a known focus.
In our case, we had the Iris-AO (segmented mirror) set on HiCAT, in addition to the two deformable mirrors, and it provided us very original conditions: segment gaps, huge local phase differences, and cophasing errors.
In particular, we could reconstruct piston, tip, and tilt errors that we were applying on purpose on the Iris-AO to validate the reconstruction. The direct mode of COFFEE (without coronagraph) worked extremely smoothly, and after a few days the coronagraphic mode could also be validated (see images below). This result is particularly impressive since no prerequisite was required from COFFEE about this particular pupil: COFFEE was not aware that the pupil was segmented! Furthermore, COFFEE can not only reconstruct the cophasing errors, but also the print-through of the DM actuators that generate high-frequency effects.

Left: phase reconstructed by COFFEE, in direct mode (no coronagraph). Right: theoretical phase obtained from the commands sent to the Iris AO.

Left: phase reconstructed by COFFEE, in coronagraphic mode. Right: theoretical phase obtained from the commands sent to the Iris AO.

Wednesday, March 28, 2018

JOST: Installation of the HiCAT python package

For a couple of years now, our group had been doing really good work in developing first-class coronagraph technology and wavefront sensing techniques for segmented apertures. During this process, one of the focus points of the work is to create a concise python package which controls the HiCAT testbed and its environment and which would eventually be ready to be freely shared for implementation on other high-contrast testbeds. 

Starting last year in October, we used the past six months to work on major infrastructure updates for JOST. We exchanged the CCD camera for a much faster CMOS camera, implemented a pupil imaging lens, and cleaned up the software. This included migrating all codes to GitHub and putting the repository on version control, translating Mathematica codes to Python, eliminating IDL pieces of the experimental software by translating them to Python as we'll and finally, implementing hardware interfaces by using those developed for HiCAT. After individual parts of the HiCAT module have been successfully tested, e.g. the parts for the camera and laser control, we decided it was time to fully install the package and integrate it in the JOST software.

The code developed for HiCAT was designed as a proper Python package installable with pip. Even further, the interfaces developed for each instrument are easily accessible by just installing the HiCAT package and importing them. While this comes with lots of code specific to HiCAT, it is a quick and easy way to access robust instrument control if you happen to use any of the same ones. We are planning to abstract out the hardware control interfaces into their own package in the future and make that package open source.

Each hardware interface follows a simple object-oriented paradigm where the parent is an abstract class (e.g. "Camera"), which defines specific methods and implements a context manager. Context managers are important for hardware control because they will gracefully close the hardware even if the program crashes unexpectedly. The child classes implement the abstract methods such as open(), close(), takeExposure() with code for the specific camera. This keeps your scripts generic and means changing cameras will have little to no impact on your code.

Implementing this on JOST meant we could see in what instances the HiCAT package needs to be more generalized. The installation and implementation worked seamlessly and fairly quick, and HiCAT and JOST are now running off the same Python package for hardware control! The modular structure of the package makes the construction of new experiments fast and straightforward and we hope to continue our work on JOST a lot smoother now.

Monday, February 26, 2018

PASTIS: Applications to sensitivity analysis of segmented telescopes

A traditional error budget aims at quantifying the deterioration of the contrast with the rms error phase applied on the segments. For example, in the case of segment-level pistons, we can easily deduce from Fig.1 the constraints in piston cophasing in term of rms error.

Fig.1. Contrast as a function of the rms piston error phase on the pupil, computed from both the end-to-end simulation (E2E) and PASTIS.

Since PASTIS provides an accurate (~3% error) estimation of the contrast, but 10^7 times faster than the end-to-end simulation, it can replace this very time-consuming method in such error budgeting, which is particularly useful when numerous cases need to be tested. Similarly, it makes simulations of performance for long-time series of high-frequency vibrations possible.

However it is known that some segments have a bigger impact on the contrast than others, which appears in the PASTIS model. This is why we propose another approach to error budgeting, which provides also a better understanding of the repartition of the requirements on the segments.

First, from PASTIS we can derive the eigen modes of the pupil. Some of them are shown in Fig. 2, in the piston case. Since these eigen modes are orthonormal, they provide a modal basis of the segment-level phases (piston case here). All phases can be projected in a unique way on this basis.

Fig. 2. Eigen modes in the local only piston case. The top line corresponds to the four modes with the highest eigen values, the bottom line to four of the modes with the lowest eigen values. In this second line, we can recognize discrete versions of some common low-order Zernike polynomials: the two astigmatisms and the tip and tilt. Furthermore, the last modes focus more on the corner segments, that are typically the segments that impact the contrast the least, since they are the most obscured by both the apodizer and the Lyot stop. Conversely, on the top line, we can also see that the segments with the most extreme piston coefficients correspond to the segments hidden by neither the apodizer nor the Lyot stop, and so are the segments that influence the contrast the most. This explains why they have the highest eigen values.

Since these eigen modes form an orthogonal basis, they contribute independently to the contrast. Therefore computing a contrast due to a certain phase is equivalent to summing the contrasts of the projections of this phase on the different eigen modes.

As a consequence, this problem can be inverted: from a fixed target contrast, it is possible to reconstruct the constraints per eigen mode. To do so, we fix the contributed contrast of each mode (the sum of these contributed contrasts has to be equal to the global target contrast). From this contrast per mode and the egein value of each mode, it is possible to compute the constraint on each mode. Fig. 3 illustrates this constraints in the case of a global target contrast of 10^-6, where the constraints on the 35 first modes provide equal contributed contrasts of 10^-6/35, and the constraint on the last mode provide a contrast of 0. The way to read this plot is that, for example, our error phase cannot be higher than 1.6 times the first mode + 1.7 times the second mode + … + 9.5 times the 35th mode.

Fig. 3. Contributions on the different piston modes to reach a final target contrast of 10^-6, in the case where only local pistons on segments deteriorate the contrast.

To conclude, it is extremely to compute the constraints per mode with this method. But even more important, it provides a better understanding of the pupil structure and impact on the contrast, targeting the critical segments. It is then easier to optimize the backplane structure or the edge sensors on these segments to limit their impact on the contrast.

This method of inversion is also applicable to quasi-static stability study and to any other Zernike polynomial.