Further author information: (Send correspondence to M.L.)
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# A Visible-light Lyot Coronagraph for SCExAO/VAMPIRES

Miles Lucas  Institute for Astronomy, University of Hawai’i, 640 N. Aohoku
Pl., Hilo, HI 96720, USA  Michael Bottom  Institute for Astronomy, University
of Hawai’i, 640 N. Aohoku Pl., Hilo, HI 96720, USA  Olivier Guyon  Subaru
Telescope, National Observatory of Japan, 650 N. Aohoku Pl., Hilo, HI 96720,
USA  Steward Observatory, University of Arizona,  Astrobiology Center, NINS,
2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan  College of Optical Sciences,
University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721, USA  Julien Lozi
Subaru Telescope, National Observatory of Japan, 650 N. Aohoku Pl., Hilo, HI
96720, USA  Barnaby Norris  Sydney Institute for Astronomy, University of
Sydney, Physics Rd., NSW 2006, Australia  Vincent Deo  Subaru Telescope,
National Observatory of Japan, 650 N. Aohoku Pl., Hilo, HI 96720, USA
Sébastien Vievard  Subaru Telescope, National Observatory of Japan, 650 N.
Aohoku Pl., Hilo, HI 96720, USA  Astrobiology Center, NINS, 2-21-1 Osawa,
Mitaka, Tokyo 181-8588, Japan  Kyohoon Ahn  Subaru Telescope, National
Observatory of Japan, 650 N. Aohoku Pl., Hilo, HI 96720, USA  Nour Skaf
Subaru Telescope, National Observatory of Japan, 650 N. Aohoku Pl., Hilo, HI
96720, USA  LESIA, Observatoire de Paris, Univ. PSL, CNRS, Sorbonne Univ.,
Univ. de Paris, 5 pl. Jules Janssen, 92195 Meudon, France  Department of
Physics and Astronomy, University College London, London, United Kingdom
Peter Tuthill  Sydney Institute for Astronomy, University of Sydney, Physics
Rd., NSW 2006, Australia

###### Abstract

We describe the design and initial results from a visible-light Lyot
coronagraph for SCExAO/VAMPIRES. The coronagraph is comprised of four hard-
edged, partially transmissive focal plane masks with inner working angles of
36;55;92;129, respectively. The Lyot stop is a reflective, undersized design
with a geometric throughput of 65.7%. Our preliminary on-sky contrast is
${10}^{-2}$ at $None$ to ${10}^{-4}$ at $None$ for all mask sizes. The
coronagraph was deployed in early 2022 and is available for open use.

###### keywords:

Coronagraph, Optical, High-Contrast Imaging, Exoplanets

##  1 Introduction

In recent decades exoplanet science has advanced tremendously, with over
$5000$ confirmed planet detections[1]. These planets have predominantly been
discovered and characterized using the indirect methods of transit photometry
or radial velocity analysis[2]. High-contrast imaging, or direct imaging,
complements the phase space of exoplanet size, masses, and orbits that these
indirect methods probe and is the only way to directly observe exoplanet
spectra and orbits. To accomplish the difficult task of imaging a planet
around another star, a combination of high-performance instrumentation, like
large diameter telescopes and low-noise detectors, observational techniques,
like angular differential imaging, and post-processing algorithms must be all
be employed.

In the past decade, high-contrast instruments like SPHERE[3], GPI[4], and
SCExAO[5] have greatly advanced the field of direct imaging. These instruments
typically operate in the near-infrared (near-IR), from Y to L band, for two
reasons. First, the increased brightness of thermal emission of exoplanets in
the near-IR lowers the relative flux ratio between the star and the exoplanet
(contrast) and ultimately improves the detection sensitivity to smaller
planets. Second, in the near-IR, wavefront control with adaptive optics (AO)
is easier than in the visible. This is because the same path length error is a
smaller phase error in the near-IR than the visible, simply due to the
wavelength difference.

Despite the challenges of high-performance, diffraction-limited imaging at
shorter wavelengths, there are significant motivations for extending high-
contrast imaging into the visible. First is the detection of reflected light
from exoplanets, which is considered the most promising method of imaging
terrestrial planets[6]. Second, an important component of improving planet-
formation theory is studying the birth of exoplanets in protoplanetary disks,
which can be imaged using light reflected from small dust grains suspended in
the gas disk. Such observations of protoplanetary disks complement radio
imaging of the debris and probe smaller angles, better angular resolutions,
and different grain chemistries than near-IR reflected light imaging. Lastly,
using H$\alpha$ emission (656.28) as a tracer for accretion allows direct
imaging of matter in-flows onto forming exoplanets[7], as well as studying
matter out-flows in giant stars[8]. Some of these science cases are out of
reach of current ground-based telescopes, but it is still important to
understand the limitations of the techniques and how they can be applied to
future ground and space-based telescopes.

The Visible Aperture-Masking Polarimetric Imager/Interferometer for Resolving
Exoplanetary Signatures (VAMPIRES)[9] is an optical dual-beam imager for the
Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument on the Subaru
telescope. A schematic of SCExAO/VAMPIRES is shown in Figure 1. VAMPIRES
operates between 600800 with capabilities for polarimetric imaging[8],
H$\alpha$ imaging[10], and focal plane wavefront sensing[11, 12, 13]. VAMPIRES
also has a suite of non-redundant sparse aperture masks for sub-diffraction-
limited interferometric imaging. For this work, though, we will focus on the
traditional and polarimetric imaging modes.

Figure 1: Schematic of SCExAO and VAMPIRES. The first two levels of SCExAO are
shown in each box, with all unrelated components faded out. A dashed line
outlines VAMPIRES on the visible bench. The focal plane masks for the
coronagraph are installed on the visible bench in the field stop (red
rectangle, left) and the Lyot stop is installed in the pupil mask wheel (red
rectangle, middle).

VAMPIRES currently uses two electron-multiplying (EM) CCDs (model Andor iXon
897) for low read noise with framerates from 1100. While these detectors
perform very well in the photon-limited regime, the strong non-linearities and
compressed dynamic range from electron multiplication makes imaging bright
targets ($m_{I}<7$) difficult. To address this problem, we have designed and
deployed a classic Lyot coronagraph (CLC), which greatly attenuates the
stellar point spread function (PSF), allowing the use of high EM gain without
saturation. This is the primary motivation for building a coronagraph for
VAMPIRES- avoiding saturation is key for CCD imaging, but this limits the off-
axis signal-to-noise ratio (S/N). By attenuating the on-axis light, the off-
axis signal can be increased without saturation from the stellar PSF,
ultimately improving the S/N.

Furthermore, coronagraphy improves the detection sensitivity of circumstellar
regions by controlling the stellar diffraction pattern. In other words, the
coronagraph does not simply mask the central region of the image but rather
attenuates the effects of the stellar PSF throughout the entire field of view
(FOV). The diffraction control of a coronagraph is highly dependent on the
quality of the incoming wavefront, though, necessitating the use of AO for
high-contrast imaging. When combined with extreme AO, such as provided by
SCExAO, a coronagraph can enable detections of sources many orders of
magnitude fainter than their host stars ($\sim$${10}^{-6}$)[14].

This report details our design and deployment of a visible-light coronagraph
for VAMPIRES. In section 2 we detail our modeling and simulation of the
coronagraph and the construction of the optics. In section 3 we describe our
characterization of the coronagraph, including throughput and inner working
angle. Finally, in section 4 we discuss the performance of the coronagraph
with the calibration light source and on-sky.

##  2 Methods

###  2.1 Coronagraph Design

We used the open-source python package HCIPy[15] for simulating our
coronagraph design with Fourier optics. We defined our wavefronts on a
rasterized image of the SCExAO pupil sampled on a 256x256 pixel grid (Figure
2a). Initially, we do not introduce any wavefront errors. We used existing
pupil masks to determine the beam diameter in VAMPIRES precisely (7.03), which
corresponds to a focal ratio of F/28.4 for the coronagraph. With HCIPy, we use
a Fraunhofer propagator with this focal ratio to form the intermediate focal
plane, where the focal plane mask will be inserted. VAMPIRES has a FOV of
$None$$\times$$None$, however, for our exploratory simulations we only
calculated the first 16 airy rings, or $\sim$38 (Figure 2b). The focal plane
masks are hard-edged circles and were modeled using a circular apodizer with
either 0% or 0.1% transmission. We designed four focal plane masks with radii
of 38.6;57.9;96.5;135, respectively. These radii correspond to $2357$
$\lambda/D$ at 750, or 35.9;53.9;89.8;126. The focal plane after the mask was
propagated to the next pupil plane, where the Lyot stop apodized the
wavefront.

Figure 2: (a) The SCExAO pupil, which is slightly undersized compared to the
Subaru aperture and contains additional features. The aperture diameter is 95%
of the Subaru clear aperture; effectively 7.79. The central obstruction is 31%
of this diameter. The two additional circles are masks for inactive deformable
mirror actuators, one of which lies on a spider segment, while the other
requires an additional spider. (b) The VAMPIRES PSF simulated using HCIPy. The
four grayscale circles correspond to the coronagraph focal plane mask sizes.

The Lyot stop was modeled using a series of circular and rectangular apodizers
with 0% transmission. The stop design follows the shape of the SCExAO pupil
with an undersized diameter and oversized obstructions. The outer diameter is
90% the clear aperture diameter, the inner obstruction is 45% the clear
aperture diameter, the secondary support struts are 200% their original width,
and the bad deformable mirror actuators are 150% oversized. The ratio of areas
of the Lyot stop and the SCExAO pupil is 63.7%, and will theoretically widen
the diffraction limit by 10%. This final wavefront was propagated to the
detector focal plane, forming the post-coronagraphic point-spread function.

We repeated the above process for a series of wavelengths to approximate a
broadband PSF. We summed the images produced with 10 wavefronts from 725775 to
mimic the “750-50” filter (750 central wavelength with 50 uniform bandpass).
We chose this filter because at these wavelengths VAMPIRES has the highest
throughput and best polarimetric efficiency. As an additional step, we
generated many datasets with random tip and tilt errors sampled from a
bivariate Gaussian with 10 root-mean-square (RMS) jitter to test the
coronagraph’s resiliency to tip-tilt jitter. SCExAO typically has a higher RMS
tip-tilt error than 10, which is closer to the 90th-percentile of on-sky
performance. However, since VAMPIRES often operates in high-framerate lucky
imaging mode, the effects of tip-tilt can be partially mitigated: the apparent
movement of the focal plane mask will blur the edge, degrading sensitivity
close in, but the rest of the FOV will be sharpened.

We evaluated the performance and quality of our simulations from the raw
contrast curves of each mask as shown in Figure 3. These curves measure the
noise in concentric annuli around the PSF. Each annulus is one full-width at
half-maximum (FWHM) wide, and the noise is calculated using the biweight scale
statistic, which is robust to outliers such as cosmic rays. The noise estimate
also takes into account small-sample statistics[16], which bias the noise
measured in annuli close to the PSF. We take the radial profile of this noise
and normalize it to the non-coronagraphic PSF flux to determine the raw
contrast, where we then apply a 5$\sigma$ detection threshold. For clarity, we
describe all our contrast curves as “raw” since we never do PSF subtraction in
this work. To create these contrast curves We used the open-source package
ADI.jl[17].

Figure 3: Simulated raw 5$\sigma$ contrast curves for an unocculted PSF (black
line) and for each focal plane mask size (orange to purple lines). These
curves are calculated from images simulated with HCIPy. The mask inner working
angles are marked by vertical dotted lines

From the raw contrast curves, we found that the CLC-2 mask does not attenuate
the PSF well, especially at close angles ($<$$None$). The CLC-3 mask only
offers a factor of a few improved contrast compared to the unocculted PSF. We
found no significant performance differences between the CLC-5 and CLC-7
masks, both showing an improvement of an order of magnitude of sensitivity
throughout the FOV. The typical read noise and non-common path wavefront
errors in VAMPIRES are expected to ultimately limit our contrast. As we will
describe in subsection 2.2, the focal plane masks are diced from a single
piece of glass producing four substrates. We constructed all four mask sizes
with two variations each: one partially transmissive (0.1%) and the other
fully opaque.

###  2.2 Construction and Installation

We used a metallic vapor deposition process (https://opto-line.com/) for
applying the focal plane mask and Lyot stop patterns to our substrates. The
metals are deposited onto a glass substrate with micrometer-precision, giving
us great flexibility and precision in our design patterns and the thickness of
the material. One downside of this approach is that the glass focal plane mask
shifts the focus since it is located in a converging beam. In VAMPIRES, there
is a custom optics chassis mounted in the focal plane with 8 $\times$ 8 slots,
so we arranged for four masks to be diced from a single 30 anti-reflection
(AR) coated optical flat (Edmund Optics #84-466), making sure each segment was
within the clear aperture. The focal plane mask dots were deposited using
chromium with thicknesses of 110;300. The thickness was determined from the
optical penetration depth for the desired transmission

$\hat{s}(\lambda)=-\frac{\lambda}{4\pi\tilde{k}(\lambda)}\ln{\frac{I(\lambda)}{I_{0}(\lambda)}}$
(1)

where $\hat{s}$ is the thickness, $\lambda$ is the wavelength (tested across
the 600-800 nm range for VAMPIRES), $\tilde{k}$ is the extinction coefficient,
and $I/I_{0}$ is the relative intensity for transmitted light. The thicknesses
of 110;300 correspond to transmissions of ${10}^{-3}$ and ${10}^{-8}$,
respectively, matching our design goals of 0.1% and 0%.

The Lyot stop pattern was deposited onto a 25 AR-coated optical flat (Edmund
Optics #84-465) with no further processing. We chose a reflective gold coating
that allows easy mask alignment with VAMPIRES’ pupil camera. Following advice
from our vendor, this gold layer was deposited on top of a layer of chromium,
which adheres better to AR coatings than gold. We used Equation 1 to determine
a combined thickness of 285 for ${10}^{-8}$ transmission. The final thickness
of the chromium and gold deposit was specified as 300.

(a)

(b)

Figure 4: (a) The four focal plane masks mounted in the custom-machined focal
plane mount for VAMPIRES. The size of each slot is 8 $\times$ 8\. (b) The
undersized Lyot stop with its reflective gold coating. The diameter of the
glass substrate and stop outer diameter are marked.

##  3 Operation and Characterization

Both the focal plane masks and Lyot stop are installed in mounts with precise
motor controllers for alignment. The Lyot stop is aligned using the reflected
light in a pupil alignment camera on VAMPIRES. We found that the Lyot stop
stays consistently aligned in-between instrument cranings, meaning that no
adjustments were necessary for months. The focal plane masks take around a
minute to manually align and focus and need to be realigned for each target.

###  3.1 Artificial Calibration Speckles (“Astrogrid”)

A common problem with coronagraphic imaging is accurately determining the flux
and position of the host star while behind the focal plane mask. Even though
the focal plane masks in our coronagraph are transmissive, there is not enough
signal to precisely measure the photometry or astrometry of the star. Rather,
this transmission helps with initial alignment when the Lyot stop is removed
allowing a much higher S/N through the mask. Instead, we utilize a technique
that creates artificial PSFs throughout the FOV with known photometry and
astrometry. This technique, called “astrogrid”[18], creates “satellite spots”
by adding sinusoidal patterns to the deformable mirror (DM). These sinusoids
create two opposing copies of the PSF, where the sinusoid frequency defines
the separation and the amplitude defines the relative brightness. The sinusoid
phase is modulated in time to remove coherence between the astrogrid and the
underlying speckles. The astrogrid is applied in a cross pattern so that the
center of the star can be estimated (Figure 5). The astrogrid method has been
successfully demonstrated on SCExAO/CHARIS with astrometric precision
$\sim$1.7 and photometric precision $\sim$0.3%[19].

Figure 5: Coronagraphic images using the CLC-5 mask (92 IWA, denoted with
white circle) with 50 “astrogrid” calibration speckles. (a) A single frame of
testbed data using the internal calibration source through the 750-50 filter
with 110 EM gain, and 20 exposure length. (b) On-sky data of HIP 56083 from
May 25, 2022 in poor seeing ($\sim$$None$), using the 750-50 filter, 300 EM
gain, and 200 exposure length.

###  3.2 Coronagraphic Characterization

We characterized our coronagraph by measuring the Lyot stop throughput, focal
plane mask inner working angle (IWA), and focal plane mask transmission. The
Lyot stop throughput is proportional to the unobstructed area of the mask
compared to the pupil. From our CAD models, we estimated the throughput as
63.7% using the ratio of unobstructed areas between the Lyot stop and the
SCExAO pupil. We measured the throughput using the pupil-imaging camera with
the calibration light source, comparing the total intensity measured with a
mirror in the pupil wheel (100% of the incident light) versus the Lyot stop
(blocked light only). We calculated a geometric throughput of 65.7%, which is
close to the expected value.

To calculate the IWA we measured the coronagraphic throughput for each mask by
gradually moving the focal plane mask off-axis from the calibration source,
taking images at each step. The fluxes from all of the images were normalized
between 0 for the on-axis flux, and 1 for the maximum off-axis flux (Figure
6). We interpolated the IWA using the 50% throughput point from each curve
(36;55;92;129, respectively). These IWAs are in good agreement with the radii
of the masks, as shown in Table 1.

Lastly, we verified the transmission of the focal plane masks by taking data
without the Lyot stop inserted. By removing the Lyot stop, we no longer reject
the light blocked by the mask. We measured the total flux behind the masks and
compared that to the total flux in the same radius around the unobstructed
PSF. Our masks were designed for 0.1% transmission and the average
transmission measured with the calibration source is 0.06%.

Figure 6: Off-axis coronagraphic throughput for each focal plane mask. The flux throughput is normalized between 0 and 1. 50% throughput is marked with a black dashed line and the inner working angles are denoted by the orange to purple dotted lines. Table 1: Coronagraph parameters for all four focal plane masks. Name | Mask radius | IWA | Lyot throughput
---|---|---|---
() | () | ()
CLC-2 | 38.6 | 35.9 | 36 | 65.7%
CLC-3 | 57.9 | 53.9 | 55 | 65.7%
CLC-5 | 96.5 | 89.8 | 92 | 65.7%
CLC-7 | 135 | 126 | 129 | 65.7%

##  4 Results

###  4.1 Testbed results

Our first tests use the calibration source on SCExAO for determining the
contrast of the coronagraph for each focal plane mask. For these tests we used
the 750-50 filter with the astrogrid set to 50 amplitude and a spatial
frequency of 15.5 $\lambda/D$ (308).

First, we took non-coronagraphic data allowing us to characterize the
photometry and astrometry of the astrogrid speckles. For data reduction, we
median-combined a series of 100 images and centered the frame using the
satellite spots. For the astrogrid calibration, we used a hierarchical model
of Moffat functions with shared shape and amplitude parameters. Around each
PSF we measured the photometry using circular apertures with background
subtraction from annular apertures. The relative photometry of the 50
amplitude astrogrid was $10^{-1.52}$.

Then we inserted the focal plane mask and Lyot stop and refocused. We median-
combined a series of 100 images and centered using the satellite spots. We fit
each satellite spot using a hierarchical model of Moffat functions, again. We
measured the photometry of each satellite spot using circular apertures with
an annulus for background subtraction. The stellar flux was estimated from the
median flux of the four satellite spots scaled by the relative photometry fit
above ($10^{-1.52}$).

Lastly, we removed the focal plane mask and Lyot stop without adjusting the
source brightness or exposure settings. It was paramount that we used 0 EM
gain because our detectors saturated heavily without the coronagraph. We took
another set of 100 frames, median-combined them, and centered using the
satellite spots. All saturated pixels were masked before calculating the
contrast, which was normalized using the source flux measured in the
coronagraphic images because the satellite spots were partially saturated.

From here we created raw contrast curves the same way as in subsection 2.1,
calculating the 5$\sigma$ detection limits in concentric annuli one FWHM wide
(accounting for small-sample statistics[16]) without PSF subtraction. Because
we are not performing any kind of differential imaging, the satellite spots
heavily bias the contrast, so we mask them out during the noise calculations.
We also calculated the background noise from our dark frames and converted it
to contrast, which was $\sim$$3\text{\times}{10}^{-6}$ (5$\sigma$).

From the raw contrast curves (Figure 7), we note similar performance between
all the mask sizes. At $None$, the coronagraph achieves a raw contrast of
$\sim$ ${10}^{-3}$, and background-limited contrast beyond $\sim$$None$ of
$\sim$${10}^{-5}$. Throughout the entire FOV, the coronagraphs attenuate the
light by $0.21$ orders of magnitude. We expect the diffraction control
relative to the unocculted PSF to be consistent throughout the FOV until the
noise limit is reached, as in Figure 3. Here we see very little diffraction
control beyond $None$, suggesting residual wavefront errors are dominating the
noise.

These bench contrast curves represent an ideal observing scenario (i.e., high
S/N, no seeing), although we did not attempt to “tune up” the PSF ahead of
time to reduce the testbed wavefront errors, which limit our detection
sensitivity. The unocculted data is particularly unrealistic because we let
the detector saturate to maintain the same exposure settings as the
coronagraphic data. This is not typical for on-sky observations, and cannot be
done at all with EM gain, sacrificing the benefits of the EM process. For high
S/N observations with the coronagraph, the limiting brightness will be the
satellite spots. So, for example, with 50 astrogrid we improve our background-
limited contrast by $10^{1.52}$ compared to the same data taken without the
coronagraph with the exposure setting adjusted to avoid saturation. Without
using the astrogrid, the long-exposure limit will be reached when the speckle
halo saturates, which offers $\sim$${10}^{2}$ improved contrast, which means
VAMPIRES can observe targets $\sim$100 times brighter than its current limits.

Figure 7: Raw 5$\sigma$ contrast curves measured from 2 ($100$ frames) of
testbed data. These curves account for small-sample statistics and have no PSF
subtraction. The black curve is the non-coronagraphic contrast measured from a
saturated PSF (which has been masked out), while the orange through purple
curves correspond to each focal plane mask. The IWA for each curve is marked
with a dotted vertical line. The astrogrid speckles are also masked out.

###  4.2 On-sky results

We have not had any opportunities to use the coronagraph in good conditions
for testing; most of our on-sky tests had $>$$None$ seeing. Our best data is
from May 12, 2022, of target HIP 56083. We used a 50 amplitude astrogrid with
a separation of 15.5 $\lambda/D$, the same as our testbed data. An example
coronagraphic image is shown in Figure 5b. We used 300 EM gain with 200 ms
exposure times, median combining 100 frames for a total of 20 of integration
time. This caused significant blurring from seeing but was necessary to
achieve a high signal-to-noise ratio (S/N). In the future, we want to
investigate further the trade-off between S/N and sharpness from shorter
exposure times on coronagraphic contrast.

We constructed 5$\sigma$ contrast curves for each focal plane mask size
following the same procedure as the testbed data (Figure 8). Note for these
observations we used a tighter field of view (256$\times$256) which limits the
max separation to $None$. We used the same scaling for the satellite spot
photometry as fit from the testbed data ($10^{-1.52}$) and also masked out the
satellite spots. At $None$, all masks have a raw contrast around $10^{-2.5}$
and drop off to ${10}^{-4}$ at $None$. The on-sky contrast is around an order
of magnitude worse than the testbed data throughout the cropped
$None$$\times$$None$ FOV. We expect that under better observing conditions we
could achieve many times better contrast performance with high S/N data
aligned and stacked using lucky imaging for improved sharpness.

Figure 8: Raw 5$\sigma$ contrast curves measured from 20 ($100$ frames) of on-
sky data of HIP 56083. These data were obtained on May 12, 2022, through the
750-50 filter with 300 EM gain and 200 ms exposures. The orange through purple
curves correspond to each focal plane mask. The IWA for each curve is marked
with a dotted vertical line. The astrogrid speckles are masked out.

##  5 Conclusions

In this paper, we have described the design, construction, and deployment of a
visible-light Lyot coronagraph on SCExAO/VAMPIRES. This coronagraph attenuates
$\sim$2 orders of magnitude of light, greatly improving the dynamic range of
the EM-CCDs used on VAMPIRES with maximum EM gain. Additionally, the
diffraction control will improve high-contrast performance, which has
important applications in the optical for exoplanet science, both companion
and protoplanetary disk imaging, as well as H$\alpha$ imaging. The coronagraph
was approved for open-use observation starting in the 2022B observing
semester.

Four partially transmissive focal plane masks were installed with IWAs of
36;55;92;129, respectively. The Lyot stop has a measured throughput of 65.7%.
During operation, the coronagraph uses “astrogrid” artificial speckles for
photometric and astrometric calibration. We tested the coronagraph using the
SCExAO internal source for characterizing the IWA, Lyot stop throughput,
satellite spot relative flux, and measured contrast curves for each mask size
using 2 of median-combined data. The contrast was similar for each mask size,
spanning ${10}^{-3}$ to ${10}^{-5}$ from $None$ to $>$$None$, offering 0.2 to
1 orders of magnitude improvement over saturated non-coronagraphic images. We
found the background limit for our detectors was
$\sim$$3\text{\times}{10}^{-6}$ (5$\sigma$). We also measured the contrast for
each mask size using 20 of median-combined data of HIP 56083 in poor seeing
conditions. This data is highly limited by the seeing halo, and achieves raw
5$\sigma$ contrast of ${10}^{-2}$ to ${10}^{-4}$ from $None$ to $None$.

In the future, we want to implement various speckle control algorithms which
have been demonstrated with SCExAO for improving post-coronagraphic contrast.
The “DrWHO” focal plane wavefront sensing algorithm[20] reduces the effects of
non-common path aberrations (NCPAs) between the wavefront sensor and VAMPIRES
by altering the wavefront sensor reference for convergence of the AO loop.
DrWHO has been demonstrated on-sky[21] and coronagraphically in the near-
IR[20]. Another technique for improving post-coronagraphic contrast is spatial
linear dark field control (LDFC), which uses electric field conjugation to
“learn” the NCPAs while on a bright reference star, and then removes NCPAs
from our science target using the learned NCPAs. LDFC has been demonstrated
with the near-IR coronagraphs on SCExAO[22].

In addition to implementing advanced wavefront control algorithms, there are
hardware changes planned for the facility AO system (AO188[23]) which will
improve wavefront control on SCExAO[24]. With this improved wavefront control,
we want to explore phase-based focal plane masks such as the four-quadrant
phase mask (4QPM)[25]. Phase-based masks offer improved contrast over
amplitude-based designs like the classic Lyot style, but are highly sensitive
to pointing errors and thus require fine tip-tilt control for effective
use[26]. We are also interested in exploring apodized Lyot stops to achieve
similar or improved performance in the presence of aberrations without
sacrificing as much throughput.

##  Appendix A Code and Data Availability

The code used for simulating the coronagraph (subsection 2.1), reducing and
analyzing testbed (subsection 4.1) and on-sky data (subsection 4.2), and for
producing the figures in this paper are all available under an open-source
license in a GitHub repository (mileslucas/vampires-coronagraph). This code
makes significant use of the Julia programming language[27] along with the
open-source packages HCIPy[15], ADI.jl[17], numpy[28], and astropy[29, 30].
The CAD drawings for the focal plane masks and Lyot stops are also available
in the online repository. Data is openly available upon request to accommodate
the large data volumes. Further requests or questions about code or data are
welcomed.

###### Acknowledgements.

We wish to recognize and acknowledge the significant cultural role and
reverence that the summit of Maunakea has always had within the indigenous
Hawaiian community. We are grateful and thank the community for the privilege
to conduct observations from this mountain. We would like to thank Paul Sumner
for his useful advice during the construction of the Lyot stop and focal plane
masks. We thank Jonathan Williams, Thayne Currie, and Timothy Brandt for
generously offering observation time to use VAMPIRES for additional
characterization of the coronagraph on-sky. This research was funded by the
Heising-Simons Foundation through grant #2020-1823. N.S. and V.D. acknowledge
support from NASA (Grant #80NSSC19K0336). This work is based on data collected
at the Subaru Telescope, which is operated by the National Astronomical
Observatory of Japan. The development of SCExAO is supported by the Japan
Society for the Promotion of Science (Grant-in-Aid for Research #23340051,
#26220704, #23103002, #19H00703, #19H00695, and #21H04998), the Subaru
Telescope, the National Astronomical Observatory of Japan, the Astrobiology
Center of the National Institutes of Natural Sciences, Japan, the Mt Cuba
Foundation and the Heising-Simons Foundation.

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