1.

Introduction

Observing hydrogen lines provides fruitful opportunities to investigate mass accretion, shocks, jets, atmospheres, and other astrophysical phenomena. A variety of observations have been implemented, but previous observations basically targeted an isolated object or multi-objects that can be spatially resolved under seeing-limited conditions. An improvement in instrumentation has enabled better angular resolution than set by the seeing limit—adaptive optics (AO)¹ systems can make real-time corrections to wavefront distortions by the Earth’s atmosphere using a guide star and delivers a point spread function (PSF) close to the diffraction-limited one. In particular, AO is very important for high-contrast imaging of exoplanets or protoplanetary disks by removing stellar halo and instrumental speckles that bury such faint signals in the stellar halo. However, the AO correction at optical wavelengths was difficult in the early years of the AO instruments because the Fried parameter ($\propto {\lambda }^{6/5}$)² is so small at optical wavelengths, and hence a large number of actuators are required across the telescope aperture and fast temporal operation for wavefront sensing. Therefore, classical AO instruments were mostly applied near-infrared (NIR) wavelengths (e.g., JHKLM band), which benefit exoplanetary science because low-mass objects have less contrast with respect to their host stars in the NIR and thus high-contrast imaging at these wavelengths provides the best sensitivity.

Recently, further improvements in instrumentation have made it possible to operate AO correction at optical wavelengths [e.g., very large telescope (VLT)/multi unit spectroscopic explorer (MUSE),³ VLT/spectro-polarimetric high-contrast exoplanet research (SPHERE),⁴ Magellan AO (MagAO),⁵ and Subaru/Subaru Coronagraphic Extreme Adaptive Optics (SCExAO)⁶] and have kicked off a new era of high-contrast imaging at $\mathrm{H}\alpha$ ($\lambda =656.28\mathrm{nm}$). One of the most important subjects of $\mathrm{H}\alpha$ observation with AO is active mass accretion onto protoplanets (e.g., PDS 70 bc^7,8). Recent disk observations with ALMA or NIR polarimetric observations have shown a variety of asymmetric features within 1″ that may be related to planet formation (e.g., gap, ring, or spiral^9,10), but the number of confirmed protoplanets is still smaller than the number of predictions of potential protoplanets. Therefore, the planet formation mechanism is still controversial, and exploring for planets at such inner regions while avoiding the stellar halo with high-performance AO correction is important. The performance at optical wavelengths with current instruments highly depends on airmass. For example, the performance of MUSE/narrow-field-mode empirically decreases with airmass $\ge 1.6$ (MUSE manual¹¹). We also checked some archival MUSE data¹² and compared airmass and full width at half maximum (FWHM) in the $\mathrm{H}\alpha$ channel (see Table 1), which confirms the degradation of AO correction at high airmass. Poor AO correction leads to ineffective post-processing to remove the stellar halo and to achieve high contrast. As VLT and MagAO are located in the Southern Hemisphere, their observations of northern targets, e.g. the Taurus star-forming region, may not have sufficient sensitivity to detect $\mathrm{H}\alpha$ in the vicinity of a star.

Table 1

VLT/MUSE archival data of YSOs.

Here, we have installed a new observing mode of The Visible Aperture Masking Polarimetric Imager for Resolved Exoplanetary Structures (VAMPIRES) at Subaru Telescope,¹⁵ which is the only instrument capable of $\mathrm{H}\alpha$ imaging fed by AO in the Northern Hemisphere at the moment. In this paper, we present the current performance of high-contrast $\mathrm{H}\alpha$ observations with VAMPIRES. The effective bandwidth of $\mathrm{H}\alpha$ is narrower than the widths of broadband filters used in the optical-NIR astronomy,^16,17 and thus investigating such emissions or absorption’s requires a specified narrowband filter or spectroscopic instrument with $R\gtrsim 1000$. VAMPIRES adopts a narrowband filter and details of the specifications are described in Sec. 2. Section 3 presents our engineering observations and the results. Finally, we summarize our work and briefly mention future prospects with AO upgrades in Sec. 4.

2.

SCExAO + VAMPIRES Specifications

The VAMPIRES instrument¹⁵ is a module of the SCExAO instrument at the Subaru telescope.^6,18,19 SCExAO, installed behind Subaru’s facility adaptive optics AO188, performs a second stage of wavefront correction using a 2000-element deformable mirror and a visible pyramid wavefront sensor (PyWFS). The control loop typically corrects the wavefront at a frequency of 2000 Hz. The NIR light (0.95 to $2.4\mu \mathrm{m}$) typically goes through a coronagraph and is recorded using the integral field spectrograph CHARIS. In median seeing conditions, SCExAO provides extreme-AO performance with NIR Strehl ratios over 80%. In visible light (600 to 900 nm), the light not used by the PyWFS is sent toward the VAMPIRES module. Optical Strehl ratio’s with SCExAO depends on conditions (e.g., seeing, airmass, and brightness of a guide star) and we show examples of estimated Strehl ratios in our observations in Sec. 3.2.

VAMPIRES is capable of performing diffraction limited, polarimetric imaging at visible wavelengths (600 to 800 nm). It uses two electron-multiplying CCD (EMCCD) cameras that in normal operation each record an orthogonal polarisation, which in combination with a ferroelectric liquid crystal modulator and half-waveplate allow precise polarimetric differential imaging (PDI). The high speed of the cameras (up to $\sim 1000$ frames/s depending on subwindow size) allows lucky imaging techniques to be used to enhance resolution, and also include non-redundant masks for super-diffraction limited imaging.

With the upgrade presented here, the polarisation-splitting optics can be automatically interchanged for wavelength-splitting optics, recording simultaneous images in a narrowband centered at $\mathrm{H}\alpha$ (${\lambda }_{\mathrm{cen}}=656.3\mathrm{nm}$, $\mathrm{\Delta }\lambda =1.0\mathrm{nm}$) in one camera and an adjacent continuum bandpass (${\lambda }_{\mathrm{cen}}=647.68\mathrm{nm}$, $\mathrm{\Delta }\lambda =2.05\mathrm{nm}$) in the other. The filter information is summarized in Appendix A. The current field of view (FOV) of VAMPIRES is $\sim {3.3}^{″}\times {3.3}^{″}$. Moreover, the choice of which of these filters is positioned in front of which camera can be rapidly switched during observation, to allow non-common path errors to be mitigated by a “double-difference” approach during data reduction (see Fig. 1 and the instrument papers for details^6,15). The splitting of the light before encountering the filters is performed via a non-polarizing beamsplitter, to minimize mixing of polarization effects with spectral differential imaging (SDI; see Sec. 3)²⁰ signal.

Fig. 1

Schematic view of the entire SCExAO visible bench. The VAMPIRES instrument is highlighted by the dashed orange box.

3.

Science Verification

3.2.

Observation

SCExAO is operated under angular differential imaging (ADI) mode²⁷ by fixing the pupil, with which we can utilize a combination of SDI and the ADI technique to detect faint objects around the target star. VAMPIRES uses a beam-switcher where both filters can be converted frequently, and hence, the spectral content of the beams is switched between the two detectors. To reduce further bias, which arises from non-common path aberrations and systematic differences between the detectors, and to achieve better sensitivity, we utilize double differential imaging (DDI)²⁸ techniques for SDI reduction (see also Figs. 2 and 3 for the schematic of the post-processing). To calibrate the plate scale, we imaged astrometric binaries HD 117902 and HIP 17954 and measured plate scale to be $6.475\pm 0.09\mathrm{mas}/\mathrm{pix}$.

Fig. 2

Flowchart of data reduction from VAMPIRES data cube through final outputs. Keyword “dSDI” corresponds to double-SDI.

Fig. 3

Schematic of dSDI with VAMPIRES $\mathrm{H}\alpha$ mode. “$\mathrm{H}\alpha$,” “Cont,” and “$\epsilon$” correspond to $\mathrm{H}\alpha$, continuum flux, and bias between cam2 and cam1, respectively. In the state 1, we subtract the cam1 (continuum) image from the cam2 ($\mathrm{H}\alpha$) image, and in the state 2, we do the other way around.

We observed SAO 105500, omi Cet, and RY Tau in our engineering runs on May 22, 2019, September 8, 2019, and January 31, 2020 UT, respectively. Table 2 summarizes our observations used in this study and Table 3 summarizes the Strehl ratios of our data. We used the beginning part of these data sets for measuring them. To estimate the Strehl ratio we (1) computed the ratio between the total flux inside the core of the PSF ($2.44\lambda /D$ in diameter) and the total flux of the PSF inside a circle of $85\lambda /D$ (to reject the diffraction pattern created by the quilting mode of the deformable mirror) and (2) computed the same ratio calculated for a simulated perfect PSF using the shape and orientation of the pupil. Then, the Strehl ratio is the flux ratio of the on-sky image divided by the flux ratio of the simulated image. The Strehl ratios measured from the single exposures indicate the performance of the “fast-AO correction” with SCExAO + VAMPIRES. For comparison, we also show the Strehl ratios with the long exposure (simply cube-combined PSF without image registration). We note that at the data reduction stage, we do image registration of each slice and then conduct the post-processing technique (see Sec. 3.3), the performance of which is indicated in the last column of Table 3. For the SAO 105500 and RY Tau data, we see the same characteristics in that the top 5% PSF has the highest Strehl ratio. The single exposure of RY Tau has lower signal-to-noise ratio (SNR) because this target is faint in the optical wavelength, which may affect the background evaluation and the Strehl ratio measurement. For the omi Cet data, the long-exposure PSF has the highest Strehl ratio, but this is likely related to measurement errors of the Strehl ratio and the background: we combined 3201 slices to make the long-exposure image (and $\sim 2880$ slices to make the combined image) and the background values are much better estimated than the single-exposure images.

Table 2

Observing logs.

Target	Date (UT)	Seeing (″)a	Airmass	R mag	ttotal (s)		Remarks
					State 1	State2
SAO 105500	May 22, 2019	0.62	1.07	2.23b	256.16c	256.16c	No ADI
omi Cet	September 8, 2019	0.70	1.15	4.34d	463.96e	448.14f	Smaller FOVg
RY Tau	January 31, 2020	0.66	1.01	9.05d	2497h		State 1 only, no DDI

^aMean DIMM seeing at the summit of Mauna Kea.

^bJohnson R-band photometry.29

^c20 ms/slice × 1601  slices/cube ×  8 cubes.

^dThese targets are variable at optical wavelength and we adopt photometric data provided by Ref. 30 on the nearest date to our observations.

^e20 ms/slice × 3201 slices/cube × 7 cubes + 20 ms/slice × 791 slices/cube × 1 cube.

^f20 ms/slice × 3201 slices/cube × 7 cubes.

^g∼1.65″×1.65″.

^h1 s/slice × 101 slices/cube × 24 cubes + 1 s/slice × 73 slices/cube × 1 cube.

Table 3

Strehl ratios.

Target	Short exposurea				Long exposureb		Shift and combinedc
	teq (s)d	5% percentile	30% percentile	50% percentile	teq (s)d
SAO 105500	0.02	$\sim 44\%$	$\sim 40\%$	$\sim 35\%$	32.02	$\sim 35\%$	$\sim 39\%$
omi Cet	0.02	$\sim 41\%$	$\sim 39\%$	$\sim 37\%$	64.02	$\sim 45\%$	$\sim 44\%$
RY Tau	1	$\sim 9\%$	$\sim 8\%$	$\sim 6\%$	101	$\sim 8\%$	$\sim 9\%$

^aWe selected the single exposures whose PSFs have 5%, 30%, and 50% percentile peaks among all the single exposures using the fitted PSF information and then estimated the Strehls from these selected PSFs. This value indicates the performance of the short-exposure AO correction.

^bWe combined a data cube into an image without image registration. This value indicates the performance of the long-exposure AO correction (exposure time corresponds to the product of the single exposure time and the number of slices in the data cube, see also Table 2).

^cWe selected a set of slices in a data cube (top 90% peaks), and then shifted all the images to align the center of the PSF, and finally combined them to make the combined image. This data set is basically used for the post-processing in this study.

^dEquivalent integration time.

Figure 3 shows difference between state 1 (cam1: continuum, cam2: $\mathrm{H}\alpha$) and state 2 (cam1: $\mathrm{H}\alpha$, cam2: continuum) so that we can conduct the DDI technique to reduce the effects of the non-common path aberrations, which is explained in Sec. 3.3.1. The VAMPIRES output constitutes a data cube ($x$, $y$, and time) and exposure time/cube format information is summarized in Table 2. It is worth noting that we replaced an $\mathrm{H}\alpha$ narrowband filter before the RY Tau observation and we observed SAO 105500 and omi Cet with a different $\mathrm{H}\alpha$ filter ($\lambda =656.4\mathrm{nm}$, $\mathrm{\Delta }\lambda =2.0\mathrm{nm}$).

3.4.

Results

We present a variety of results that were reduced via SDI and ADI reduction techniques. We note that in this study, we do not analyze $\mathrm{H}\alpha$ intensities of each detection and discuss mechanisms of (possible) $\mathrm{H}\alpha$ emissions from omi Cet, omi Cet B, and RY Tau.

3.4.1.

Omi Cet

Figure 4(a) shows a single exposure raw $\mathrm{H}\alpha$ image of omi Cet. We note that omi Cet B was detected in both combined $\mathrm{H}\alpha$ and continuum images from one data cube [see Figs. 4(b) and 4(c)]. Figures 4(d) and 4(e) compare the SDI-reduced images of state 1 and 2, respectively. Figure 4(f) shows the dSDI result, and Fig. 5 plots an azimuthally-averaged radial profile of the dSDI result. There is a ring-like feature at a separation of $\sim {0.03}^{″}$. We also checked encircled energy of both combined $\mathrm{H}\alpha$ and continuum images, and $\mathrm{H}\alpha$ profile is slightly brighter than the continuum profile at $\sim {0.03}^{″}$ (see Fig. 6), though the difference is marginal compared with the $\mathrm{H}\alpha$ and continuum observations of $\eta$ Carinae.³⁵ This feature represents either of the expected astrophysical feature—limb brightening of the shock feature at $\mathrm{H}\alpha$—or the difference of PSFs at wavelengths between the $\mathrm{H}\alpha$ and the continuum filters. To further test whether our data reduction can be affected by an artifact (e.g. different AO correction), we apply the dSDI reduction to the SAO 105500 data (see Sec. 3.4.3 for the result). A scientific analysis of these resolved observations of the $\mathrm{H}\alpha$ shock region will be presented in a forthcoming paper.

Fig. 4

Flowchart of the SDI reduction for the omi Cet data. (a) Single $\mathrm{H}\alpha$ image of omi Cet (exposure time = 20 ms) before the dark subtraction. (b) Combined continuum image of omi Cet from a single data cube at state 1. The location of omi Cet B is indicated by a white arrow. (c) Combined $\mathrm{H}\alpha$ image of omi Cet from a single data cube at state 1. The companion (omi Cet B) is located east. (d) SDI-reduced image ($\mathrm{H}\alpha$-continuum) of state 1. (e) SDI-reduced image ($\mathrm{H}\alpha$-continuum) of state 2. The bias made the apparent result different from the SDI result of state 1 (d). (f) dSDI result of omi Cet. A ring feature is visible around the central star, corresponding to the expected shock arising from the stellar pulsations.

Fig. 5

Azimuthally-averaged radial profile of surface brightness around omi Cet after the dSDI reduction [see Fig. 4(f)].

Fig. 6

Comparison of the encircled energies for combined $\mathrm{H}\alpha$ [red, Fig. 4(c)] and continuum [blue, Fig. 4(b)] images. The $\mathrm{H}\alpha$ profile is brighter than that of the continuum profile at $\sim {0.03}^{″}$.

Figure 7 compares the outputs of combining ADI and dSDI reduction techniques. For ADI reduction, we adopted $\mathrm{KL}=3$ to show our outputs because we had a small number of data cubes and the larger KL number does not work properly. The smaller number of KL modes subtracts the starlight less efficiently and thus leaves a lot of residuals. Both of the reduction approaches resulted in almost the same outputs and detected omi Cet B with SNRs $>5000$, but with the ADI + dSDI reduction [Fig. 7(b)], there still remains some stellar halo at the inner working angle. The noise was estimated by calculating the standard deviation within an annular region at different separations, which is used for signal-to-noise (SN) maps and detection limits.

Fig. 7

Flowchart of combining ADI and dSDI for the omi Cet data. (a) ADI-reduced image (KL = 3) after implementing dSDI reduction (dSDI + ADI). Central star is masked by the algorithm. (b) dSDI-reduced image after implementing ADI (KL = 3) reduction (ADI + dSDI).

Figure 8 compares $5\sigma$ detection limits as a function of separation. The right vertical axis corresponds to apparent flux converted from contrast (${\mathrm{erg}/\mathrm{s}/\mathrm{cm}}^2$) assuming the $R$-band flux for omi Cet. The humps at 0.4″ to 0.5″ seen in the limits of dSDI + ADI and ADI + dSDI are affected by the existence of omi Cet B. Regarding the throughput calculation to correct flux loss by the post-processing, we assumed that a companion can be detected in only $\mathrm{H}\alpha$ wavelength and that SDI reduction does not lose the signal of $\mathrm{H}\alpha$. Therefore, we injected fake sources in the $\mathrm{H}\alpha$ images and calculated the throughputs of ADI reduction. In case, a companion is detected in both continuum and $\mathrm{H}\alpha$ filters, such as omi Cet B, it is better to use photometric results from both combined $\mathrm{H}\alpha$ and continuum images to accurately obtain $\mathrm{H}\alpha$ intensity.

Fig. 8

Comparison of $5\sigma$ contrast limits of omi Cet data with a variety of reduction methods. “dSDI + ADI” and “ADI + dSDI” correspond to running ADI reduction after dSDI reduction [Fig. 7(a)] and the reverse order [Fig. 7(b)], respectively.

3.4.2.

RY Tau

Figure 9(a) shows a single exposure raw $\mathrm{H}\alpha$ image of RY Tau. Figures 9(b) and 10(a) show SDI-reduced and ADI-reduced images of state 1. We note that RY Tau observation took only state 1, and we did not conduct the DDI reduction. Figures 10(c) and 10(e) compare the outputs of combining ADI and dSDI reduction techniques. For ADI reduction we adopted $\mathrm{KL}=5$ to show our outputs. Both of the reduction ways detected the jet with $\mathrm{SNR}\sim 4$ to 5, but its SNR is slightly higher in the SDI + ADI result [Fig. 10(c)]. Figures 10(b), 10(d), and 10(f) show cropped SN maps of Figs. 10(a), 10(c), and 10(e), respectively. Indeed a simple ADI reduction could detect the same feature to some extent as seen in the SDI + ADI image, but there is another feature that corresponds to speckles because of insufficient AO correction at optical wavelengths.

Fig. 9

Flowchart of the SDI reduction for the RY Tau data. (a) Single $\mathrm{H}\alpha$ image of RY Tau (exposure time = 1 s) before the dark subtraction. (b) SDI-reduced image of RY Tau.

Fig. 10

Flowchart of combining ADI and SDI for the RY Tau data. (a) ADI-reduced $\mathrm{H}\alpha$ image. (b) Cropped SN map of (a). (c) ADI-reduced image after implementing SDI reduction. (d) Cropped SN map of (c). (e) SDI-reduced image after implementing ADI reduction. (f) Cropped SN map of (e).

The most significant feature in our post-processed image extends $\sim {0.3}^{″}$, which is consistent with the SPHERE/ZIMPOL $\mathrm{H}\alpha$ observation.²¹ The SPHERE observation also reported a fainter and more extended $\mathrm{H}\alpha$ region extending $\sim 1^{″}$, and our SDI + ADI-reduced image marginally confirms the inner part ($\rho \sim {0.3}^{″}-{0.6}^{″}$) of this feature with $\mathrm{SNR}\sim 3$.

Figure 11 compares $5\sigma$ detection limits as a function of separation. At larger separations ($\rho \gtrsim {0.5}^{″}$) ADI reduction achieved higher contrast than the combination of ADI and SDI reduction because subtracting continuum image (camera 1) from $\mathrm{H}\alpha$ image (camera 2) leaves the bias that increases the background noise. At inner separations ($\rho \lesssim 0.3$), the detection limit of SDI + ADI looks worse than that of ADI + SDI, but this feature may be affected by higher SNR of the jet. From a point of view of contrast, the omi Cet observation (Fig. 8) achieved higher contrast than the RY Tau observation because of better wavefront sensing and AO correction, but RY Tau observation could achieve deeper detection limits in apparent flux. For future observations, the beam switching with VAMPIRES and DDI reduction will help to achieve a better contrast level than the RY Tau result. Compared with other $\mathrm{H}\alpha$ high-contrast imaging observations, SCExAO + VAMPIRES has a similar sensitivity of $\mathrm{H}\alpha$ to SPHERE/ZIMPOL,^36,37 MagAO,⁷ and MUSE⁸ and provides great opportunities for high-contrast $\mathrm{H}\alpha$ imaging in the Northern Hemisphere.

Fig. 11

Comparison of $5\sigma$ contrast limits of RY Tau data with a variety of reduction methods. “SDI + ADI” and “ADI + SDI” correspond to running ADI reduction after SDI reduction [Fig. 10(c)] and the reverse order [Fig. 10(e)], respectively.

3.4.3.

SAO 105500

For comparing the post-processing results of the other two targets, we reduced the SAO 105500 data. We note that because of small field rotation, we could not conduct the ADI reduction and we show the SDI results in this section. Figures 12(a)–12(d) show the single $\mathrm{H}\alpha$ image and the SDI-state1, SDI-state2, and dSDI results, respectively. We see the same tendency of the positive/negative counts at the central star at the SDI-reduced images in state 1/2 as the case of omi Cet [Figs. 4(d) and 4(e)]. The residual at the center probably reflects the difference of its spectrum at wavelengths of the $\mathrm{H}\alpha$-filter and the continuum-filter. Figure 13 shows an azimuthally-averaged radial profile of the surface brightness, and there is no ring-like feature as seen in the case of omi Cet [Fig. 4(f)]. Figure 14 compares difference of the encircled energies between $\mathrm{H}\alpha$ and continuum PSFs. The slight rise in the SAO 105500 profile by $\sim 0.4\%$ at 0.3″ is likely caused by the difference of AO correction at $\mathrm{H}\alpha$ and continuum wavelengths. The omi Cet profile has much greater difference by $\sim 5\%$ at 0.3″. Considering that AO correction to SAO 105500 works as effectively as to omi Cet, the difference profile at omi Cet may not only be affected by the difference of AO correction. We need to model the expected $\mathrm{H}\alpha$ shock around omi Cet to discuss in detail as mentioned in Sec. 3.4.1.

Fig. 12

Flowchart of the SDI reduction for the SAO 105500 data. (a) Single $\mathrm{H}\alpha$ image of SAO 105500 (exposure time = 20 ms) before the dark subtraction. (b) SDI-reduced image of state1. (c) SDI-reduced image of state2. The bias made the apparent result different from the SDI result of State 1 (b). (d) dSDI-reduced image of SAO 105500.

Fig. 13

Azimuthally-averaged radial profile of surface brightness around SAO 105500 after the dSDI reduction [see Fig. 12(d)].

Fig. 14

Difference of the encircled energies between $\mathrm{H}\alpha$ and continuum PSFs.

Fig. 15

Comparison of $5\sigma$ contrast limits of SAO 105500 data with a variety of reduction methods.

We also show the $5\sigma$ detection limits of the SAO 105500 data in Fig. 15. The humps at $\sim {0.8}^{″}$ are affected by diffraction patterns arising from the bright central star. These detection limits reach similar contrast levels to the omi Cet case because of almost the same AO efficiency.

Fig. 16

Transmission curves of the narrowband filters used in this study. The old $\mathrm{H}\alpha$ filter was used for the SAO 105500 and omi Cet observation, and the new $\mathrm{H}\alpha$ filter was used for the RY Tau observation. The continuum filter has not been replaced.

4.

Summary and Future Prospects

We present high-contrast $\mathrm{H}\alpha$ observations with Subaru/SCExAO + VAMPIRES. VAMPIRES adopts the beam-switching system where we can efficiently conduct SDI reduction by utilizing DDI technique. We also show the combination of ADI reduction with SDI with our engineering data sets of omi Cet and RY Tau. Our dSDI reduction could resolve a ring feature around omi Cet (corresponding to the expected shock arising from this star’s pulsations) and detect omi Cet B in both continuum and $\mathrm{H}\alpha$ filter, and SDI + ADI reduction could resolve a jet around RY Tau. We achieved $\sim {10}^{-4}$ at 0.5″ for omi Cet and $\sim 5\times {10}^{-4}$ at 0.5″ for RY Tau, respectively. Our detection limits in apparent flux are comparable to other high-contrast $\mathrm{H}\alpha$ imaging with SPHERE/ZIMPOL, MUSE, and MagAO located in the Southern Hemisphere. Our instrument will provide great opportunities of implementing high-contrast $\mathrm{H}\alpha$ explorations of northern targets.

In the next few years, AO188 will benefit from two major upgrades that will benefit SCExAO and VAMPIRES. AO188’s 188-element deformable mirror will be replaced with a $64\times 64$-element deformable mirror, which will improve significantly the wavefront correction at all wavelengths. The second upgrade is the addition of an NIR PyWFS inside AO188, which will be used to probe redder targets such as TTS.³⁸ SCExAO is also being upgraded to perform PDI at NIR wavelengths, using a fast detector similarly to VAMPIRES, and also by doing spectro-polarimetry using CHARIS. A differential imaging mode is also envisioned to include an SDI mode at the $\mathrm{Pa}\beta$ ($1.28\mu \mathrm{m}$) wavelength. In case of planet formation, for instance, theoretical models suggest that hydrogen emissions depend on several parameters such as number density of hydrogen, pre-shock velocity, extinction of the source, and filling factor of the emission³⁹ and obtaining only $\mathrm{H}\alpha$ cannot solve degeneracy between these parameters. Therefore $\mathrm{Pa}\beta$ will help to solve the degeneracies and promote detailed discussions of accretion mechanisms. Currently, a limited number of instruments enable high-contrast imaging explorations of $\mathrm{Pa}\beta$ (e.g., Keck/OH-suppressing infra-red imaging spectrograph⁴⁰) and SCExAO will be more useful instruments for hydrogen emission observations.

5.

Appendix A: Filter Information

Figure 16 summarizes the narrow-band filters we used in this study. The $\mathrm{H}\alpha$ filter was replaced in January 2020. For high-contrast $\mathrm{H}\alpha$ imaging with VAMPIRES, we designed the bandpass of the filter to be able to transmit sufficient signal in light of various broadening effects. For example, the maximum accretion velocity of a Jupiter mass planet is $\sim 60\mathrm{km}/\mathrm{s}$. To account for an object larger than a Jovian planet, we adopted a velocity of $\pm 100\mathrm{km}/\mathrm{s}$. In addition, the radial velocity (RV) motion of a planet around such a star is $\lesssim 10\mathrm{km}/\mathrm{s}$, and the RV motion of the star from the observer is $\lesssim 50\mathrm{km}/\mathrm{s}$. Therefore, we set a budget of 200 km/s, which corresponds to a 0.8-nm wavelength range at 600 nm, which should cover all the astrophysical features one may like to study.

We found an off-the-shelf filter from Chroma that had specifications very close to our requirements (3-nm bandwidth; see also the manuscript webpage at Chroma⁴¹) and requested it be modified to have an FWHM bandwidth of 2 nm instead. This is still larger than the 0.8 nm needed and was chosen because of the uncertainty the manufacturer offered in the center wavelength of the filter and our ability to align it with respect to the beam. This filter was purchased and installed. However, the VLT/MUSE observation to study accretion from PDS 70 bc revealed that the effective width of $\mathrm{H}\alpha$ is $\sim 100$ to $120\mathrm{km}/\mathrm{s}$.^8,42 We found that detecting such a signal with the 2-nm bandwidth filter will require higher contrast, enough to detect the accreting planet. Therefore, we decided to replace the previous $\mathrm{H}\alpha$ filter with a new filter (1-nm bandwidth) in January 2020. This bandwidth is the minimum acceptable value for the $\mathrm{H}\alpha$ imaging with our assumptions. Out of band, the optical density (OD) of the new $\mathrm{H}\alpha$ filter is larger than 4 (OD4 means that the out-of-band suppression is 0.01%) across 400 to 1200 nm, which covers the entire bandpass of the EMCCD. Similarly, the suppression of the old $\mathrm{H}\alpha$ and continuum filters was better than OD5 (the out-of-band suppression is 0.001%) from 400 to 1000 nm. The detailed information for the new $\mathrm{H}\alpha$ filter is shown at Alluxa.⁴³