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Precise Radial Velocities of Cool Low Mass Stars With iSHELL

T0 review · 4 major / 6 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read A K-band spectrograph with a methane-isotopologue gas cell and a 48-parameter forward model achieves 3–5 m/s radial velocities on cool K and M dwarfs, enough to confirm TESS planet candidates with semi-amplitudes above about 3 m/s.

desk verdict First iSHELL K-band RV precision paper: solid pipeline work, honest limitations, but the m/s claims are internal scatter and need an external check before I'd trust them for TESS follow-up. read the letter →

arxiv 1908.07560 v1 pith:3EWCGETH submitted 2019-08-20 astro-ph.IM astro-ph.EPastro-ph.SR

Bryson Cale , Peter Plavchan , Danny LeBrun , Jonathan Gagné , Peter Gao , Angelle Tanner , Charles Beichman , Sharon Xeusong-Wang
show 6 more authors
Eric Gaidos Johanna Teske David Ciardi Gautam Vasisht Stephen R. Kane Kaspar von Braun
This is my paper · ORCID
classification astro-ph.IMastro-ph.EPastro-ph.SR
keywords radialvelocitiesMdwarfsK-bandspectroscopyiSHELLspectrographgascellcalibrationforwardmodelingstellartemplateexoplanetconfirmation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper claims that radial velocities of cool low-mass stars can be measured to 5 meters per second over a year and 3 meters per second over a month using K-band spectra from the iSHELL spectrograph, with a methane-isotopologue gas cell providing the wavelength reference. The central advance is that the stellar reference spectrum is not taken from atmosphere models; it is built from the target observations themselves by iteratively co-adding barycenter-shifted residuals into a template. On three stars previously known to be stable in radial velocity, the method reports best-case long-term RMS values of 4.3 m/s for Barnard's Star, 2.7 m/s for GJ 15 A, and 3.8 m/s for 61 Cygni A. If the precision holds, the same instrument can confirm and weigh planet candidates from the TESS transit survey around bright K and M dwarfs, and can search for planets around moderately active and young cool stars where visible-wavelength velocities are corrupted by spots.

What carries the argument

The load-bearing mechanism is the iterative stellar template retrieval: starting from a flat guess, the pipeline forward-models each spectrum, subtracts the model, shifts the residuals into the star's barycentric rest frame, median-combines them with inverse-RMS-squared weights, and adds the result back into the template; after 5–40 iterations the extracted velocities stabilize and the template approaches the deconvolved stellar spectrum. Two calibration devices carry the precision: the methane isotopologue ($^{13}$CH$_4$) gas cell, whose FTS-measured transmission provides a common optical-path wavelength reference and constrains the line-spread function, and explicit Fabry-Perot models for the two fringing sources, the order-selection filter and the anti-reflection coating of the silicon immersion grating. The 48-parameter model is optimized with a custom Nelder-Mead solver that alternates full simplex calls with two-dimensional subspace calls, because standard simplex optimization did not converge in this parameter space.

What would settle it

Inject a known synthetic Doppler shift, for example 10 m/s, into one night's raw spectra before running the pipeline; if the recovered shift differs from the injected value by more than the quoted nightly uncertainty, the stellar template has absorbed correlated noise rather than the true stellar spectrum.

Watch

Extended reading notes

Core claim

On its own terms, the paper demonstrates that a 48-parameter forward model can reproduce K-band (2.18–2.47 µm) spectra of cool dwarfs well enough to extract relative radial velocities at the few-m/s level on baselines from one month to one year. The model accounts for the Doppler-shifted stellar spectrum, the methane gas cell transmission, Doppler-shifted telluric water, methane, nitrous oxide, and carbon dioxide, the residual blaze function, a quadratic-plus-spline wavelength solution, the spectrograph line-spread function, and two separate quasi-sinusoidal fringing patterns from the order-selection filter and the immersion-grating anti-reflection coating. The stellar template is derived iteratively: beginning from a flat guess, the pipeline forward-models every spectrum, shifts the residuals into the star's barycentric rest frame, median-combines them with $\mathrm{RMS}^{-2}$ weighting, and adds the result back into the template, repeating for 41 iterations. The quoted best-case multi-order long-term RMS values are 4.3 m/s for Barnard's Star (high-SNR orders), 5.13 m/s using all Barnard data, 2.72 m/s for GJ 15 A, and 3.77 m/s for 61 Cygni A.

Load-bearing premise

The method assumes the template built from the star's own spectra converges to the true stellar spectrum, rather than gradually soaking up fringing, telluric, or bad-pixel artifacts that would make the measured velocities look more precise than they really are.

Editorial extensions

If this is right

  • Planet candidates from the TESS transit survey that orbit K and M dwarfs brighter than K magnitude 9 and have velocity semi-amplitudes above roughly 3 m/s can be confirmed and their masses measured; the paper estimates on the order of 100 such candidates are amenable to iSHELL follow-up.
  • Near-infrared activity jitter should be reduced relative to the optical by roughly the frequency ratio, so a star with 5 m/s optical activity would show less than about 1.5 m/s in the K band, opening searches around moderately active and young cool stars.
  • Because the stellar template is empirical and built from the target itself, the method avoids relying on synthetic stellar atmosphere models, which are known to be deficient for late M dwarfs with complex molecular opacities.
  • Combining at least eight echelle orders should deliver long-term precision of 5–7 m/s for typical K and M dwarfs with sufficient RV content, because single-order precision improves as $N^{-1/2}$ with the number of orders.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The same iterative-template scheme could in principle be run on archival iSHELL K-band data, producing long-baseline RV time series for a much larger sample without any new observations.
  • The paper's finding that telluric optical depths are consistent across orders suggests that a future joint fit over all orders, sharing telluric and fringing parameters, could shrink the 48-parameter freedom and push precision below the current 3–5 m/s floor.
  • Since the template is built from barycenter-shifted residuals, a testable requirement is that each target be observed at enough epochs spread over the year; one could derive a minimum-epoch criterion from the convergence behavior, something the paper does not quantify.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 6 minor

Summary. This manuscript describes a new data-analysis pipeline for extracting radial velocities from K-band (2.18-2.47 μm) spectra taken with iSHELL at the IRTF. The pipeline forward-models each echelle order with 48 parameters: a 13CH4 gas-cell transmission, four telluric absorbers, two fringing sources (OS filter and AR coating), a residual blaze, a Hermite-polynomial LSF, a wavelength solution with spline corrections, and an iteratively retrieved stellar template. RVs are combined across orders using weighted statistics or a TFA-like detrending minimization. Applying the pipeline to Barnard's Star, GJ 15 A, and 61 Cygni A, the authors report best-case long-term RV RMS values of 4.3, 2.7, and 3.8 m/s, respectively, after selecting a subset of orders by a powerset search and, for 61 Cyg A, discarding one night with a +1 km/s outlier. The paper claims 5 m/s precision over one-year baselines for two stars and 3 m/s over one month for GJ 15 A, and argues that this enables TESS planet confirmation around K and M dwarfs.

Significance. The manuscript's contribution, if the claimed precision is externally validated, is significant: it would make iSHELL one of the few instruments delivering few-m/s RVs in the K band using a Cassegrain-mounted spectrograph and a methane isotopologue gas cell, with public data. The forward-model architecture is detailed, and the inclusion of multiple fringing sources and iterative template retrieval is technically ambitious. The paper also makes honest statements about its limitations, including template corruption, uncharacterized telluric error, and order-selection freedom. The main weakness is that the headline numbers are internal, best-case metrics rather than predictive, externally anchored benchmarks: the stellar template is derived from the same spectra, the order subset is chosen post hoc, and no known planetary signal is recovered. Consequently, the paper currently demonstrates internal consistency and a plausible precision floor, but not that real RV signals at the few-m/s level survive the pipeline. If the recommended external-validation tests are added, this would be a valuable instrument-paper for TESS follow-up.

major comments (4)
  1. [Section 5.1, Table 5, Fig. 8] The headline precision values are minima of a powerset search over order combinations. For Barnard's Star (high SNR), the reported 4.33 m/s is the minimum of 4083 combinations; for GJ 15 A, 2.72 m/s comes from only three orders (8, 9, 10) and six nights; for 61 Cyg A, 3.77 m/s comes from five orders. A minimum over a large set is an optimistically biased statistic and is not a prediction of the precision obtained when the order set is fixed in advance. The authors partially acknowledge this at the end of Section 5.2 ('when observing stars with unknown RVs, we do not have this freedom'), but the Abstract and Section 5.1 still present the best-case values as the demonstrated precision. Additionally, the best single-order precisions in Table 4 are quoted at order-dependent 'best iteration' values, and it is unclear whether the multi-order subsets use different iterations per order, which adds further post-hoc freedom. I recommend reporting the full distribution of σ over the powerset or quoting a pre-specified fixed-order precision (e.g., the 5-7 m/s for at least 8 orders mentioned in Section 5.2) as the primary claim.
  2. [Section 4.3, Eq. (1), Table 5] The stellar template is constructed iteratively from the same target spectra, and the authors themselves state that 'residual correlated noise can gradually get repeatedly added into the stellar template from missed bad pixels, or from non-stellar spectral features that are not well fit.' This creates a circularity for the precision claim: low scatter of RVs relative to a template that may have absorbed some of the correlated signal does not prove that real, time-variable stellar velocities are preserved. The seasonal template comparison in Section 6 checks consistency of deep stellar lines, but it does not test whether signals at the few-m/s level survive. Because GJ 15 A is listed in Table 1 as hosting a planet with K=2.9 m/s and P=11.44 d, the paper should attempt to recover this known signal (e.g., by fitting the six nights to the published ephemeris or showing an RV periodogram) as an external validation. Barnard's Star's 233-day, 1.2 m/s signal is smaller but could also be checked. Without such a test, the m/s claim remains an internal precision metric rather than a demonstrated capability to detect or confirm planets.
  3. [Section 2 and Section 5.2] Telluric error is explicitly uncharacterized. The text states 'we do not characterize this' regarding water vapor variability and, in Section 5.2, 'Determining telluric induced error on RVs is the subject of a future investigation.' The K-band orders contain deep, variable water and methane lines; the forward model has four telluric species with a shared velocity shift; and order 14 is flagged as an outlier for all three targets, suggesting a telluric or gas-cell template problem. Since telluric absorption is a major potential contributor to the m/s error budget, the paper needs at least an upper-limit estimate, for example comparing RVs from orders with high versus low telluric absorption or injecting synthetic telluric variations. Until then, the claim that the achieved precision is below the telluric noise floor is unsupported.
  4. [Section 5.1, Table 5 (61 Cyg A)] The night JD 263.01044249 with RV = 1403 m/s is discarded on the assumption that it is an observational error or a flare, with no independent evidence. This exclusion is load-bearing for the '3.8 m/s for 61 Cyg A' claim. The paper should state the RMS with and without this night and ideally investigate the cause (e.g., checking target acquisition, flat fields, or telluric residuals). Also, the phrase 'over one year timescales' for 61 Cyg A is based on 10 nights spanning about 254 days after the exclusion; the effective baseline and number of epochs should be stated explicitly.
minor comments (6)
  1. [Table 3] Row 10 labels the 'OS Filter Fringing Finesse' as 'FAR' but the symbol for the OS fringing finesse should be 'FOS' to match Eq. (5); 'FAR' is already used for the AR fringing finesse in row 15.
  2. [Section 4.3] The first paragraph contains the duplicated phrase 'which can which can'; this should be corrected.
  3. [Section 5.2, Eq. (17)] The reduced chi-squared values of 0.5-0.8 in Table 5 are computed using uncertainties that themselves come from the forward model; a sentence clarifying that these values do not independently validate the error bars would prevent over-interpretation.
  4. [Section 6] The comparison of the two seasonal templates is qualitative only; reporting a quantitative metric (e.g., RMS difference over pixels with line depth >2%) would make the assessment more reproducible.
  5. [Figure 8] The caption should explicitly state that the yellow histogram includes combinations of 2-12 orders while the green histogram is restricted to 10-12 orders; the current caption relies on the main text for this information.
  6. [Reproducibility] The core pipeline PySHELL is listed as 'Available upon request' rather than deposited in a public repository; making it available publicly, as was done for the reduction code, would strengthen the reproducibility of the results.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation: the m/s claim is an in-sample self-calibration statistic, with overfitting and template-fidelity risks but no input-output identity.

full rationale

The paper's headline precision is the scatter of nightly RVs measured against a stellar template that is itself retrieved from the same observations (Sec. 4.3: 'we choose to rely on the target observations themselves to extract the stellar spectrum using an iterative deconvolution method'). This is a self-calibration, not a circular reduction: the forward model minimizes per-spectrum RMS residuals, not the long-term RV RMS, and the template does not by construction force the nightly scatter to zero. Per-order means are subtracted before combining (Eqs. 11-12), so only the constant zero-point is removed, which is standard for relative RVs. The powerset order selection in Sec. 5.1 ('looking at all possible values of sigma_RV from the powerset') is an in-sample best-case choice; the paper explicitly labels it 'best case' and separately quotes 5-7 m/s for configurations with at least 8 orders, so the best value is not being renamed as an out-of-sample prediction. The seasonal template comparison in Sec. 6 and the photon-noise estimates provide independent checks of internal consistency, even though they do not prove that real time-variable signals survive at the m/s level. The deferred derivation of the AR fringing model (Eq. 7, 'Cale et al. in prep') is an omitted proof, not a circular step. No load-bearing argument reduces to a self-citation, and no equation in the paper is identical to its input by construction. Residual concerns about template absorption of correlated noise and order-selection optimism are correctness and external-validation issues, not circularity.

Assumptions & free parameters 9 free parameters · 6 assumptions · 0 invented entities

The central claim is a measured precision, so the ledger is dominated by fitted model parameters and data-selection choices. The 48-parameter forward model, the iteratively retrieved stellar template, the powerset order selection, and the discarded outlier all affect the reported numbers. The most consequential assumptions are that the telluric and gas-cell templates are correct, that the fringing models capture the real instrument behavior, and that the self-built stellar template does not absorb systematic noise.

free parameters (9)
  • Per-spectrum stellar Doppler shift v_star = unbounded, output RVs
    Central output; fitted for every spectrum. Reported precision is the scatter of these fitted values, not an externally anchored quantity.
  • Multi-order subset selection (powerset) = e.g., orders 7-9, 11, 13 for Barnard's Star high-SNR run
    The 'best' precision is the minimum over all order combinations (Section 5.1), so the reported number is partly selected to minimize scatter.
  • Telluric optical depths (H2O, CH4, N2O, CO2) = bounds: 0.02-4.0, 0.1-3.0, 0.05-3.0, 0.05-3.0
    Fitted per spectrum and order; water depth correlates with wavelength solution points (Section 7.2), so telluric parameters can trade against wavelength zero points.
  • OS and AR fringing parameters (amplitudes, cavity scales, phase, finesse) = bounds in Table 3
    Fitted per order; nightly-consistent but poorly constrained across orders (Section 7.1), indicating model degeneracy.
  • LSF width a0 and 6 Hermite coefficients = a0 bounds 5.5-12, aj +/-0.4
    LSF width is degenerate with even Hermite terms (Section 7.2), so the instrument profile is not uniquely determined.
  • Wavelength solution Lagrange points and 7 spline points = 3 quadratic points +/-0.05 nm, 7 splines +/-0.0125 nm
    Spline corrections are included because they improve RVs, but the optimal number of splines varies by order (Section 8.1).
  • Blaze function quadratic terms and 14 spline corrections = b0 0.98-1.08, splines +/-0.135
    Fitted per order; residual blaze is not analytically modeled and spline parameters are correlated with neighboring points.
  • Stellar template (iteratively retrieved function) = not a scalar; derived from target spectra
    The template is a free function built from the same data whose RVs are measured; correlated noise can enter it (Section 4.3).
  • TFA per-night and per-order offsets RV'_i and RV'_m = bounds +/-50 and +/-5 m/s
    Detrending solves for zero-point offsets that can absorb real common-mode signals; the paper reports agreement with weighted statistics but does not validate against an external ephemeris.
assumptions (6)
  • domain assumption Telluric templates from TAPAS with Maunakea T/P profile for April 12, 2018, 'arbitrarily chosen', are accurate for all epochs
    Section 4.2 states the date is arbitrarily chosen; variable water content is not characterized (Section 2), and order 15 requires systematically higher water depth, indicating template error.
  • domain assumption The 13CH4 gas cell FTS spectrum and optical depth tau_g=0.97 accurately represent the cell in the spectrograph beam
    Section 4.2: tau_g is set to 0.97 because of an off-axis angle in the FTS; order 14 appears to have an error in the gas cell or telluric template (Section 5.2).
  • domain assumption Iterative stellar template retrieval converges to the true unconvolved stellar spectrum
    Section 4.3 states in the limit the template approaches the unconvolved spectrum, but also warns correlated noise can be added; no minimum epoch count is established (Section 6).
  • ad hoc to paper The 61 Cygni A +1 km/s night is an observational error or flare and can be discarded
    Section 5.1: the outlier survived code modifications, is suspected to be observing the B component or a flare, and is excluded from long-term calculations.
  • domain assumption The two fringing models (OS and AR) capture all significant quasi-sinusoidal fringing
    Section 4.2.1 introduces both models; the AR model derivation is deferred to Cale et al. (in prep), and unmodeled pre-diffraction AR fringing is noted as absent without quantitative upper limit.
  • domain assumption Barycentric correction using exposure midpoint is adequate despite lack of exposure meter
    Section 2: error scales with square of exposure time; no correction for non-constant photon rate is applied.

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Cite this review

Pith. "Pith review of Precise Radial Velocities of Cool Low Mass Stars With iSHELL." pith.science (2026). https://pith.science/paper/3EWCGETH

@misc{pith2026190807560,
  author       = {Pith},
  title        = {Pith review of: Precise Radial Velocities of Cool Low Mass Stars With iSHELL},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/3EWCGETH}},
  note         = {Machine review of arXiv:1908.07560}
}
read the original abstract

The coolest dwarf stars are intrinsically faint at visible wavelengths and exhibit rotationally modulated stellar activity from spots and plages. It is advantageous to observe these stars at near infrared (NIR) wavelengths (1-2.5 microns) where they emit the bulk of their bolometric luminosity and are most quiescent. In this work we describe our methodology and results in obtaining precise radial velocity (RV) measurements of low mass stars using K-band spectra taken with the R~80,000 iSHELL spectrograph and the NASA Infrared Telescope Facility (IRTF) using a methane isotopologue gas cell in the calibration unit. Our novel analysis pipeline extracts RVs by minimizing the RMS of the residuals between the observed spectrum and a forward model. The model accounts for the gas cell, tellurics, blaze function, multiple sources of quasi-sinusoidal fringing, and line spread function of the spectrograph (LSF). The stellar template is derived iteratively using the target observations themselves through averaging barycenter-shifted residuals. We have demonstrated 5 ms^-1 precision over one year timescales for the M4 dwarf Barnard's Star and K dwarf 61 Cygni A, and 3 ms^-1 over a month for the M2 dwarf GJ 15 A. This work demonstrates the potential for iSHELL to determine dynamical masses for candidate exoplanets discovered with the NASA TESS mission, and to search for exoplanets orbiting moderately active and/or young K and M dwarfs.

Figures

Figures reproduced from arXiv: 1908.07560 by the authors.

Figure 1
Figure 1. A sub-frame of an unprocessed multi-order spectral image of 61 Cygni A from Oct 16. The full frame contains 29 orders with dimensions 2048 x 2048. Numerous “hot” pixels appearing on the stellar trace as dark values, and between traces as bright values, are flagged during data reduction, but can be missed if the SNR is not sufficient to properly identify them as outliers. 2 Available at https://github.com/jgagneastro… view at source ↗
Figure 2
Figure 2. Top Left: A sub-frame of a raw flat-field image. Top Right: The same image and region as the top left but with a high resolution color scaling (narrow range in counts) centered around the fringing signal. Bottom Left: The fringing present in the flat-fields isolated through a rolling median with a window comparable to the dominant period in wavelength of ∆λ ∼ 0.3nm. iSHELL fringing is further discussed in Section 4.… view at source ↗
Figure 3
Figure 3. A reduced spectrum as a function of pixels (blue to red in wavelength) for 61 Cygni A from Oct. 16, 2016 for order 28 (m = 239, λ = 2.18 − 2.194 µm). The optimally (weighted) extracted spectrum used in RV calculations is shown in black, and the unweighted is shown in red. Inversely weighing pixels by their distance from the center of the trace mitigates sky noise resulting in fewer outliers and an overall smoother s… view at source ↗
Figures from the paper (28 more)
Figure 4
Figure 4. Figure 4: A reduced spectrum for 61 Cygni A from Oct. 16, 2016 for order 16 (m = 227). The wavelength grid was generated with the initial guess parameters to the RV pipeline (see Section 4). The unmodified input templates for the methane gas cell, telluric water, & telluric meth…
Figure 5
Figure 5. Figure 5: A diagram of the silicon immersion grating. A single echelle order spans from λmin to λmax. After the incident beam (along the the blaze wavelength λB) is diffracted at grating, the light is spatially separated and travels through the AR coating with different path len…
Figure 6
Figure 6. Figure 6: A schematic of the RV pipeline. The proposed parameters for the first iteration are given in [PITH_FULL_IMAGE:figures/full_fig_p017_6.png]
Figure 7
Figure 7. Figure 7: Top: An example fit to a spectrum of Barnard’s Star from July 29, 2017, for order 6 (m = 217) from iteration 41 (last) from the high SNR run. The data is in blue and the model in red. The deep and wide absorption lines with near zero transmission correspond to water in…
Figure 8
Figure 8. Figure 8: Left: The orange circles correspond to the average long-term RV RMS obtained for all possible combinations of N orders. The trend is obtained by fitting a function AN −1/2 Ord where A is a constant parameter. On average our multi-order velocities are consistent with av…
Figure 9
Figure 9. Figure 9: The best case multi-order RV combination that yielded the lowest RMS for Barnard’s Star from the high SNR run. The unweighted standard deviation is 4.33 ms−1 . JD0 corresponds to the first nightly JD for each target given in [PITH_FULL_IMAGE:figures/full_fig_p023_9.png]
Figure 10
Figure 10. Figure 10: The best case multi-order RV combination that yielded the lowest RMS for Barnard’s Star for the full dataset. The unweighted standard deviation is 5.13 ms−1 for the optimized set. The weighted statistics formulation (Section 4.5) agrees well with the optimized RVs (Se…
Figure 11
Figure 11. Figure 11: The best case multi-order RV combination that yielded the lowest RMS for GJ 15 A. The unweighted standard deviation is 2.72 ms−1 [PITH_FULL_IMAGE:figures/full_fig_p024_11.png]
Figure 12
Figure 12. Figure 12: The best case multi-order RV combination that yielded the lowest RMS for 61 Cyg A. The unweighted standard deviation is 3.77 ms−1 . The last data point is not shown [PITH_FULL_IMAGE:figures/full_fig_p024_12.png]
Figure 13
Figure 13. Figure 13: The nightly Barnard’s Star RV uncertainties for each order (markers), averaged over nights, alongside the estimated photon noise limit (solid line). Nights from the full data set are in red, and the high SNR run are shown in orange. The lower SNR data (last 4 nights) …
Figure 14
Figure 14. Figure 14: Same as [PITH_FULL_IMAGE:figures/full_fig_p026_14.png]
Figure 15
Figure 15. Figure 15: Same as [PITH_FULL_IMAGE:figures/full_fig_p027_15.png]
Figure 16
Figure 16. Figure 16: The corresponding values of χ 2 red from all possible combinations of multi-order RVs. Points are colored according to the number of orders used for that combination, showing the expected improvement in RV precision by using increasing numbers of orders. For our optim…
Figure 17
Figure 17. Figure 17: The generation of the stellar template for Barnard’s Star for order 16 (m = 227) for the high SNR run. Stellar features continue to get added to the template through early iterations, but a noisy continuum develops at later iterations, although RVs continue to improve…
Figure 18
Figure 18. Figure 18: Same as [PITH_FULL_IMAGE:figures/full_fig_p030_18.png]
Figure 19
Figure 19. Figure 19: The generation of the stellar template for GJ 15 A for order 26 (m=237). The stellar RV information is less shortward the CO bandhead (< 2.29 µm), but there are still broad lines from other molecules that can provide nightly RV precisions of 10–20 ms−1 (see [PITH_FUL…
Figure 20
Figure 20. Figure 20: The generation of the stellar template for 61 Cyg A for order 16. K dwarfs also exhibit a strong CO bandhead past 2.29 µm [PITH_FULL_IMAGE:figures/full_fig_p032_20.png]
Figure 21
Figure 21. Figure 21: Two separately retrieved stellar templates for Barnard’s Star (fall 2016, spring-summer 2017) [PITH_FULL_IMAGE:figures/full_fig_p033_21.png]
Figure 22
Figure 22. Figure 22: An absorption vs. absorption plot for two separately retrieved stellar templates for Barnard’s Star (fall 2016, spring-summer 2017). Only features deeper than 2% in both templates are shown. A one-to-one line corresponding to perfect agreement between the separately r…
Figure 23
Figure 23. Figure 23: Left: The water optical depth for multiple orders from the high SNR run. Right: Same, but for telluric methane. Only every other observation is plotted. The water and methane depths are also unique supporting our hypothesis of variable atmospheric content [PITH_FULL_…
Figure 24
Figure 24. Figure 24: Left: Same as [PITH_FULL_IMAGE:figures/full_fig_p035_24.png]
Figure 25
Figure 25. Figure 25: A correlation plot for all forward model parameters from order 8 (CO2 and N2O are not considered here). Parameters are in the same order as given in [PITH_FULL_IMAGE:figures/full_fig_p036_25.png]
Figure 26
Figure 26. Figure 26: A series of correlation plots for orders 8, 13, & 15 (from left to right) highlighting strongly correlated parameters. Parameter symbols are defined in [PITH_FULL_IMAGE:figures/full_fig_p037_26.png]
Figure 27
Figure 27. Figure 27: A correlation plot for the single-order nightly RVs from the Barnard’s star high SNR run. Each block is colored according to the value of the Pearson Correlation Coefficient. Neighboring orders (near the diagonal) are typically more correlated than orders further away…
Figure 28
Figure 28. Figure 28: The obtained RV precision for Barnard’s Star using different spline implementations for the wavelength solution for orders 7, 8, & 10 using the high SNR data set. Most orders show improvement when using splines, but the number of splines is inconsistent and can in som…
Figure 29
Figure 29. Figure 29: Same as [PITH_FULL_IMAGE:figures/full_fig_p040_29.png]
Figure 30
Figure 30. Figure 30: The average spline correction that gets added to a quadratic in the wavelength solution for all three runs (using the full data set for Barnard’s Star). The average correction is approximately the same for all orders and targets, strengthening the case for including t…
Figure 31
Figure 31. Figure 31: The LSF width across the detector for the cropped portion of the data (spectral pixels 200-1848). This data set is an average of the high SNR Barnard’s Star observations (61 spectra) and 6 echelle orders high in gas cell RV content (Eq. 16). A higher order LSF model m…

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Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.