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arxiv: 2605.06648 · v1 · submitted 2026-05-07 · 🌌 astro-ph.IM · astro-ph.EP

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A preliminary exploration of the effects of baseline length for the LIFE space mission

Jonah T. Hansen , Thomas Birbacher , Felix A. Dannert , Philipp Huber , Andrea Fortier , Adrian M. Glauser , Jens Kammerer , Romain Laugier
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Lia Sartori Sascha P. Quanz
Authors on Pith no claims yet

Pith reviewed 2026-05-08 04:51 UTC · model grok-4.3

classification 🌌 astro-ph.IM astro-ph.EP
keywords nulling interferometryexoplanetsspace missionbaseline lengthhabitable planetsinterferometryplanet yieldLIFE mission
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The pith

The LIFE space mission can achieve comparable habitable exoplanet yields using shorter nulling baselines of 25-80 meters or discrete sets.

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

The paper examines if the LIFE mission needs the full 10-100 meter range of nulling baselines assumed in earlier studies or if a reduced range is viable. Updated planet occurrence statistics and the LIFEsim simulator are used to quantify impacts on planet detection and fringe tracking. Results show that a 25-80 meter range or even discrete baselines incur less than 10% performance loss. This matters for mission design as shorter baselines could ease the challenges of maintaining precise spacecraft formations in space. The study also proposes a new method for selecting the best baselines tailored to each target star.

Core claim

Utilizing the LIFEsim simulator along with revised mathematical tools and updated planet occurrence rates, the analysis shows that LIFE could utilize a considerably shorter range of baselines, such as 25-80 m, or even discrete baselines without much (<10%) loss of performance in planet yield and fringe tracking, while also determining a new astrophysically motivated technique for choosing optimal baselines for a given science target.

What carries the argument

The LIFEsim mission simulator, which models interferometric performance, paired with a new astrophysically motivated technique for selecting optimal nulling baselines based on the science target.

If this is right

  • Careful trade-offs between performance and implementation simplification must be considered for the mission.
  • Planet yield and fringe tracking performance remain largely unaffected by the reduced baseline range.
  • Any required spectral weighting by scientific goals may influence the optimal baseline choices.
  • Some loss of target-specific baseline optimization could occur with a fixed shorter range.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar re-evaluations of baseline requirements could benefit other proposed space interferometry concepts.
  • The target-specific selection method might improve efficiency in ground-based nulling interferometers.
  • Reducing baseline complexity may allow for more flexible mission architectures or lower operational risks.

Load-bearing premise

The LIFEsim simulator and the revised planet occurrence statistics accurately represent real mission performance and exoplanet demographics.

What would settle it

A comparison of the simulated planet yields using the proposed shorter baselines against yields from actual future observations of habitable zone exoplanets would test the <10% loss claim.

Figures

Figures reproduced from arXiv: 2605.06648 by Adrian M. Glauser, Andrea Fortier, Felix A. Dannert, Jens Kammerer, Jonah T. Hansen, Lia Sartori, Philipp Huber, Romain Laugier, Sascha P. Quanz, Thomas Birbacher.

Figure 1
Figure 1. Figure 1: LIFEsim yield/mission time simulations for a range of baseline limits. The parameters for the simulation are detailed in the text, primarily section 4. The columns denote the three stellar samples in decreasing order of scientific priority. Top row: the raw yields for each baseline limit, given in planets detected. Middle row: the total amount of search time needed to find the nominal planet sample for eac… view at source ↗
Figure 2
Figure 2. Figure 2: The percentage of extra search time needed to fulfil the targets of all three stellar populations (50, 25 and 20 planets for stellar types F0-K5, K6-M3 and M4-M9 respectively) for a range of maximum and minimum baselines compared to the reference 10-100 m case. 5 10 15 20 25 30 35 40 Distance (pc) 3000 4000 5000 6000 7000 Stellar effective temperature (K) 1 10 24 24 96 96 1 10 10 24 24 96 96 G0 K0 M0 K6 M3… view at source ↗
Figure 3
Figure 3. Figure 3: Integration time required for an Earth-twin around a given star to reach an SNR of 7, plotted as a function of stellar parameters. The baseline limits are set at 25-80 m. The LIFE stellar sample is over-plotted in black, and integration time contours are over-plotted in white. Dotted contours show the same integration time contours, but for the 10-100 m case for comparative purposes. Solid horizontal lines… view at source ↗
Figure 4
Figure 4. Figure 4: The percentage of extra mission time that is needed compared to the flexible 10-100 m baseline array to detect the total number of planets specified in section 4 (50, 25 and 20 planets for stellar types F0-K5, K6-M3 and M4-M9 respectively), plotted for a variety of discrete baseline cases. Dashed contour lines at 10% and 20% are also displayed. The plot inset uses a much larger y-axis scaling to demonstrat… view at source ↗
Figure 5
Figure 5. Figure 5: Detection curve for a selection of baseline architectures, highlighting the cumulative number of exoEarth planet detections around solar-type stars as the mission unfolds. Baseline ranges are plotted as continuous lines, and discrete baselines as dashes. Having a single baseline of 10 m is incredibly problematic for the mission, resulting in a staggering 18 fold increase in mission time. Beyond the short, … view at source ↗
Figure 6
Figure 6. Figure 6: Integration time required for an Earth-twin around a given star to reach an SNR of 7, plotted as a function of stellar parameters, for two different discrete baseline configurations. The LIFE stellar sample is over-plotted in black, and integration time contours are over-plotted in white. Dotted contours show the same integration time contours, but for the 10-100 m baseline range case for comparative purpo… view at source ↗
Figure 7
Figure 7. Figure 7: Squared visibility as a function of stellar angular diameter and baseline. Over-plotted is the LIFE stellar catalogue, whereby we choose the nulling baseline to correspond to optimising against a planet at half the inner edge of the habitable zone. More than 95% of potential planets should lie at angular separations larger than this. The blue shaded region shows the 25-80 m nulling baseline range as discus… view at source ↗
Figure 8
Figure 8. Figure 8: Requirements on the fringe tracking residuals for a grid of stellar parameters (distance and effective temperature). The LIFE stellar catalogue within 40 pc is over-plotted in black. Solid horizontal lines show the boundaries between stellar types of F, G, K and M; and dashed horizontal lines show the boundaries between LIFE’s target stellar populations. Left: no restrictions on the baseline. Right: baseli… view at source ↗
Figure 9
Figure 9. Figure 9: Allowable fringe tracking bandwidth for varying stellar parameters. Overplotted in black is the LIFE catalog within 40 pc, and bandwidth contours are shown in white. A baseline limit of 25-80 m was imposed, and the OPD residuals were drawn from fig. 8. Solid horizontal lines show the boundaries between stellar types of F, G, K and M; and dashed horizontal lines show the boundaries between LIFE’s target ste… view at source ↗
Figure 10
Figure 10. Figure 10: Modulation efficiency curve of the Double Bracewell for varying aspect ratios as a function of off-axis angle. 2022; J. T. Hansen et al. 2022a), can be found at 0.59λ/B, and produces an average transmission of 0.55 telescope fluxes. The total planet flux is then the product of the planet’s spectral flux density Ep, the modulation efficiency, and the FOV taper function ρ(D, θ, λ), integrated over wavelengt… view at source ↗
Figure 11
Figure 11. Figure 11: The reduction in stellar leakage due to limb darkening (eq. (B21)) for various stellar models. Each point is an element of the table of parameters from A. Claret & S. Bloemen (2011), assuming the parameter cuts discussed in appendix B. The colours represent various Spitzer filters, with darker colours inferring shorter wavelengths. 3000 4000 5000 6000 7000 Stellar effective temperature (K) 0.0 0.1 0.2 0.3… view at source ↗
Figure 12
Figure 12. Figure 12 view at source ↗
Figure 13
Figure 13. Figure 13: Field of view coupling efficiency for a Gaussian and a uniform beam as a function of off-axis angle. Dashed lines indicate the outer working angle (50% of the maximum coupling efficiency). Left: linear scaling; Right: logarithmic scaling. 10 1 10 0 10 1 Off-axis angle (arcsec) 10 3 10 2 10 1 10 0 Collecting Power (AU) 3m, 4µm 2m, 4µm 1m, 4µm 0.5m, 4µm 3m, 10µm 2m, 10µm 1m, 10µm 0.5m, 10µm view at source ↗
Figure 14
Figure 14. Figure 14: Collecting power of different telescope sizes as a function of off-axis angle, arbitrarily scaled such that an on-axis source for a 3 m mirror is one. Shown for wavelengths of 4 µm (left) and 10 µm (right). Equivalent to the coupling efficiency plot in fig. 13 multiplied by the collecting area of the primary mirror. The off-axis coupling of a Gaussian beam into a single mode fibre is derived in Appendix A… view at source ↗
Figure 15
Figure 15. Figure 15: SNR for a variety of planet systems as a function of aperture diameter. EE refers to an ExoEarth twin at 1 AU, scaled by the square root of the stellar luminosity, and OHZ refers to an Earth placed at the outer edge of the habitable zone. A question arises as to whether it is advantageous to reduce (or stop-down) the aperture such that the increase in off-axis coupling efficiency overcomes the reduction i… view at source ↗
Figure 16
Figure 16. Figure 16: SNR as a function of baseline for various planet archetypes around a solar analogue star at 10 pc. Vertical dashed lines represent the optimal baseline for each case. 0 10 20 30 40 50 Baseline (m) 0 5 10 15 20 SNR 2 pc G dwarf at 0.2 AU 5 pc G dwarf at 0.5 AU 10 pc G dwarf at 1 AU 20 pc G dwarf at 2 AU 10 pc K dwarf at 1 AU 14.36 m 15.61 m 15.24 m 14.49 m 14.54 m view at source ↗
Figure 17
Figure 17. Figure 17: SNR as a function of baseline for different star archetypes considering an Earth analogue at 100 mas from the star. The first four lines are for a G2 dwarf at various distances (but holding angular separation constant) and the latter a cooler K7 dwarf at 10 pc. Vertical dashed lines represent the optimal baseline for each case. to see the effects of the limited FOV come into effect (hence why the star is … view at source ↗
Figure 18
Figure 18. Figure 18: SNR as a function of baseline multiplied by separation for an Earth twin around a solar analogue at 2 pc, shown for planets of varying separations. Vertical dashed lines represent the optimal baseline for each case. 10 1 10 2 10 3 Baseline (m) 1.0 0.5 0.0 0.5 1.0 Coefficient residual 1e 6 10 1 10 2 10 3 Baseline (m) 10 1 10 2 Baseline (m) view at source ↗
Figure 19
Figure 19. Figure 19: Residuals for each of the various MC parametric fits described in table 1 as a function of baseline. Left: Character￾isation model, with residual σ of 1.7 × 10−7 m rad, Middle: Kepler detection model, with residual σ of 5.9 × 10−8 m rad, Right: Uniform detection model, with residual σ of 4.4 × 10−8 m rad. The two detection models were run with fewer samples due to computational constraints. drawing insigh… view at source ↗
Figure 20
Figure 20. Figure 20: Number of exoplanet detections within the habitable zone for different baseline optimisations, stellar populations and statistical planet populations. The yields were run via LIFEsim (F. A. Dannert et al. 2022), with modifications described in the text. The various optimisation routines (shown in different colours) are: setting the “reference wavelength“ to 15 µm as previously done in LIFE yield papers; o… view at source ↗
read the original abstract

By aiming to find and characterise dozens of habitable exoplanets through the technique of nulling interferometry, the LIFE space mission will produce transformational science. One of the key parameters for such an interferometric mission is the nulling baseline length - the distance between nulled apertures, which past studies have assumed to be 10-100m. Advances in planet occurrence statistics and simulation tools allow us now to revisit this key assumption with significantly more detail, particularly with the intention to reduce the range of baselines considered due to mission implementation concerns. We utilise the LIFEsim mission simulator along with revised mathematical tools to identify whether the range of baselines could be reduced without significantly affecting planet yield and fringe tracking performance. Along the way, we also determine a new astrophysically motivated technique for choosing which baselines are optimal for a given science target. We find that indeed, LIFE could utilise a considerably shorter range of baselines, such as 25-80m, or even discrete baselines without much (<10%) loss of performance. Nevertheless, careful trade-offs between performance and implementation simplification must be made, especially considering any spectral weighting that may be required by the scientific goals, and the potential loss of target-specific baseline optimisation.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper claims that the LIFE space mission could utilize a considerably shorter range of nulling baselines (e.g., 25-80 m or discrete baselines) with less than 10% loss in planet yield and fringe-tracking performance relative to the previously assumed 10-100 m range. This conclusion is reached via forward modeling with the LIFEsim simulator fed by revised planet occurrence statistics, together with a new astrophysically motivated technique for selecting optimal baselines per target.

Significance. If the <10% loss result holds under scrutiny, the work would be significant for simplifying the technical implementation of the LIFE nulling interferometer, potentially lowering cost and complexity while retaining most of the mission's capability to characterize habitable-zone exoplanets. The incorporation of updated occurrence rates and the introduction of a target-specific baseline optimization method are clear strengths.

major comments (2)
  1. [Results section (baseline-range comparisons)] The central quantitative claim of <10% performance loss for the 25-80 m (or discrete) baseline ranges is presented without error bars, simulation-run statistics, exclusion criteria, or sensitivity analyses to key LIFEsim parameters (null depth vs. wavelength, stellar leakage, integration-time scaling, or inner-working-angle mapping). This directly affects the robustness of the headline result.
  2. [Methods (LIFEsim description and simulation setup)] The manuscript provides no external calibration, cross-code comparison, or validation against real interferometric data to confirm that LIFEsim's treatment of baseline-dependent quantities remains accurate when the range is truncated to 25-80 m; any systematic bias in those modules would rescale the reported loss figure.
minor comments (2)
  1. [Introduction] The introduction's reference to earlier studies that assumed 10-100 m baselines would be strengthened by explicit citations to those works.
  2. [Figures and tables] Figure or table captions comparing yields across baseline sets could more explicitly define the performance metrics (e.g., which spectral weighting is applied) to improve clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive review and for recognizing the potential significance of our findings for simplifying the LIFE mission architecture. We address each major comment point by point below, with a commitment to revisions that improve the robustness of the presented results while remaining faithful to the scope of this preliminary exploration.

read point-by-point responses

  1. Referee: [Results section (baseline-range comparisons)] The central quantitative claim of <10% performance loss for the 25-80 m (or discrete) baseline ranges is presented without error bars, simulation-run statistics, exclusion criteria, or sensitivity analyses to key LIFEsim parameters (null depth vs. wavelength, stellar leakage, integration-time scaling, or inner-working-angle mapping). This directly affects the robustness of the headline result.

    Authors: We agree that the absence of error bars, run statistics, and sensitivity tests limits the ability to assess the robustness of the <10% loss claim. The LIFEsim runs underlying our figures are stochastic due to the planet occurrence rate sampling, but we did not report the associated variances. In the revised manuscript we will (i) rerun the key comparisons with a larger number of Monte Carlo realizations and display standard deviations as error bars on the yield and fringe-tracking metrics, (ii) state the exclusion criteria applied to targets (e.g., minimum SNR thresholds), and (iii) add a short sensitivity study varying null depth, stellar leakage, integration-time scaling, and inner-working-angle mapping within plausible ranges. These additions will be placed in the Results section and will demonstrate that the <10% conclusion is stable under reasonable parameter variations. revision: yes

  2. Referee: [Methods (LIFEsim description and simulation setup)] The manuscript provides no external calibration, cross-code comparison, or validation against real interferometric data to confirm that LIFEsim's treatment of baseline-dependent quantities remains accurate when the range is truncated to 25-80 m; any systematic bias in those modules would rescale the reported loss figure.

    Authors: LIFEsim is a purpose-built simulator whose baseline-dependent modules (fringe tracking, null depth, leakage) have been documented and exercised in earlier LIFE-related papers for the canonical 10-100 m range. Because the LIFE mission is still a concept, no on-sky interferometric data exist for any baseline range, precluding direct empirical validation. We will nevertheless strengthen the Methods section by (i) explicitly listing the assumptions made in the baseline-dependent calculations, (ii) showing that the functional forms used for null depth and leakage are analytic and therefore insensitive to the absolute range once the projected baseline is fixed, and (iii) adding a brief comparison of the truncated-range results against a simplified analytic model that reproduces the dominant scaling. These steps provide the strongest internal consistency check feasible at present; we do not claim external calibration beyond what already exists in the literature for the simulator as a whole. revision: partial

Circularity Check

0 steps flagged

No circularity: results from forward simulation with external tools

full rationale

The paper derives its central claim (shorter 25-80 m or discrete baselines yield <10% performance loss) by running the external LIFEsim simulator on revised planet occurrence statistics and directly comparing output yields and fringe-tracking metrics across baseline configurations. No load-bearing step reduces to a self-definition, a fitted parameter renamed as prediction, or a self-citation chain; the new baseline-selection technique is introduced as an independent astrophysical criterion rather than a re-derivation of the same inputs. The numerical experiment is self-contained against the simulator outputs and does not force the reported loss figure by construction.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on the accuracy of the LIFEsim simulator (external tool) and updated planet occurrence rates (external input). The chosen baseline ranges (25-80 m) are derived from simulation outputs rather than first-principles derivation.

free parameters (1)
  • baseline range bounds
    25-80 m selected post-simulation as the reduced range that preserves performance; not derived from first principles.
axioms (1)
  • domain assumption Nulling interferometry performance for habitable-zone planets is adequately modeled by LIFEsim under the revised occurrence statistics
    Invoked throughout the simulation comparison to prior 10-100 m assumption.

pith-pipeline@v0.9.0 · 5551 in / 1338 out tokens · 27456 ms · 2026-05-08T04:51:08.091439+00:00 · methodology

discussion (0)

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