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REVIEW 3 major objections 5 minor 44 references

Post-processing subtraction of tilt-to-length noise in LISA in the presence of gravitational wave signals

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Gravitational-wave contamination doesn't break LISA's tilt-to-length noise subtraction.

desk verdict Solid engineering validation for LISA TTL subtraction with GW signals; abstract overstates signal-preservation evidence. read the letter →

arxiv 2411.14191 v3 pith:GTCFANGH submitted 2024-11-21 astro-ph.IM gr-qc

Marie-Sophie Hartig , Sarah Paczkowski , Martin Hewitson , Gerhard Heinzel , Gudrun Wanner This is my paper · ORCID
classification astro-ph.IMgr-qc
keywords tilt-to-lengthcouplingLISAgravitationalwavesignalsnoisesubtractiontime-delayinterferometryMCMCcoefficientestimationspace-basedobservatoryinstrumentmodeling
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

LISA will measure gravitational waves from 0.1 mHz to 1 Hz, and one of its main noise sources is tilt-to-length (TTL) coupling: angular jitter of the spacecraft and optical assemblies leaking into the interferometric length readout. The mission plans to subtract this noise in post-processing by fitting TTL coupling coefficients to the data, but the same data also contain gravitational-wave (GW) signals, so the fit must not mistake signals for noise or damage them. This paper claims, using simulated LISA data, that GW responses — from verification binaries, a stellar-origin stochastic background, galactic white dwarf binaries, massive black hole mergers, and a combined multi-source data set — have little effect on the quality of the TTL fit and subtraction. In all tested cases the coupling coefficients are recovered within 0.1 mm/rad, the residual noise after subtraction falls below the LISA requirement, and the GW signal content is not perceptibly altered. If true, the planned in-flight TTL subtraction strategy can proceed without a dedicated separation of GW signals, and the science data will not be corrupted by the noise removal.

What carries the argument

The load-bearing object is the linear tilt-to-length coupling model of Eq. (3), $\hat{x}^{\mathrm{TTL}}_{ij} = C^{\varphi\mathrm{Rx}}_{ij}\varphi^{\mathrm{DWS}}_{ij} + C^{\eta\mathrm{Rx}}_{ij}\eta^{\mathrm{DWS}}_{ij} + \cdots$: each of the six links has four coupling coefficients multiplying the differential-wavefront-sensing measured angular jitter of the local and remote spacecraft/MOSA pairs, with the remote terms delayed by the light travel time. Propagated through second-generation time-delay interferometry into the orthogonal AET combinations, this model becomes the template that the Markov-chain Monte Carlo fitter matches to the simulated length data, iteratively whitening the noise between 3 mHz and 0.9 Hz; the fitted coefficients then define the subtraction. The argument's strength rests on this linear template being the true coupling and on the fit band being populated by white jitter.

What would settle it

Run the same one-day MCMC fit on simulated LISA data in which the spacecraft/MOSA jitter follows a colored spectrum, such as the control-loop roll-off expected in flight, with a massive black hole merger overlapping the fit band; the central claim fails if coefficient errors exceed 0.1 mm/rad or if the residual after subtracting the fitted TTL model no longer matches the injected GW waveform.

Watch

Extended reading notes

Core claim

The central claim is that the post-processing TTL subtraction scheme planned for LISA works essentially as well when gravitational-wave signals are present as when they are absent. Using simulated one-day data with identical noise and jitter realizations, the authors fit the 24 TTL coupling coefficients of the linear model (Eq. 3) to TDI AET data with an iterative-whitening Markov-chain Monte Carlo algorithm over the 3 mHz–0.9 Hz band. For verification binaries, a stochastic gravitational-wave background, detached galactic white dwarf binaries, massive black hole binary mergers, and the combined multi-source data set, estimated coefficient deviations stay below the 0.1 mm/rad requirement, residuals after subtraction lie below the LISA mission noise requirement, and the residual TTL noise remains about an order of magnitude below the other instrument noises. Comparing the fitted-TTL-subtraction residual with the injected GW response in data that contain no other instrument noise shows that the subtraction does not perceivably alter the GW signal. The authors also show that changing arm lengths, whether from Keplerian or ESA science orbits, do not change the conclusions, supporting the static-arm assumption of earlier work.

Load-bearing premise

The load-bearing premise is that the true TTL coupling is exactly the linear model of Eq. (3) with white spacecraft and MOSA jitter in the 3 mHz–0.9 Hz fit band; if real jitter is colored or the coupling has unmodeled nonlinearity or slow drifts, the fitted coefficients and subtraction residuals could degrade beyond the reported margins.

Editorial extensions

If this is right

  • The planned post-processing TTL subtraction can be run on LISA data without first separating or masking gravitational-wave signals; the tested source classes and the combined multi-source data set all leave coefficient errors below 0.1 mm/rad.
  • After subtraction the total noise meets the LISA requirement even when a massive black hole merger overlaps the TTL-dominated band, so the noise cleanup does not have to wait for quiet data stretches.
  • Because the GW response in the residuals matches the injected signal, the subtraction does not imprint a spurious waveform component, which is a prerequisite for unbiased astrophysical parameter estimation.
  • The static-unequal-arm assumption used in earlier TTL subtraction studies is adequate: Keplerian and ESA science orbit arm-length changes give nearly identical residuals.
  • The combined multi-source data set behaves like the merger-dominated case, indicating that the loudest source on a given day controls the TTL fit quality.

Reading between the lines

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

  • If real spacecraft/MOSA jitter is colored rather than white, the effective TTL-dominated band shrinks and the fit leans on low frequencies where GW confusion is strongest; testing the same MCMC scheme with control-loop-shaped jitter would show whether the 0.1 mm/rad margin survives.
  • The one-day analysis leaves open long-integration effects: over months of data, slow drifts of coupling coefficients or a slowly evolving GW foreground could bias the TTL fit, so the claim should be re-checked on full-mission-length simulations with parameter-estimation follow-up.
  • The linear model in Eq. (3) omits possible nonlinear or time-varying TTL terms; a dedicated injection of a nonlinear coupling term would reveal how much unmodeled structure the fit absorbs into the linear coefficients.
  • Extending to source classes not tested here, such as extreme-mass-ratio inspirals or a cosmological stochastic background, would stress the low-frequency band where the GW response sits above the TTL noise; the paper itself identifies these as open cases.
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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

3 major / 5 minor

Summary. The paper investigates whether post-processing subtraction of tilt-to-length (TTL) noise in LISA remains accurate and non-destructive when gravitational wave (GW) signals are present in the data. The authors simulate one day of LISA data with LISANode, include four classes of GW signals (verification binaries, a stochastic GW background, galactic white-dwarf binaries, massive black hole binary mergers, and a full LDC Sangria combination), and use an MCMC fit to estimate the 24 TTL coupling coefficients in the TDI AET variables. They report that coefficient estimation errors remain below the 0.1 mm/rad requirement, that residual noise after subtraction stays below the LISA requirement, and that visual overlays of amplitude spectral densities suggest the GW signal is not degraded by the subtraction. The manuscript also confirms that static-arm simulations are adequate despite small real arm-length variations.

Significance. If the central claim holds, the paper provides valuable evidence for the LISA data-processing pipeline: TTL noise subtraction should not be catastrophically confused with GW signals, and the subtraction itself should not corrupt the GW response. The study's strengths include the use of realistic LISANode simulations, public LDC data, multiple GW source types, and an MCMC estimator that is not given the true coupling coefficients, so the coefficient-error results are a genuine test of the estimation procedure. The residual ASDs and coefficient-error plots are informative and support the main quantitative claims about noise subtraction. However, the claim that 'GW signal characteristics were not altered' is supported only by qualitative ASD overlays over one day of data, which is not sufficient for the strength of the abstract statement.

major comments (3)
  1. [Section V.C, V.D and Summary] The abstract's claim that 'the GW signal characteristics were not altered by the TTL coupling subtraction' is not supported by the evidence presented. In Fig. 9 and Fig. 14 the test is a visual overlap between the ASD of the injected GW response (purple) and the residual obtained by subtracting the fitted TTL model from data with no instrument noise other than TTL (yellow). An ASD match is insensitive to phase-coherent distortions, time shifts, or spectral leakage, any of which could bias astrophysical parameter recovery while leaving the ASD nearly unchanged. The Summary itself concedes that the signal-preservation point 'was shown only indirectly in figures 9 and 14 for one day of data' and that confirmation with longer integration times and parameter estimation is required. Please either add a phase-coherent or parameter-estimation test on the residual data, or qualify the abstract and conclusions accordingly.
  2. [Abstract and Section V.D] The simulations assume jitter that is white in the 3 mHz to 0.9 Hz fit band (Appendix A, Eqs. (A1)-(A3)), while real LISA jitter is expected to be colored. Section V.D states: 'We cannot say, whether or how other jitter shapes would affect the findings of this paper.' Because the central claim concerns in-flight applicability, this is a substantial limitation. The abstract should not present the results without this caveat. Either demonstrate robustness to a colored-jitter model (e.g., by repeating the coefficient-fit and subtraction tests with a roll-off or otherwise colored spectrum) or explicitly scope the headline claim to the white-jitter case.
  3. [Section V.C, V.D and Summary] All signal-preservation tests are performed on one day of data. The claim that GW signals are not altered is therefore limited to a one-day timescale; the Summary acknowledges that longer integration times and the ultimate effect on astrophysical parameter estimation remain open. Since LISA science analyses will integrate for weeks to months, the manuscript should either extend the analysis to a longer data stretch or at least move the one-day limitation into the abstract so that the strength of the claim matches the evidence.
minor comments (5)
  1. [Section II heading] The heading 'TIL T-TO-LENGTH NOISE IN LISA' contains a typo; it should read 'TILT-TO-LENGTH NOISE IN LISA'.
  2. [Appendix A] In the sentence introducing the interferometer noises, 'lenght readout' should be 'length readout'.
  3. [Figure 2 caption] The caption spells 'Keplarian' orbits; the standard spelling is 'Keplerian'.
  4. [Section V.A] The verification binary 'HMCnc' is presumably 'HM Cnc' (the cataclysmic variable HM Cancri); please use the standard astronomical designation.
  5. [Section V.D] The phrase 'The here presented results cannot directly be compared with [10]' would read more naturally as 'The results presented here cannot be directly compared with [10]'.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the GW-robustness claim is tested with an MCMC estimator that is not given the true TTL coefficients or the injected GW signals, and the same-model simulation limits scope without making the result definitional.

full rationale

The paper's central empirical claim is that an MCMC estimator of the 24 TTL coupling coefficients, applied to simulated TDI-AET data containing injected GW signals, still estimates the coefficients to within 0.1 mm/rad and that subtraction leaves the GW response essentially unchanged. This is not a circular derivation: the GW signals come from external simulators (LISANode, LISA GW Response, and the Sangria/LDC data sets), and the estimator is not given the true coupling coefficients or the GW waveforms. Equation (3) is the assumed physical noise model used to construct the simulated TTL noise; it is not a quantity the paper claims to derive from the data. The subtraction checks are direct consistency checks: after subtracting the fitted model, the residual is compared with the injected GW response (Figs. 9 and 14), so the result could have failed if the GW signals biased the coefficient estimates. The paper itself limits the strength of the signal-preservation claim: 'the latter was shown only indirectly in figures 9 and 14 for one day of data. The results would need to be confirmed considering the longer integration times for GW analyses and their ultimate effect on the astrophysical parameter estimation.' It also explicitly flags the white-jitter scope limitation: 'We cannot say, whether or how other jitter shapes would affect the findings of this paper.' These are validation limitations, not circular steps. The self-citations to [7] and [8] for the fitting scheme are standard method attribution; they do not supply the GW-robustness result, which is tested against independent simulated benchmarks in this paper. No fitted parameter is renamed as a prediction, and no load-bearing uniqueness claim is imported from the authors' prior work. Therefore no step reduces by construction to its input; the appropriate circularity score is 0.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The paper contributes a simulation validation, not new physics. Its central result rests on the fidelity of the simulated TTL model, the jitter and noise assumptions from Appendix A, and the MCMC fitting algorithm from prior work.

free parameters (4)
  • True TTL coupling coefficient C = 2.3 mm/rad
    All 24 simulated TTL coefficients set to 2.3 mm/rad, as in [7,8]. Results are tested against this value; different coefficient values could alter fit accuracy.
  • Fit frequency range = 3 mHz to 0.9 Hz
    Chosen for TTL dominance; a reduced range 3 mHz to 0.2 Hz gave comparable results (Appendix B), so the central finding is not sensitive to this choice.
  • Jitter amplitudes = SC 5 nrad/√Hz, MOSA 2 and 1 nrad/√Hz
    From the LISA performance model; white in the fit band, not the expected colored jitter. Central to the test.
  • DWS readout noise = 70/335 nrad/√Hz
    From [22]; affects both angle measurements and the subtraction residual.
assumptions (5)
  • domain assumption TTL coupling is linear in angles at nanoradian jitter (Eq. 3)
    Used to generate simulated data and as the fit model. If unmodeled nonlinear terms exist, the subtraction could fail; the paper does not validate the linear model against real LISA data.
  • domain assumption Jitter and instrument noise spectra in Appendix A represent LISA
    All conclusions depend on these simulated noise shapes; the paper notes telescope path length noise is smaller than current estimates and jitter is white where colored is expected.
  • standard math The MCMC estimator from [7] converges and is unbiased under the simulated model
    The estimator is taken from prior work; convergence and unbiasedness are assumed, not re-derived here.
  • domain assumption TDI AET combinations are suitable for fitting with no cross-correlation
    Used to transform TDI XYZ to AET; orthogonality holds in the idealized equal-arm case (Section II.B).
  • domain assumption Static unequal arm lengths are sufficient for TTL studies
    Tested in Section IV; found no significant difference, so used for GW signal cases.

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Cite this review

Pith. "Pith review of Post-processing subtraction of tilt-to-length noise in LISA in the presence of gravitational wave signals." pith.science (2026). https://pith.science/paper/GTCFANGH

@misc{pith2026241114191,
  author       = {Pith},
  title        = {Pith review of: Post-processing subtraction of tilt-to-length noise in LISA in the presence of gravitational wave signals},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GTCFANGH}},
  note         = {Machine review of arXiv:2411.14191}
}
read the original abstract

The Laser Interferometer Space Antenna (LISA) will be the first space-based gravitational wave (GW) observatory. It will measure gravitational wave signals in the frequency regime from 0.1 mHz to 1 Hz. The success of these measurements will depend on the suppression of the various instrument noises. One important noise source in LISA will be tilt-to-length (TTL) coupling. Here, it is understood as the coupling of angular jitter, predominantly from the spacecraft, into the interferometric length readout. The current plan is to subtract this noise in-flight in post-processing as part of a noise minimization strategy. It is crucial to distinguish TTL coupling well from the GW signals in the same readout to ensure that the noise will be properly modeled. Furthermore, it is important that the subtraction of TTL noise will not degrade the GW signals. In the present manuscript, we show on simulated LISA data and for four different GW signal types that the GW responses have little effect on the quality of the TTL coupling fit and subtraction. Also, the GW signal characteristics were not altered by the TTL coupling subtraction.

Figures

Figures reproduced from arXiv: 2411.14191 by the authors.

Figure 1
Figure 1. FIG. 1. Naming conventions for the LISA SC and MOSAs. [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. Deviations of the estimated coupling coefficients from [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. ASDs of the TDI X combination for the simulations [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (11 more)
Figure 4
Figure 4. Figure 4: FIG. 4. Performance of the TTL coupling subtraction in the [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]
Figure 7
Figure 7. Figure 7: FIG. 7. Deviations of the estimated coupling coefficients [PITH_FULL_IMAGE:figures/full_fig_p005_7.png]
Figure 8
Figure 8. Figure 8: FIG. 8. Performance of the TTL coupling subtraction in the [PITH_FULL_IMAGE:figures/full_fig_p006_8.png]
Figure 9
Figure 9. Figure 9: FIG. 9. Close-up view on the performance of the TTL cou [PITH_FULL_IMAGE:figures/full_fig_p006_9.png]
Figure 11
Figure 11. Figure 11: FIG. 11. Deviations of the estimated coupling coeffi [PITH_FULL_IMAGE:figures/full_fig_p007_11.png]
Figure 12
Figure 12. Figure 12: FIG. 12. Performance of the TTL coupling subtraction for [PITH_FULL_IMAGE:figures/full_fig_p007_12.png]
Figure 13
Figure 13. Figure 13: FIG. 13. Deviations of the estimated coupling coefficients [PITH_FULL_IMAGE:figures/full_fig_p008_13.png]
Figure 14
Figure 14. Figure 14: FIG. 14. Close-up view on the performance of the TTL cou [PITH_FULL_IMAGE:figures/full_fig_p008_14.png]
Figure 15
Figure 15. Figure 15: FIG. 15. Performance of the TTL coupling subtraction in the [PITH_FULL_IMAGE:figures/full_fig_p009_15.png]
Figure 16
Figure 16. Figure 16: FIG. 16. Deviations of the estimated coupling coefficients [PITH_FULL_IMAGE:figures/full_fig_p009_16.png]
Figure 17
Figure 17. Figure 17: FIG. 17. Deviations of the estimated coupling coefficients [PITH_FULL_IMAGE:figures/full_fig_p012_17.png]

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Reference graph

Works this paper leans on

44 extracted references · 39 canonical work pages

  1. [1]

    static arms with beam propagation times: τ12 ≈ 8.425 s, τ13 ≈ 8.322 s, τ23 ≈ 8.372 s, τ21 ≈ 8.322 s, τ31 ≈ 8.322 s, τ32 ≈ 8.372 s

    work page

  2. [2]

    changing arm lengths gained from Keplerian orbit files [25]

    work page

  3. [3]

    The static arm lengths given are those assumed in [7]

    changing arm lengths gained from ESA LISA sci- ence orbit files [25, 26]. The static arm lengths given are those assumed in [7]. While the lengths for the individual links are within the LISA length variations, the variations for the full con- stellation were chosen for study purposes and may not be particularly realistic. We find larger arm length vari- ...

    work page

  4. [4]

    Non- geometric tilt-to-length coupling in space interferometry: mechanisms and analytical descriptions

    M-S Hartig, S Schuster, G Heinzel, and G Wanner. Non- geometric tilt-to-length coupling in space interferometry: mechanisms and analytical descriptions. Journal of Op- tics, 25(5):055601, apr 2023

    work page 2023

  5. [5]

    LISA: unveiling a hidden universe

    K Danzmann, T Prince, P Binetruy, P Bender, S Buch- man, J Centrella, M Cerdonio, N Cornish, M Cruise, C Cutler, et al. LISA: unveiling a hidden universe. As- sessment Study Report ESA/SRE, 3:2, 2011

    work page 2011

  6. [6]

    LISA definition study report

    M Colpi, K Danzmann, M Hewitson, K Holley- Bockelmann, P Jetzer, G Nelemans, A Petiteau, D Shoe- maker, C Sopuerta, R Stebbins, et al. LISA definition study report. ArXiv e-prints, 2024

    work page 2024

  7. [7]

    Geometric tilt- to-length coupling in precision interferometry: mecha- nisms and analytical descriptions

    M-S Hartig, S Schuster, and G Wanner. Geometric tilt- to-length coupling in precision interferometry: mecha- nisms and analytical descriptions. Journal of Optics, 24(6):065601, 2022

    work page 2022

  8. [8]

    Paczkowski et al

    S. Paczkowski et al. Update on TTL coefficient estima- tion for LISA using noise minimisation, 2024. In prepa- ration

    work page 2024

Show all 44 references
  1. [9]

    Preliminary results on the suppression of sensing cross-talk in LISA Pathfinder

    G Wanner, N Karnesis, and LISA Pathfinder collabora- tion. Preliminary results on the suppression of sensing cross-talk in LISA Pathfinder. Journal of Physics: Con- ference Series, 840(1):012043, 2017

    2017

  2. [10]

    Armano, H

    M. Armano, H. Audley, J. Baird, M. Born, D. Bortoluzzi, N. Cardines, E. Castelli, A. Cavalleri, A. Cesarini, A. M. Cruise, et al. Tilt-to-length coupling in LISA Pathfinder: A data analysis. Phys. Rev. D, 108:102003, Nov 2023

    2023

  3. [11]

    Paczkowski, R

    S. Paczkowski, R. Giusteri, M. Hewitson, N. Karnesis, E. D. Fitzsimons, G. Wanner, and G. Heinzel. Postpro- cessing subtraction of tilt-to-length noise in LISA. Phys. Rev. D, 106:042005, Aug 2022

    2022

  4. [12]

    Houba, S

    N. Houba, S. Delchambre, T. Ziegler, G. Hechenblaikner, and W. Fichter. LISA spacecraft maneuver design to estimate tilt-to-length noise during gravitational wave events. Phys. Rev. D, 106:022004, Jul 2022

    2022

  5. [13]

    George, J

    D. George, J. Sanjuan, P. Fulda, and G. Mueller. Calcu- lating the precision of tilt-to-length coupling estimation and noise subtraction in LISA using Fisher information. Phys. Rev. D, 107:022005, Jan 2023

    2023

  6. [14]

    Hartig, J

    M-S. Hartig, J. Marmor, D. George, S. Paczkowski, and J. Sanjaun. Tilt-to-length coupling in LISA – uncertainty and biases. ArXiv e-prints, 2024

    2024

  7. [15]

    Houba, S

    N. Houba, S. Delchambre, T. Ziegler, and W. Fichter. Optimal estimation of tilt-to-length noise for spaceborne gravitational-wave observatories. J. Guid. Control Dyn., 45(6):1078–1092, 2022

    2022

  8. [16]

    Time-delay interferometry

    M Tinto and S Dhurandhar. Time-delay interferometry. Living Rev. Relativ., 24(1), 2021

    2021

  9. [17]

    Wegener, S

    H. Wegener, S. Paczkowski, M-S. Hartig, M. Hewitson, G. Heinzel, and G. Wanner. Design of dedicated tilt-to- length calibration maneuvers for LISA. ArXiv e-prints, 2024

    2024

  10. [18]

    Auto- matic alignment of optical interferometers

    E Morrison, B Meers, D Robertson, and H Ward. Auto- matic alignment of optical interferometers. Appl. Opt., 33(22), 1994

    1994

  11. [19]

    Methods for simulat- ing the readout of lengths and angles in laser interfer- ometers with Gaussian beams

    G Wanner, G Heinzel, E Kochkina, C Mahrdt, B Sheard, S Schuster, and K Danzmann. Methods for simulat- ing the readout of lengths and angles in laser interfer- ometers with Gaussian beams. Optics communications, 285(24):4831–4839, 2012

    2012

  12. [20]

    Uncovering gravitational-wave backgrounds from noises of unknown shape with LISA

    Q Baghi, N Karnesis, J-B Bayle, M Besan¸ con, and H In- chausp´ e. Uncovering gravitational-wave backgrounds from noises of unknown shape with LISA. J. Cosmol. Astropart. Phys, 2023(04):066, apr 2023

    2023

  13. [21]

    Second- generation time-delay interferometry

    M Tinto, S Dhurandhar, and D Malakar. Second- generation time-delay interferometry. Phys. Rev. D, 107:082001, Apr 2023

    2023

  14. [22]

    Wanner, S

    G. Wanner, S. Shah, M. Staab, H. Wegener, and S. Paczkowski. In-depth modeling of tilt-to-length cou- pling in LISA’s interferometers and TDI Michelson ob- servables. Phys. Rev. D, 110:022003, Jul 2024

    2024

  15. [23]

    LISA optimal sensitivity

    T A Prince, M Tinto, S L Larson, and J W Armstrong. LISA optimal sensitivity. Phys. Rev. D, 66:122002, Dec 2002

    2002

  16. [24]

    PyTDI (1.3.1)

    M Staab, J-B Bayle, and O Hartwig. PyTDI (1.3.1). Zen- odo, 2023. https://doi.org/10.5281/zenodo.8429119

    2023 doi

  17. [25]

    Technical Report No

    M Hewitson. Technical Report No. LISA-LCST-INST- DD-003. Max-Planck Institute for Gravitational Physics (Albert Einstein Institute), 2021

    2021

  18. [26]

    LISANode (1.4)

    J-B Bayle, O Hartwig, A Petiteau, and M Lilley. LISANode (1.4). Zenodo, September 2022. https: //doi.org/10.5281/zenodo.6461078

    2022 doi

  19. [27]

    Optical Simulations

    to generate the LISA data sets and considered ESA LISA science orbits [26]. In the other cases we used the ‘Sangria’ data set from the LISA Data Challenge (LDC) 2a [28, 29]. As these data sets were created for equal arm length orbits, we simulated an orbit file with these prop...

  20. [28]

    Unified model for the LISA measurements and instrument simulations

    J-B Bayle and O Hartwig. Unified model for the LISA measurements and instrument simulations. Phys. Rev. 11 D, 107:083019, Apr 2023

    2023

  21. [29]

    LISA Orbits (2.3)

    J-B Bayle, A Hees, M Lilley, C Le Poncin-Lafitte, W Martens, and E Joffre. LISA Orbits (2.3). Zenodo,

  22. [30]

    LISA Con- stants (1.3)

    J-B Bayle, M Le Jeune, and A Hees. LISA Con- stants (1.3). Zenodo, 2022. https://doi.org/10.5281/ zenodo.6627346

    2022

  23. [31]

    Trajectory design for the ESA LISA mission

    W Martens and E Joffre. Trajectory design for the ESA LISA mission. J. Astronaut. Sci., 68, Jun 2021

    2021

  24. [32]

    LISA GW Response (1.1)

    J-B Bayle, Q Baghi, A Renzini, and M Le Jeune. LISA GW Response (1.1). Zenodo, 2022. https://doi.org/ 10.5281/zenodo.6423436

    2022 doi

  25. [33]

    LISA Data Challenge San- gria (LDC2a) (Version v2) [Data set]

    M Le Jeune and S Babak. LISA Data Challenge San- gria (LDC2a) (Version v2) [Data set]. Zenodo, 2022. https://doi.org/10.5281/zenodo.7132178

    2022 doi

  26. [34]

    LISA Data Chal- lenge software (1.2.0)

    LISA Data Challenge working group. LISA Data Chal- lenge software (1.2.0). Zenodo, 2022. https://doi.org/ 10.5281/zenodo.7332221

    2022 doi

  27. [35]

    Cosmology with the laser interferometer space antenna

    P Auclair, D Bacon, T Baker, T Barreiro, N Bartolo, E Belgacem, N Bellomo, I Ben-Dayan, D Bertacca, M Be- sancon, et al. Cosmology with the laser interferometer space antenna. Living Rev. Relativ., 26(5), Aug 2023

    2023

  28. [36]

    LISA galactic binaries with astrometry from Gaia DR3

    T Kupfer, V Korol, T B Littenberg, S Shah, E Savalle, P J Groot, T R Marsh, M Le Jeune, G Nelemans, A F Pala, A Petiteau, G Ramsay, D Steeghs, and S Babak. LISA galactic binaries with astrometry from Gaia DR3. Astrophys. J., 963(2):100, mar 2024

    2024

  29. [37]

    Abbott, T

    R. Abbott, T. D. Abbott, S. Abraham, F. Acernese, K. Ackley, A. Adams, C. Adams, R. X. Adhikari, V. B. Adya, C. Affeldt, et al. Upper limits on the isotropic gravitational-wave background from Advanced LIGO and Advanced Virgo’s third observing run. Phys. Rev. D, 104:022004, Jul 2021

    2021

  30. [38]

    Impact of the noise knowledge uncertainty for the science exploitation of cos- mological and astrophysical stochastic gravitational wave background with LISA

    M Muratore, J Gair, and L Speri. Impact of the noise knowledge uncertainty for the science exploitation of cos- mological and astrophysical stochastic gravitational wave background with LISA. Phys. Rev. D, 109:042001, Feb 2024

    2024

  31. [39]

    Stochastic gravitational wave background reconstruction for a nonequilateral and unequal-noise LISA constella- tion

    O Hartwig, M Lilley, M Muratore, and M Pieroni. Stochastic gravitational wave background reconstruction for a nonequilateral and unequal-noise LISA constella- tion. Phys. Rev. D, 107:123531, Jun 2023

    2023

  32. [41]

    Stochastic gravitational wave background from stellar origin binary black holes in LISA

    S Babak, C Caprini, D G Figueroa, N Karnesis, P Mar- coccia, G Nardini, M Pieroni, A Ricciardone, A Sesana, and J Torrado. Stochastic gravitational wave background from stellar origin binary black holes in LISA. Journal of Cosmology and Astroparticle Physics, 2023(08):034, aug 2023

    2023

  33. [42]

    LISA Data Challenge: Sangria

    S Babak, M Le Jeune, A Petiteau, and M Val- lisneri. LISA Data Challenge: Sangria. Ref.-No. LISA-LCST-SGS-MAN-001, 2021. https://lisa- ldc.lal.in2p3.fr/static/data/pdf/LDC-manual- Sangria.pdf

    2021

  34. [43]

    New LISA dynamics feedback control scheme: Common-mode isolation of test mass control and probes of test-mass acceleration

    H Inchausp´ e, M Hewitson, O Sauter, and P Wass. New LISA dynamics feedback control scheme: Common-mode isolation of test mass control and probes of test-mass acceleration. Phys. Rev. D, 106:022006, Jul 2022

    2022

  35. [44]

    LISA dynamics and control: Closed-loop simulation and numerical demonstration of time delay interferometry

    L Heisenberg, H Inchausp´ e, D Q Nam, O Sauter, R Waibel, and P Wass. LISA dynamics and control: Closed-loop simulation and numerical demonstration of time delay interferometry. Phys. Rev. D, 108:122007, Dec 2023. Appendix A: Jitters and noises used in our analysis In this sec...

    2023

  36. [2023]

    https://doi.org/10.5281/zenodo.7700361

    doi

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Reviewed August 12, 2026 · model on record in the stance chip above.