PhysicsarXiv
Ranked by formulaVerdict: NotableTDCOSMO 2026: A 3% measurement of the Hubble constant from strong lensing and stellar kinematics
We present cosmological constraints from 11 strongly lensed quasars with measured time delays (hereafter, the TDCOSMO-2026 sample).
Key numbers
- 3.3% uncertainty that accounts for
Caveats
- Preprint; not yet peer reviewed.
VerdictWorth a reader's time today.
Abstract
We present cosmological constraints from 11 strongly lensed quasars with measured time delays (hereafter, the TDCOSMO-2026 sample). In addition to expanding the sample, we improve many aspects of our blind analysis with respect to our 2025 analysis. Among other improvements, spatially resolved kinematics are available for nine systems, including six with JWST-NIRSpec, compared to one in 2025; for three lens models, JWST-NIRCam images now replace HST; axisymmetric dynamical modeling is applied directly to the spatially resolved data, instead of an axisymmetric correction factor applied to spherical models; and the line-of-sight convergence is now based on the Euclid Flagship simulations instead of the Millennium Simulation. Our baseline and primary result is based on the TDCOSMO-2026 sample, in combination with a prior on Ω_m from the DES-Dovekie supernova sample. In the flat $Λ$ cold dark matter ($Λ$CDM) cosmology, we find H₀=71.1⁺2.4_-2.3 km.s⁻¹.Mpc⁻¹, a 3.3% uncertainty that accounts for the mass-sheet degeneracy. The SLACS and SL2S samples are in excellent agreement with the TDCOSMO-2026 sample, improving the precision on H₀ in flat $Λ$CDM to 3.0%. Using the DESI-DR2 baryon acoustic oscillations (BAO) likelihood instead of DES-Dovekie yields fully consistent results. We also present constraints in the open $Λ$CDM, wCDM, w₀w_aCDM, and w_φCDM cosmologies; the TDCOSMO H₀ inference is robust and consistent across all of them. The combination of the TDCOSMO+SLACS+SL2S likelihood with those from DESI-DR2 and DES-Dovekie disfavors w=-1 at the $2.3$-$2.5σ$ level in all three dark energy extensions that we tested. We find, e.g., w₀=-0.88⁺0.04_-0.05 in w_φCDM and w₀ = -0.85⁺0.07_-0.06 in w₀w_aCDM, while w_a = -0.48⁺0.46_-0.44 remains consistent with zero.
The editor's rubric
| Dimension | Level | Weight | What that level means |
|---|---|---|---|
| Leverage | ████░ 4 | 18% | A general-purpose tool used across several fields (Adam, ResNet, LoRA, next-generation sequencing). |
| Magnitude | ███░░ 3 | 20% | Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem. |
| Evidence | ███░░ 3 | 22% | Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data. |
| Novelty | ███░░ 3 | 22% | A genuinely new approach to an open problem. |
| Trajectory | ██░░░ 2 | 10% | Some room to improve with obvious engineering. |
| Stakes | ██░░░ 2 | 8% | Benefits a professional community (practitioners, clinicians, engineers). |
Editor’s rationale
Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose, we report); breadth (many tasks); gains (relative gain); novelty (alternative to status quo); verification (error bars, multiple benchmarks, code released); stakes (energy).
How the score was computed
- Merit
- 6.0 / 10
- Adjusted merit
- 4.9 / 10
- Attention
- 0%
- Freshness
- 68%