Constraining the jet base emission of M87* with past and future Event Horizon Telescope observations

Technical Summary: Constraining the Jet Base Emission of M87 with Past and Future Event Horizon Telescope Observations*

Problem Statement
While the Event Horizon Telescope (EHT) has successfully imaged the shadow and ring-like structure of the supermassive black hole M87*, the detection of the relativistic jet base at horizon scales remains challenging. Although M87 is known to host a powerful jet, current observations at 230 GHz have only weakly constrained its emission close to the black hole. The primary difficulty lies in the lack of short and intermediate baselines in earlier EHT configurations (2017–2018), which limits sensitivity to extended, diffuse structures. Recent campaigns (2021–2022) have introduced new telescopes (NOEMA, KP, LMT) to improve baseline coverage, yet the minimum jet intensity required for reliable detection across different array configurations and imaging methodologies has not been rigorously quantified.

Methodology
The authors employ a synthetic observation approach to assess jet detectability limits.

• Input Models: Semi-analytic accretion–jet models are used, where the jet emission (non-thermal synchrotron) can be tuned independently of the accretion flow (thermal synchrotron). Three total flux density scenarios are tested at 230 GHz: 3.6 Jy (jet-enhanced), 1.0 Jy, and 0.8 Jy (compact-dominated). The jet axis is oriented to match 86 GHz observations, and the models cover a 1 mas Field of View.
• Synthetic Data Generation: The Symba pipeline generates end-to-end synthetic VLBI datasets for three array configurations: 2021, 2022, and a "near-future" configuration including KVN stations. These datasets incorporate realistic atmospheric, instrumental, and calibration effects.
• Imaging Pipelines: Synthetic data are reconstructed using four distinct approaches:
  1. Regularized Maximum Likelihood (RML) via eht-imaging.
  2. Bayesian methods: Themis (geometric crescent + adaptive spline), Resolve (Gaussian-process priors), and Comrade (spline-based priors with joint inference).
• Analysis Metrics: Detectability is quantified via:
  • Flux Recovery: The ratio of recovered to true flux density in defined jet ($R_J$) and counter-jet ($R_{CJ}$) regions.
  • Image Fidelity: Normalized cross-correlation ($\rho_{NX}$) and integrated flux fractions ($F_J, F_{CJ}, F_{out}$).
  • Uncertainty: Relative uncertainty maps ($\sigma/I$) derived from Bayesian posterior distributions.
  • Blind Tests: Imaging tests were conducted where jet orientation was unknown to the imagers to rule out bias from prior assumptions.

Key Results

• Dependence on Jet Intensity: Jet detectability is strongly dependent on intrinsic jet brightness. In the high-jet model (3.6 Jy), all pipelines recover $\sim70-100\%$ of the jet flux. As intensity drops to the low-jet model (0.8 Jy), recovery ratios decrease to $\sim50-70\%$.
• Array Configuration Impact:
  • 2021: Limited by sparse short baselines; faint jet features are harder to reconstruct, with higher relative uncertainty.
  • 2022: The reintroduction of the LMT and the formation of a closed intermediate baseline triangle (LMT–SMT–KP) significantly improve robustness. This configuration provides the most balanced performance, offering reliable jet recovery ratios and consistency across different imaging pipelines.
  • Near-Future: The inclusion of KVN stations yields the highest posterior confidence (lowest relative uncertainty) for the faintest jet structures in Bayesian reconstructions. However, this improvement is not uniform across all pipelines, likely due to increased calibration complexity associated with new stations.
• Imaging Methodology: Comrade is identified as providing the most conservative flux recovery while maintaining high fidelity and avoiding extreme counter-jet artifacts. Counter-jet recovery ratios ($R_{CJ}$) are often inflated in low-flux models due to the intrinsically weak signal, serving as a diagnostic for misplaced flux rather than true detection.
• Detection Limits: The study establishes that the current EHT array (specifically the 2022 configuration) is sensitive enough to recover jet emission down to total flux densities of 0.8 Jy. Below this threshold, reliable reconstruction becomes increasingly sensitive to noise and method-dependent assumptions.

Significance and Claims
The paper claims to provide the first systematic constraints on the minimum jet intensity detectable by the EHT at horizon scales. The authors conclude that:

1. Current Sensitivity: The 2022 EHT array configuration is already sensitive to weak jet emission at horizon scales. If the inner jet contributes a significant fraction of the unresolved compact flux, it should be visible in post-2021 observations.
2. Interpretation of Non-Detection: Conversely, if no clear jet signature is found in real data, it suggests the horizon-scale jet contributes only a small fraction of the compact emission, consistent with recent closure phase analyses suggesting faint components ($\sim60$ mJy).
3. Future Prospects: The continued expansion of the EHT, particularly with new stations in the Canary Islands and Namibia, will further improve intermediate baseline coverage and phase information, enabling more robust localization of jet emission.
4. Caveats: The authors note that their semi-analytic models represent diffuse emission and may be conservative regarding flux detection. If the true 230 GHz morphology is dominated by compact bright knots (as seen in 86 GHz), such features might be detectable even at lower total flux densities than modeled here.

The work serves as a benchmark for interpreting current and future EHT data, distinguishing between instrumental limitations and physical properties of the M87* jet base.