Navigating stellar wobbles for imaging with the solar gravitational lens
Bibliographic record
Abstract
The solar gravitational lens (SGL) offers unique capabilities for direct high-resolution imaging of faint, distant objects, such as exoplanets. For that purpose, in the near future, a spacecraft carrying a meter-class telescope with a solar coronagraph would be placed in the focal region of the SGL. That region begins at $\ensuremath{\sim}547$ astronomical units from the Sun and occupies the immediate vicinity of the target-specific primary optical axis---the line that connects the center of the target and that of the Sun. Clearly, this axis is not at rest. It undergoes complex motion as the exoplanet orbits its host star, as that star moves with respect to the Sun, and even as the Sun itself moves with respect to the Solar System's barycenter due to the gravitational pull of planets in our Solar System. Although less prominent, other motions exist. An image of an extended object is projected by the SGL into an image plane and moves within that plane, responding to the motion of the optical axis. To sample the image, a telescope must always be on the move, following the projection, with precise knowledge of its own position with respect to the image. We consider the dominant motions that determine the position of the focal line as a function of time. We evaluate the needed navigational capability for the telescope to conduct a multiyear exoplanet imaging mission in the focal region for the SGL. We show that even in a rather conservative case, when an Earth-like exoplanet is in our immediate stellar neighborhood at $\ensuremath{\sim}10$ light years, the motion of the image is characterized by a small total acceleration that is driven primarily by the orbital motion of the exoplanet (its effect on the projected image estimated to be at the level of $\ensuremath{\sim}6\text{ }\text{ }\ensuremath{\mu}{\mathrm{m}/\mathrm{s}}^{2}$, decreasing inversely with distance to a target) and by the reflex motion of our Sun (target independent, contributing at $\ensuremath{\sim}0.2\text{ }\text{ }\ensuremath{\mu}{\mathrm{m}/\mathrm{s}}^{2}$). We discuss how the amplified light of the host star allows us to establish a local reference frame that significantly relaxes navigational requirements for the imaging operations. We conclude that the required navigation in the SGL's focal region, although complex, can be accurately modeled, and a $\ensuremath{\sim}10$-year prospective imaging mission is achievable with the already available propulsion technology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".