Interstellar Interferometry: Precise Curvature Measurement from Pulsar Secondary Spectra
Bibliographic record
Abstract
The parabolic structure of the secondary or conjugate spectra of pulsars is often the result of isolated one-dimensional (or at least highly anisotropic) lenses in the ISM. The curvature of these features contains information about the velocities of the Earth, ISM, and pulsar along the primary axis of the lens. As a result, measuring variations in the curvature over the course of a year, or the orbital period for pulsars in binaries, can constrain properties of the screen and pulsar. In particular the pulsar distance and orbital inclination for binary systems can be found for multiple screens or systems with prior information on $\sin(i)$. By mapping the conjugate spectra into a space where the main arc and inverted arclets are straight lines, we are able to make use of the full information content from the inverted arclet curvatures, amplitudes, and phases using eigenvectors to uniquely and optimally retrieve phase information. This allows for a higher precision measurement than the standard Hough transform for systems where these features are available. Our technique also directly yields the best fit 1D impulse response function for the interstellar lens given in terms of the Doppler shift, time delay, and magnification of images on the sky as seen from a single observatory. This can be extended for use in holographic imaging of the lens by combining multiple telescopes. We present examples of this new method for both simulated data and actual observations of PSR B0834+06.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".