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The Effects of Finite Emission Height in Precision Pulsar Timing

2006· preprint· en· W6948187502 on OpenAlexaff

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2006
Typepreprint
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeutron starPulsarGravitational waveMillisecond pulsarBinary numberBinary starNeutronLight curve

Abstract

fetched live from OpenAlex

Precision timing is the key ingredient of ongoing pulsar-based gravitational wave searches and tests of general relativity using binary pulsars. The conventional approach to timing explicitly assumes that the radio emitting region is located at the center of the pulsar, while polarimetric observations suggest that radio emission is in fact produced at altitudes ranging from tens to thousands of kilometers above the neutron star surface. Here we present a calculation of the effects of finite emission height on the timing of binary pulsars using a simple model for the emitting region geometry. Finite height of emission changes the propagation path of radio photons through the binary and gives rise to a large spin velocity of the emission region co-rotating with the neutron star. Under favorable conditions these two effects introduce corrections to the conventional time delays at the microsecond level (for a millisecond pulsar in a double neutron star binary with a period of several hours and assuming the emission height of 100 km). Exploiting the dependence of the emission height on frequency (radius-to-frequency mapping) and using multi-frequency observations one should be able to detect these timing corrections even though they are formally degenerate with conventional time delays. Although even in the most accurately timed systems the magnitude of the finite emission height effects is currently somewhat below timing precision, longer-term observations and future facilities like SKA will make measurement of these effects possible, providing an independent check of existing emission height estimates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.273
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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