Bessel beam side lobe suppression via non-degenerate two-photon excitation
Bibliographic record
Abstract
Bessel beams are commonly used in two-photon microscopy to extend the depth of field and thereby achieve functional volumetric imaging of the living brain. In practice, this approach suffers from background signals and limited lateral resolution due to the Bessel beam's strong side lobes. We introduce and demonstrate a new approach to side lobe suppression based on non-degenerate two-photon excitation, in which dual wavelength illumination produces an imaging point-spread function that is the product of the two coaxial Bessel beams. This technique can reduce the main side lobe intensity of a Bessel beam by 50% or more. We illustrate the approach conceptually with an analytical paraxial model and use detailed physical simulation to show that the approach is effective in the presence of the symmetry-breaking aberrations that amplify side lobes in high NA systems. We experimentally demonstrated the technique using a refractive axicon and the pump and tunable beams of a femtosecond laser. This work establishes non-degenerate two-photon excitation as a practical and broadly applicable strategy for improving point spread-function quality in high-resolution volumetric microscopy.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".