Deployment of beam alignment hardware at the Magdalena Ridge Observatory interferometer

Luis, J.; Buscher, David F.; Dahl, C.; Dooley, J.; Farris, Allen; Haniff, Christopher A.; Ligon, E. R.; Norouzi, Siavash; Sun, Xiaowei; Young, John S.

doi:10.1117/12.2562863

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This allows us to measure beam position because some lenslets are illuminated while others are unilluminated. Our algorithm reduces the image of the grid of focal spots to an image of the beam profile where each pixel is the summed brightness of a microlens [3]. The image is first segmented based on the location and size of the microlenses, then all pixels within each segment are summed.…”

Section: Introductionmentioning

confidence: 99%

CNN to mitigate atmospheric turbulence effect on Shack-Hartmann Wavefront Sensing: A case study on the Magdalena Ridge Observatory Interferometer.

Siavash¹,

D.²,

Ramyaa³

et al. 2022

Self Cite

View full text Add to dashboard Cite

The Magdalena Ridge Observatory Interferometer (MROI) utilizes Shack-Hartmann Wavefront Sensing (SH-WFS) for the back-end stability of its beam relay systems in a unique design. The SH-WFS, however, is sensitive to atmospheric turbulence scintillation which can drastically affect its precision in calculating the position of the beam profile it sees. A large number of images are needed to counteract the turbulence effect. Here we use deep learning as an alternative to long averaging cycles. A CNN was trained to map from a number of initial images of a series of star frames to the average image of the entire series at different positions of the beam profile. Under typical seeing conditions expected at MROI, the results showed that the network can map 10 input frames to the average of 100 within the permissible error margin of 0.1 pixels and furnish proper generalization to beam position movements not seen during training. The network can also perform better than the averaging technique when both techniques operate on small numbers of input frames such as 10 or 20.

show abstract

Section: Introductionmentioning

confidence: 99%

CNN to mitigate atmospheric turbulence effect on Shack-Hartmann Wavefront Sensing: A case study on the Magdalena Ridge Observatory Interferometer.

Siavash¹,

D.²,

Ramyaa³

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…We will outline up-to-date alignment schemes, requirements and component designs that have progressed since this system was described at SPIE meetings in 2018 3 and 2020. 4 We then report on several results of performance verification experiments for the two most important hardware components of the AAS. Finally we summarise near term plans for their remaining factory acceptance tests.…”

Section: Introductionmentioning

confidence: 99%

Factory acceptance of the automated alignment system for the Magdalena Ridge Observatory Interferometer

Luis

Buscher²,

Creech‐Eakman³

et al. 2022

Optical and Infrared Interferometry and Imaging VIII

View full text Add to dashboard Cite

The Magdalena Ridge Observatory Interferometer (MROI) will soon incorporate an Automated Alignment System (AAS) to help limit visibility losses due to beam misalignment to ∼1%. This paper focuses on two key AAS components: (1) a dual-wavelength beacon at each unit telescope and (2) a detector for measuring the shear and tilt of beams of light arriving from the telescopes in the beam combining laboratory. We share initial results of acceptance tests for these components. Finally, we outline a plan for fully validating their performance against a list of derived requirements.

show abstract

Deployment of beam alignment hardware at the Magdalena Ridge Observatory interferometer

Cited by 2 publications

References 0 publications

CNN to mitigate atmospheric turbulence effect on Shack-Hartmann Wavefront Sensing: A case study on the Magdalena Ridge Observatory Interferometer.

CNN to mitigate atmospheric turbulence effect on Shack-Hartmann Wavefront Sensing: A case study on the Magdalena Ridge Observatory Interferometer.

Factory acceptance of the automated alignment system for the Magdalena Ridge Observatory Interferometer

Contact Info

Product

Resources

About