Simulation and Optimization of an Astrophotonic Reformatter

Abstract

Image slicing is a powerful technique in astronomy. It allows the instrument designer to reduce the slit width of the spectrograph, increasing spectral resolving power whilst retaining throughput. Conventionally this is done using bulk optics, such as mirrors and prisms, however more recently astrophotonic components known as photonic lanterns (PLs) and photonic reformatters have also been used. These devices reformat the multi-mode (MM) input light from a telescope into single-mode (SM) outputs, which can then be re-arranged to suit the spectrograph. The photonic dicer (PD) is one such device, designed to reduce the dependence of spectrograph size on telescope aperture and eliminate modal noise. We simulate the PD, by optimising the throughput and geometrical design using Soapy and BeamProp. The simulated device shows a transmission between 8 and 20 %, depending upon the type of adaptive optics (AO) correction applied, matching the experimental results well. We also investigate our idealised model of the PD and show that the barycentre of the slit varies only slightly with time, meaning that the modal noise contribution is very low when compared to conventional fibre systems. We further optimise our model device for both higher throughput and reduced modal noise. This device improves throughput by 6.4 % and reduces the movement of the slit output by 50%, further improving stability. This shows the importance of properly simulating such devices, including atmospheric effects. Our work complements recent work in the field and is essential for optimising future photonic reformatters.

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Cited by in corpus (6)

• Final Design and On-Sky Testing of the iLocater SX Acquisition Camera: Broadband Single-Mode Fiber Coupling
• Design considerations of photonic lanterns for diffraction-limited spectrometry
• A Radial Velocity Error Budget for Single-mode Fiber Doppler Spectrographs
• 3D-M3: High-spatial resolution spectroscopy with extreme AO and 3D printed micro-lenslets
• Modal noise mitigation for high-precision spectroscopy using a photonic reformatter
• Learning the Lantern: Neural network applications to broadband photonic lantern modelling