What Is the Correct Way to Apply Richarson Lucy Deconvolution to Luminance Data?
I think the answer is in Jim Kasson's Post (The Zone System and Digital Cameras) you linked to:

If you are only moderately familiar with the Zone System, you may be asking yourself about the utility of recording light brighter than 100% reflectance. The 100% reflectance calibration assumes a matte subject with perfectly Lambertian reflectance. The higher light levels occur when the subject has some specularity or gloss to it. Water is a classic, and photographically-important example. Metals, glass, plastics, skin, stone and many paints are also often far from Lambertian. So we often need the headroom to accommodate those materials.
All of the above assumes that the camera is calibrated using UniWB, and that the UniWB hack works perfectly to predict raw file values. However, UniWB never achieved much penetration among digital camera users, and I think the number of users is waning today as cameras get more and more dynamic range, so it’s worthwhile looking at what happens with widely-used camera setups.

So the model to of Reflectance and the actual number of photons the sensors is exposed to are linear only if the camera is behaving according to UniWB Model (See also Guillermo Luijk - UniWB Tutorial) and the material used is indeed perfectly Lambertian.
Both probably doesn't hold and create some non linear effects.
CMOS / CCD Sensors are indeed linear in their response (At least before they are clipped).
So, given a RAW data with Linear Demosaicing (Pay attention that some algorithms may be non linear in this step) you can indeed apply the Lucy Richardson Convolution on the data.
Pay attention that LAB Color Space is a non linear transformation of the RGB colors (even without the Gamma Correction).
So I'd apply the deconvolution in the following order:

Demosaic RAW Data.
Convert data into YCbCr Color Space (Or similar) which decompose the colors into luminosity and color data with Linear Transformation.
Apply the deconvolution on the Y channel.
Convert back to RGB based color space.