Fig. 1

In any image, the number of detected probe particles is fundamentally limited, either due to finite acquisition times or  probe-induced sample damage. In order to optimize the sensitivity of a microscope, the information that can be extracted from each detected probe particle has to be maximized.  We achieve this by employing cavity enhancement (multi-pass microscopy, see fig 1 and [1]), quantum enhancement, and wave-front shaping techniques.

[1] Multi-pass microscopy; T. Juffmann, B. B. Klopfer, T. L.I. Frankort, P. Haslinger & M. A. Kasevich; Nature Communications, Vol. 7, 12858 (2016)

Fig. 2

One prominent example where this becomes important is cryogenic electron microscopy. Images have to be taken at low electron dose to avoid sample damage, at which point shot-noise (the statistical fluctuations in the number of detected electrons) and the small signal limit the achievable spatial resolution. In order to solve the atomic structure of a protein, tens of thousands of images have to be averaged to obtain one image of sufficient signal to noise. While this method had enormous impact on our understanding of biology (2017 Nobel Prize in Chemistry), it cannot be applied to small proteins, or to proteins that exist in various folding configurations, due to insufficient signal-to-noise. This is a severe limitation given that misfoldings indicate, or cause, several diseases. Cavity and quantum enhanced measurement techniques can alleviate this problem, potentially reducing probe induced sample damage by more than one order of magnitude (see fig. 2 and [2]).

[2] Multi-pass transmission electron microscopy; T. Juffmann, S. A. Koppell, B. B. Klopfer, C. Ophus, R. M. Glaeser & M. A. Kasevich; Scientific Reports, Vol. 7, 1699 (2017)