A universal loss-limited optimum for fixed multi-pass quantum sensing per absorbed photon

Abstract: Multi-pass schemes send a photon through a sample several times to learn more about it. When the sample rather than the light is scarce, the natural figure of merit is the information gained per photon the object absorbs. We show that one constant fixes the loss-limited optimum of every fixed scheme in which a single photon passes repeatedly through the sample and is detected once at the end. Three properties suffice: information that grows as the square of the pass number, a fixed survival probability per pass, and no dose from a photon already lost. They force a single trade-off function $h(x)=x<sup>2/(e<sup>x-1)$, where $x$ is the number of passes times the loss per pass. Its maximum, 0.648, sits at $x_{\mathrm{opt}}=1.594$. The loss-limited ceiling of interaction-free interrogation and the multi-pass phase optimum of Yu et al. are two instances. Phase sensing of a weakly absorbing object is a third, optimal at $m_{\mathrm{opt}}=x_{\mathrm{opt}}/(ε+α)$ passes; the absorption $α$ and the parasitic loss $ε$ enter the optimum only through their sum, but the damage counts only $α$. N00N states and their loss-robust generalisations do worse per absorbed photon, and optimising over photon number and pass number together returns a single recycled photon. Two further problems are priced in the same measure. Absorption estimation gains nothing, for any scheme. Detecting a faint companion below the Rayleigh limit costs the companion a dose that does not depend on its faintness, while under direct imaging the dose grows without bound. For a fragile sample the gentlest measurement is also the simplest one: a single photon, recycled.