Quantum multiphoton microscopy utilizes quantum correlation effects of photons to improve the imaging quality of biological samples at low light illumination. Based on a N-photon NOON state, the microscopy imaging has been successfully demonstrated in recent two experiments, which shows the imaging quality better than that of coherent light illumination by a factor of
A binary-outcome photon counting measurement is employed in present work, where the detection event with equal number of photons is a measurement outcome. All the other detection events are treated as another outcome. Starting from general principle of quantum metrology, we first calculate the Fisher information and the Cramer-Rao lower bound (CRB) of the phase sensitivity, which determine the enhancement factor of the imaging quality for the N-photon twin-Fock states. Then, we derive the phase distribution (the likelihood function) and the maximum likelihood estimator (MLE) by considering the binary-outcome measurements. Using Monte Carlo method, we simulate the measurement probabilities of the six-photon twin-Fock state and the single-photon state, where the experimental imperfection is added artificially. The microscopy imaging is reconstructed using numerical result of the MLE. Finally, we derive the likelihood function and show the microscopy imaging for a combination of two binary-outcome measurements with and without an offset phase shift.
Regardless of the specific model, we first prove analytically that the likelihood functions of single and two groups of binary-outcome photon counting measurements can approximate a Gaussian function, the maximum likelihood estimator is asymptotically unbiased which can saturate the lower limit of phase measurement of the above two measurement schemes. Based on the six-photon twin-Fock state, this paper studies the maximum likelihood estimator and phase sensitivity of the binary-outcome photon counting measurements, and reconstructs the two-dimensional microscopy imaging of the birefringent sample with the MLE. Our results show that a combination of binary-outcome photon counting measurements can avoid the divergence of phase sensitivity at dark spots, thus overcoming the speckle problem of microscopy imaging. The maximum likelihood estimator at each pixel in the reconstructed image is close to the optimal phase working point, and the overall quality factor of the image is measured by the root-mean-square error of the estimator.