Quantum imaging of biological organisms through spatial and polarization entanglement

Abstract

Quantum imaging holds potential benefits over classical imaging but has faced challenges such as poor signal-to-noise ratios, low resolvable pixel counts, difficulty in imaging biological organisms, and inability to quantify full birefringence properties. Here, we introduce quantum imaging by coincidence from entanglement (ICE), using spatially and polarization-entangled photon pairs to overcome these challenges. With spatial entanglement, ICE offers higher signal-to-noise ratios, greater resolvable pixel counts, and the ability to image biological organisms. With polarization entanglement, ICE provides quantitative quantum birefringence imaging capability, where both the phase retardation and the principal refractive index axis angle of an object can be remotely and instantly quantified without changing the polarization states of the photons incident on the object. Furthermore, ICE enables 25 times greater suppression of stray light than classical imaging. ICE has the potential to pave the way for quantum imaging in diverse fields, such as life sciences and remote sensing.

Fig. 1.. Experimental setup and SSN signal retrieval.

(A) Setup schematics. CW, continuous wave; GL, Glan-Laser polarizer; HWP, half-wave plate; QP, quartz plate; BBO, β-barium borate crystals; LPF, long-pass filter; PBS, polarizing beam splitter; BPF, band-pass filter; SPCM, single-photon counting module. Inset, illustration of the entanglement pinhole. (B) Signal N_s, idler N_i, and coincidence N_c counts acquired from a series of trials. (C) Transmittance of the object experimentally measured using the ratio (eq. S2), optimized subtraction (eq. S4), and CoV (eq. S8) algorithms with N_s and N_i. (D) Histograms of the transmittance measured in (C). (E) Transmittance of the object experimentally measured using the ratio, optimized subtraction, and CoV algorithms with N_c and N_i. (F) Histograms of the transmittance measured in (E).

Fig. 2.. Effect of the entanglement pinhole on ICE.

(A and B) Classical imaging and ICE of a USAF resolution target at focus (A) and at different z positions (B), where z = 0 mm denotes the focus of classical imaging. (C) ESFs, LSFs, and spatial resolutions measured at different z positions. The ESFs were fitted from the profiles along the yellow dotted lines in (A). The means and SEs of the resolution are shown on the right. (D) Resolution versus z for classical imaging and ICE. Dots represent experimental measurements. Solid and dash-dotted lines denote fits. Norm., normalized. Scale bars, 50 μm.

Fig. 3.. ICE of carbon fibers embedded in thick agarose.

(A) Classical and ICE images of carbon fibers embedded in agarose at different z positions. Profiles along the yellow dotted lines are plotted in the close-ups to compare the spatial resolutions. (B) Average of the stacks in (A). Scale bars, 100 μm.

Fig. 4.. ICE of a mouse brain slice.

(A and B) Classical (A) and ICE (B) images of a hematoxylin and eosin–stained mouse brain slice. ANcr, cerebellar hemisphere ansiform lobule crus; arb, arbor vitae; CENT, cerebellar vermis central lobule; CUL, cerebellar vermis culmen; FL, cerebellar hemisphere flocculus; GRN, gigantocellular reticular nucleus; PFL, cerebellar hemisphere paraflocculus; SIM, cerebellar hemisphere simple lobule. (C) Regions of interest (ROIs) denoted by the cyan rectangles in (A) and (B). (D) Profiles along the yellow dotted lines in (C). (E) ROIs denoted by the orange rectangles in (A) and (B). (F) Profiles along the yellow dotted lines in (E). Scale bars, 200 μm.

Fig. 5.. ICE in the presence of stray light.

(A) Classical and ICE images of a whole zebrafish in the presence of stray light. The pseudo-colors encode the z positions of the sample. Scale bars, 200 μm. (B) Classical and ICE images of carbon fibers acquired at different stray light optical powers. Scale bars, 100 μm. (C) Top: SSIM calculated between the images in (B) and the ones without the stray light. Black dashed line, a threshold (SSIM = 0.1) used to quantify the robustness of ICE and classical imaging. Bottom: Difference between the SSIM curves for ICE and classical imaging.

Fig. 6.. Quantitative quantum birefringence imaging of a whole zebrafish with ICE.

(A) ICE images acquired with a polarizer of a constant angle α and a polarizer of a variable angle β. (B) Transmittance (T) and principal refractive index axis angle (pseudo-colors) calculated using the ICE images in (A). (C) Transmittance (T) and phase retardation between the two refractive index axes (lines and pseudo-colors) calculated using the ICE images in (A). Scale bars, 200 μm.