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Biomedical Optics Express

Decoherence of photon entanglement by transmission through brain tissue with Alzheimer’s disease

Enrique J. Galvez, Baibhav Sharma, F. K. Williams, Chan Ju You, Behzad Khajavi, J. Castrillón, Lingyan Shi, Sandra Mamani, Laura A. Sordillo, L. Zhang, R. R. Alfano

Published Nov 14, 2022• 9 citations
Publisher

Abstract

The generation, manipulation and quantification of non-classical light, such as quantum-entangled photon pairs, differs significantly from methods with classical light. Thus, quantum measures could be harnessed to give new information about the interaction of light with matter. In this study we investigate if quantum entanglement can be used to diagnose disease. In particular, we test whether brain tissue from subjects suffering from Alzheimer's disease can be distinguished from healthy tissue. We find that this is indeed the case. Polarization-entangled photons traveling through brain tissue lose their entanglement via a decohering scattering interaction that gradually renders the light in a maximally mixed state. We found that in thin tissue samples (between 120 and 600 micrometers) photons decohere to a distinguishable lesser degree in samples with Alzheimer's disease than in healthy-control ones. Thus, it seems feasible that quantum measures of entangled photons could be used as a means to identify brain samples with the neurodegenerative disease.

DOI
10.1364/boe.474469

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Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.
Photon entanglement, a key feature of quantum correlations, provides a level of coherence absent in classical correlations, potentially offering new information when interacting with biological matter. One promising application is using entanglement decoherence to distinguish between healthy and diseased samples. However, achieving this requires efficient entangled photon sources capable of surviving through biological samples for reliable detection. In this work, we show the applicability of a polarization-entangled photon source as a label-free diagnostic tool for distinguishing between transgenic mouse models of amyloidosis and tauopathy and their respective control strains. We investigated cortical and hippocampal regions of these models, and our findings revealed greater preservation of entanglement in the transgenic samples compared to controls. To further enhance classification accuracy, we employed a supervised machine learning approach, achieving reliable distinctions between disease and control groups in unseen test samples. The quantum-based results were further validated through confocal imaging of the transgenic and control samples. These findings suggest that quantum sensing could serve as a label-free approach for distinguishing biological samples, with potential applications in the study of neurodegenerative disorders.
We investigated the preservation of non-local correlations between polarization-entangled photons when one of them traveled through brain tissue slices of different thicknesses. Using down-converted photons at a wavelength of 802 nm minimized the absorption by the tissue. After the light passed through the tissue samples, we performed quantum state tomography to obtain quantitative measures of the entanglement. We found that entanglement is preserved to a surprising degree, and when it degrades, it does so following a particular path in a tangle versus linear-entropy graph. Such a trajectory reveals direct transfer of probability from entangled to mixed state.
Photon entanglement, a key feature of quantum correlations, provides a level of coherence absent in classical correlations, potentially offering new information when interacting with biological matter. One promising application is using entanglement decoherence to distinguish between healthy and diseased samples. However, achieving this requires efficient entangled photon sources capable of surviving through biological samples for reliable detection. In this work, we show the applicability of a polarization-entangled photon source as a label-free diagnostic tool for distinguishing between transgenic mouse models of amyloidosis and tauopathy and their respective control strains. We investigated cortical and hippocampal regions of these models, and our findings revealed greater preservation of entanglement in the transgenic samples compared to controls. To further enhance classification accuracy, we employed a supervised machine learning approach, achieving reliable distinctions between disease and control groups in unseen test samples. The quantum-based results were further validated through confocal imaging of the transgenic and control samples. These findings suggest that quantum sensing could serve as a label-free approach for distinguishing biological samples, with potential applications in the study of neurodegenerative disorders.