Temperature is one of the most relevant parameters for the regulation of intracellular processes. Measuring localized subcellular temperature gradients is fundamental for a deeper understanding of cell function, such as the genesis of action potentials, and cell metabolism.
In this work I will review our latest progresses in NV-based thermometry ultimately leading to the first localized temperature increase detection in a firing neuronal network with precision under 0.1 K.
We report on a robust method for reconstructing multi-mode optical fields. In particular, our method correctly identifies the number and types of modes as well as each mode’s energy, which we demonstrated experimentally. Our method uses multidetector trees and both high-order autocorrelation functions of detected photons (the Glauber function) and high-order autocorrelation functions of no-photon detection. Here we show successful reconstruction for classical and nonclassical multimode fields that contain up to 4 modes whose types are not disclosed to the reconstruction algorithm. This method is significantly more successful than the previously reported one, based on high-order Glauber functions only.
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