No abstract

Measuring temperature in nanoscale spatial resolution either at or far from equilibrium is of importance in many scientific and technological applications. Although negatively charged nitrogen-vacancy (NV(-)) centers in diamond have recently emerged as a promising nanometric temperature sensor, the technique has been applied only under steady state conditions so far. Here, we present a three-point sampling method that allows real-time monitoring of the temperature changes over ±100 K and a pump-probe-type experiment that enables the study of nanoscale heat transfer with a temporal resolution of better than 10 μs. The utility of the time-resolved luminescence nanothermometry was demonstrated with 100 nm fluorescent nanodiamonds spin-coated on a glass substrate and submerged in gold nanorod solution heated by a near-infrared laser, and the validity of the measurements was verified with finite-element numerical simulations. The combined theoretical and experimental approaches will be useful to implement time-resolved temperature sensing in laser processing of materials and even for devices in operation at the nanometer scale.

Abstract:We demonstrate the use of phase-space imaging for 3D localization of multiple point sources inside scattering material. The effect of scattering is to spread angular (spatial frequency) information, which can be measured by phase space imaging. We derive a multi-slice forward model for homogenous volumetric scattering, then develop a reconstruction algorithm that exploits sparsity in order to further constrain the problem. By using 4D measurements for 3D reconstruction, the dimensionality mismatch provides significant robustness to multiple scattering, with either static or dynamic diffusers. Experimentally, our high-resolution 4D phase-space data is collected by a spectrogram setup, with results successfully recovering the 3D positions of multiple LEDs embedded in turbid scattering media.

Multiple scattering of an electromagnetic wave as it passes through an object is a fundamental problem that limits the performance of current imaging systems. In this paper, we describe a new technique-called Series Expansion with Accelerated Gradient Descent on Lippmann-Schwinger Equation (SEAGLE)-for robust imaging under multiple scattering based on a combination of a new nonlinear forward model and a total variation (TV) regularizer. The proposed forward model can account for multiple scattering, which makes it advantageous in applications where linear models are inaccurate. Specifically, it corresponds to a series expansion of the scattered wave with an accelerated-gradient method. This expansion guarantees the convergence even for strongly scattering objects. One of our key insights is that it is possible to obtain an explicit formula for computing the gradient of our nonlinear forward model with respect to the unknown object, thus enabling fast image reconstruction with the state-of-the-art fast iterative shrinkage/thresholding algorithm (FISTA). The proposed method is validated on both simulated and experimentally measured data.