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Register a new userSuper-resolution microscopy of single rare-earth emitters
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We demonstrate super-resolution imaging of single rare-earth emitting centers, namely, trivalent cerium, in yttrium aluminum garnet (YAG) crystals by means of stimulated emission depletion (STED) microscopy. The achieved all-optical resolution is $approx$ 80nm. Similar results were obtained on H3 color centers in diamond with resolution of $approx$ 60nm. In both cases, STED resolution is improving slower than the inverse square-root of the depletion beam intensity. This is caused by excited state absorption (ESA) and interaction of the emitter with non-fluorescing crystal defects in its near surrounding.
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One of the main characteristics of optical imaging systems is the spatial resolution, which is restricted by the diffraction limit to approximately half the wavelength of the incident light. Along with the recently developed classical super-resolution techniques, which aim at breaking the diffraction limit in classical systems, there is a class of quantum super-resolution techniques which leverage the non-classical nature of the optical signals radiated by quantum emitters, the so-called antibunching super-resolution microscopy. This approach can ensure a factor of $sqrt{n}$ improvement in the spatial resolution by measuring the n-th order autocorrelation function. The main bottleneck of the antibunching super-resolution microscopy is the time-consuming acquisition of multi-photon event histograms. We present a machine learning-assisted approach for the realization of rapid antibunching super-resolution imaging and demonstrate 12 times speed-up compared to conventional, fitting-based autocorrelation measurements. The developed framework paves the way to the practical realization of scalable quantum super-resolution imaging devices that can be compatible with various types of quantum emitters.
Super-resolution fluorescence microscopy is an important tool in biomedical research for its ability to discern features smaller than the diffraction limit. However, due to its difficult implementation and high cost, the universal application of super-resolution microscopy is not feasible. In this paper, we propose and demonstrate a new kind of super-resolution fluorescence microscopy that can be easily implemented and requires neither additional hardware nor complex post-processing. The microscopy is based on the principle of stepwise optical saturation (SOS), where $M$ steps of raw fluorescence images are linearly combined to generate an image with a $sqrt{M}$-fold increase in resolution compared with conventional diffraction-limited images. For example, linearly combining (scaling and subtracting) two images obtained at regular powers extends resolution by a factor of $1.4$ beyond the diffraction limit. The resolution improvement in SOS microscopy is theoretically infinite but practically is limited by the signal-to-noise ratio. We perform simulations and experimentally demonstrate super-resolution microscopy with both one-photon (confocal) and multiphoton excitation fluorescence. We show that with the multiphoton modality, the SOS microscopy can provide super-resolution imaging deep in scattering samples.
Terahertz subwavelength imaging aims at developing THz microscopes able to resolve deeply subwavelength features. To improve the spatial resolution beyond the diffraction limit, a current trend is to use various subwavelength probes to convert the near-field to the far-field. These techniques, while offering significant gains in spatial resolution, inherently lack the ability to rapidly obtain THz images due to the necessity of slow pixel-by-pixel raster scan and often suffer from low light throughput. In parallel, in the visible spectral range, several super-resolution imaging techniques were developed that enhance the image resolution by recording and statistically correlating multiple images of an object backlit with light from stochastically blinking fluorophores. Inspired by this methodology, we develop a Super-resolution Orthogonal Deterministic Imaging (SODI) technique and apply it in the THz range. Since there are no natural THz fluorophores, we use optimally designed mask sets brought in proximity with the object as artificial fluorophores. Because we directly control the form of the masks, rather than relying on statistical averages, we aim at employing the smallest possible number of frames. After developing the theoretical basis of SODI, we demonstrate the second-order resolution improvement experimentally using phase masks and binary amplitude masks with only 8 frames. We then numerically show how to extend the SODI technique to higher orders to further improve the resolution. As our formulation is based on the equation of linear imaging and it uses spatial modulation of either the phase or the amplitude of the THz wave, our methodology can be readily adapted for the use with existing phase-sensitive single pixel imaging systems or any amplitude sensitive THz imaging arrays.
Spatial resolution is one of the most important specifications of an imaging system. Recent results in quantum parameter estimation theory reveal that an arbitrarily small distance between two incoherent point sources can always be efficiently determined through the use of a spatial mode sorter. However, extending this procedure to a general object consisting of many incoherent point sources remains challenging, due to the intrinsic complexity of multi-parameter estimation problems. Here, we generalize the Richardson-Lucy (RL) deconvolution algorithm to address this challenge. We simulate its application to an incoherent confocal microscope, with a Zernike spatial mode sorter replacing the pinhole used in a conventional confocal microscope. We test different spatially incoherent objects of arbitrary geometry, and we find that the resolution enhancement of sorter-based microscopy is on average over 30% higher than that of a conventional confocal microscope using the standard RL deconvolution algorithm. Our method could potentially be used in diverse applications such as fluorescence microscopy and astronomical imaging.
Based on compressive sampling techniques and short exposure imaging, super-resolution imaging with thermal light is experimentally demonstrated exploiting the sparse prior property of images for standard conventional imaging system. Differences between super-resolution imaging demonstrated in this letter and super-resolution ghost imaging via compressive sampling (arXiv. Quant-ph/0911.4750v1 (2009)), and methods to further improve the imaging quality are also discussed.
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