Artificial Intelligence in Classical and Quantum Photonics

The last decades saw a huge rise of artificial intelligence (AI) as a powerful tool to boost industrial and scientific research in a broad range of fields. AI and photonics are developing a promising two-way synergy: on the one hand, AI approaches can be used to control a number of complex linear and nonlinear photonic processes, both in the classical and quantum regimes; on the other hand, photonics can pave the way for a new class of platforms to accelerate AI-tasks. This review provides the reader with the fundamental notions of machine learning (ML) and neural networks (NNs) and presents the main AI applications in the fields of spectroscopy and chemometrics, computational imaging (CI), wavefront shaping and quantum optics. The review concludes with an overview of future developments of the promising synergy between AI and photonics

Comparing Transmission- and Epi-BCARS: A Transnational Round Robin on Solid State Materials

Broadband coherent anti-Stokes Raman scattering (BCARS) is an advanced Raman spectroscopy method that combines the spectral sensitivity of spontaneous Raman scattering (SR) with the increased signal intensity of single-frequency coherent Raman techniques. These two features make BCARS particularly suitable for ultra-fast imaging of heterogeneous samples, as already shown in biomedicine. Recent studies demonstrated that BCARS also shows exceptional spectroscopic capabilities when inspecting crystalline materials like lithium niobate and lithium tantalate, and can be used for fast imaging of ferroelectric domain walls. These results strongly suggest the extension of BCARS towards new imaging applications like mapping defects, strain, or dopant levels, similar to standard SR imaging. Despite these advantages, BCARS suffers from a spurious and chemically unspecific non-resonant background (NRB) that distorts and shifts the Raman peaks. Post-processing numerical algorithms are then used to remove the NRB and to obtain spectra comparable to SR results. Here, we show the reproducibility of BCARS by conducting an internal Round Robin with two different BCARS experimental setups, comparing the results on different crystalline materials of increasing structural complexity: diamond, 6H-SiC, KDP, and KTP. First, we compare the detected and phase-retrieved signals, the setup-specific NRB-removal steps, and the mode assignment. Subsequently, we demonstrate the versatility of BCARS by showcasing how the selection of pump wavelength, pulse width, and detection geometry can be tailored to suit the specific objectives of the experiment. Finally, we compare and optimize measurement parameters for the high-speed, hyperspectral imaging of ferroelectric domain walls in lithium niobate.Comment: 12 pages, 8 figure

Deep ensemble learning and transfer learning methods for classification of senescent cells from nonlinear optical microscopy images

The success of chemotherapy and radiotherapy anti-cancer treatments can result in tumor suppression or senescence induction. Senescence was previously considered a favorable therapeutic outcome, until recent advancements in oncology research evidenced senescence as one of the culprits of cancer recurrence. Its detection requires multiple assays, and nonlinear optical (NLO) microscopy provides a solution for fast, non-invasive, and label-free detection of therapy-induced senescent cells. Here, we develop several deep learning architectures to perform binary classification between senescent and proliferating human cancer cells using NLO microscopy images and we compare their performances. As a result of our work, we demonstrate that the most performing approach is the one based on an ensemble classifier, that uses seven different pre-trained classification networks, taken from literature, with the addition of fully connected layers on top of their architectures. This approach achieves a classification accuracy of over 90%, showing the possibility of building an automatic, unbiased senescent cells image classifier starting from multimodal NLO microscopy data. Our results open the way to a deeper investigation of senescence classification via deep learning techniques with a potential application in clinical diagnosis

Fingerprint multiplex CARS at high speed based on supercontinuum generation in bulk media and deep learning spectral denoising

We introduce a broadband coherent anti-Stokes Raman scattering (CARS) microscope based on a 2-MHz repetition rate ytterbium laser generating 1035-nm high-energy (≈µJ level) femtosecond pulses. These features of the driving laser allow producing broadband red-shifted Stokes pulses, covering the whole fingerprint region (400-1800 cm-1), employing supercontinuum generation in a bulk crystal. Our system reaches state-of-the-art acquisition speed (<1 ms/pixel) and unprecedented sensitivity of ≈14.1 mmol/L when detecting dimethyl sulfoxide in water. To further improve the performance of the system and to enhance the signal-to-noise ratio of the CARS spectra, we designed a convolutional neural network for spectral denoising, coupled with a post-processing pipeline to distinguish different chemical species of biological tissues

Noninvasive morpho-molecular imaging reveals early therapy-induced senescence in human cancer cells

Anticancer therapy screening in vitro identifies additional treatments and improves clinical outcomes. Systematically, although most tested cells respond to cues with apoptosis, an appreciable portion enters a senescent state, a critical condition potentially driving tumor resistance and relapse. Conventional screening protocols would strongly benefit from prompt identification and monitoring of therapy-induced senescent (TIS) cells in their native form. We combined complementary all-optical, label-free, and quantitative microscopy techniques, based on coherent Raman scattering, multiphoton absorption, and interferometry, to explore the early onset and progression of this phenotype, which has been understudied in unperturbed conditions. We identified TIS manifestations as early as 24 hours following treatment, consisting of substantial mitochondrial rearrangement and increase of volume and dry mass, followed by accumulation of lipid vesicles starting at 72 hours. This work holds the potential to affect anticancer treatment research, by offering a label-free, rapid, and accurate method to identify initial TIS in tumor cells

Full-Spectrum CARS Microscopy of Cells and Tissues with Ultrashort White-Light Continuum Pulses

Coherent anti-StokesRaman scattering (CARS) microscopyis an emergingnonlinear vibrational imaging technique that delivers label-free chemicalmaps of cells and tissues. In narrowband CARS, two spatiotemporallysuperimposed picosecond pulses, pump and Stokes, illuminate the sampleto interrogate a single vibrational mode. Broadband CARS (BCARS) combinesnarrowband pump pulses with broadband Stokes pulses to record broadvibrational spectra. Despite recent technological advancements, BCARSmicroscopes still struggle to image biological samples over the entireRaman-active region (400-3100 cm(-1)). Here,we demonstrate a robust BCARS platform that answers this need. Oursystem is based on a femtosecond ytterbium laser at a 1035 nm wavelengthand a 2 MHz repetition rate, which delivers high-energy pulses usedto produce broadband Stokes pulses by white-light continuum generationin a bulk YAG crystal. Combining such pulses, pre-compressed to sub-20fs duration, with narrowband pump pulses, we generate a CARS signalwith a high (<9 cm(-1)) spectral resolution inthe whole Raman-active window, exploiting both the two-color and three-colorexcitation mechanisms. Aided by an innovative post-processing pipeline,our microscope allows us to perform high-speed (approximate to 1 ms pixeldwell time) imaging over a large field of view, identifying the mainchemical compounds in cancer cells and discriminating tumorous fromhealthy regions in liver slices of mouse models, paving the way forapplications in histopathological settings

Label-free multimodal nonlinear optical microscopy reveals features of bone composition in pathophysiological conditions

Bone tissue features a complex microarchitecture and biomolecular composition, which determine biomechanical properties. In addition to state-of-the-art technologies, innovative optical approaches allowing the characterization of the bone in native, label-free conditions can provide new, multi-level insight into this inherently challenging tissue. Here, we exploited multimodal nonlinear optical (NLO) microscopy, including co-registered stimulated Raman scattering, two-photon excited fluorescence, and second-harmonic generation, to image entire vertebrae of murine spine sections. The quantitative nature of these nonlinear interactions allowed us to extract accurate biochemical, morphological, and topological information on the bone tissue and to highlight differences between normal and pathologic samples. Indeed, in a murine model showing bone loss, we observed increased collagen and lipid content as compared to the wild type, along with a decreased craniocaudal alignment of bone collagen fibres. We propose that NLO microscopy can be implemented in standard histopathological analysis of bone in preclinical studies, with the ambitious future perspective to introduce this technique in the clinical practice for the analysis of larger tissue sections

Functional analysis of photosynthetic pigment binding complexes in the green alga Haematococcus pluvialis reveals distribution of astaxanthin in Photosystems

Astaxanthin is a ketocarotenoid produced by photosynthetic microalgae. It is a pigment of high industrial interest in acquaculture, cosmetics, and nutraceutics due to its strong antioxidant power. Haematococcus pluvialis, a fresh-water microalga, accumulates high levels of astaxanthin upon oxidative stress, reaching values up to 5% per dry weight. H. pluvialis accumulates astaxanthin in oil droplets in the cytoplasm, while the chloroplast volume is reduced. In this work, we investigate the biochemical and spectroscopic properties of the H. pluvialis pigment binding complexes responsible for light harvesting and energy conversion. Our findings demonstrate that the main features of chlorophyll and carotenoid binding complexes previously reported for higher plants or Chlamydomonas reinhardtii are preserved under control conditions. Transition to astaxanthin rich cysts however leads to destabilization of the Photosystems. Surprisingly, astaxanthin was found to be bound to both Photosystem I and II, partially substituting β-carotene, and thus demonstrating possible astaxanthin biosynthesis in the plastids or transport from the cytoplasm to the chloroplast. Astaxanthin binding to Photosystems does not however improve their photoprotection, but rather reduces the efficiency of excitation energy transfer to the reaction centers. We thus propose that astaxanthin binding partially destabilizes Photosystem I and II

Broadband stimulated Raman imaging based on multi-channel lock-in detection for spectral histopathology

Spontaneous Raman microscopy reveals the chemical composition of a sample in a label-free and non-invasive fashion by directly measuring the vibrational spectra of molecules. However, its extremely low cross section prevents its application to fast imaging. Stimulated Raman scattering (SRS) amplifies the signal by several orders of magnitude thanks to the coherent nature of the nonlinear process, thus unlocking high-speed microscopy applications that provide analytical information to elucidate biochemical mechanisms with subcellular resolution. Nevertheless, in its standard implementation, narrowband SRS provides images at only one frequency at a time, which is not sufficient to distinguish constituents with overlapping Raman bands. Here, we report a broadband SRS microscope equipped with a home-built multichannel lock-in amplifier simultaneously measuring the SRS signal at 32 frequencies with integration time down to 44 μs, allowing for detailed, high spatial resolution mapping of spectrally congested samples. We demonstrate the capability of our microscope to differentiate the chemical constituents of heterogeneous samples by measuring the relative concentrations of different fatty acids in cultured hepatocytes at the single lipid droplet level and by differentiating tumor from peritumoral tissue in a preclinical mouse model of fibrosarcoma