Conference Agenda

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Extending single-photon detection capabilities into the mid-infrared is expected to have far-reaching implications for long-wavelength quantum optics, quantum and free-space communication, astronomy, environmental monitoring, and fundamental molecular sciences. We showcase the development of short-wave infrared (2.2-2.3 µm) and mid-wave infrared (3.0 µm) superconducting nanowire single-photon detectors (SNSPDs). In both wavelength ranges, we venture beyond state-of-the-art and achieve the best-reported system detection efficiencies and specific detectivity. We discuss the challenges in cryogenics, optics, and SNSPD design and use our mid-infrared single-photon detection to characterize emerging materials platforms and quantum emitters in a previously unattainable manner.

There is a growing interest in infrared technology for surveillance, military and space applications. Designs in infrared waveband have evolved taking advantage of new detector developments. New generation of High-Definition detectors allow for better performance and resolution. The increase in image field height, implies new challenges for designers to achieve aberration correction and unwanted light control. The need to use different fields of view and a rapid response to switch between different FOVs, increases the interest for continuous zoom in infrared. In such systems it is a significant challenge to control the parameters previously mentioned for all zoom positions. This paper presents a compact 10:1 optical zoom, with focal lengths from 20 to 200mm, F#2.8 in the 3.6-4.2µm waveband, with a 1280x1024 pixels, pixel pitch 7.5 µm cooled detector. The design consists in seven lenses. The optical system is able to focus at 25m near distance for SNFOV and 10m for WFOV. Athermalization ranging from -40ºC to 70ºC is achieved with an active focusing lens system.

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Wavefront shaping allows focusing and imaging at depth in disordered media such as biological tissues, exploiting the ability to control multiply scattered light. Many so-called guide-star mechanisms have been investigated to deliver light and image non-invasively, among which incoherent processes such as non-linear fluorescence feedback. However, the most common microscopy contrast mechanism, linear fluorescence, remains extremely challenging. I will discuss some of our recent works, exploiting signal processing and machine learning frameworks, to recover images behind scattering layers exploiting linear fluorescence.

Structured illumination microscopy (SIM) is a technique that employs non-uniform illumination to shift spatial frequencies that are normally unobservable into the region of the non-zero optical transfer function (OTF). Several images are combined to reconstruct these spatial frequencies, yielding up to twofold increase in resolution beyond the diffraction limit. However, the reconstruction process is affected by noise, and spatial frequencies can only be estimated with a certain precision and accuracy that depends on the procedure used. The spectral signal-to-noise ratio (SSNR) serves as an indicator of the possible quality of a reconstruction. Conventional SIM reconstruction is based on a least-squares estimate; while this approach yields high SSNR, it is performed in the Fourier domain and assumes uniform imaging conditions (illumination brightness, modulation depth, aberration coefficients) across the field of view (FOV). In large FOVs, this assumption is often violated, resulting in artifacts. An existing spatial-domain procedure produces low SSNR at high spatial frequencies, rendering these effectively unresolvable under low-light conditions. In this work, we present a local SIM reconstruction procedure with an order-of-magnitude higher SSNR. We demonstrate that it nearly achieves the SSNR of Fourier domain reconstruction, and we also show that further improvement is not possible.

Novel formulas have been derived for the primary spherical aberration, coma and axial color of systems of thin lenses in contact. Even in complex optical systems, groups of lenses can be modelled as thin lenses in contact. The new mathematical formalism helps explaining significant qualitative properties of the lens design landscape.

Distortion is a common annoyance in optical imaging. Learning from computer vision, many distortion correction algorithms are developed, mostly based on the Brown-Conrady model. An analysis of the field dependence of aberrations in terms of the zero aberration points in the field of view, the so-called nodes, provides another inroad to study distortion. Using the Nodal Aberration Theory, we show that the distortion field is the gradient of a scalar field. Structural changes in the distortion field are characterized by a complex sequence of creation, annihilation and reorganization of up to five nodes driven by tilt and decenter misalignments of the optical components. This description can be fruitfully applied in alignment protocols for complex optical systems, in image registration of multi-color localization microscopy, and of correlative light and electron microscopy.

Elevation topography equipment measures freeform surfaces by representing the surface with elevation maps, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature. From a geodetic point of view, every regular point on a parametric surface can be described as a function of the principal curvatures and the local torsion concerning a reference path at each point. Here, we present some fundamentals required to create these density maps to represent the absolute torsion and the local conic constant of all points on a regular freeform surface.

Photonic Ising machines leverage large-scale parallelism for solving large combinatorial problems, yet multiple minima hamper Metropolis-based algorithm. A double single-pixel detection approach enables adiabatic energetic transitions from nonlocal to local Hamiltonians, finding the ground state of complex landscapes.

I will show experimental results with nonlinear quadratic materials, in particular lithium niobate and barium titanate, for optical computing.

controlling light in complex media by wavefront shaping allows focusing and imaging, but it is also possible to control quantum states, such as indistinguishable photon pairs. I will discuss how one can control such states through a multimode fiber, and how it can be used for various tasks, ranging from emulating simple quasi-unitary circuits, to basic machine learning tasks, with a potential quantum advantage.

Light-based in-vivo brain imaging relies on light transport through highly scattering tissues over long distances. As scattering gradually reduces imaging contrast and resolution, visualising structures at greater depths becomes challenging, even when using multi-photon techniques. To overcome this limitation, minimally invasive endo-microscopy techniques have been developed that typically use graded-index rod lenses. A recently proposed alternative involves the exploitation of holographic control of light transport through multimode optical fibres [1], which promises superior imaging performance with less traumatic application [2]. Following the review of the fundamental and technological bases, the talk will introduce a 110µm thin laser-scanning endo-microscope, which enables volumetric imaging of the entire depth of the mouse brain in vivo [3]. The system is equipped with multi-wavelength detection and three-dimensional random-access options, and it has a lateral resolution of less than 1µm. Various modes of its application will be presented including the observations of fluorescently labelled neurons, their processes, and blood vessels. Finally, the use of the instrument for monitoring calcium signalling and measurements of blood flow in individual vessels at high speeds will be discussed.

[1] Nature communications 3.1, 1027 (2012).

[2] Light-Science & Applications 7, 92 (2018).

[3] Nature Communications, 14, 1897 (2023).

Optical sensors are limited to measuring intensity. For this reason, wavefront sensors need to convert phase information into intensity modulations. One method to achieve this involves using a Hartmann mask positioned near a camera sensor. This technique is compatible with low-coherence illumination and has been implemented using various encoding optical elements, such as arrays of holes or microlens arrays. For instance, high-resolution and quantitative phase imaging has been demonstrated using a diffraction grating, a method known as lateral shearing interferometry (LSI).

In this presentation, we will illustrate how LSI can also measure broadband speckle wavefields generated through multiple scattering media, enabling digital fluorescence phase conjugation through tissues. Additionally, we will present a generalization of LSI using a birefringent diffraction grating to perform polarimetric LSI of vector beams, which is relevant for optical metrology and polarization-resolved fluorescence microscopy. Finally, we will demonstrate that this generalized principle can be applied to single-shot hyperspectral wavefront sensing, leveraging the spectral dispersion of thin scattering media, with applications in the metrology of ultrashort lasers.

Optical fields’ polarimetry follows well-known principles in paraxial conditions where light polarization is manipulated in transverse planes. In non-paraxial optics such as microscopy imaging, complex media propagation or nanophotonics, it is however still a challenge that requires formalisms appropriate to 3D polarized fields. In this work, we present a few illustrations of how the analysis and control of polarized wavefronts in high numerical aperture microscopy provides access to 3D field’s properties at the nanoscale. We show that the point spread functions (PSFs) of dipole’s radiation through a microscope can be treated similarly to radiation sources possessing 3D-Stokes extensions to 2D paraxial Stokes parameters. By engineering phase and polarization through the detection path of a microscope, it is possible to encode, in a PSF, quantitative information on the 3D orientation of fluorescent single molecules, together with the knowledge of their averaged angular fluctuations (wobbling) and their 3D spatial localization at 10’s nm precision. We demonstrate an extension of PSF engineering to 3D nano-polarimetry to monitor polarization states in 3D (including spin and depolarization), scattered from metal nanoparticles. We finally show the advantages of general 3D Stokes decompositions to analyze polarization properties of light sources through an imaging system.