Correlated phenomena play a central role in condensed matter physics, but in many cases there are no tools available that allow for measurements of correlations at the relevant length scales (nanometers - microns). We have recently demonstrated that nitrogen vacancy (NV) centers in diamond can be used as point sensors for measuring two-point magnetic field correlators [1]. NV centers are atom-scale defects that can be used to sense magnetic fields with high sensitivity and spatial resolution. Typically, the magnetic field is measured by averaging sequential measurements of single NV centers, or by spatial averaging over ensembles of many NV centers, which provides mean values that contain no nonlocal information about the relationship between two points separated in space or time. We recently proposed and implemented a sensing modality whereby two or more NV centers are measured simultaneously, from which we extract temporal and spatial correlations in their signals that would otherwise be inaccessible. We demonstrate measurements of correlated applied noise using spin-to-charge readout of two NV centers and implement a spectral reconstruction protocol for disentangling local and nonlocal noise sources. This novel quantum sensing platform will allow us to measure new physical quantities that are otherwise inaccessible with current tools, particularly in condensed matter systems where two-point correlators can be used to characterize charge transport, magnetism, and non-equilibrium dynamics.

Diamond offers unique opportunities for applications in photonics, essentially because its very large band-gap leads to a wide transparency window and to the availability of numerous color centers. However, it is still challenging to obtain scalable and reproducible optoelectronics based on these defects. An important aspect in this respect is represented by the feasibility of electroluminescence devices, which combine diamond electronics with the photo-physics of color centers. Here, we demonstrate electrically-driven light emission from color centers based on a phosphorous-doped diamond Schottky diodes. Compared to conventional p-i-n systems, our approach simplifies the fabrication process, and it promotes the implementation of novel light sources based on diamond.

The negatively charged nitrogen-vacancy color center in diamond has been identified as a sensitive magnetic field sensor based on the optically detected magnetic resonance (ODMR). However, it requires knowledge of the crystal axes and it needs an external magnetic bias field to measure the field’s orientation, or the use of single centers. Recently, by combining ensembles of color centers with polarimetry, we have been able to determine the magnitude and direction of an unknown magnetic field. The out-of-plane polarization components of the excitation laser create asymmetry in the polarization resolved ODMR spectrum. This provides the necessary conditions to reconstruct the three-dimensional magnetic field vector without a bias field. Our approach is general for other spin-1 color centers with the same symmetry, and it is compatible with standard microscopy methods, such as scanning probe, super-resolution, confocal, and wide-field imaging.

Spectrally broadened ensembles of rare-earth ions embedded in optical waveguides offer a powerful platform for realising practical on-chip optical elements with applications to quantum information and enjoy a long-established experimental toolbox. Studies into the (quantum) optical properties and ensemble dynamics of spectrally inhomogeneous emitters in the framework of waveguide QED are lacking, despite much focus in the context of cavity QED. In this work, we show that strong coupling of cavity QED can be simulated using waveguide-based ensembles, and analyse their linear and nonlinear optical response. The work further establishes waveguide-based ensembles as a fruitful platform for quantum information.

Modern imaging systems can be enhanced in efficiency, compactness, and range of applications through introduction of multilayer nanopatterned structures for manipulation of light based on its fundamental properties. High transmission efficiency multispectral imaging is surprisingly elusive due to the use of absorptive or reflective filter arrays which discard most of the incident light. Further, most cameras in use today do not leverage the wealth of information in the polarization and spatial degrees of freedom. Metaoptical components can be tailored to respond to these varying electromagnetic properties, but have been mostly explored in single-layer, ultrathin geometries, which limits their capacity for multifunctional behavior. Here we show the design of several pixel-sized scattering structures which sort light efficiently based on its wavelength, polarization state, and spatial mode.

Dicke superradiance is a landmark of quantum optics. It enables a group of N emitters to interact both collectively and coherently. However, a strict limitation is the separation between the emitters that should be smaller than the wavelength of light restricting its applicability. This limitation can be alleviated using near-zero refractive index materials due to the large wavelength and spatial coherence. We theoretically and numerically demonstrate enhanced extended superradiance using a near-zero metamaterial designs. Ultra-high superradiant decay rate enhancement over distances greater than 13 times the free-space wavelength for both two emitters and many-body configurations of emitters is predicted.

The recent progress in radiative cooling shows exciting promises for achieving sub-ambient refrigeration by tapping the cooling potential from deep space. Spectrally selective materials have been the core of these high-efficiency thermal energy harvesting, in both radiative cooling and solar heating. As many successful demonstrations made their way into practical thermal engineering, multifunctionality became increasingly important. For example, how do we deal with the spatiotemporal variation of the environment and demand? How do we design the next generation of high-performance radiative heat management devices with promising paths for large-scale deployment? How do we co-develop photonic designs and materials science to achieve novel properties? In this talk, I will give an overview of radiative cooling and heating and its impact on sustainability and human-building-energy nexus. I will introduce recent examples of multifunctional photonic thermal engineering from colleagues and my group, including multispectral selectivity, dynamic tunability, angular selectivity, and near-perfect emitters.

The energy demand under climate change has reached unprecedented levels that require efficient technologies to be developed. Thermal radiation control offers a promising strategy to mitigate the enormous building energy consumption and to better meet the basic human needs in combating the effects of climate change. To achieve localized heating and cooling effects, the thermal radiation emitted by objects is an essential aspect to consider. In this talk, I will present my recent research efforts on material design and manufacturing to achieve passive regulation of radiative heat transfer for energy savings. The significance of combining radiation control concepts with nanophotonic materials is demonstrated with two examples: 1) 3D printable daytime radiative cooling materials for building energy savings; and 2) visibly transparent and infrared reflective coatings for personal thermal management and thermal camouflage. These works demonstrate the new possibilities of bridging thermal science and nanophotonics for achieving a sustainable energy future.

Achieving passive daytime radiative cooling requires cooling coatings to have both high solar reflection and large infrared radiation, which minimize heat gain and simultaneously maximize heat dissipation. Conventional polymer coatings with commercially available TiO2 nanoparticles can passively cool down buildings, but the cooling effect is limited by the UV absorption of TiO2. In address this issue, we introduce fluorescent pigments into commercially available white coatings to compete with TiO2 on UV absorption and re-emit part of the absorbed UV light as fluorescence in the visible range (Advanced Materials 2020, 32(42), 1906751; Journal of Materials Chemistry A 2022, 10(37), 19635-19640). This not only reduces the net heat gain from solar irradiation but also makes the cooling coatings colourful (EcoMat 2022, 4(2), e12169), thereby promoting large-scale applications of the passive daytime radiative cooling technology for combating global warming and energy crisis and enabling effective heat management in wearable electronics and miniaturized optoelectronics (Science Advances 2023, 9(14), eadg1837).

Using finite-difference time domain (FDTD) calculations we show that hybrid graphene-dielectric-metal nanostructures can achieve daytime radiative cooling. While a metal back mirror reflects solar light, metal nanoparticles on the dielectric-graphene heterostructure host acoustic graphene plasmons that allow for electrostatic tuning of their resonance wavelengths; in particular, the resonance wavelengths can be tuned to overlap in the mid-infrared (mid-IR) with the atmospherically transparent windows between 3 um and 5 um and also between 8 um and 12 um, thereby achieving net radiative cooling at ambient temperatures. M.N.L. achknowledges support by the ORISE fellowship 2022/2023.

Hot carriers generated during plasmonic decay in metal nanostructures may be utilised to improve the efficiency of photo-catalytic processes, particularly in combination with a metal oxide to drive photochemical reactions. Here, we report a novel method for the fabrication of core-shell copper/copper oxide nanorods with dimensions designed for an efficient nanocatalyst for the plasmon-driven catalytic conversion of carbon dioxide (CO2) into multi-carbon products. The initial optical properties are determined by the choice of template geometry. However, anodising the copper metamaterial in alkaline electrolytes facilitates the controllable growth of a copper oxide nanoshell. This route not only provides an additional mechanism for tuning the optical properties, but provides a designable catalytic surface over a large surface area opening the door for efficient photo-electrochemical catalysis of CO2. In this work, the fabrication techniques and optical properties.

Holographic data storage is a powerful potential technology to solve the problem of mass data long-term storage. To increase the storage capacity, the information to be stored is encoded into a complex amplitude. Fast and accurate retrieval of amplitude and phase from the reconstructed beam is necessary during data readout. In this talk, we propose a complex amplitude demodulation method based on deep learning from a single-shot diffraction intensity image and verified it by a non-interferometric lensless experiment demodulating four-level amplitude and four-level phase. By analyzing the correlation between the diffraction intensity features and the amplitude and phase encoding data pages, the inverse problem is decomposed into two backward operators denoted by two convolutional neural networks to demodulate amplitude and phase respectively. The stable and simple complex amplitude demodulation and strong anti-noise performance from the deep learning provide an important guarantee for the practicality of holographic data storage.

This study employs computational intelligence techniques to optimize complex photonic devices. Traditional surrogate models have limitations in accurately modeling complex devices like vortex phase masks (VPMs). VPMs are essential for observing faint light sources near bright objects, such as exoplanets near stars. To address this, a data-efficient surrogate optimization setup using a deep neural network (U-Net) and particle swarm optimization is proposed. The U-Net achieves high accuracy and efficiency. The resulting surrogate optimization setup outperforms both carefully devised grid-based searches and optimizers.

I will discuss diffractive optical networks designed by deep learning to all-optically implement various complex functions as the input light diffracts through spatially-engineered surfaces. These diffractive processors designed by deep learning have various applications, e.g., all-optical image analysis, feature detection, object classification, computational imaging and seeing through diffusers, also enabling task-specific camera designs and new optical components for spatial, spectral and temporal beam shaping and spatially-controlled wavelength division multiplexing. These deep learning-designed diffractive systems can broadly impact (1) all-optical statistical inference engines, (2) computational camera and microscope designs and (3) inverse design of optical systems that are task-specific. I will give examples of each group, enabling transformative capabilities for various applications, e.g., autonomous systems, defense/security, telecommunications and biomedical imaging/sensing.

By integrating different signal contrast mechanisms into one imaging apparatus, multi-modality microscopy has enabled more insightful and fruitful information acquisition for scientific characterizations, especially for biomedical research. The correlation between different signal modalities essentially provides more advanced analytical capability for imaging-based problem on a multi-domain and cross-landscape level. It can further lead to new techniques and applications if AI-based principle is included. In this talk, I will discuss our recent progresses on dual-modality super-resolution microscopy combining fluorescence structured illumination microscopy and optical diffraction tomography as well as its application in bio-science and AI-based imaging technique.

Computational techniques such as photonics inverse design, along with new nanofabrication approaches and photonic materials, play a crucial role in addressing challenges of building scalable quantum and nonlinear photonics. We illustrate this with several recent examples, including on chip nonlinear optical isolators, miniaturized Ti:sapphire lasers, chip-to-chip and on-chip optical interconnects with error free communication rates exceeding terabit per second, and scalable quantum systems based on color centers in wide band gap semiconductors such as diamond and silicon carbide.

Quantitative phase imaging (QPI) techniques can reveal the subtle interactions between light and the physical objects. However, the reconstruction problem is inherently ill-posed because only intensity can be directly recorded by the image sensor. Here, we propose a general computational framework for single-shot, high-quality QPI by exploring the sparsity features of the complex sample field. The resulting image reconstruction algorithm is highly scalable and features theoretically tractable convergence behaviors. We successfully demonstrate single-shot QPI in various metrological and biomedical applications. The proposed algorithmic framework can also be extended to exploit spatiotemporal priors and diversity measurement schemes, thereby pushing the imaging performance toward higher limits.

The interaction of complex vector light with atoms is an emerging research area, combining state-of-the-art technologies in controlling the amplitude, phase and polarization profile of complex vector light with the mature research field of atom cooling and trapping. Light-atom interaction is, by its very nature, a vectorial process, that depends explicitly on the alignment between an external magnetic field and the optical and atomic polarizations. With a suitable atomic-state interferometer we can imprint spatially varying polarization directions of a vector beam onto spatially varying atomic spin polarizations within a cold Rubidium gas. This allows us to shape the transparency of atomic vapours, to determine magnetic field directions from a single absorption image, and most recently to map the degree of spatial correlations in a vector beam to the visibility of interference fringes in its absorption profile.

Time-varying media have recently emerged as a new paradigm for wave manipulation. In this talk we provide a discussion of the recent progress achieved with photonic metamaterials whose properties stem from their modulation in time. We review the basic concepts underpinning temporal switching and its relationship with spatial scattering, and deploy the resulting insight to review photonic time-crystals and their emergent research avenues such as topological and non-Hermitian physics. We then extend our discussion to account for spatiotemporal modulation and its applications to nonreciprocity, synthetic motion, giant anisotropy, amplification and other effects. Finally, we conclude with a review of the most attractive experimental avenues recently demonstrated, and provide a few perspectives on emerging trends for future implementations of time-modulation in photonics.