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Register a new userInverse Design of Quantum Holograms in Three-Dimensional Nonlinear Photonic Crystals
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We introduce a systematic approach for designing 3D nonlinear photonic crystals and pump beams for generating desired quantum correlations between structured photon-pairs. Our model is fully differentiable, allowing accurate and efficient learning and discovery of novel designs.
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This paper gives an overview of recent work on three-dimensional (3D) photonic crystals with a full and complete 3D photonic band gap. We review five main aspects: 1) spontaneous emission inhibition, 2) spatial localization of light within a tiny nanoscale volume (aka a nanobox for light), 3) the introduction of a gain medium leading to thresholdless lasers, 4) breaking of the weak-coupling approximation of cavity QED, both in the frequency and in the time-domain, 5) decoherence, in particular the shielding of vacuum fluctuations by a 3D photonic bandgap. In addition, we list and evaluate all known photonic crystal structures with a demonstrated 3D band gap.
Gradient-based inverse design in photonics has already achieved remarkable results in designing small-footprint, high-performance optical devices. The adjoint variable method, which allows for the efficient computation of gradients, has played a major role in this success. However, gradient-based optimization has not yet been applied to the mode-expansion methods that are the most common approach to studying periodic optical structures like photonic crystals. This is because, in such simulations, the adjoint variable method cannot be defined as explicitly as in standard finite-difference or finite-element time- or frequency-domain methods. Here, we overcome this through the use of automatic differentiation, which is a generalization of the adjoint variable method to arbitrary computational graphs. We implement the plane-wave expansion and the guided-mode expansion methods using an automatic differentiation library, and show that the gradient of any simulation output can be computed efficiently and in parallel with respect to all input parameters. We then use this implementation to optimize the dispersion of a photonic crystal waveguide, and the quality factor of an ultra-small cavity in a lithium niobate slab. This extends photonic inverse design to a whole new class of simulations, and more broadly highlights the importance that automatic differentiation could play in the future for tracking and optimizing complicated physical models.
We present ultrafast optical switching experiments on 3D photonic band gap crystals. Switching the Si inverse opal is achieved by optically exciting free carriers by a two-photon process. We probe reflectivity in the frequency range of second order Bragg diffraction where the photonic band gap is predicted. We find good experimental switching conditions for free-carrier plasma frequencies between 0.3 and 0.7 times the optical frequency: we thus observe a large frequency shift of up to D omega/omega= 1.5% of all spectral features including the peak that corresponds to the photonic band gap. We deduce a corresponding large refractive index change of Dn_Si/n_Si= 2.0% and an induced absorption length that is longer than the sample thickness. We observe a fast decay time of 21 ps, which implies that switching could potentially be repeated at GHz rates. Such a high switching rate is relevant to future switching and modulation applications.
Photonic inverse design has emerged as an indispensable engineering tool for complex optical systems. In many instances it is important to optimize for both material and geometry configurations, which results in complex non-smooth search spaces with multiple local minima. Finding solutions approaching global optimum may present a computationally intractable task. Here, we develop a framework that allows expediting the search of solutions close to global optimum on complex optimization spaces. We study the way representative black box optimization algorithms work, including genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and mesh adaptive direct search (NOMAD). We then propose and utilize a two-step approach that identifies best performance algorithms on arbitrarily complex search spaces. We reveal a connection between the search space complexity and algorithm performance and find that PSO and NOMAD consistently deliver better performance for mixed integer problems encountered in photonic inverse design, particularly with the account of material combinations. Our results differ from a commonly anticipated advantage of GA. Our findings will foster more efficient design of photonic systems with optimal performance.
We have performed an x-ray holotomography study of a three-dimensional (3D) photonic band gap crystal. The crystals was made from silicon by CMOS-compatible methods. We manage to obtain the 3D material density throughout the fabricated crystal. We observe that the structural design is for most aspects well-realized by the fabricated nanostructure. One peculiar feature is a slight shear-distortion of the cubic crystal structure. We conclude that 3D X-ray tomography has great potential to solve many future questions on optical metamaterials.
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