Material- and shape-dependent optical modes of hyperbolic spheroidal nano-resonators.

Hyperbolic nanoresonators, composed of anisotropic materials with opposite signs of permittivity, have unique optical properties due to a large degree of freedom that hyperbolic dispersion provides in designing their response. Here, we focus on uniaxial hyperbolic nanoresonators composed of a model silver-silica multilayer in the form of spheroids with a broad aspect ratio encompassing both prolate and oblate particles. The origin and evolution of the optical response and mode coupling are investigated using both numerical (T-matrix and FDTD) and theoretical methods. We show the tunability of the optical resonances and the interplay of the shape and material anisotropy in determining the spectral response. Depending on the illumination conditions as well as shape and material anisotropy, a single hyperbolic spheroid can show a dominant electric resonance, behaving as a pure metallic nanoparticle, or a strong dipolar magnetic resonance even in the quasistatic regime. The quasistatic magnetic response of indicates a material-dependent origin of the mode, which is obtained due to coupling of the magnetic and electric multipoles. Such coupling characteristics can be employed in various modern applications based on metasurfaces.

Far-field signature of sub-wavelength microscopic objects.

Information about microscopic objects with features smaller than the diffraction limit is almost entirely lost in a far-field diffraction image but could be partly recovered with data completition techniques. Any such approach critically depends on the level of noise. This new path to superresolution has been recently investigated with use of compressed sensing and machine learning. We demonstrate a two-stage technique based on deconvolution and genetic optimization which enables the recovery of objects with features of 1/10 of the wavelength. We indicate that l1-norm based optimization in the Fourier domain unrelated to sparsity is more robust to noise than its l2-based counterpart. We also introduce an extremely fast general purpose restricted domain calculation method for Fourier transform based iterative algorithms operating on sparse data.

Effective dipolar polarizability of amorphous arrays of size-dispersed nanoparticles.

Inhomogeneity of nanoparticle size, shape, and distribution is ubiquitous and inherent in fabricated arrays or may be a deliberate attempt to engineer the optical response. It leads to a spread of polarizabilities of interacting elements and phases of scattered light, and quantitative understanding of these effects is important. Focusing on random/amorphous arrays of optical antennas, we combine T-matrix calculations and an analytical approach based on an effective dipolar polarizability within a film of dipoles framework to quantify the spectral response as a function of the particle inhomogeneity and stochastic clustering. The interplay of position-dependent stochastic coupling and size distribution of antennas determines the optical properties of such arrays as a function of mean/standard deviation of diameter and minimum separation. The resonance wavelength, amplitude, and scattering-to-absorption ratio exhibit oscillations around their size-averaged values with periods and amplitudes given by average structural factors.

Single-pixel imaging with sampling distributed over simplex vertices.

We propose a method of reduction of experimental noise in single-pixel imaging by expressing the subsets of sampling patterns as linear combinations of vertices of a multidimensional regular simplex. This method also may be directly extended to complementary sampling. The modified measurement matrix contains nonnegative elements with patterns that may be directly displayed on intensity spatial light modulators. The measurement becomes theoretically independent of the ambient illumination, and in practice becomes more robust to the varying conditions of the experiment. We show how the optimal dimension of the simplex depends on the level of measurement noise. We present experimental results of single-pixel imaging using binarized sampling and real-time reconstruction with the Fourier domain regularized inversion method.

Real-time single-pixel video imaging with Fourier domain regularization.

We present a closed-form image reconstruction method for single-pixel imaging based on the generalized inverse of the measurement matrix. Its numerical cost scales proportionally with the number of measured samples. Regularization of the inverse problem is obtained by minimizing the norms of the convolution between the reconstructed image and a set of spatial filters. The final reconstruction formula can be expressed in terms of matrix pseudoinverse. At high compression, this approach is an interesting alternative to the methods of compressive sensing based on l1-norm optimization, which are too slow for real-time applications. For instance, we demonstrate experimental single-pixel detection with real-time reconstruction obtained in parallel with measurement at a frame rate of 11 Hz for highly compressive measurements with a resolution of 256 × 256. To this end, we preselect the sampling functions to match the average spectrum obtained with an image database. The sampling functions are selected from the Walsh-Hadamard basis, from the discrete cosine basis, or from a subset of Morlet wavelets convolved with white noise. We show that by incorporating the quadratic criterion into the closed-form reconstruction formula, we can use binary rather than continuous sampling and reach similar reconstruction quality as is obtained by minimizing the total variation. This makes it possible to use cosine- or Morlet-based sampling with digital micromirror devices without advanced binarization methods.

Ultrastrong Coupling of a Single Molecule to a Plasmonic Nanocavity: A First-Principles Study.

Ultrastrong coupling (USC) is a distinct regime of light-matter interaction in which the coupling strength is comparable to the resonance energy of the cavity or emitter. In the USC regime, common approximations to quantum optical Hamiltonians, such as the rotating wave approximation, break down as the ground state of the coupled system gains photonic character due to admixing of vacuum states with higher excited states, leading to ground-state energy changes. USC is usually achieved by collective coherent coupling of many quantum emitters to a single mode cavity, whereas USC with a single molecule remains challenging. Here, we show by time-dependent density functional theory (TDDFT) calculations that a single organic molecule can reach USC with a plasmonic dimer, consisting of a few hundred atoms. In this context, we discuss the capacity of TDDFT to represent strong coupling and its connection to the quantum optical Hamiltonian. We find that USC leads to appreciable ground-state energy modifications accounting for a non-negligible part of the total interaction energy, comparable to k B T at room temperature.

A nanofabricated plasmonic core-shell-nanoparticle library.

Three-layer core-shell-nanoparticle nanoarchitectures exhibit properties not achievable by single-element nanostructures alone and have great potential to enable rationally designed functionality. However, nanofabrication strategies for crafting core-shell-nanoparticle structure arrays on surfaces are widely lacking, despite the potential of basically unlimited material combinations. Here we present a nanofabrication approach that overcomes this limitation. Using it, we produce a library of nanoarchitectures composed of a metal core and an oxide/nitride shell that is decorated with few-nanometer-sized particles with widely different material combinations. This is enabled by resolving a long-standing challenge in this field, namely the ability to grow a shell layer around a nanofabricated core without prior removal of the lithographically patterned mask, and the possibility to subsequently grow smaller metal nanoparticles locally on the shell only in close proximity of the core. Focusing on the application of such nanoarchitectures in plasmonics, we show experimentally and by Finite-Difference Time-Domain (FDTD) simulations that these structures exhibit significant optical absorption enhancement in small metal nanoparticles grown on the few nanometer thin dielectric shell layer around a plasmonic core, and derive design rules to maximize the effect by the tailored combination of the core and shell materials. We predict that these structures will find application in plasmon-mediated catalysis and nanoplasmonic sensing and spectroscopy.

Single-pixel imaging with Morlet wavelet correlated random patterns.

Single-pixel imaging is an indirect imaging technique which utilizes simplified optical hardware and advanced computational methods. It offers novel solutions for hyper-spectral imaging, polarimetric imaging, three-dimensional imaging, holographic imaging, optical encryption and imaging through scattering media. The main limitations for its use come from relatively high measurement and reconstruction times. In this paper we propose to reduce the required signal acquisition time by using a novel sampling scheme based on a random selection of Morlet wavelets convolved with white noise. While such functions exhibit random properties, they are locally determined by Morlet wavelet parameters. The proposed method is equivalent to random sampling of the properly selected part of the feature space, which maps the measured images accurately both in the spatial and spatial frequency domains. We compare both numerically and experimentally the image quality obtained with our sampling protocol against widely-used sampling with Walsh-Hadamard or noiselet functions. The results show considerable improvement over the former methods, enabling single-pixel imaging at low compression rates on the order of a few percent.

Effective Optical Properties of Inhomogeneously Distributed Nanoobjects in Strong Field Gradients of Nanoplasmonic Sensors.

Accurate and efficient modeling of discontinuous, randomly distributed entities is a computationally challenging task, especially in the presence of large and inhomogeneous electric near-fields of plasmons. Simultaneously, the anisotropy of sensed entities and their overlap with inhomogeneous fields means that typical effective medium approaches may fail at describing their optical properties. Here, we extend the Maxwell Garnett mixing formula to overcome this limitation by introducing a gradient within the effective medium description of inhomogeneous nanoparticle layers. The effective medium layer is divided into slices with a varying volume fraction of the inclusions and, consequently, a spatially varying effective permittivity. This preserves the interplay between an anisotropic particle distribution and an inhomogeneous electric field and enables more accurate predictions than with a single effective layer. We demonstrate the usefulness of the gradient effective medium in FDTD modeling of indirect plasmonic sensing of nanoparticle sintering. First of all, it yields accurate results significantly faster than with explicitly modeled nanoparticles. Moreover, by employing the gradient effective medium approach, we prove that the detected signal is proportional to not only the nanoparticle size but also its size dispersion and potentially shape. This implies that the simple volume fraction parameter is insufficient to properly homogenize these types of nanoparticle layers and that in order to quantify optically the state of the layer more than one independent measurement should be carried out. These findings extend beyond nanoparticle sintering and could be useful in analysis of average signals in both plasmonic and dielectric systems to unveil dynamic changes in exosomes or polymer brushes, phase changes of nanoparticles, or quantifying light absorption in plasmon assisted catalysis.