arXiv subjects

Momchil Minkov

Publications and source records attributed to Momchil Minkov.

At least 19 recordsLinked to original sources

arXiv2022

Anderson localization of electromagnetic waves in three dimensions

Anderson localization marks a halt of diffusive wave propagation in disordered systems. Despite extensive studies over the past 40 years, Anderson localization of light in three dimensions has remained elusive, leading to the question of its very existence. Recent orders-of-magnitude speed-up of finite-difference time-domain calculations allows us to conduct brute-force numerical simulations of light transport in fully disordered 3D systems with unprecedented dimension and refractive index contrast. We demonstrate three-dimensional localization of vector electromagnetic waves in random packings of metallic spheres, in sharp contrast to the absence of localization for dielectric spheres with a refractive index contrast up to 10. Our work opens a wide range of avenues in both fundamental research related to Anderson localization and potential applications using 3D localized light.

physics.optics↗

arXiv2022

Theory of photonic crystal polaritons in periodically patterned multilayer waveguides

We present a formalism for studying the radiation-matter interaction in multilayered dielectric structures with active semiconductor quantum wells patterned with an in-plane periodic lattice. The theory is based on the diagonalization of the generalized Hopfield matrix, and it includes loss channels in a non-Hermitian formulation. Hybrid elementary excitations named photonic crystal polaritons arise in these systems, whose detailed dispersion and loss characteristics are shown to depend on material composition as well as on symmetry properties of the lattice. We show the generality of the approach by calculating polariton dispersions in very diverse material platforms, such as multilayered perovskite-based lattices or inorganic semiconductor heterostructures. As an application of the method, we show how to engineer lossless polariton modes through excitonic coupling to bound states in the continuum at either zero or finite in-plane wavevector, and discuss their topological properties. Detailed comparison with a semiclassical approach based on the scattering matrix method is provided, which allows to interpret the optical spectra in terms of polarization-dependent excitation of the different polariton branches. This work introduces an efficient and invaluably versatile numerical approach to engineer photonic crystal polaritons, with potential applications ranging from low-threshold lasers to symmetry-protected propagating modes of hybrid radiation-matter states.

cond-mat.mes-hall↗

arXiv2022

Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks

Neural networks are widely deployed models across many scientific disciplines and commercial endeavors ranging from edge computing and sensing to large-scale signal processing in data centers. The most efficient and well-entrenched method to train such networks is backpropagation, or reverse-mode automatic differentiation. To counter an exponentially increasing energy budget in the artificial intelligence sector, there has been recent interest in analog implementations of neural networks, specifically nanophotonic neural networks for which no analog backpropagation demonstration exists. We design mass-manufacturable silicon photonic neural networks that alternately cascade our custom designed "photonic mesh" accelerator with digitally implemented nonlinearities. These reconfigurable photonic meshes program computationally intensive arbitrary matrix multiplication by setting physical voltages that tune the interference of optically encoded input data propagating through integrated Mach-Zehnder interferometer networks. Here, using our packaged photonic chip, we demonstrate in situ backpropagation for the first time to solve classification tasks and evaluate a new protocol to keep the entire gradient measurement and update of physical device voltages in the analog domain, improving on past theoretical proposals. Our method is made possible by introducing three changes to typical photonic meshes: (1) measurements at optical "grating tap" monitors, (2) bidirectional optical signal propagation automated by fiber switch, and (3) universal generation and readout of optical amplitude and phase. After training, our classification achieves accuracies similar to digital equivalents even in presence of systematic error. Our findings suggest a new training paradigm for photonics-accelerated artificial intelligence based entirely on a physical analog of the popular backpropagation technique.

cs.ET↗

arXiv2022

A full degree-of-freedom photonic crystal spatial light modulator

Harnessing the full complexity of optical fields requires complete control of all degrees-of-freedom within a region of space and time -- an open goal for present-day spatial light modulators (SLMs), active metasurfaces, and optical phased arrays. Here, we solve this challenge with a programmable photonic crystal cavity array enabled by four key advances: (i) near-unity vertical coupling to high-finesse microcavities through inverse design, (ii) scalable fabrication by optimized, 300 mm full-wafer processing, (iii) picometer-precision resonance alignment using automated, closed-loop "holographic trimming", and (iv) out-of-plane cavity control via a high-speed micro-LED array. Combining each, we demonstrate near-complete spatiotemporal control of a 64-resonator, two-dimensional SLM with nanosecond- and femtojoule-order switching. Simultaneously operating wavelength-scale modes near the space- and time-bandwidth limits, this work opens a new regime of programmability at the fundamental limits of multimode optical control.

physics.optics↗

arXiv2021

Doubly resonant photonic crystal cavities for efficient second-harmonic generation in III-V semiconductors

Second-order nonlinear effects, such as second-harmonic generation, can be strongly enhanced in nanofabricated photonic materials when both fundamental and harmonic frequencies are spatially and temporally confined. Practically designing low-volume and doubly resonant nanoresonators in conventional semiconductor compounds is challenging owing to their intrinsic refractive index dispersion. In this work we review a recently developed strategy to design doubly resonant nanocavities with low mode volume and large quality factor by localized defects in a photonic crystal structure. We build on this approach by applying an evolutionary optimisation algorithm in connection with Maxwell equations solvers, showing that the proposed design recipe can be applied to any material platform. We explicitly calculate the second-harmonic generation efficiency for doubly resonant photonic crystal cavity designs in typical III-V semiconductor materials, such as GaN and AlGaAs, targeting a fundamental harmonic at telecom wavelengths, and fully accounting for the tensor nature of the respective nonlinear susceptibilities. These results may stimulate the realisation of small footprint photonic nanostructures in leading semiconductor material platforms to achieve unprecedented nonlinear efficiencies.

physics.optics↗

arXiv2020

Integrated Nonreciprocal Photonic Devices with Dynamic Modulation

Nonreciprocal components, such as isolators and circulators, are crucial components for photonic systems. In this article we review theoretical and experimental progress towards developing nonreciprocal photonic devices based on dynamic modulation. In particular, we focus on approaches that operate at optical wavelengths and device architectures that have the potential for chip-scale integration. We first discuss the requirements for constructing an isolator or circulator using dynamic modulation. We review a number of different isolator and circulator architectures, including waveguide and resonant devices, and describe their underlying operating principles. We then compare these device architectures from a system-level performance perspective, considering how their figures of merit, such as footprint, bandwidth, isolation, and insertion loss scale with respect to device parameters.

physics.optics↗

arXiv2020

Arbitrary linear transformations for photons in the frequency synthetic dimension

Arbitrary linear transformations are of crucial importance in a plethora of photonic applications spanning classical signal processing, communication systems, quantum information processing and machine learning. Here, we present a new photonic architecture to achieve arbitrary linear transformations by harnessing the synthetic frequency dimension of photons. Our structure consists of dynamically modulated micro-ring resonators that implement tunable couplings between multiple frequency modes carried by a single waveguide. By inverse design of these short- and long-range couplings using automatic differentiation, we realize arbitrary scattering matrices in synthetic space between the input and output frequency modes with near-unity fidelity and favorable scaling. We show that the same physical structure can be reconfigured to implement a wide variety of manipulations including single-frequency conversion, nonreciprocal frequency translations, and unitary as well as non-unitary transformations. Our approach enables compact, scalable and reconfigurable integrated photonic architectures to achieve arbitrary linear transformations in both the classical and quantum domains using current state-of-the-art technology.

physics.optics↗

arXiv2020

$\mathcal{PT}$-Symmetric Topological Edge-Gain Effect

We demonstrate a non-Hermitian topological effect that is characterized by having complex eigenvalues only in the edge states of a topological material, despite the fact that the material is completely uniform. Such an effect can be constructed in any topological structure formed by two gapped sub-systems, e.g., a quantum spin-Hall system, with a suitable non-Hermitian coupling between the spins. The resulting complex-eigenvalued edge state is robust against defects due to the topological protection. In photonics, such an effect can be used for the implementation of topological lasers, in which a uniform pumping provides gain only in the edge lasing state. Furthermore, such a topological lasing model is reciprocal and is thus compatible with standard photonic platforms.

physics.optics↗

arXiv2020

Doubly resonant second-harmonic generation of a vortex beam from a bound state in the continuum

Second harmonic generation in nonlinear materials can be greatly enhanced by realizing doubly-resonant cavities with high quality factors. However, fulfilling such doubly resonant condition in photonic crystal (PhC) cavities is a long-standing challenge, because of the difficulty in engineering photonic bandgaps around both frequencies. Here, by implementing a second-harmonic bound state in the continuum (BIC) and confining it with a heterostructure design, we show the first doubly-resonant PhC slab cavity with $2.4\times10^{-2}$ W$^{-1}$ conversion efficiency under continuous wave excitation. We also report the confirmation of highly normal-direction concentrated far-field emission pattern with radial polarization at the second harmonic frequency. These results represent a solid verification of previous theoretical predictions and a cornerstone achievement, not only for nonlinear frequency conversion but also for vortex beam generation and prospective nonclassical sources of radiation.

physics.optics↗

arXiv2020

Inverse design of photonic crystals through automatic differentiation

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.

physics.optics↗

arXiv2019

Wave Physics as an Analog Recurrent Neural Network

Analog machine learning hardware platforms promise to be faster and more energy-efficient than their digital counterparts. Wave physics, as found in acoustics and optics, is a natural candidate for building analog processors for time-varying signals. Here we identify a mapping between the dynamics of wave physics, and the computation in recurrent neural networks. This mapping indicates that physical wave systems can be trained to learn complex features in temporal data, using standard training techniques for neural networks. As a demonstration, we show that an inverse-designed inhomogeneous medium can perform vowel classification on raw audio signals as their waveforms scatter and propagate through it, achieving performance comparable to a standard digital implementation of a recurrent neural network. These findings pave the way for a new class of analog machine learning platforms, capable of fast and efficient processing of information in its native domain.

physics.comp-ph↗

arXiv2019

Higher-order topological insulators in synthetic dimensions

Conventional topological insulators support boundary states that have one dimension lower than the bulk system that hosts them, and these states are topologically protected due to quantized bulk dipole moments. Recently, higher-order topological insulators have been proposed as a way of realizing topological states that are two or more dimensions lower than the bulk, due to the quantization of bulk quadrupole or octupole moments. However, all these proposals as well as experimental realizations have been restricted to real-space dimensions. Here we construct photonic higher-order topological insulators (PHOTI) in synthetic dimensions. We show the emergence of a quadrupole PHOTI supporting topologically protected corner modes in an array of modulated photonic molecules with a synthetic frequency dimension, where each photonic molecule comprises two coupled rings. By changing the phase difference of the modulation between adjacently coupled photonic molecules, we predict a dynamical topological phase transition in the PHOTI. Furthermore, we show that the concept of synthetic dimensions can be exploited to realize even higher-order multipole moments such as a 4th order hexadecapole (16-pole) insulator, supporting 0D corner modes in a 4D hypercubic synthetic lattice that cannot be realized in real-space lattices.

cond-mat.mes-hall↗

arXiv2019

Parallel fault-tolerant programming of an arbitrary feedforward photonic network

Reconfigurable photonic mesh networks of tunable beamsplitter nodes can linearly transform $N$-dimensional vectors representing input modal amplitudes of light for applications such as energy-efficient machine learning hardware, quantum information processing, and mode demultiplexing. Such photonic meshes are typically programmed and/or calibrated by tuning or characterizing each beam splitter one-by-one, which can be time-consuming and can limit scaling to larger meshes. Here we introduce a graph-topological approach that defines the general class of feedforward networks commonly used in such applications and identifies columns of non-interacting nodes that can be adjusted simultaneously. By virtue of this approach, we can calculate the necessary input vectors to program entire columns of nodes in parallel by simultaneously nullifying the power in one output of each node via optoelectronic feedback onto adjustable phase shifters or couplers. This parallel nullification approach is fault-tolerant to fabrication errors, requiring no prior knowledge or calibration of the node parameters, and can reduce the programming time by a factor of order $N$ to being proportional to the optical depth (or number of node columns in the device). As a demonstration, we simulate our programming protocol on a feedforward optical neural network model trained to classify handwritten digit images from the MNIST dataset with up to 98% validation accuracy.

cs.ET↗

arXiv2019

A single photonic cavity with two independent physical synthetic dimensions

The concept of synthetic dimensions, which has enabled the study of higher-dimensional physics on lower-dimensional physical structures, has generated significant recent interest in many branches of science ranging from ultracold-atomic physics to photonics, since such a concept provides a versatile platform for realizing effective gauge potentials and novel topological physics. Previous experiments demonstrating this concept have augmented the real-space dimensionality by one additional physical synthetic dimension. Here we endow a single ring resonator with two independent physical synthetic dimensions. Our system consists of a temporally modulated ring resonator with spatial coupling between the clockwise and counterclockwise modes, creating a synthetic Hall ladder along the frequency and pseudospin degrees of freedom for photons propagating in the ring. We experimentally observe a wide variety of rich physics, including effective spin-orbit coupling, magnetic fields, spin-momentum locking, a Meissner-to-vortex phase transition, and chiral currents, completely in synthetic dimensions. Our experiments demonstrate that higher-dimensional physics can be studied in simple systems by leveraging the concept of multiple simultaneous synthetic dimensions.

physics.optics↗

arXiv2019

Forward-Mode Differentiation of Maxwell's Equations

We present a previously unexplored forward-mode differentiation method for Maxwell's equations, with applications in the field of sensitivity analysis. This approach yields exact gradients and is similar to the popular adjoint variable method, but provides a significant improvement in both memory and speed scaling for problems involving several output parameters, as we analyze in the context of finite-difference time-domain (FDTD) simulations. Furthermore, it provides an exact alternative to numerical derivative methods, based on finite-difference approximations. To demonstrate the usefulness of the method, we perform sensitivity analysis of two problems. First we compute how the spatial near-field intensity distribution of a scatterer changes with respect to its dielectric constant. Then, we compute how the spectral power and coupling efficiency of a surface grating coupler changes with respect to its fill factor.

physics.optics↗

arXiv2019

Doubly-resonant $χ^{(2)}$ nonlinear photonic crystal cavity based on a bound state in the continuum

Photonic nanostructures simultaneously maximizing spectral and spatial overlap between fundamental and second-harmonic confined modes are highly desirable for enhancing second-order nonlinear effects in nonlinear media. These conditions have thus far remained challenging to satisfy in photonic crystal cavities because of the difficulty in designing a band gap at the second-harmonic frequency. Here, we solve this issue by using instead a bound state in the continuum at that frequency, and we design a doubly-resonant photonic crystal slab cavity with strongly improved figures of merit for nonlinear frequency conversion when compared to previous photonic crystal designs. Furthermore, we show that the far-field emission at both frequencies is highly collimated around normal incidence, which allows for simultaneously efficient pump excitation and collection of the generated nonlinear signal. Our results could lead to unprecedented conversion efficiencies in both parametric down conversion and second harmonic generation in an extremely compact architecture.

physics.optics↗

arXiv2019

Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks

We introduce an electro-optic hardware platform for nonlinear activation functions in optical neural networks. The optical-to-optical nonlinearity operates by converting a small portion of the input optical signal into an analog electric signal, which is used to intensity-modulate the original optical signal with no reduction in processing speed. Our scheme allows for complete nonlinear on-off contrast in transmission at relatively low optical power thresholds and eliminates the requirement of having additional optical sources between each layer of the network. Moreover, the activation function is reconfigurable via electrical bias, allowing it to be programmed or trained to synthesize a variety of nonlinear responses. Using numerical simulations, we demonstrate that this activation function significantly improves the expressiveness of optical neural networks, allowing them to perform well on two benchmark machine learning tasks: learning a multi-input exclusive-OR (XOR) logic function and classification of images of handwritten numbers from the MNIST dataset. The addition of the nonlinear activation function improves test accuracy on the MNIST task from 85% to 94%.

eess.SP↗

arXiv2019

Entropy methods for CMB analysis of anisotropy and non-Gaussianity

We propose several pseudoentropy measures that agree well with the Wehrl entropy, but are significantly faster to compute. All of them are rotationally invariant measures of entanglement very sensitive to non-Gaussianity, anisotropy, and statistical dependence of spherical harmonic coefficients. We provide a simple proof that the projection pseudoentropy converges to the Wehrl entropy with increasing dimensionality of the ancilla projection space. Furthermore, for $l=2$, we show that both the Wehrl entropy and the angular pseudoentropy can be expressed as functions of the squared chordal distance of multipole vectors. We also show that the angular pseudoentropy can distinguish between Gaussian and non-Gaussian temperature fluctuations at large multipoles and henceforth provides a non-brute-force method for identifying non-Gaussianities. This allows us to study possible hints of statistical anisotropy and non-Gaussianity in the CMB up to multipole $l=1000$ using Planck 2015/2018, and WMAP 7-yr data. We find that $l=5$ and $28$ have a large entropy at $2$--$3σ$ significance and a slight hint towards a connection of this with the cosmic dipole. On a wider range of large angular scales we do not find indications of isotropy/Gaussianity violation. We also find a small-scale range, $l\in[895,905]$, that is incompatible with the assumptions at about $3σ$ level, although how much this significance can be reduced by taking into account the selection effect is left as an open question. We find overall similar results in our analysis of the 2015 and the 2018 data. Finally, we also demonstrate how a range of angular momenta can be studied with the range angular pseudoentropy. Our main purpose is to introduce the methods, analyze their mathematical background, and demonstrate their usage for providing researchers in this field with an additional tool.

astro-ph.CO↗