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In this work, we explore the capabilities of multiplexed gradient descent (MGD), a scalable and efficient perturbative zeroth-order training method for estimating the gradient of a loss function in hardware and training it via stochastic gradient descent. We extend the framework to include both weight and node perturbation, and discuss the advantages and disadvantages of each approach. We investigate the time to train networks using MGD as a function of network size and task complexity. Previous research has suggested that perturbative training methods do not scale well to large problems, since in these methods the time to estimate the gradient scales linearly with the number of network parameters. However, in this work we show that the time to reach a target accuracy--that is, actually solve the problem of interest--does not follow this undesirable linear scaling, and in fact often decreases with network size. Furthermore, we demonstrate that MGD can be used to calculate a drop-in replacement for the gradient in stochastic gradient descent, and therefore optimization accelerators such as momentum can be used alongside MGD, ensuring compatibility with existing machine learning practices. Our results indicate that MGD can efficiently train large networks on hardware, achieving accuracy comparable to backpropagation, thus presenting a practical solution for future neuromorphic computing systems.

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field.

Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. Prior neuromorphic computing benchmark efforts have not seen widespread adoption due to a lack of inclusive, actionable, and iterative benchmark design and guidelines. To address these shortcomings, we present NeuroBench: a benchmark framework for neuromorphic computing algorithms and systems. NeuroBench is a collaboratively-designed effort from an open community of researchers across industry and academia, aiming to provide a representative structure for standardizing the evaluation of neuromorphic approaches. The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings. In this article, we outline tasks and guidelines for benchmarks across multiple application domains, and present initial performance baselines across neuromorphic and conventional approaches for both benchmark tracks. NeuroBench is intended to continually expand its benchmarks and features to foster and track the progress made by the research community., Comment: To appear in Nature Neuromorphic Hardware and Computing collection

We present multiplexed gradient descent (MGD), a gradient descent framework designed to easily train analog or digital neural networks in hardware. MGD utilizes zero-order optimization techniques for online training of hardware neural networks. We demonstrate its ability to train neural networks on modern machine learning datasets, including CIFAR-10 and Fashion-MNIST, and compare its performance to backpropagation. Assuming realistic timescales and hardware parameters, our results indicate that these optimization techniques can train a network on emerging hardware platforms orders of magnitude faster than the wall-clock time of training via backpropagation on a standard GPU, even in the presence of imperfect weight updates or device-to-device variations in the hardware. We additionally describe how it can be applied to existing hardware as part of chip-in-the-loop training, or integrated directly at the hardware level. Crucially, the MGD framework is highly flexible, and its gradient descent process can be optimized to compensate for specific hardware limitations such as slow parameter-update speeds or limited input bandwidth.

Superconducting optoelectronic hardware is being explored as a path towards artificial spiking neural networks with unprecedented scales of complexity and computational ability. Such hardware combines integrated-photonic components for few-photon, light-speed communication with superconducting circuits for fast, energy-efficient computation. Monolithic integration of superconducting and photonic devices is necessary for the scaling of this technology. In the present work, superconducting-nanowire single-photon detectors are monolithically integrated with Josephson junctions for the first time, enabling the realization of superconducting optoelectronic synapses. We present circuits that perform analog weighting and temporal leaky integration of single-photon presynaptic signals. Synaptic weighting is implemented in the electronic domain so that binary, single-photon communication can be maintained. Records of recent synaptic activity are locally stored as current in superconducting loops. Dendritic and neuronal nonlinearities are implemented with a second stage of Josephson circuitry. The hardware presents great design flexibility, with demonstrated synaptic time constants spanning four orders of magnitude (hundreds of nanoseconds to milliseconds). The synapses are responsive to presynaptic spike rates exceeding 10 MHz and consume approximately 33 aJ of dynamic power per synapse event before accounting for cooling. In addition to neuromorphic hardware, these circuits introduce new avenues towards realizing large-scale single-photon-detector arrays for diverse imaging, sensing, and quantum communication applications., Comment: 23 pages, 20 figures

Integrated photonics is at the heart of many classical technologies, from optical communications to biosensors, LIDAR, and data center fiber interconnects. There is strong evidence that these integrated technologies will play a key role in quantum systems as they grow from few-qubit prototypes to tens of thousands of qubits. The underlying laser and optical quantum technologies, with the required functionality and performance, can only be realized through the integration of these components onto quantum photonic integrated circuits (QPICs) with accompanying electronics. In the last decade, remarkable advances in quantum photonic integration and a dramatic reduction in optical losses have enabled benchtop experiments to be scaled down to prototype chips with improvements in efficiency, robustness, and key performance metrics. The reduction in size, weight, power, and improvement in stability that will be enabled by QPICs will play a key role in increasing the degree of complexity and scale in quantum demonstrations. In the next decade, with sustained research, development, and investment in the quantum photonic ecosystem (i.e. PIC-based platforms, devices and circuits, fabrication and integration processes, packaging, and testing and benchmarking), we will witness the transition from single- and few-function prototypes to the large-scale integration of multi-functional and reconfigurable QPICs that will define how information is processed, stored, transmitted, and utilized for quantum computing, communications, metrology, and sensing. This roadmap highlights the current progress in the field of integrated quantum photonics, future challenges, and advances in science and technology needed to meet these challenges., Comment: Submitted to the Journal of Physics: Photonics

We show several techniques for using integrated-photonic waveguide structures to simultaneously characterize multiple waveguide-integrated superconducting-nanowire detectors with a single fiber input. The first set of structures allows direct comparison of detector performance of waveguide-integrated detectors with various widths and lengths. The second type of demonstrated integrated-photonic structure allows us to achieve detection with a high dynamic range. This device allows a small number of detectors to count photons across many orders of magnitude in count rate. However, we find a stray light floor of -30 dB limits the dynamic range to three orders of magnitude. To assess the utility of the detectors for use in synapses in spiking neural systems, we measured the response with average incident photon numbers ranging from less than $10^{-3}$ to greater than $10$. The detector response is identical across this entire range, indicating that synaptic responses based on these detectors will be independent of the number of incident photons in a communication pulse. Such a binary response is ideal for communication in neural systems. We further demonstrate that the response has a linear dependence of output current pulse height on bias current with up to a factor of 1.7 tunability in pulse height. Throughout the work, we compare room-temperature measurements to cryogenic measurements. The agreement indicates room-temperature measurements can be used to determine important properties of the detectors.

We report on the fabrication and characterization of single-photon-sensitive WSi superconducting detectors with wire widths from 1 {\mu}m to 3 {\mu}m. The devices achieve saturated internal detection efficiency at 1.55 {\mu}m wavelength and exhibit maximum count rates in excess of 10^5 s^-1. We also investigate the material properties of the silicon-rich WSi films used for these devices. We find that many devices with active lengths of several hundred microns exhibit critical currents in excess of 50% of the depairing current. A meandered detector with 2.0 {\mu}m wire width is demonstrated over a surface area of 362x362 {\mu}m^2, showcasing the material and device quality achieved.

We demonstrate adiabatically tapered fibers terminating in sub-micron tips that are clad with a higher-index material for coupling to an on-chip waveguide. This cladding enables coupling to a high-index waveguide without losing light to the buried oxide. A technique to clad the tip of the tapered fiber with a higher-index polymer is introduced. Conventional tapered waveguides and forked tapered waveguide structures are investigated for coupling from the clad fiber to the on-chip waveguide. We find the forked waveguide facilitates alignment and packaging, while the conventional taper leads to higher bandwidth. The insertion loss from a fiber through a forked coupler to a sub-micron silicon nitride waveguide is 1.1 dB and the 3 dB-bandwidth is 90 nm. The coupling loss in the packaged device is 1.3 dB. With a fiber coupled to a conventional tapered waveguide, the loss is 1.4 dB with a 3 dB bandwidth extending beyond the range of the measurement apparatus, estimated to exceed 250 nm.

W centers are trigonal defects generated by self-ion implantation in silicon that exhibit photoluminescence at 1.218 $\mu$m. We have shown previously that they can be used in waveguide-integrated all-silicon light-emitting diodes (LEDs). Here we optimize the implant energy, fluence and anneal conditions to maximize the photoluminescence intensity for W centers implanted in silicon-on-insulator, a substrate suitable for waveguide-integrated devices. After optimization, we observe near two orders of magnitude improvement in photoluminescence intensity relative to the conditions with the stopping range of the implanted ions at the center of the silicon device layer. The previously demonstrated waveguide-integrated LED used implant conditions with the stopping range at the center of this layer. We further show that such light sources can be manufactured at the 300-mm scale by demonstrating photoluminescence of similar intensity from 300 mm silicon-on-insulator wafers. The luminescence uniformity across the entire wafer is within the measurement error.

We design, fabricate and characterize integrated photonic routing manifolds with 10 inputs and 100 outputs using two vertically integrated planes of silicon nitride waveguides. We analyze manifolds via top-view camera imaging. This measurement technique allows the rapid acquisition of hundreds of precise transmission measurements. We demonstrate manifolds with uniform and Gaussian power distribution patterns with mean power output errors (averaged over 10 sets of 10 inputs) of 0.7 and 0.9 dB, respectively, establishing this as a viable architecture for precision light distribution on-chip. We also assess the performance of the passive photonic elements comprising the system via self-referenced test structures, including high-dynamic-range beam taps, waveguide cutback structures, and waveguide crossing arrays.

Circuits using superconducting single-photon detectors and Josephson junctions to perform signal reception, synaptic weighting, and integration are investigated. The circuits convert photon-detection events into flux quanta, the number of which is determined by the synaptic weight. The current from many synaptic connections is inductively coupled to a superconducting loop that implements the neuronal threshold operation. Designs are presented for synapses and neurons that perform integration as well as detect coincidence events for temporal coding. Both excitatory and inhibitory connections are demonstrated. It is shown that a neuron with a single integration loop can receive input from 1000 such synaptic connections, and neurons of similar design could employ many loops for dendritic processing., Comment: 14 pages, 11 figures

A superconducting optoelectronic neuron will produce a small current pulse upon reaching threshold. We present an amplifier chain that converts this small current pulse to a voltage pulse sufficient to produce light from a semiconductor diode. This light is the signal used to communicate between neurons in the network. The amplifier chain comprises a thresholding Josephson junction, a relaxation oscillator Josephson junction, a superconducting thin-film current-gated current amplifier, and a superconducting thin-film current-gated voltage amplifier. We analyze the performance of the elements in the amplifier chain in the time domain to calculate the energy consumption per photon created for several values of light-emitting diode capacitance and efficiency. The speed of the amplification sequence allows neuronal firing up to at least 20\,MHz with power density low enough to be cooled easily with standard $^4$He cryogenic systems operating at 4.2\,K., Comment: 16 pages, 11 figures

The design of neural hardware is informed by the prominence of differentiated processing and information integration in cognitive systems. The central role of communication leads to the principal assumption of the hardware platform: signals between neurons should be optical to enable fanout and communication with minimal delay. The requirement of energy efficiency leads to the utilization of superconducting detectors to receive single-photon signals. We discuss the potential of superconducting optoelectronic hardware to achieve the spatial and temporal information integration advantageous for cognitive processing, and we consider physical scaling limits based on light-speed communication. We introduce the superconducting optoelectronic neurons and networks that are the subject of the subsequent papers in this series., Comment: 10 pages, 1 figure

Networks of superconducting optoelectronic neurons are investigated for their near-term technological potential and long-term physical limitations. Networks with short average path length, high clustering coefficient, and power-law degree distribution are designed using a growth model that assigns connections between new and existing nodes based on spatial distance as well as degree of existing nodes. The network construction algorithm is scalable to arbitrary levels of network hierarchy and achieves systems with fractal spatial properties and efficient wiring. By modeling the physical size of superconducting optoelectronic neurons, we calculate the area of these networks. A system with 8100 neurons and 330,430 total synapses will fit on a 1\,cm $\times$ 1\,cm die. Systems of millions of neurons with hundreds of millions of synapses will fit on a 300\,mm wafer. For multi-wafer assemblies, communication at light speed enables a neuronal pool the size of a large data center comprising 100 trillion neurons with coherent oscillations at 1\,MHz. Assuming a power law frequency distribution, as is necessary for self-organized criticality, we calculate the power consumption of the networks. We find the use of single photons for communication and superconducting circuits for computation leads to power density low enough to be cooled by liquid $^4$He for networks of any scale., Comment: 21 pages, 16 figures

As a means of dynamically reconfiguring the synaptic weight of a superconducting optoelectronic loop neuron, a superconducting flux storage loop is inductively coupled to the synaptic current bias of the neuron. A standard flux memory cell is used to achieve a binary synapse, and loops capable of storing many flux quanta are used to enact multi-stable synapses. Circuits are designed to implement supervised learning wherein current pulses add or remove flux from the loop to strengthen or weaken the synaptic weight. Designs are presented for circuits with hundreds of intermediate synaptic weights between minimum and maximum strengths. Circuits for implementing unsupervised learning are modeled using two photons to strengthen and two photons to weaken the synaptic weight via Hebbian and anti-Hebbian learning rules, and techniques are proposed to control the learning rate. Implementation of short-term plasticity, homeostatic plasticity, and metaplasticity in loop neurons is discussed., Comment: 17 pages, 12 figures

Optical communication achieves high fanout and short delay advantageous for information integration in neural systems. Superconducting detectors enable signaling with single photons for maximal energy efficiency. We present designs of superconducting optoelectronic neurons based on superconducting single-photon detectors, Josephson junctions, semiconductor light sources, and multi-planar dielectric waveguides. These circuits achieve complex synaptic and neuronal functions with high energy efficiency, leveraging the strengths of light for communication and superconducting electronics for computation. The neurons send few-photon signals to synaptic connections. These signals communicate neuronal firing events as well as update synaptic weights. Spike-timing-dependent plasticity is implemented with a single photon triggering each step of the process. Microscale light-emitting diodes and waveguide networks enable connectivity from a neuron to thousands of synaptic connections, and the use of light for communication enables synchronization of neurons across an area limited only by the distance light can travel within the period of a network oscillation. Experimentally, each of the requisite circuit elements has been demonstrated, yet a hardware platform combining them all has not been attempted. Compared to digital logic or quantum computing, device tolerances are relaxed. For this neural application, optical sources providing incoherent pulses with 10,000 photons produced with efficiency of 10$^{-3}$ operating at 20\,MHz at 4.2\,K are sufficient to enable a massively scalable neural computing platform with connectivity comparable to the brain and thirty thousand times higher speed., Comment: 10 pages, 7 figures

We propose and experimentally demonstrate a photonic routing architecture that can efficiently utilize the space of multi-plane (3D) photonic integration. A wafer with three planes of amorphous silicon waveguides was fabricated and characterized, demonstrating $<3\times10^{-4}$ dB loss per out-of-plane waveguide crossing, $0.05 \pm 0.02 $ dB per interplane coupler, and microring resonators on three planes with a quality factors up to $8.2 \times 10^{4}$. We also explore a phase velocity mapping strategy to mitigate the crosstalk between co-propagating waveguides on different planes. These results expand the utility of 3D photonic integration for applications such as optical interconnects, neuromorphic computing and optical phased arrays.

We demonstrate cryogenic, electrically-injected, waveguide-coupled Si light-emitting diodes (LEDs) operating at 1.22 $\mu$m. The active region of the LED consists of W centers implanted in the intrinsic region of a $p$-$i$-$n$ diode. The LEDs are integrated on waveguides with superconducting nanowire single-photon detectors (SNSPDs). We demonstrate the scalability of this platform with an LED coupled to eleven SNSPDs in a single integrated photonic device. Such on-chip optical links may be useful for quantum information or neuromorphic computing applications.

We present an approach to fabrication and packaging of integrated photonic devices that utilizes waveguide and detector layers deposited at near-ambient temperature. All lithography is performed with a 365 nm i-line stepper, facilitating low cost and high scalability. We have shown low-loss SiN waveguides, high-$Q$ ring resonators, critically coupled ring resonators, 50/50 beam splitters, Mach-Zehnder interferometers (MZIs) and a process-agnostic fiber packaging scheme. We have further explored the utility of this process for applications in nonlinear optics and quantum photonics. We demonstrate spectral tailoring and octave-spanning supercontinuum generation as well as the integration of superconducting nanowire single photon detectors with MZIs and channel-dropping filters. The packaging approach is suitable for operation up to 160 \degree C as well as below 1 K. The process is well suited for augmentation of existing foundry capabilities or as a stand-alone process., Comment: 13 pages, 7 figures

Neural networks have proven effective for solving many difficult computational problems. Implementing complex neural networks in software is very computationally expensive. To explore the limits of information processing, it will be necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density necessary to scale to systems with enormous entropy. The proposed processing units can operate at speeds of at least $20$ MHz with fully asynchronous activity, light-speed-limited latency, and power densities on the order of 1 mW/cm$^2$ for neurons with 700 connections operating at full speed at 2 K. The processing units achieve an energy efficiency of $\approx 20$ aJ per synapse event. By leveraging multilayer photonics with deposited waveguides and superconductors with feature sizes $>$ 100 nm, this approach could scale to systems with massive interconnectivity and complexity for advanced computing as well as explorations of information processing capacity in systems with an enormous number of information-bearing microstates., Comment: 34 pages, 22 figures

A silicon-compatible light source is the final missing piece for completing high-speed, low-power on-chip optical interconnects. In this paper, we present a germanium-based light emitter that encompasses all the aspects of potential low-threshold lasers: highly strained germanium gain medium, strain-induced pseudo-heterostructure, and high-Q optical cavity. Our light emitting structure presents greatly enhanced photoluminescence into cavity modes with measured quality factors of up to 2,000. The emission wavelength is tuned over more than 400 nm with a single lithography step. We find increased optical gain in optical cavities formed with germanium under high (>2.3%) tensile strain. Through quantitative analysis of gain/loss mechanisms, we find that free carrier absorption from the hole bands dominates the gain, resulting in no net gain even from highly strained, n-type doped germanium., Comment: J.P. and D.N. contributed equally to this work

Engineering the electromagnetic environment of a nanoscale light emitter by a photonic cavity can significantly enhance its spontaneous emission rate through cavity quantum electrodynamics in the Purcell regime. This effect can greatly reduce the lasing threshold of the emitter, providing the ultimate low-threshold laser system with small footprint, low power consumption and ultrafast modulation. A state-of-the-art ultra-low threshold nanolaser has been successfully developed though embedding quantum dots into photonic crystal cavity (PhCC). However, several core challenges impede the practical applications of this architecture, including the random positions and compositional fluctuations of the dots, extreme difficulty in current injection, and lack of compatibility with electronic circuits. Here, we report a new strategy to lase, where atomically thin crystalline semiconductor, i.e., a tungsten-diselenide (WSe2) monolayer, is nondestructively and deterministically introduced as a gain medium at the surface of a pre-fabricated PhCC. A new type of continuous-wave nanolaser operating in the visible regime is achieved with an optical pumping threshold as low as 27 nW at 130 K, similar to the value achieved in quantum dot PhCC lasers. The key to the lasing action lies in the monolayer nature of the gain medium, which confines direct-gap excitons to within 1 nm of the PhCC surface. The surface-gain geometry allows unprecedented accessibilities to multi-functionalize the gain, enabling electrically pumped operation. Our scheme is scalable and compatible with integrated photonics for on-chip optical communication technologies., Comment: 19 pages in total, including main text and supplements. Nature in press

We present the design, fabrication and characterization of cubic (3C) silicon carbide microdisk resonators with high quality factor modes at visible and near infrared wavelengths (600 - 950 nm). Whispering gallery modes with quality factors as high as 2,300 and corresponding mode volumes V ~ 2 ({\lambda}/n)^3 are measured using laser scanning confocal microscopy at room temperature. We obtain excellent correspondence between transverse-magnetic (TM) and transverse-electric (TE) polarized resonances simulated using Finite Difference Time Domain (FDTD) method and those observed in experiment. These structures based on ensembles of optically active impurities in 3C-SiC resonators could play an important role in diverse applications of nonlinear and quantum photonics, including low power optical switching and quantum memories., Comment: 11 pages, 5 figures

We demonstrate the design, fabrication and characterization of nanobeam cavities with multiple higher order modes. Designs with two high Q modes with frequency separations of an octave are introduced, and we fabricate such cavities exhibiting resonances with wavelength separations of up to 740 nm., Comment: 12 pages, 7 figures

We demonstrate the design, fabrication and characterization of nanobeam photonic crystal cavities in (111)-GaAs with multiple high quality factor modes, with large frequency separations (up to 740 nm in experiment, i.e., a factor of 1.5 and up to an octave in theory). Such structures are crucial for efficient implementation of nonlinear frequency conversion. Here, we employ them to demonstrate sum frequency generation from 1300 nm and 1950 nm to 780 nm. These wavelengths are particularly interesting for quantum frequency conversion between Si vacancy centers in diamond and the fiber optic network., Comment: 4 pages, 4 figures

We demonstrate second harmonic generation in photonic crystal cavities in (001) and (111)B oriented GaAs. The fundamental resonance is at 1800 nm, leading to second harmonic below the GaAs bandgap. Below-bandgap operation minimizes absorption of the second harmonic and two photon absorption of the pump. Photonic crystal cavities were fabricated in both orientations at various in-plane rotations of the GaAs substrate. The rotation dependence and farfield patterns of the second harmonic match simulation. We observe similar maximum efficiencies of 1.2 %/W in (001) and (111)B oriented GaAs., Comment: replaced with minor changes

Monolayers of transition metal dichalcogenides (TMDCs) have emerged as new optoelectronic materials in the two dimensional (2D) limit, exhibiting rich spin-valley interplays, tunable excitonic effects, and strong light-matter interactions. An essential yet undeveloped ingredient for many photonic applications is the manipulation of its light emission. Here we demonstrate the control of excitonic light emission from monolayer tungsten diselenide (WSe2) in an integrated photonic structure, achieved by transferring one monolayer onto a photonic crystal (PhC) with a cavity. In addition to the observation of greatly enhanced (~60 times) photoluminescence of WSe2 and an effectively coupled cavity-mode emission, we are able to redistribute the emitted photons both polarly and azimuthally in the far field through designing PhC structures, as revealed by momentum-resolved microscopy. A 2D optical antenna is thus constructed. Our work suggests a new way of manipulating photons in hybrid 2D photonics, important for future energy efficient optoelectronics and 2D nano-lasers., Comment: 21 pages, including main manuscript + supplementary materials

We present the design, fabrication, and characterization of high quality factor and small mode volume planar photonic crystal cavities from cubic (3C) thin films (thickness ~ 200 nm) of silicon carbide (SiC) grown epitaxially on a silicon substrate. We demonstrate cavity resonances across the telecommunications band, with wavelengths from 1,250 - 1,600 nm. Finally, we discuss possible applications in nonlinear optics, optical interconnects, and quantum information science., Comment: 7 pages, 6 figures

We demonstrate second harmonic generation at telecommunications wavelengths in L3 photonic crystal cavities in (111)-oriented GaAs. The second harmonic power from photonic crystal cavities fabricated in (111)-oriented GaAs is significantly increased compared to those fabricated in conventional (001)-oriented GaAs., Comment: 5 pages, 3 figures, re-uploaded post-reviewer comments

We use the third- and fourth-order autocorrelation functions $g^{(3)}(\tau_1,\tau_2)$ and $g^{(4)}(\tau_1,\tau_2, \tau_3)$ to detect the non-classical character of the light transmitted through a photonic-crystal nanocavity containing a strongly-coupled quantum dot probed with a train of coherent light pulses. We contrast the value of $g^{(3)}(0, 0)$ with the conventionally used $g^{(2)}(0)$ and demonstrate that in addition to being necessary for detecting two-photon states emitted by a low-intensity source, $g^{(3)}$ provides a more clear indication of the non-classical character of a light source. We also present preliminary data that demonstrates bunching in the fourth-order autocorrelation function $g^{(4)}(\tau_1,\tau_2, \tau_3)$ as the first step toward detecting three-photon states.

Fast, high efficiency, and low error single photon sources are required for implementation of a number of quantum information processing applications. The fastest triggered single photon sources to date have been demonstrated using epitaxially grown semiconductor quantum dots (QDs), which can be conveniently integrated with optical microcavities. Recent advances in QD technology, including demonstrations of high temperature and telecommunications wavelength single photon emission, have made QD single photon sources more practical. Here we discuss the applications of single photon sources and their various requirements, before reviewing the progress made on a quantum dot platform in meeting these requirements., Comment: Review article

Indistinguishable single photons are necessary for quantum information processing applications. Resonant or quasiresonant excitation of single quantum dots provides greater single photon indistinguishability than incoherent pumping, but is also more challenging experimentally. Here, we demonstrate high signal to noise quasiresonant excitation of InP/InGaP quantum dots. The excitation is provided via second harmonic generated from a telecommunications wavelength laser resonant with the fundamental mode of a photonic crystal cavity, fabricated at twice the quantum dot transition wavelength. The second harmonic is generated using the \chi(2) nonlinearity of the InGaP material matrix.

We demonstrate room temperature visible wavelength photoluminescence from In0.5Ga0.5As quantum dots embedded in a GaP membrane. Time-resolved above band photoluminescence measurements of quantum dot emission show a biexpontential decay with lifetimes of ~200 ps. We fabricate photonic crystal cavities which provide enhanced outcoupling of quantum dot emission, allowing the observation of narrow lines indicative of single quantum dot emission. This materials system is compatible with monolithic integration on Si, and is promising for high efficiency detection of single quantum dot emission as well as optoelectronic devices emitting at visible wavelengths.

We demonstrate enhanced second harmonic generation in a gallium phosphide photonic crystal waveguide with a measured external conversion efficiency of 5$\times10^{-7}$/W. Our results are promising for frequency conversion of on-chip integrated emitters having broad spectra or large inhomogeneous broadening, as well as for frequency conversion of ultrashort pulses., Comment: 3 figures

We propose and experimentally demonstrate a photonic crystal nanocavity with multiple resonances that can be tuned nearly independently. The design is composed of two orthogonal intersecting nanobeam cavities. Experimentally, we measure cavity quality factors of 6,600 and 1000 for resonances separated by 382 nm; we measure a maximum separation between resonances of 506 nm. These structures are promising for enhancing efficiency in nonlinear optical processes such as sum/difference frequency and stimulated Raman scattering., Comment: 3 figures

We demonstrate a quantum dot single photon source at 900 nm triggered at 300 MHz by a continuous wave telecommunications wavelength laser followed by an electro-optic modulator. The quantum dot is excited by on-chip-generated second harmonic radiation, resonantly enhanced by a GaAs photonic crystal cavity surrounding the InAs quantum dot. Our result suggests a path toward the realization of telecommunications-wavelength-compatible quantum dot single photon sources with speeds exceeding 1 GHz., Comment: corrected typos