Abstract: An ensemble of spin defect centers or other atom-like quantum systems in a solid-state host can be used as a compact alternative for an atomic clock thanks to an architecture that overcomes magnetic and temperature-induced systematics. A polariton-stabilized solid-state spin clock hybridizes a microwave resonator with a magnetic-field-insensitive spin transition within the ground state of a spin defect center (e.g., a nitrogen vacancy center in diamond). Detailed numerical and analytical modeling of this polariton-stabilized solid-state spin clock indicates a potential fractional frequency instability below 10?13 over a 1-second measurement time, assuming present-day experimental parameters. This stability is a significant improvement over the state-of-the-art in miniaturized atomic vapor clocks.

Abstract: Nitrogen vacancy (NV) centers in diamond combine exceptional sensitivity with nanoscale spatial resolution by optically detected magnetic resonance (ODMR). Infrared (IR)-absorption-based readout of the NV singlet state transition can increase ODMR contrast and collection efficiency. Here, a resonant diamond metallodielectric metasurface amplifies IR absorption by concentrating the optical field near the diamond surface. This plasmonic quantum sensing metasurface (PQSM) supports plasmonic surface lattice resonances and balances field localization and sensing volume to optimize spin readout sensitivity. Combined electromagnetic and rate-equation modeling suggests a near-spin-projection-noise-limited sensitivity below 1 nT Hz?1/2 per ?m2 of sensing area using numbers for contemporary NV diamond samples and fabrication techniques.

Abstract: A two-photon logic gate introduces a phase shift between two photons using a Q-switched cavity with some nonlinearity. The two-photon logic gate catches photons in and releases photons from de-coupled cavity modes in response to electronic or photonic control signals. This “catch-and-release” two-photon gate can be formed in semiconductor photonic integrated circuit (PIC) that operates at room temperature. When combined with sources, linear circuits, other logic gates, and detectors, it can be used to make a quantum computer with up to 1000 error-corrected logical qubits on a cm2 PIC, with full qubit connectivity to avoid overhead. Two-qubit gate fidelity exceeding 99% is possible with near-term technology, and scaling beyond 99.9% is possible. Two-photon logic gates are also suitable for gate-based quantum digital computing and for analog quantum computing schemes, such as adiabatic quantum computing or quantum annealing.

Abstract: Deep neural networks (DNNs) have become very popular in many areas, especially classification and prediction. However, as the number of neurons in the DNN increases to solve more complex problems, the DNN becomes limited by the latency and power consumption of existing hardware. A scalable, ultra-low latency photonic tensor processor can compute DNN layer outputs in a single shot. The processor includes free-space optics that perform passive optical copying and distribution of an input vector and integrated optoelectronics that implement passive weighting and the nonlinearity. An example of this processor classified the MNIST handwritten digit dataset (with an accuracy of 94%, which is close to the 96% ground truth accuracy). The processor can be scaled to perform near-exascale computing before hitting its fundamental throughput limit, which is set by the maximum optical bandwidth before significant loss of classification accuracy (determined experimentally).

Abstract: Component errors prevent linear photonic circuits from being scaled to large sizes. These errors can be compensated by programming the components in an order corresponding to nulling operations on a target matrix X through Givens rotations X?T†X, X?XT†. Nulling is implemented on hardware through measurements with feedback, in a way that builds up the target matrix even in the presence of hardware errors. This programming works with unknown errors and without internal sources or detectors in the circuit. Modifying the photonic circuit architecture can reduce the effect of errors still further, in some cases even rendering the hardware asymptotically perfect in the large-size limit. These modifications include adding a third directional coupler or crossing after each Mach-Zehnder interferometer in the circuit and a photonic implementation of the generalized FFT fractal.

Abstract: A hybrid quantum system performs high-fidelity quantum state transduction between a superconducting (SC) microwave qubit and the ground state spin system of a solid-state artificial atom. This transduction is mediated via an acoustic bus connected by piezoelectric transducers to the SC microwave qubit. For SC circuit qubits and diamond silicon vacancy centers in an optimized phononic cavity, the system can achieve quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of SC circuit quantum computing and artificial atoms, the hybrid quantum system provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.

Abstract: Deep neural networks (DNNs) have become very popular in many areas, especially classification and prediction. However, as the number of neurons in the DNN increases to solve more complex problems, the DNN becomes limited by the latency and power consumption of existing hardware. A scalable, ultra-low latency photonic tensor processor can compute DNN layer outputs in a single shot. The processor includes free-space optics that perform passive optical copying and distribution of an input vector and integrated optoelectronics that implement passive weighting and the nonlinearity. An example of this processor classified the MNIST handwritten digit dataset (with an accuracy of 94%, which is close to the 96% ground truth accuracy). The processor can be scaled to perform near-exascale computing before hitting its fundamental throughput limit, which is set by the maximum optical bandwidth before significant loss of classification accuracy (determined experimentally).

Abstract: It remains a challenge to generate coherent radiation in the spectral range of 0.1-10 THz (“the THz gap”), a band for applications ranging from spectroscopy to security and high-speed wireless communications. Here, we disclose how to produce coherent radiation spanning the THz gap using efficient second-harmonic generation (SHG) in low-loss dielectric structures, starting from an electronic oscillator (EO) that generates coherent radiation at frequencies of about 100 GHz. The EO is coupled to cascaded, hybrid THz-band dielectric cavities that combine (1) extreme field concentration in high-quality-factor resonators with (2) nonlinear materials enhanced by phonon resonances. These cavities convert the input radiation into higher-frequency coherent radiation at conversion efficiencies of >103%/W, making it possible to bridge the THz gap with 1 W of input power.

Abstract: Programmable photonic circuits of reconfigurable interferometers can be used to implement arbitrary operations on optical modes, providing a flexible platform for accelerating tasks in quantum simulation, signal processing, and artificial intelligence. A major obstacle to scaling up these systems is static fabrication error, where small component errors within each device accrue to produce significant errors within the circuit computation. Mitigating errors usually involves numerical optimization dependent on real-time feedback from the circuit, which can greatly limit the scalability of the hardware. Here, we present a resource-efficient, deterministic approach to correcting circuit errors by locally correcting hardware errors within individual optical gates. We apply our approach to simulations of large-scale optical neural networks and infinite impulse response filters implemented in programmable photonics, finding that they remain resilient to component error well beyond modern day process tolerances.

Abstract: Optical microcavity resonance measurements can have readout noise matching the fundamental limit set by thermal fluctuations in the cavity. Small-heat-capacity, wavelength-scale microcavities can be used as bolometers that bypass the limitations of other bolometer technologies. The microcavities can be implemented as photonic crystal cavities or micro-disks that are thermally coupled to strong mid-IR or LWIR absorbers, such as pyrolytic carbon columns. Each microcavity and the associated absorber(s) rest on hollow pillars that extend from a substrate and thermally isolate the cavity and the absorber(s) from the rest of the bolometer. This ensures that thermal transfer to the absorbers is predominantly from radiation as opposed to from conduction. As the absorbers absorb thermal radiation, they shift the resonance wavelength of the cavity.

Abstract: The typical approach to transfer quantum information between two superconducting quantum computers is to transduce the quantum information into the optical regime at the first superconducting quantum computer, transmit the quantum information in the optical regime to the second superconducting quantum computer, and then transduce the quantum information back into the microwave regime at the second superconducting quantum computer. However, direct microwave-to-optical and optical-to-microwave transduction have low fidelity due to the low microwave-optical coupling rates and added noise. These problems compound in consecutive microwave-to-optical and optical-to-microwave transduction steps. We break this rate-fidelity trade-off by heralding end-to-end entanglement with one detected photon and teleportation. In contrast to cascaded direct transduction, our technology absorbs the low optical-microwave coupling efficiency into the entanglement heralding step.

Abstract: Most artificial neural networks are implemented electronically using graphical processing units to compute products of input signals and predetermined weights. The number of weights scales as the square of the number of neurons in the neural network, causing the power and bandwidth associated with retrieving and distributing the weights in an electronic architecture to scale poorly. Switching from an electronic architecture to an optical architecture for storing and distributing weights alleviates the communications bottleneck and reduces the power per transaction for much better scaling. The weights can be distributed at terabits per second at a power cost of picojoules per bit (versus gigabits per second and femtojoules per bit for electronic architectures). The bandwidth and power advantages are even better when distributing the same weights to many optical neural networks running simultaneously.

Abstract: An ensemble of spin defect centers or other atom-like quantum systems in a solid-state host can be used as a compact alternative for an atomic clock thanks to an architecture that overcomes magnetic and temperature-induced systematics. A polariton-stabilized solid-state spin clock hybridizes a microwave resonator with a magnetic-field-insensitive spin transition within the ground state of a spin defect center (e.g., a nitrogen vacancy center in diamond). Detailed numerical and analytical modeling of this polariton-stabilized solid-state spin clock indicates a potential fractional frequency instability below 10-13 over a 1-second measurement time, assuming present-day experimental parameters. This stability is a significant improvement over the state-of-the-art in miniaturized atomic vapor clocks.

Abstract: An evaporatively cooled device and a system including the same. In some embodiments, the system includes an oligolayer conductive sheet; a superconductor; a tunneling barrier, between the oligolayer conductive sheet and the superconductor; and a bias circuit, configured to apply a bias voltage across the tunneling barrier, the bias voltage being less than a gap voltage of the superconductor and greater than one-half of the gap voltage of the superconductor.

Abstract: The next-generation of optoelectronic systems will require efficient optical signal transfer between many discrete photonic components integrated onto a single substrate. While modern assembly processes can easily integrate thousands of electrical components onto a single board, photonic assembly is far more challenging due to the wavelength-scale alignment tolerances required. Here we address this problem by introducing a self-aligning photonic coupler insensitive to x, y, z displacement and angular misalignment. The self-aligning coupler provides a translationally invariant evanescent interaction between waveguides by intersecting them at an angle, which enables a lateral and angular alignment tolerance fundamentally larger than non-evanescent approaches such as edge coupling. This technology can function as a universal photonic connector interfacing photonic integrated circuits and microchiplets across different platforms.

Abstract: Chemical-shift nuclear magnetic resonance (NMR) spectroscopy involves measuring the effects of chemical bonds in a sample on the resonance frequencies of nuclear spins in the sample. Applying a magnetic field to the sample causes the sample nuclei to emit alternating current magnetic fields that can be detected with color centers, which can act as very sensitive magnetometers. Cryogenically cooling the sample increases the sample's polarization, which in turn enhances the NMR signal strength, making it possible to detect net nuclear spins for very small samples. Flash-heating the sample or subjecting it to a magic-angle-spinning magnetic field (instead of a static magnetic field) eliminates built-in magnetic field inhomogeneities, improving measurement sensitivity without degrading the sample polarization.

Abstract: It remains a challenge to generate coherent radiation in the spectral range of 0.1-10 THz (“the THz gap”), a band for applications ranging from spectroscopy to security and high-speed wireless communications. Here, we disclose how to produce coherent radiation spanning the THz gap using efficient second-harmonic generation (SHG) in low-loss dielectric structures, starting from an electronic oscillator (EO) that generates coherent radiation at frequencies of about 100 GHz. The EO is coupled to cascaded, hybrid THz-band dielectric cavities that combine (1) extreme field concentration in high-quality-factor resonators with (2) nonlinear materials enhanced by phonon resonances. These cavities convert the input radiation into higher-frequency coherent radiation at conversion efficiencies of >103%/W, making it possible to bridge the THz gap with 1 W of input power.

Abstract: Nitrogen vacancy (NV) centers in diamond combine exceptional sensitivity with nanoscale spatial resolution by optically detected magnetic resonance (ODMR). Infrared (IR)-absorption-based readout of the NV singlet state transition can increase ODMR contrast and collection efficiency. Here, a resonant diamond metallodielectric metasurface amplifies IR absorption by concentrating the optical field near the diamond surface. This plasmonic quantum sensing metasurface (PQSM) supports plasmonic surface lattice resonances and balances field localization and sensing volume to optimize spin readout sensitivity. Combined electromagnetic and rate-equation modeling suggests a near-spin-projection-noise-limited sensitivity below 1 nT Hz?1/2 per m2 of sensing area using numbers for contemporary NV diamond samples and fabrication techniques.

Abstract: Typically, quantum systems are very sensitive to environmental fluctuations, and diagnosing errors via measurements causes unavoidable perturbations. Here, an in situ frequency-locking technique monitors and corrects frequency variations in single-photon sources based on resonators. By using the classical laser fields used for photon generation as probes to diagnose variations in the resonator frequency, the system applies feedback control to correct photon frequency errors in parallel to the optical quantum computation without disturbing the physical qubit. Our technique can be implemented on a silicon photonic device and with sub 1 pm frequency stabilization in the presence of applied environmental noise, corresponding to a fractional frequency drift of <1% of a photon linewidth. These methods can be used for feedback-controlled quantum state engineering.

Abstract: Deep learning performance is limited by computing power, which is in turn limited by energy consumption. Optics can make neural networks faster and more efficient, but current schemes suffer from limited connectivity and the large footprint of low-loss nanophotonic devices. Our optical neural network architecture addresses these problems using homodyne detection and optical data fan-out. It is scalable to large networks without sacrificing speed or consuming too much energy. It can perform inference and training and work with both fully connected and convolutional neural-network layers. In our architecture, each neural network layer operates on inputs and weights encoded onto optical pulse amplitudes. A homodyne detector computes the vector product of the inputs and weights. The nonlinear activation function is performed electronically on the output of this linear homodyne detection step.