Abstract: A 1D diamond nanobeam can act as a coherent mechanical interface between spin defect centers in diamond and telecom optical modes. The nanobeam includes embedded mechanical and electric field concentrators with mechanical and optical mode volumes of V m ? e ? c ? h / ? p 3 ? 1 ? 0 - 5 and Vopt/?3˜10?3, respectively. With a Group IV vacancy in the concentrator, the nanobeam can operate at spin-mechanical coupling rates approaching 40 MHz with high acousto-optical couplings. This nanobeam, used in an entanglement heralding scheme, can provide high-fidelity Bell pairs between quantum repeaters. Using the mechanical interface as an intermediary between the optical and spin subsystems enables addressing the spin defect center with telecom optics, bypassing the native wavelength of the spin. As the spin is never optically excited or addressed, the device can operate at temperatures up to 40 K with no appreciable spectral diffusion, limited by thermal losses.

Abstract: A sample holder for advanced in-situ microscopy is described. The sample holder includes integrated devices to apply external fields and other stimuli to samples being inspected. The integrated devices can emulate operating environments for the samples. The sample holder and advanced microscopy can be used to study quantum characteristics and properties of samples.

Abstract: In-network Optical Inference (IOI) provides low-latency machine learning inference by leveraging programmable switches and optical matrix multiplication. IOI uses a transceiver module, called a Neuro Transceiver, with an optical processor to perform linear operations, such as matrix multiplication, in the optical domain. IOI's transceiver modules can be plugged into programmable packet switches, which are programmed to perform non-linear activations in the electronic domain and to respond to inference queries. Processing inference queries at the programmable packet switches inside the network, without sending them to cloud or edge inference servers, significantly reduces end-to-end inference latency experienced by users.

Abstract: A photonic system is provided. The photonic system comprises a first photonic component and a second photonic component. The photonic system additionally comprises a photonic ribbon cable comprising a waveguide extending from a first end of the photonic ribbon cable to a second end of the photonic ribbon cable and having a winding geometry configured to deform, enabling the first end of the photonic ribbon cable to be extended away from the second end of the photonic ribbon cable. The first end of the photonic ribbon cable is optically coupled to the first photonic component and the second end of the waveguide is optically coupled to the second photonic component.

Abstract: Methods and systems are described for precisely adjusting characteristics of microfabricated devices after device fabrication. The adjustments can be carried out in parallel on a plurality of the microfabricated devices. By carrying out the adjustment process, uniformity of feature sizes to a few picometers (one standard deviation) and corresponding uniformity of operating characteristics for a plurality of microfabricated devices are possible.

Abstract: Analog optical neural networks (ONNs) can reduce the energy of matrix-vector multiplication in neural network inference below that of digital electronics. However, realizing this promise remains challenging due to digital-to-analog (DAC) conversion—even at low bit precisions b, encoding 2b levels of digital weights and inputs into the analog domain involves power-hungry electronics. Faced with similar challenges, telecommunications uses complex-valued Quadrature-Amplitude Modulation (QAM). QAM maximally exploits the complex amplitude to provide a quadratic 0(N2)?0(N) energy saving over intensity-only modulation. QAMNet, an ONN with lower energy consumption than existing ONNs, uses the complex nature of the amplitude of light with QAM. QAMNet accelerates complex-valued deep neural networks with accuracies indistinguishable from digital hardware.

Abstract: Optical chiplets can be mounted to zero-change VLSI chips to form an integrated electro-optical device. Control signals for controlling active optical devices on the optical chiplets can be provided from the VLSI chip and coupled to the active optical devices on the optical chiplets. The technology provides small-area, low-energy, RF optical interfaces for VLSI chips.

Abstract: A system and method for measuring qubit states. In some embodiments, the system includes a first qubit and a readout circuit, the readout circuit being configured to perform a direct readout of the state of the first qubit.

Abstract: The exponential growth in deep learning models is challenging existing computing hardware. Optical neural networks (ONNs) accelerate machine learning tasks with potentially ultrahigh bandwidth and nearly no loss in data movement. Scaling up ONNs involves improving scalability, energy efficiency, compute density, and inline nonlinearity. However, realizing all these criteria remains an unsolved challenge. Here, we demonstrate a three-dimensional spatial time-multiplexed ONN architecture based on dense arrays of microscale vertical cavity surface emitting lasers (VCSELs). The VCSELs, coherently injection-locked to a leader laser, operate at gigahertz data rates with a 7T-phase-shift voltage on the 10-millivolt level. Optical nonlinearity is incorporated into the ONN with no added energy cost using coherent detection of optical interference between VCSELs.

Abstract: An atom control architecture based on VIS-IR photonic integrated circuit (PIC) technology is characterized by (1) visible (VIS) and near-infrared (IR) wavelength operation, (2) channel counts extensible beyond 1000s of individually addressable atoms, (3) high intensity modulation extinction and (4) repeatability compatible with low gate errors, and (5) fast switching times. A 16-channel SiN-based APIC with (5.8±0.4) ns response times and <?30 dB extinction ratio at a wavelength of 780 nm. Based on a complementary metal-oxide-semiconductor (CMOS) fabrication process, this atom-control PIC (APIC) technology can be used for atomic, molecular, and optical physics and emerging applications, from quantum computers with cold atoms or ions to quantum networks with solid-state color centers. This APIC technology is especially suitable for scalable quantum information processing based on optically programmable atomic systems.

Abstract: The exponential growth in deep learning models is challenging existing computing hardware. Optical neural networks (ONNs) accelerate machine learning tasks with potentially ultrahigh bandwidth and nearly no loss in data movement. Scaling up ONNs involves improving scalability, energy efficiency, compute density, and inline nonlinearity. However, realizing all these criteria remains an unsolved challenge. Here, we demonstrate a three-dimensional spatial time-multiplexed ONN architecture based on dense arrays of microscale vertical cavity surface emitting lasers (VCSELs). The VCSELs, coherently injection-locked to a leader laser, operate at gigahertz data rates with a 7T-phase-shift voltage on the 10-millivolt level. Optical nonlinearity is incorporated into the ONN with no added energy cost using coherent detection of optical interference between VCSELs.

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: 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: 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: 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: A method for interacting with quantum states over respective time intervals comprises: providing, from at least one optical fiber interface, a fiber-coupled optical mode that controls optical coupling to and/or from an optical fiber, where at least a portion of the optical fiber extends outside of an interior of a housing comprising the at least one optical fiber interface; providing a quantum state from each quantum state emission element (QSEE) housed on or inside the housing; providing, from each of multiple portions of one or more directional structures, a preferential direction for an associated element-coupled optical mode that controls optical coupling to and from a different respective subset of one or more of the QSEEs; and scanning a scanning structure housed on or inside the housing to change an overlap between the fiber-coupled optical mode and a different respective one of the element-coupled optical modes over each time interval.

Abstract: Quantum information processing involves entangling large numbers of qubits, which can be realized as defect centers in a solid-state host. The qubits can be implemented as individual unit cells, each with its own control electronics, that are arrayed in a cryostat. Free-space control and pump beams address the qubit unit cells through a cryostat window. The qubit unit cells emit light in response to these control and pump beams and microwave pulses applied by the control electronics. The emitted light propagates through free space to a mode mixer, which interferes the optical modes from adjacent qubit unit cells for heralded Bell measurements. The qubit unit cells are small (e.g., 10 ?m square), so they can be tiled in arrays of up to millions, addressed by free-space optics with micron-scale spot sizes. The processing overhead for this architecture remains relatively constant, even with large numbers of qubits, enabling scalable large-scale quantum information processing.

Abstract: In-network Optical Inference (IOI) provides low-latency machine learning inference by leveraging programmable switches and optical matrix multiplication. IOI uses a transceiver module, called a Neuro Transceiver, with an optical processor to perform linear operations, such as matrix multiplication, in the optical domain. IOI's transceiver modules can be plugged into programmable packet switches, which are programmed to perform non-linear activations in the electronic domain and to respond to inference queries. Processing inference queries at the programmable packet switches inside the network, without sending them to cloud or edge inference servers, significantly reduces end-to-end inference latency experienced by users.

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.