Search

The development of color centers in silicon enables scalable quantum technologies by combining telecom-wavelength emission and compatibility with mature silicon fabrication. However, large-scale integration requires precise control of each emitter's optical transition to generate indistinguishable photons for quantum networking. Here, we demonstrate a foundry-fabricated photonic integrated circuit (PIC) combining suspended silicon waveguides with a microelectromechanical (MEMS) cantilever to apply local strain and spectrally tune individual G-centers. Applying up to 35 V between the cantilever and the substrate induces a reversible wavelength shift of the zero-phonon line exceeding 100 pm, with no loss in brightness. Moreover, by modeling the strain-induced shifts with a `digital twin' physical model, we achieve vertical localization of color centers with sub-3 nm vertical resolution, directly correlating their spatial position, dipole orientation, and spectral behavior. This method enables on-demand, low-power control of emission spectrum and nanoscale localization of color centers, advancing quantum networks on a foundry-compatible platform., Comment: 30 pages, 28 figures

Color centers are among the most promising candidates for quantum information processing. Central requirements for their practical applications include controlled and efficient local activation in nanophotonic devices and identical spectral features. However, producing color centers in a controlled and reliable way is inherently challenging due to the lack of comprehensive theoretical insights into their formation and the difficulty of streamlining the generation process for rapid in-situ optimization. We address these challenges by developing an end-to-end first-principles model that captures the underlying formation process of color centers. Emitters are activated through laser annealing, which allows for in-situ creation and the possibility of model-based control. Notably, our model enables the estimation of the emitters' inhomogeneous broadening down to 16 GHz in bare silicon, which translates into the creation of emitters with highly similar spectral properties. Finally, we address the challenge of in-situ deterministic activation of color centers in nanophotonic devices by going beyond bare silicon and demonstrating successful laser writing in photonic crystal optical cavities. These results lay the foundation for deterministic and large-scale integration of color centers within quantum photonic platforms., Comment: 17 pages, 10 figures, 1 table

Motivated by the recent discovery of flat bands (FBs) in breathing Kagome lattices (BKLs), we present a detailed first-principles study of the optical response of single-layer (SL) Nb$_3$Cl$_8$ using the GW-Bethe-Salpeter equation (GW-BSE) method, incorporating self-energy corrections and excitonic effects. Our findings reveal a rich spectrum of strongly bound excitons. The key results are fourfold: (i) SL Nb$_3$Cl$_8$ exhibits a dark spin-triplet Frenkel exciton ground state with binding energy substantially larger than the GW-renormalized band gap, giving rise to a negative exciton energy peak at $-0.14$ eV and indicating an excitonic Mott insulator phase potentially stable at room temperature ($k_B T = 0.025$ eV); (ii) the brightest exciton peak appears at 1.2 eV, in excellent agreement with experimental optical absorption spectra. (iii) We map the low-energy Frenkel exciton system onto a Hubbard model with spin-1 particles on a triangular lattice, resulting in frustrated spin configurations due to antiferromagnetic spin-spin exchange interaction. (iv) As the spin-triplet Frenkel excitons have electric dipoles that interact with each other via electric dipole-dipole interaction, we obtain antiferroelectric ordering, possibly stable at room temperature. Thus, we propose that Nb$_3$Cl$_8$ is a multiferroic dark spin-triplet excitonic Mott insulator., Comment: 9 pages, 5 figures

In this paper, we introduce a numerical framework designed to solve problems within the emerging field of Waveguide Quantum Electrodynamics (WQED). The framework is based on collision quantum optics, where a localized quantum system interacts sequentially with individual time-bin modes. This approach provides a physically intuitive model that allows researchers familiar with tools such as QuTiP in Python, Quantum Optics Toolbox for Matlab, or QuantumOptics.jl in Julia to efficiently set up and execute WQED simulations. Despite its conceptual simplicity, we demonstrate the framework's robust ability to handle complex WQED scenarios. These applications include the scattering of single- or two-photon pulses by quantum emitters or cavities, as well as the exploration of non-Markovian dynamics, where emitted photons are reflected back, thereby introducing feedback mechanisms., Comment: 14 pages, 7 figures

Single photon detectors (SPDs) are essential technology in quantum science, quantum network, biology, and advanced imaging. To detect the small quantum of energy carried in a photon, conventional SPDs rely on energy excitation across either a semiconductor bandgap or superconducting gap. While the energy gap suppresses the false-positive error, it also sets an energy scale that can limit the detection efficiency of lower energy photons and spectral bandwidth of the SPD. Here, we demonstrate an orthogonal approach to detect single near-infrared photons using graphene calorimeters. By exploiting the extremely low heat capacity of the pseudo-relativistic electrons in graphene near its charge neutrality point, we observe an electron temperature rise up to ~2 K using a hybrid Josephson junction. In this proof-of-principle experiment, we achieve an intrinsic quantum efficiency of 87% (75%) with dark count < 1 per second (per hour) at operation temperatures as high as 1.2 K. Our results highlight the potential of electron calorimetric SPDs for detecting lower-energy photons from the mid-IR to microwave regimes, opening pathways to study space science in far-infrared regime, to search for dark matter axions, and to advance quantum technologies across a broader electromagnetic spectrum.

Advancements in light modulator technology have been driving discoveries and progress across various fields. The problem of large-scale coherent optical control of atomic quantum systems-including cold atoms, ions, and solid-state color centers-presents among the most stringent requirements. This motivates a new generation of high-speed large-scale modulator technology with the following requirements: (R1) operation at a design wavelength of choice in the visible (VIS) to near-infrared (NIR) spectrum, (R2) a scalable technology with a high channel density (> 100mm-2 ), (R3) a high modulation speed (> 100MHz), and (R4) a high extinction ratio (> 20 dB). To fulfill these requirements, we introduce a modulator technology based on piezoelectrically actuated silicon nitride resonant waveguide gratings fabricated on 200mm diameter silicon wafers with CMOS compatible processes. We present a proof-of-concept device with 4 x 4 individually addressable 50 {mu}m x 50 {mu}m pixels or channels, each containing a resonant waveguide grating with a ~ 780 nm design wavelength, supporting > 100MHz modulation speeds, and a spectral response with > 20 dB extinction., Comment: 9 pages + 2 pages supplementary

The family of 2D layered semiconductors, including transition metal chalcogenides (TMCs) of the form MX (M=Ga, In; X=S, Se, Te) exhibit exceptional nonlinear optical properties. The energetically most favorable crystal ordering for nonlinear response is the AB layer stacking, which breaks central inversion symmetry for an arbitrary number of layers, resulting in non-zero off-diagonal elements of the $\chi^{(2n')}$ tensor, $n'$ being a positive integer, for arbitrary thickness of the materials. We perform first-principles many-body calculations of bandstructures and linear and nonlinear optical responses of monolayer (ML) and bulk TMC crystals based on $GW$-Bethe-Salpeter and Kadanoff-Baym approaches in and out of equilibrium, respectively, while taking many-body band gap renormalization and excitonic effects into account. We develop a detailed analysis of the linear and nonlinear optical selection rules by means of group and representation theory. We observe the general trend that the lowest-energy excitons are dark in 2D ML TMCs whereas they are bright or mixed bright-dark in 3D bulk TMCs, which we attribute to the difference between spatially dependent screening in 2D and constant screening in 3D. In particular, we derive general formulas for the nonlinear optical response based on exciton states in semiconductor materials. We find anti-bound excitons in ML GaS, which we attribute to dominant exciton exchange interaction. We show that by choosing elements with larger mass and by reducing the detuning energy it is possible to increase the nonlinear response not only for $\chi^{(2)}$ and $\chi^{(3)}$, responsible for SHG and third harmonic generation (THG), but also in general for $\chi^{(n)}$ nonlinear response with $n>3$, giving rise to high harmonic generation (HHG) in 2D semiconductor materials., Comment: 24 pages, 16 figures

Nanophotonic resonators are central to numerous applications, from efficient spin-photon interfaces to laser oscillators and precision sensing. A leading approach consists of photonic crystal (PhC) cavities, which have been realized in a wide range of dielectric materials. However, translating proof-of-concept devices into a functional system entails a number of additional challenges, inspiring new approaches that combine: resonators with wavelength-scale confinement and high quality factors; scalable integration with integrated circuits and photonic circuits; electrical or mechanical cavity tuning; and, in many cases, a need for heterogeneous integration with functional materials such as III-V semiconductors or diamond color centers for spin-photon interfaces. Here we introduce a concept that generates a finely tunable PhC cavity at a select wavelength between two heterogeneous optical materials whose properties satisfy the above requirements. The cavity is formed by stamping a hard-to-process material with simple waveguide geometries on top of an easy-to-process material consisting of dielectric grating mirrors and active tuning capability. We simulate our concept for the particularly challenging design problem of multiplexed quantum repeaters based on arrays of cavity-coupled diamond color centers, achieving theoretically calculated unloaded quality factors of $10^6$, mode volumes as small as $1.2(\lambda/n_{eff})^3$, and maintaining >60 percent total on-chip collection efficiency of fluorescent photons. We further introduce a method of low-power piezoelectric tuning of these hybrid diamond cavities, simulating optical resonance shifts up to ~760 GHz and color center fluorescence tuning of 5 GHz independent of cavity tuning. These results will motivate integrated photonic cavities toward larger scale systems-compatible designs., Comment: 15 pages, 6 figures, 2 supplementary figures

The energy consumption of neural network inference has become a topic of paramount importance with the growing success and adoption of deep neural networks. 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 conversion: even at low bit precisions $b$, encoding the $2^b$ levels of digital weights and inputs into the analog domain requires specialized and power-hungry electronics. Faced with similar challenges, the field of telecommunications has developed the complex-valued Quadrature-Amplitude Modulation (QAM), the workhorse modulation format for decades. QAM maximally exploits the complex amplitude to provide a quadratic $O(N^2) \to O(N)$ energy saving over intensity-only modulation. Inspired by this advantage, this work introduces QAMNet, an optical neural network hardware and architecture with superior energy consumption to existing ONNs, that fully utilizes the complex nature of the amplitude of light with QAM. When implemented with conventional telecommunications equipment, we show that QAMNet accelerates complex-valued deep neural networks with accuracies indistinguishable from digital hardware, based on physics-based simulations. Compared to standard ONNs, we find that QAMNet ONNs: (1) attain higher accuracy above moderate levels of total bit precision, (2) are more accurate above low energy budgets, and (3) are an optimal choice when hardware bit precision is limited., Comment: 9 pages, 7 figures

Detecting non-classical light is a central requirement for photonics-based quantum technologies. Unrivaled high efficiencies and low dark counts have positioned superconducting nanowire single photon detectors (SNSPDs) as the leading detector technology for fiber and integrated photonic applications. However, a central challenge lies in their integration within photonic integrated circuits regardless of material platform or surface topography. Here, we introduce a method based on transfer printing that overcomes these constraints and allows for the integration of SNSPDs onto arbitrary photonic substrates. We prove this by integrating SNSPDs and showing through-waveguide single-photon detection in commercially manufactured silicon and lithium niobate on insulator integrated photonic circuits. Our method eliminates bottlenecks to the integration of high-quality single-photon detectors, turning them into a versatile and accessible building block for scalable quantum information processing., Comment: 11 pages, 12 figures

The scalability of many programmable photonic circuits is limited by the $2\pi$ tuning range needed for the constituent phase shifters. To address this problem, we introduce the concept of a phase-efficient circuit architecture, where the average phase shift is $\ll 2\pi$. We derive a universal information-theoretic limit to the phase-shift efficiency of universal multiport interferometers, and propose a "3-MZI" architecture that approaches this limit to within a factor of $2\times$, approximately a $10\times$ reduction in average phase shift over the prior art, where the average phase shift scales inversely with system size as $O(1/\sqrt{N})$. For non-unitary circuits, we show that the 3-MZI saturates the theoretical bound for Gaussian-distributed target matrices. Using this architecture, we show optical neural network training with all phase shifters constrained to $\lesssim 0.2$ radians without loss of accuracy., Comment: 15 pages, 8 figures, 4 tables

Secure multiparty computation enables the joint evaluation of multivariate functions across distributed users while ensuring the privacy of their local inputs. This field has become increasingly urgent due to the exploding demand for computationally intensive deep learning inference. These computations are typically offloaded to cloud computing servers, leading to vulnerabilities that can compromise the security of the clients' data. To solve this problem, we introduce a linear algebra engine that leverages the quantum nature of light for information-theoretically secure multiparty computation using only conventional telecommunication components. We apply this linear algebra engine to deep learning and derive rigorous upper bounds on the information leakage of both the deep neural network weights and the client's data via the Holevo and the Cram\'er-Rao bounds, respectively. Applied to the MNIST classification task, we obtain test accuracies exceeding $96\%$ while leaking less than $0.1$ bits per weight symbol and $0.01$ bits per data symbol. This weight leakage is an order of magnitude below the minimum bit precision required for accurate deep learning using state-of-the-art quantization techniques. Our work lays the foundation for practical quantum-secure computation and unlocks secure cloud deep learning as a field.

Up to 10% of memory-safety vulnerabilities in languages like C and C++ stem from uninitialized variables. This work addresses the prevalence and lack of adequate software mitigations for uninitialized memory issues, proposing architectural protections in hardware. Capability-based addressing, such as the University of Cambridge's CHERI, mitigates many memory defects, including spatial and temporal safety violations at an architectural level. However, current CHERI designs do not handle undefined behavior from uninitialized variables. We extend the CHERI capability model to include "conditional capabilities", enabling memory-access policies based on prior operations. This allows enforcement of policies that satisfy memory safety objectives such as "no reads to memory without at least one prior write" (Write-before-Read). We present our architecture extension, compiler support, and a detailed evaluation of our approach using the QEMU full-system simulator and our modified FPGA-based CHERI-RISCV softcore. Our evaluation shows Write-before-Read conditional capabilities are practical, with high detection accuracy while adding a small (~3.5%) overhead to the existing CHERI architecture.

We present the first phase retrieval algorithm guaranteed to solve the multidimensional phase retrieval problem in polynomial arithmetic complexity without prior information. The method successfully terminates in O(N log(N)) operations for Fourier measurements with cardinality N. The algorithm is guaranteed to succeed for a large class of objects, which we term "Schwarz objects". We further present an easy-to-calculate and well-conditioned diagonal operator that transforms any feasible phase-retrieval instance into one that is solved by our method. We derive our method by combining techniques from classical complex analysis, algebraic topology, and modern numerical analysis. Concretely, we pose the phase retrieval problem as a multiplicative Cousin problem, construct an approximate solution using a modified integral used for the Schwarz problem, and refine the approximate solution to an exact solution via standard optimization methods. We present numerical experimentation demonstrating our algorithm's performance and its superiority to existing method. Finally, we demonstrate that our method is robust against Gaussian noise.

Photonic crystal cavities (PhCCs) can confine optical fields in ultra-small volumes, enabling efficient light-matter interactions for quantum and non-linear optics, sensing and all-optical signal processing. The inherent nanometric tolerances of micro-fabrication platforms can induce cavity resonant wavelength shifts two-orders of magnitude larger than cavity linewidths, prohibiting fabrication of arrays of nominally identical devices. We address this device variability by fabricating PhCCs as releasable pixels that can be transferred from their native substrate to a receiver where ordered micro-assembly can overcome the inherent fabrication variance. We demonstrate the measurement, binning and transfer of 119 PhCCs in a single session, producing spatially ordered arrays of PhCCs, sorted by resonant wavelength. Furthermore, the rapid in-situ measurement of the devices enables measurements of the PhCCs dynamic response to the print process for the first time, showing plastic and elastic effects in the seconds to hours range.

A seamless chip-to-world photonic interface enables wide-ranging advancements in optical ranging, display, communication, computation, imaging, and light-matter interaction. An optimal solution allows for 2D scanning of a diffraction-limited beam from anywhere on a photonic chip over a large number of beam-spots in free-space. Currently, devices with direct PIC integration rely on tiled apertures with poor mode qualities, large footprints, and complex control systems. Micro-mechanical beam scanners have good beam quality but lack direct PIC integration and are inertially-limited due to the use of bulk optical components or structures in which the optical aperture and actuator sizes are inextricably linked, resulting in trade-offs among resolution, speed, and footprint. Here, we overcome these limitations with the photonic "ski-jump": a nanoscale optical waveguide monolithically integrated atop a piezoelectrically actuated cantilever which passively curls ~90$^{\circ}$ out-of-plane in a footprint of <0.1 mm$^{2}$, emits sub-micron diffraction-limited optical modes, and exhibits kHz-rate mechanical resonances with quality factors exceeding 10,000. This enables two-dimensional beam-scanning with footprint-adjusted spot-rates of 68.6 mega-spots/(s$\cdot$mm$^{2}$) at CMOS-level voltages, which is equivalent to a 1 megapixel display at 100 Hz from a 1.5 mm$^{2}$ footprint, and exceeds the performance of state-of-the-art MEMS mirrors by >50$\times$. Using this device, we demonstrate image projection, video projection, and the initialization and readout of single photons from silicon vacancy centers in diamond waveguides. Based on current performance, we identify pathways for achieving >1 giga-spots at kHz-rates in a ~1 cm$^{2}$ area to provide a seamless, scalable optical pipeline between integrated photonic processors and the free-space world., Comment: 12 pages main text, 1 page methods, 10 pages supplementary information

With Fourier sensing, it is commonly the case that the field-of-view (FOV), the area of space to be imaged, is known prior to reconstruction. To date, reconstruction algorithms have focused on FOVs with simple geometries: a rectangle or a hexagon. This yields sampling patterns that are more burdensome than necessary. Due to the reduced area of imaging possible with an arbitrary (e.g., non-rectangular) FOV, the number of samples required for a high-quality images is reduced. However, when an arbitrary FOV has been considered, the reconstruction algorithm is computationally expensive. In this manuscript, we present a method to reduce the sampling pattern for an arbitrary FOV with an accompanying direct (non-iterative) reconstruction algorithm. We also present a method to decrease the computational cost of the (iterative) model-based reconstruction (MBR) algorithm. We present results using MRI data of an ankle, a pineapple, and a brain.

Distributing quantum states reliably among distant locations is a key challenge in the field of quantum networks. One-way quantum networks address this by using one-way communication and quantum error correction. Here, we analyze quantum circuit switching as a protocol to distribute quantum states in one-way quantum networks. In quantum circuit switching, pairs of users can request the delivery of multiple quantum states from one user to the other. After waiting for approval from the network, the states can be distributed either sequentially, forwarding one at a time along a path of quantum repeaters, or in parallel, sending batches of quantum states from repeater to repeater. Since repeaters can only forward a finite number of quantum states at a time, a pivotal question arises: is it advantageous to send them sequentially (allowing for multiple requests simultaneously) or in parallel (reducing processing time but handling only one request at a time)? We compare both approaches in a quantum network with a star topology. Using tools from queuing theory, we show that requests are met at a higher rate when packets are distributed in parallel, although sequential distribution can generally provide service to a larger number of users simultaneously. We also show that using a large number of quantum repeaters to combat channel losses limits the maximum distance between users, as each repeater introduces additional processing delays. These findings provide insight into the design of protocols for distributing quantum states in one-way quantum networks., Comment: Main text: 9 pages, 5 figures. Appendices: 14 pages, 8 figures

A central challenge in quantum information science and technology is achieving real-time estimation and feedforward control of quantum systems. This challenge is compounded by the inherent inhomogeneity of quantum resources, such as qubit properties and controls, and their intrinsically probabilistic nature. This leads to stochastic challenges in error detection and probabilistic outcomes in processes such as heralded remote entanglement. Given these complexities, optimizing the construction of quantum resource states is an NP-hard problem. In this paper, we address the quantum resource scheduling issue by formulating the problem and simulating it within a digitized environment, allowing the exploration and development of agent-based optimization strategies. We employ reinforcement learning agents within this probabilistic setting and introduce a new framework utilizing a Transformer model that emphasizes self-attention mechanisms for pairs of qubits. This approach facilitates dynamic scheduling by providing real-time, next-step guidance. Our method significantly improves the performance of quantum systems, achieving more than a 3$\times$ improvement over rule-based agents, and establishes an innovative framework that improves the joint design of physical and control systems for quantum applications in communication, networking, and computing.

Quantum sensors based on solid-state defects, in particular nitrogen-vacancy (NV) centers in diamond, enable precise measurement of magnetic fields, temperature, rotation, and electric fields. However, the sensitivity of leading NV spin ensemble sensors remains far from the intrinsic spin-projection noise limit. Here we move towards this quantum limit of performance by introducing (i) a cavity quantum electrodynamic (cQED) hybrid system operating in the strong coupling regime, which enables high readout fidelity of an NV ensemble using microwave homodyne detection; (ii) a comprehensive nonlinear model of the cQED sensor operation, including NV ensemble inhomogeneity and optical polarization; and (iii) ``spin refrigeration'' where the optically-polarized spin ensemble sharply reduces the ambient-temperature microwave thermal noise, resulting in enhanced sensitivity. Applying these advances to magnetometry, we demonstrate a broadband sensitivity of 580 fT/$\sqrt{\mathrm{Hz}}$ around 15 kHz in ambient conditions. We then discuss the implications of this model for design of future magnetometers, including devices approaching 12 fT/$\sqrt{\mathrm{Hz}}$ sensitivity. Applications of these techniques extend to the fields of gyroscope and clock technologies., Comment: 7 pages, 5 figures

A central challenge in quantum networking is transferring quantum states between different physical modalities, such as between flying photonic qubits and stationary quantum memories. One implementation entails using spin-photon interfaces that combine solid-state spin qubits, such as color centers in diamond, with photonic nanostructures. However, while high-fidelity spin-photon interactions have been demonstrated on isolated devices, building practical quantum repeaters requires scaling to large numbers of interfaces yet to be realized. Here, we demonstrate integration of nanophotonic cavities containing tin-vacancy (SnV) centers in a photonic integrated circuit (PIC). Out of a six-channel quantum micro-chiplet (QMC), we find four coupled SnV-cavity devices with an average Purcell factor of ~7. Based on system analyses and numerical simulations, we find with near-term improvements this multiplexed architecture can enable high-fidelity quantum state transfer, paving the way towards building large-scale quantum repeaters., Comment: to be published in Optica Quantum

Programmable spatiotemporal control of light is crucial for advancements in optical communications, imaging, and quantum technologies. Commercial spatial light modulators (SLMs) typically have megapixel-scale apertures but are limited to ~kHz operational speeds. Developing a device that controls a similar number of spatial modes at high speeds could potentially transform fields such as imaging through scattering media, quantum computing with cold atoms and ions, and high-speed machine vision, but to date remains an open challenge. In this work we introduce and demonstrate a free-form, resonant electro-optic (EO) modulator with megapixel apertures using CMOS integration. The optical layer features a Lithium Niobate (LN) thin-film integrated with a photonic crystal (PhC), yielding a guided mode resonance (GMR) with a Q-factor>1000, a field overlap coefficient ~90% and a 1.6 GHz 3-dB modulation bandwidth (detector limited). To realize a free-form and scalable SLM, we fabricate the PhC via interference lithography and develop a procedure to bond the device to a megapixel CMOS backplane. We identify limitations in existing EO materials and CMOS backplanes that must be overcome to simultaneously achieve megapixel-scale, GHz-rate operation. The `LN on Silicon' (LNoS) architecture we present is a blueprint towards realizing such devices.

The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), internet of things (IoT) and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware. Here we demonstrate a hypermultiplexed integratedphotonics-based tensor optical processor (HITOP) that can perform trillions of operations per second (TOPS) at the energy efficiency of 40 TOPS/W. Space-time-wavelength three-dimensional (3D) optical parallelism enables O($N^{2}$) operations per clock-cycle using O($N$) modulator devices. The system is built with wafer-fabricated III/V micron-scale lasers and high-speed thin-film Lithium-Niobate electro-optics for encoding at 10s femtojoule/symbol. Lasing threshold incorporates analog inline rectifier (ReLu) nonlinearity for low-latency activation. The system scalability is verified with machine learning models of 405,000 parameters. A combination of high clockrates, energy-efficient processing and programmability unlocks the potential of light for large-scale AI accelerators in applications ranging from training of large AI models to real-time decision making in edge deployment.

Semiconductor single-photon detectors cannot be straightforwardly adapted for the microwave regime, primarily because microwave photons carry far less energy and thus require cryogenic temperatures and specialized architectures. Here, we propose a hybrid spin-optomechanical interface to detect single microwave photons where the microwave photons are coupled to a phononic resonator via piezoelectric actuation. This phononic cavity also acts as a photonic cavity with either a single embedded Silicon-Vacancy (SiV) center in diamond or an ensemble of these centers, bridging optical single-photon detection protocols into the microwave domain. We model the detection process as a communication channel whose capacity is quantified by the mutual information \(I(A;B)\) between the true photon occupancy (A) and the detector outcome (B). Depending on experimentally achievable parameters, simulations predict \(I(A;B)\) in the range \(0.57\,\ln(2)\) to \(0.67\,\ln(2)\), corresponding to true-positive (detection) probabilities above 90\% and false-positive (dark count) probabilities below 10\% per detection interval. These results suggest a viable path to low-noise, high-efficiency single-photon detection at microwave frequencies.

Photonic neural networks have demonstrated their potential over the past decades, but have not yet reached the full extent of their capabilities. One reason for this lies in an essential component - the nonlinear activation function, which ensures that the neural network can perform the required arbitrary nonlinear transformation. The desired all-optical nonlinear activation function is difficult to realize, and as a result, most of the reported photonic neural networks rely on opto-electronic activation functions. Usually, the sacrifices made are the unique advantages of photonics, such as resource-efficient coherent and frequency-multiplexed information encoding. In addition, opto-electronic activation functions normally limit the photonic neural network depth by adding insertion losses. Here, we experimentally demonstrate an in-fiber photonic nonlinear activation function based on stimulated Brillouin scattering. Our design is coherent and frequency selective, making it suitable for multi-frequency neural networks. The optoacoustic activation function can be tuned continuously and all-optically between a variety of activation functions such as LeakyReLU, Sigmoid, and Quadratic. In addition, our design amplifies the input signal with gain as high as $20\,\mathrm{dB}$, compensating for insertion losses on the fly, and thus paving the way for deep optical neural networks.

Thin-Film Lithium Niobate (TFLN) is an emerging integrated photonic platform showing great promise due to its large second-order nonlinearity at microwave and optical frequencies, cryogenic compatibility, large piezoelectric response, and low optical loss at visible and near-infrared wavelengths. These properties enabled Mach-Zehnder interferometer-based devices to demonstrate amplitude- and in-phase/quadrature (IQ) modulation at voltage levels compatible with complementary metal-oxide-semiconductor (CMOS) electronics. Maintaining low-voltage operation requires centimeter-scale device lengths, making it challenging to realize the large-scale circuits required by ever-increasing bandwidth demands in data communications. Reduced device sizes reaching the 10 um scale are possible with photonic crystal (PhC) cavities. So far, their operation has been limited to modulation of amplitudes and required circulators or lacked cascadability. Here, we demonstrate a compact IQ modulator using two PhC cavities operating as phase shifters in a Fabry-Perot-enhanced Michelson interferometer configuration. It supports cascadable amplitude and phase modulation at GHz bandwidths with CMOS-compatible voltages. While the bandwidth limitation of resonant devices is often considered detrimental, their compactness enables dense co-integration with CMOS electronics where clock-rate-level operation (few GHz) removes power-hungry electrical time-multiplexing. Recent demonstrations of chip-scale transceivers with dense-wavelength division multiplied transceivers could be monolithically implemented and driven toward ultimate information densities using TFLN electro-optic frequency combs and our PhC IQ modulators., Comment: 27 pages, 27 figures

We propose a scalable design for a spin-photon interface to a color center in a diamond microdisk. The design consists of a silicon oxynitride hexagonal lattice overlaid on a diamond microdisk to enable vertical emission from the microdisk into low-numerical aperture modes, with quantum efficiencies as high as 45\% for a tin vacancy (SnV) center. Our design is robust to manufacturing errors, potentially enabling large scale fabrication of quantum emitters coupled to optical collection modes. We also introduce a novel approach for optimizing the free space performance of a complex structure using a dipole model, achieving comparable results to full-wave finite difference time domain simulations with a 650,000 times reduction in computational time., Comment: 10 pages, 5 figures

Color centers in diamond play a central role in the development of quantum photonic technologies, and their importance is only expected to grow in the near future. For many quantum applications, high collection efficiency from individual emitters is required, but the refractive index mismatch between diamond and air limits the optimal collection efficiency with conventional diamond device geometries. While different out-coupling methods with near-unity efficiency exist, many have yet to be realized due to current limitations in nanofabrication methods, especially for mechanically hard materials like diamond. Here, we leverage electron-beam-induced etching to modify Sn-implanted diamond quantum microchiplets containing integrated waveguides with width and thickness of 280 nm and 200 nm, respectively. This approach allows for simultaneous high-resolution imaging and modification of the host matrix with an open geometry and direct writing. When coupled with the cathodoluminescence signal generated from the electron-emitter interactions, we can monitor the enhancement of the quantum emitters in real-time with nanoscale spatial resolution. The operando measurement and manipulation of single photon emitters demonstrated here provides a new foundation for the control of emitter-cavity interactions in integrated quantum photonics., Comment: 7 pages, 4 figures

Compressed sensing is an imaging paradigm that allows one to invert an underdetermined linear system by imposing the a priori knowledge that the sought after solution is sparse (i.e., mostly zeros). Previous works have shown that if one also knows something about the sparsity pattern (the locations where non-zero entries exist), one can take advantage of this structure to improve the quality of the result. A significant application of compressed sensing is magnetic resonance imaging (MRI), where samples are acquired in the Fourier domain. Compressed sensing allows one to reconstruct a high-quality image with fewer samples which can be collected with a faster scan. This increases the robustness of MRI to patient motion since less motion is possible during the shorter scan. Parallel imaging, where multiple coils are used to gather data, is another an more ubiquitously used method for accelerating MRI. Existing combinations of these acceleration methods, such as Sparse SENSE, yield high quality images with an even shorter scan time than either technique alone. In this work, we show how to modify Sparse SENSE with structured sparsity to reconstruct a high quality image with even fewer samples., Comment: 8 pages, 5 figures