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Online reviews provide valuable insights into the perceived quality of facets of a product or service. While aspect-based sentiment analysis has focused on extracting these facets from reviews, there is less work understanding the impact of each aspect on overall perception. This is particularly challenging given correlations among aspects, making it difficult to isolate the effects of each. This paper introduces a methodology based on recent advances in text-based causal analysis, specifically CausalBERT, to disentangle the effect of each factor on overall review ratings. We enhance CausalBERT with three key improvements: temperature scaling for better calibrated treatment assignment estimates; hyperparameter optimization to reduce confound overadjustment; and interpretability methods to characterize discovered confounds. In this work, we treat the textual mentions in reviews as proxies for real-world attributes. We validate our approach on real and semi-synthetic data from over 600K reviews of U.S. K-12 schools. We find that the proposed enhancements result in more reliable estimates, and that perception of school administration and performance on benchmarks are significant drivers of overall school ratings. 

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 microchiplet (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 toward building large-scale quantum repeaters. 

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurementsg⁽²⁾(0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels. 

Tin-vacancy centres in diamond are spin-photon interfaces with intrinsic environmental noise insensitivity. We reveal their high optical coherence in a nanostructured environment and generate single photons with a 99.7% purity and an indistinguishability of 63(9)%. [1] 

Abstract Single-crystalline nickel-rich cathodes are a rising candidate with great potential for high-energy lithium-ion batteries due to their superior structural and chemical robustness in comparison with polycrystalline counterparts. Within the single-crystalline cathode materials, the lattice strain and defects have significant impacts on the intercalation chemistry and, therefore, play a key role in determining the macroscopic electrochemical performance. Guided by our predictive theoretical model, we have systematically evaluated the effectiveness of regaining lost capacity by modulating the lattice deformation via an energy-efficient thermal treatment at different chemical states. We demonstrate that the lattice structure recoverability is highly dependent on both the cathode composition and the state of charge, providing clues to relieving the fatigued cathode crystal for sustainable lithium-ion batteries. 

We propose a field-based design for dielectric antennas to interface diamond color centers in dielectric membranes with a Gaussian propagating far field. This antenna design enables an efficient spin-photon interface with a Purcell factor exceeding 400 and a 93% mode overlap to a 0.4 numerical aperture far-field Gaussian mode. The antenna design with the back reflector is robust to fabrication imperfections, such as variations in the dimensions of the dielectric perturbations and the emitter dipole location. The field-based dielectric antenna design provides an efficient free-space interface for closely packed arrays of quantum memories for multiplexed quantum repeaters, arrayed quantum sensors, and modular quantum computers. 

We present an efficient microwave and optical interface for quantum memories at 1.3 K based on tin-vacancy color centers in diamond and scalable integrated photonics. 

Silicon is an extremely important technological material, but the current industrial production of silicon by carbothermic reduction of SiO₂ is energy intensive and generates CO₂ emission. Here we developed a new and more sustainable method to produce silicon nanowires in bulk quantities via direct electrochemical reduction of CaSiO₃, an abundant and inexpensive silicon source soluble in molten salts, at a low temperature of 650 ⁰C by using low melting point ternary molten salts CaCl₂-MgCl₂-NaCl, which still retains high CaSiO₃ solubility, and a supporting electrolyte of CaO, which facilitates the transport of O²¯ anions, drastically improves the reaction kinetics and enables the electrolysis at low temperatures. The Si nanowire product can be used as high-capacity Li-ion battery anode materials with excellent cycling performance. This practical strategy at lower temperatures can be applied to other molten salt systems and also promising for waste glass and coal ash recycling.