Physical AI Brief

Digital-analog radio-over-fiber (DA-RoF) has emerged as a promising fronthaul solution that combines the high spectral efficiency of analog transmission with the robustness of digital transmission. However, the performance of DA-RoF critically depends on several tightly coupled parameters, including the rounding factor (RF), scaling factor (SF), geometric shaping (GS) factor, and pre-equalization taps coefficients, which jointly affect quantization noise, nonlinear distortion, and bandwidth-induced inter-symbol interference (ISI). Conventional grid search-based optimization is computationally prohibitive and impractical for optical communication. In this work, we propose a reinforcement-learning (RL)-enabled DA-RoF fronthaul agent architecture, capable of autonomously learning optimal transmitter parameters from end-to-end signal-to-noise ratio (SNR) feedback without a differentiable channel model. Experimental results demonstrate that the trained agent steadily improves SNR through sequential decision making and outperforms baseline, achieving ~2.7-dB SNR improvement for 1- to 4-order DA-RoF transmission, reaching final SNR of 35.8 dB, 42.9 dB, 53.8 dB, and 63.2 dB and supporting 1024-, 4096-, 16384-, 65536-quadrature amplitude modulation (QAM) format, respectively. These results validate that the proposed RL-enabled framework provides online, scalable, and hardware-efficient parameter optimization for DA-RoF fronthaul systems, paving the way toward high-order modulation format and intelligent next-generation radio access networks.

Metasurfaces enable precise manipulation of light-matter interactions, and meta-atom coupling and scaling dominates their resonant properties and functional responses. Conventionally, coupled-mode theory (CMT), coupled dipole theory (CDT) and full-wave simulation are widely adopted to analyze such coupling effects. Nevertheless, CMT and CDT are essentially phenomenological theories. Although full-wave simulation delivers high calculation accuracy, it lacks physical insight and is generally regarded as a black-box method. Here, we combine transformation optics and perturbation theory to reveal that coupling and scaling fundamentally stems from the perturbation effect induced by spatial deformation. This establishes an intuitive and universal physical picture for the coupling mechanism. Based on the proposed principle, we demonstrate the anisotropic shift of grating resonant peaks, interpret the resonance frequency drift caused by coupling of the meta-atoms, and further clarify the tuning law of resonant frequency via geometric scaling of unit structures. Theoretical predictions show excellent consistency with full-wave simulation results in all three scenarios. Given the broad applicability transformation optics and perturbation theory, the established framework possesses favorable scalability and can be potentially extended to diverse research fields including photonics crystals, Bragg fibers, two-dimensional materials and crystalline optical properties.

To overcome the difficulty of single nanostructures in approaching the theoretical limit of chiroptical performance, we design a single plasmonic twisted dimer cavity whose magnetic gap plasmon mode enables magnetic polarization near-field engineering for high chirality. The structure exhibits strong extinction under circularly polarized excitation with one handedness, while its response to the orthogonally circularly polarized light is almost perfectly suppressed, yielding a chiral g-factor as high as 1.94. Meanwhile, the structure demonstrates strong chiral-selective spin-orbit angular momentum conversion: the conversion efficiency is ~95% under circularly polarized excitation with one handedness and only ~1% under the other. By tuning geometric parameters, the g-factor can be continuously adjusted from 0 to 1.94. Without relying on periodic coupling or collective effects, this work achieves near-perfect chirality and highly efficient angular momentum manipulation solely through intrinsic near-field matching, providing a new design strategy and theoretical basis for highly selective, ultra-compact integrated chiral photonic devices.

We experimentally demonstrated a high-performance frequency upconversion detector for telecom-band photons based on a passively synchronized fiber laser system. The involved coincidence pumping technique enabled to spectrally convert the pulsed infrared photons into the visible regime with a conversion efficiency of 72\%. The overall detection efficiency of the upconversion detector reached to 30\% with a low noise equivalent power of $3\times10^{-17}\ \text{W/Hz}^{1/2}$. In contrast to previous demonstrations, the whole upconversion detection system was constructed in an all-polarization-maintaining fiber structure, thus favoring substantial improvement of compactness and robustness. Moreover, the long-term stability was manifested by at least ten-hour operation with a relative fluctuation of count rates as small as 0.26\%. The achieved features here would be desirable in many practical applications requiring efficient and robust coherent manipulation of pulsed optical fields by nonlinear frequency conversion.

In quantum technologies, continuous-variable systems offer advantages over their discrete counterparts. However, continuous-variable tomography suffers from exponentially growing sample complexity. We propose protocols using quantum mirrors to transfer the complete information of incident photonic states onto a control atomic system. This enables full photonic state characterization through measurements on the control atom alone, realized via kernel functions, direct wavefunction reconstruction, and pointwise Wigner function measurements. Our approach overcomes the limitations of conventional photon counting, statistical inference, and inverse transformation, providing a robust framework for benchmarking and verifying non-Gaussian states in continuous-variable quantum optics.

Integrated tunable lasers are central to coherent communications, wavelength-routed optical interconnects, spectroscopy and frequency-modulated continuous-wave LiDAR, yet chip-scale sources rarely combine broad wavelength coverage, nanosecond switching, high spectral purity and stable high-power operation. Here we demonstrate a frequency-agile hybrid external-cavity laser enabled by the Pockels effect in thin-film lead zirconate titanate (PZT). The strong linear electro-optic response of PZT provides direct, non-thermal tuning of compact microring resonators with a wavelength-tuning efficiency of 17 pm/V. In contrast to conventional anisotropic Pockels materials, the near-isotropic in-plane electro-optic behaviour of thin-film PZT relaxes crystal-axis layout constraints, allowing efficient Vernier wavelength selection in compact ring cavities. The PZT resonators also show no measurable photorefractive resonance distortion and no resolvable DC-bias drift during operation, preserving stable wavelength-selective feedback. The demonstrated laser achieves an 82 nm tuning range, a 5 mW fiber-coupled output power, a side-mode suppression ratio (SMSR) exceeding 56.7 dB, and a wavelength-switching time of 5.5 ns. These results establish thin-film PZT photonics as a powerful electro-optic platform for compact, high-power, and frequency-agile integrated laser sources.

Neural field surrogates can accelerate photonic design loops, but a surrogate that looks accurate in global field error can still mis-rank candidate devices when the final decision depends on localized output-port readouts. This risk is acute in propagation-dominated MMI splitters and couplers, where port power, splitting, phase, and coupling are determined by accumulated modal interference and output-window aggregation rather than by average field similarity alone. We study this field-to-design mismatch through a Field/Mediator/Readout view that separates dense complex-field error from propagation-profile and output-window errors before port aggregation. To align the surrogate with this chain, we propose PaNO, a propagation-aligned neural operator that keeps the full-field prediction interface while organizing latent states around local boundary structure, transverse modal content, axial propagation, and cross-mode interaction. We also evaluate PaNO-R2, an output-aware feedback variant for residual field components near the port region. On a 15-wavelength tunable $3{\times}3$ MMI benchmark with 4608 held-out fields, PaNO lowers NeurOLight's port-power error from 0.2018 to 0.0739 despite slightly higher cMAE, showing that global field accuracy alone is not sufficient for design-relevant readout fidelity. PaNO-R2 attains the best cMAE, propagation-profile error, output-profile error, and port-power error, reducing NeurOLight's port-power and output-profile errors by 72.7\% and 72.5\%.

Recent experiments have demonstrated the successful generation and detection of moderately squeezed vacuum states with integrated photonics. However, in order to benefit from the reduced noise of highly squeezed light, many different noise sources must be mitigated. Here, we quantify the fundamental limits these noise sources impose on squeezing measurements and find surprising generality across different platforms and designs. We combine these different limitations into a simple model that provides practical guidance for the design and benchmarking of next-generation integrated squeezed-light systems.

In quantum mechanics, a wavepacket acquires a geometric phase, known as the Berry phase, as it evolves along a closed trajectory in parameter space. In condensed matter systems, the Berry phase underlies a broad range of phenomena, including the anomalous Hall effect, orbital magnetism, and electric polarization. However, in centrosymmetric materials possessing time-reversal (TR) symmetry, its manifestation is suppressed and effectively vanishes. When a system is driven by a strong terahertz (THz) field, it can be coherently driven far from equilibrium, transiently reshaping its symmetry on sub-picosecond timescales. This capability opens new avenues for quantum control with potential applications in information processing and sensing. Here, we experimentally demonstrate that a strong THz field can transiently break inversion symmetry in MgO, inducing a dynamical complex Berry phase, thereby manipulating the topological properties of the material. Applying high-harmonic generation (HHG) spectroscopy, we directly resolve the Berry phase, accessing both its real and imaginary components. The first is associated with coherent intraband dynamics while the second with quantum tunneling through a potential barrier. This observation enables the reconstruction of the time-dependent evolution of the Berry phase within the cycle of the THz field. The coherent manipulation of solids with strong fields, combined with attosecond-resolved HHG spectroscopy, represents a fundamental step toward unveiling and controlling geometric quantum phenomena in condensed matter systems.

Lithium niobate photonic crystal nanobeam cavity (PCNBC) represents a premier platform for integrated electro-optics, offering deep sub-wavelength mode confinement, enhanced light-matter interactions, and ultralow power consumption. However, accurate characterization of the electro-optic (EO) tuning efficiency in such high-Q devices is fundamentally impeded by DC drift, a time-dependent spectral instability arising from charge redistribution, surface screening, or buffer layer relaxation under sustained electric fields. Here, we report the systematic analysis of DC drift dynamics in lithium niobate nanocavities and demonstrate that conventional quasi-static DC voltage scanning yields highly unreliable characterization data. To circumvent this limitation, we introduce a drift-free, dynamic measurement methodology that employs high-frequency triangular-wave voltage sweeps to effectively decouple the instantaneous electronic Pockels response from slow charge-relaxation processes. Validated across 35 devices with varying electrode geometries, our method delivers reproducible tuning efficiency of 4.3-4.5 pm/V with a low coefficient of variation of 1.1%, showing excellent quantitative agreement with three-dimensional finite-element simulations. This robust, drift-free measurement technique establishes a rigorous standard for the characterization and optimization of resonant cavity electro-optics, accelerating the development of high-performance thin-film lithium niobate photonic integrated circuits.

Generation and detection of coherent phonons in semiconductors by femtosecond optical pulses is a powerful tool for high-frequency acoustic control of their electronic properties. Here, we demonstrate a propagating one-dimensional acoustic grating in bulk semiconductors using above-band-gap excitation by a train of laser pulses with high repetition rate of 1 GHz. This approach enables shaping of the coherent acoustic phonon spectrum and leads to a significant enhancement of Brillouin light scattering at selected probe wavelengths in pump-probe configuration. We demonstrate this effect at a cryogenic temperature of 5 K in prototypical semiconductor systems, namely bulk crystalline GaAs and (Cd,Zn)Te, which serve as benchmark materials for the proposed method. The spectral dependence of the time-domain Brillouin light scattering amplitude exhibits resonant peaks at discrete probe wavelengths arising from Bragg reflection of the probe light by the propagating acoustic grating. A 10-30-fold resonant enhancement of the signal amplitude is observed for GaAs and (Cd,Zn)Te, determined by the finite spectral width of the probe pulse. With further spectral narrowing, enhancements of the order ~ 100-150 are expected, set by the number N of strain pulses in the acoustic grating within the sample and ultimately limited by the material parameters and sample thickness.

Hexagonal boron nitride (hBN) has emerged as a leading host for optically active quantum defects. Yet introduction of specific impurity species other than carbon remains unexplored. Here, we demonstrate an in-situ silicon doping of hBN grown by high-temperature molecular beam epitaxy (HT-MBE). By systematically varying the growth temperature from 900 to 1390 °C under a constant silicon flux, we establish an optimal window for Si incorporation to host a diverse range of emitters from 430-750 nm at room temperature. By transferring silicon-doped hBN film on SiO$_2$ substrate, we verified that single photon emitter activity was sustained in the hBN, demonstrating compatibility with device integration. The plausible origins of the observed optical transitions were discussed, and several potential candidates were proposed. Our results demonstrate a step toward a comprehensive understanding of in-situ doping of hBN and its utilization for quantum photonic applications.

Photonic integrated circuits have emerged as a powerful platform for high speed communication, sensing, and information processing due to their large bandwidth, low latency, and inherent parallelism. However, the absence of efficient, scalable, and non-volatile memory elements remains a fundamental limitation for realizing fully programmable and adaptive photonic systems. Conventional electronic memories introduce significant energy overhead, latency, and architectural inefficiencies due to repeated optical electrical conversions. Non volatile opto electronic resistive memories or OERMs have recently emerged as a promising solution to address these challenges by integrating memory functionality directly within the photonic domain. These devices combine resistive switching mechanisms with optical readout, enabling persistent state retention, multilevel programmability, and energy efficient operation. In this review, we provide a comprehensive overview of OERMs, spanning from fundamental physical mechanisms to system level applications. We first discuss the underlying resistive switching phenomena, including filamentary conduction, interface type switching, phase change transitions, and ionic migration, with particular emphasis on their interaction with confined optical modes. We then examine key material platforms such as metal oxides, transparent conducting oxides, phase change materials, and emerging two-dimensional systems, highlighting their performance trade-offs. Furthermore, we analyse device architectures and benchmark their performance in terms of switching energy, speed, endurance, and optical modulation efficiency. The integration of OERMs into programmable photonic circuits, neuromorphic systems, and in-memory optical computing architectures is critically discussed. Finally, we outline the major challenges and future research directions toward scalable, reliable

We introduce an automated, agent-driven approach to the design of photonic devices. We instruct large language models (LLMs) to solve photonic design problems, given access to software tools for performance evaluation (through numerical simulations) and quantitative acceptance criteria (e.g., fabrication rules, geometric constraints, physical-consistency checks). Within this context, agents run autonomous design loops (propose, simulate, evaluate, iterate) and generate devices with state-of-the-art performance. We demonstrate this approach in two stages: First, we run it individually on four canonical problem classes in photonic chip design: a) passive components (waveguide bends, splitters, crossings, etc.); b) active devices (silicon microring modulators (MRMs)); c) radio-frequency (RF) devices (traveling-wave electrodes for a Mach-Zehnder modulator (MZM)); d) chip layout (electrical routing). Then, we combine the previous studies in one demonstration to produce a silicon photonic modulator, incorporating layout, charge transport, optical mode, and RF electrode design. The approach generalizes to any problem that combines a numerical simulator with performance criteria that an LLM can evaluate.