Frontiers in chiral sensing, ranging from microfluidic drug screening to rapid kinetic monitoring, require high photon flux to push down the shot-noise floor. Traditional lamp-based spectrophotometers cannot meet this demand due to the conservation of etendue. Conversely, the obstacle to using broadband lasers, such as supercontinuum sources, has always been the massive relative intensity noise that obscures faint chiroptical signals. We present a broadband ultrasensitive circular dichroism (CD) spectroscopy platform that enables high-brightness CD detection near the shot-noise limit. We introduce the concept of “true balance” to force broadband light source fluctuations into a strict common mode, allowing deep noise cancelation via the balanced photodetector. By employing a symmetric triple-beam-splitter topology, our true-balance architecture suppresses noise-equivalent circular dichroism to 10 μdeg across the 600 to 800 nm spectral range. Benchmarking with specific CD detectivity shows that our system outperforms state-of-the-art techniques in detection efficiency. We validate its high fidelity and immunity to structural artifacts through trace analysis of standard chiral markers, achieving a sub-nanomole limit of detection (0.48 nmol for sucrose). By reconciling immense photon flux with near-shot-noise-limited stability, we unlock the potential of laser-based CD spectroscopy for high-throughput and micro-volume chiral analysis in biophysics and pharmaceutical development.
The ability to coherently store and manipulate optical information across multiple degrees of freedom is a central requirement for scalable quantum information processing and multidimensional quantum computing. Although polarization- and space-division multiplexings have substantially increased the capacity of classical optical systems, their extension to coherent and reconfigurable photonic memories remains a key challenge. Here, we demonstrate a two-spin-channel-multiplexed photonic memory based on chiral stimulated Brillouin scattering in a chiral photonic crystal fiber. Exploiting the intrinsic preservation of circular polarization in the chiral photonic crystal fiber, left- and right-circularly polarized modes serve as two orthogonal and independent storage channels. Multiple optical data pulses can be selectively or simultaneously stored and retrieved by simply controlling the polarization states of the write-read pulses. The storage time is continuously tunable, and the underlying Brillouin process preserves coherence and channel orthogonality. The result establishes chiral Brillouin scattering as an effective mechanism for spin-channel-multiplexed optoacoustic light storage, providing a promising route toward multidimensional photonic memories based on multiple optical degrees of freedom. It also opens new opportunities for classic and quantum information processing, reconfigurable quantum networks, and hybrid light–matter interfaces based on coherent acoustic excitations.
Whereas conventional Gaussian focusing gradually concentrates optical energy around the focal plane, abruptly autofocusing waves maintain a low peak intensity over most of their evolution before undergoing a sudden, high-contrast intensity surge at a prescribed focus. Since their introduction in 2010, their two-dimensional spatial realizations have enabled applications ranging from particle manipulation and material processing to terahertz generation and nonlinear optics. The recent work of Cao et al. marks the transition from (2+1)-dimensional spatial autofocusing to the full space-time domain through the experimental synthesis of spherical Airy wavepackets. This advance opens new opportunities for ultrafast structured light, tightly localized energy delivery, and nonlinear photonics.
Quantitative phase imaging(QPI)is increasingly becoming an indispensable metrology tool across numerous fields of science and engineering.
Ghost imaging (GI) has been under development for several years and is now achievable in both single- and multiphoton regimes with both quantum and classical light. Here, we address the experimental challenge of using sunlight as a pump beam to excite spontaneous parametric down-conversion and generate photon pairs. Remarkably, our investigations reveal that photon pairs excited from sunlight exhibit strong positional correlation, enabling their application in GI with an efficiency comparable to that achieved using a laser with similar pump power. This finding demonstrates the potential of employing an incoherent beam as the pump source in GI systems. Our research holds substantial significance as it expands the range of viable illumination sources-including scattered light and nontraditional artificial incoherent light-for imaging applications. A key potential use is in space-based quantum information systems, where this approach enables operation independent of laser sources.
Semiconductor quantum dots (QDs), a class of quantum-confined nanocrystals, serve as building blocks for the composition of nanomaterials with tunable properties, and are widely used in quantum computing, optoelectronics, and biosensing. Although large-scale synthesis and assembly of colloidal QDs are well-established, precise control of the energy states of single QDs remains challenging, which is important in some forefront applications such as quantum computing that demands robust coherent coupling between QDs. Here, we propose a stress engineering method using a nanoprobe tip to achieve fine-tuned modulation of energy states of single QDs. Specifically, by applying localized uniaxial pressure at the gigapascal level onto a CdSe/ZnS QD, a partial phase transition from wurtzite to zinc-blende structure occurs, leading to an unprecedented irreversible red shift of its bandgap in a wide range exceeding 10 nm. Furthermore, by modulating the applied pressure through controlled amplitude and cycle parameters, we have realized bidirectional spectral tuning or linearly-correlated stepwise tuning of single QD emission peak. Compared with conventional methods that are limited to unidirectional reversible blue shift in bulk QD ensembles, our method offers a versatile and precise strategy for tailoring the emission energy levels of single QDs, effectively meeting the critical requirements for QD-based high-performance photonic devices.
Yellow light sources, emitting at the wavelength of 570 to similar to 590 nm, are indispensable for many applications in biological diagnosis and treatment. However, a compact yellow laser is very difficult to attain owing to the absence of efficient electronic transitions, referring to the long-standing "yellow gap" over 60 years in the solid-state laser field. Here, we proposed a phonon engineering strategy to create yellow lasers in Nd3+-doped garnet laser crystals, which combines thermally driven electron-phonon coupling and intracavity frequency-doubling simultaneously. Via an ingenious cavity design, continuous-wave yellow lasing at 575.5 to 583 nm is realized from Nd:YAG and Nd:GGG by coupling various phonon modes. Benefiting from the thermally enhanced lattice vibrations, these yellow lasers exhibit an anomalous temperature dependence with improved output powers at high temperatures. Moreover, using this high-photon-flux yellow laser as a pump source, the fluorescent intensity of the Alexa Fluor probe is boosted by 100 times compared with the traditional green laser excitation, indicating its great potential for flow cytometry applications. These findings not only open up the possibility of creating unprecedented laser emissions in the traditional crystals but also provide a light source for molecular labeling and biological detection.
Recent advancements in computer-generated holography have demonstrated that integrating neural networks can significantly enhance the speed and quality of multidepth hologram generation for complex 3D scenes. The inherent ill-conditioned nature of the mapping between diffraction fields and holograms poses a challenge, which neural networks adeptly address by nonlinearly approximating diffraction field patterns to rapidly generate holograms that meet stringent constraints. In particular, the lack of physical interpretability in phase-to-hologram mappings, the scarcity of high-quality 3D datasets, and the inefficiency of current learning strategies collectively hinder the reconstruction quality and broader applicability of neural holography. Herein, we present a stochastic physically consistent light field to address the aforementioned limitations. As revealed by mutual information analysis, our stochastic method decouples intensity-depth correlations. Benefiting from the stochastically generated spectrum-tunable intensity information, uniformly distributed depth information, and physically consistent phase, the neural network can predict ultra-multidepth, extended-depth-of-field, and full-color holograms trained on limited-depth, narrow-depth-of-field, and single-wavelength data without pre-existing training datasets. The resulting neural network model, comprising merely 712 parameters, achieves 4K full-color holographic encoding with 256 depth layers at a frame rate of 52.9 frames per second, yielding an average peak signal-to-noise ratio of 34.91 dB.
Deep learning (DL) has revolutionized imaging through scattering media, yet its widespread adoption is hindered by limited generalization, where models trained on specific datasets fail to perform reliably in unseen scenarios. Conventional wisdom attributes this limitation to feature-prior mismatches, but we identify a more root cause: a fundamental mismatch between the learned neural mapping and the system's true physical inverse operator (T-1), driven principally by inhomogeneous spatial-intensity distributions in conventional training data. To overcome this, we introduce a physics-guided dataset homogeneity strategy. We demonstrate that enforcing spatial uniformity-ensuring all spatial modes in the region of interest are equally and sufficiently sampled-effectively aligns the learned weights with the physical transmission matrix. This approach ensures the network simulates the underlying physical laws rather than merely memorizing dataset-specific statistical biases. Specifically, by optimizing training datasets, we achieve unprecedented cross-dataset generalization: networks trained on simple digits successfully reconstruct complex face images. This physics-guided framework not only overcomes generalization barriers in scattering imaging but also establishes a universal principle for designing robust DL architectures. The conceptual repositioning of DL, from pure data-fitting to physics-simulating, is a big step forward for its reliable deployments in real-world imaging applications.
Overcoming the optical memory effect range to achieve large field-of-view imaging through scattering media without prior information has remained a significant challenge. We present a single-shot large field-of-view imaging technique based on the spatial sparsity characteristics theory of speckle pattern, enabling blind reconstruction of multiple targets beyond the optical memory effect range without prior information or wavefront modulation. The theoretical innovation lies in revealing the spatially sparse distribution of speckles when multiple isolated targets exceed the optical memory effect separation distance. By establishing a sparse mapping relationship between scattering transmission and object space, the method achieves unsupervised decoupling of low-cross-talk speckle regions while simultaneously reconstructing target intensity and positional information. Combined with the modified phase retrieval algorithm, the complete scene of multiple targets beyond the optical memory effect range is reconstructed. Experiments show that under varying scattering media and spectral bandwidths, this approach achieves a field-of-view expansion exceeding 6.82 times that of conventional methods, with a relative localization accuracy of 97.5%. We present the first introduction of spatial sparsity concepts into speckle field analysis; it establishes a new theoretical framework for deep-tissue biological observation and optical sensing in complex environments.
Optical frequency combs,featuring pulsed lasers with discrete and equally spaced spectral lines,have become one of the most active fields in photonics.
We introduce a wavelength-multiplexed diffractive information storage platform composed of dielectric surfaces that are structurally optimized at the wavelength scale using deep learning to store and project thousands of distinct image patterns, each assigned to a unique wavelength. Through numerical simulations in the visible spectrum, we demonstrated that our wavelength-multiplexed diffractive system can store and project over 4000 independent desired images/patterns within its output field-of-view, with high image quality and minimal crosstalk between spectral channels. Furthermore, in a proof-of-concept experiment, we demonstrated a two-layer diffractive design that stored six distinct patterns and projected them onto the same output field of view at six different wavelengths (i.e., 500, 548, 596, 644, 692, and 740 nm). The presented architecture does not rely on engineered material dispersion for the demonstrated visible-band operation and can potentially be applied to other spectral regions through appropriate geometric scaling. The demonstrated storage capacity, reconstruction image fidelity, and wavelength-encoded read-out of our diffractive platform offer a compact and fast-access solution for large-scale optical information storage, image projection applications.
Intense full-spectrum light sources with spectral coverage spanning from the ultraviolet (UV) to the mid-infrared (MIR) hold great promise in modern scientific applications including biomedical imaging, environmental monitoring, and material analysis. We for the first time demonstrate an all-fiber structure supercontinuum (SC) source featuring full-spectral coverage from UV to MIR (370 to 4550 nm), high output power (3.05 W), and excellent long-term stability (0.61% power fluctuation over 6 h). A pre-extended seed covering two near-zero dispersion (NZD) bands at similar to 1100 nm for photonic crystal fiber (PCF) and 1600 nm for InF3 fiber (IFF) was generated using a 1550 nm seed and nonlinear fibers; after which, an innovative cascaded Er3+/Yb3+ codoped fiber and Yb3+-doped fiber amplification structure was employed to boost the power of the two NZD bands, and a time-domain synchronized intense two-band covered pumping source was achieved. The aforementioned pumping source respectively drives the generation of dispersive wave (DW) in the UV band and the Raman frequency shift in the MIR band in PCF and IFF, respectively, achieving ultrabroad coverage and high-flatness spectrum. This breakthrough overcomes key challenges in spectral coverage, power uniformity, and system miniaturization, making the source a versatile tool for applications from biomedical imaging to material science.
Polarization-insensitive metasurfaces have been intensively explored due to their promising potential in optical communications, sensing, and information processing. Conventional metasurfaces only consider the response to the polarization state of incident light, but ignore their impacts on that of the refracted/reflected light, thus greatly degrading the device performances. Here, we propose and experimentally demonstrate a new type of polarization-maintaining metasurfaces. By tuning the mode composition, we find that incident light with orthogonal polarization can be diffracted to the same angle with nearly identical amplitude and phase, enabling polarization-maintaining wavefront control of incident waves with arbitrary polarization states. This mechanism has been verified with anomalous transmission through the metasurface: at a deflection angle of 80 deg, the polarization of the transmitted light is almost the same as that of the incident light, regardless of its position on the Poincar & eacute; sphere. This research shall improve the performance of metasurfaces and promote their practical applications.
With the increasing integration of multiband detection technologies, stealth materials capable of broadband spectral compatibility have become essential for enhancing target survivability and counter-detection capabilities. We fabricated a multifunctional concave reflection metasurface containing Au/GST/ZnS multilayers via femtosecond laser processing technology, which enables broadband multispectral camouflage of laser, infrared (IR), and visible bands. The gradient concave geometry contributes to the ultrabroad high scattering control across 0.8 to 14 mu m by synergetic near-field reconstruction at short-wave and far-field phase gradient control at long-wave, enabling simultaneous low specular reflectance and emissivity for compatible laser and IR camouflage. Meanwhile, by rationally controlling the phase transition process of Ge2Sb2Te5, its heat dissipation channel switches from a "closed" to an "open" state at different temperatures, allowing for dynamic thermal regulation without compromising IR camouflage performance. We present a viable strategy for the design of integrated stealth metasurfaces, with potential applications in advanced camouflage, infrared signature management, and thermal regulation systems.
Plasmonic two-dimensional(2D)infrared photodetectors have received extensive attention for achieving outstanding photoelectric performance,which demonstrates potential to overcome the inherent limitations of conventional infrared detection technologies.Integrating plasmonic nanostructures with 2D materials allows these devices to use localized surface plasmon(LSP)resonances to enhance light ab-sorption.Meanwhile,the decay of LSPs can generate hot carriers that can be injected into the 2D material to generate photocurrent.We summarize the recent progress of plasmonic 2D infrared photodetectors,covering key materials,fabrication techniques,plasmonic hot-carrier dynamics,photodetection mechanisms,and device designs.It also outlines future directions in material and interface engineering,device architecture,scalable fabrication,and system-level integration to advance next-generation plasmonic infrared optoelec-tronic technologies.
