Learnability of Optical Physical Unclonable Functions Through the Lens of Learning With Errors
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97 MATHEMATICS AND COMPUTING↗
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Results for “Optics and optical physics”
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A cavity-enhanced spectroscopist's lens on molecular polaritons
Polariton chemistry has been hailed as a potential new route to direct molecular processes with electromagnetic fields. To make further strides, the community needs to clarify which unusual polaritonic phenomena are true hallmarks of cavity quantum electrodynamics and which can be rationalized with classical optical physics. Here, in this work, we provide a tutorial perspective on the formation, spectroscopy, and behavior of molecular polaritons using classical optics. Where possible, we draw connections to cavity-enhanced spectroscopy and recast open questions in terms that may be more familiar to the broader community of physical chemists.
Cavity quantum electrodynamics↗
End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression
A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.
36 MATERIALS SCIENCE↗
Magnetically dependent photovoltages in permalloy films and gratings
Significant photoinduced voltages observed in permalloy structures consist of two contributions with different origins, which depend on illumination conditions, structure geometry and magnetic field in distinct ways. The first component is the plasmon drag effect voltage closely associated with plasmon propagation. The second contribution is magnetically dependent and can be related to photoinduced gradients in the sample temperature and spin polarization. Possible mechanisms of the effect are discussed
36 MATERIALS SCIENCE↗
Distributed optical fibre sensing in physical oceanography: emergence and future prospects
Distributed optical fibre sensing (DOFS) is a technology that enables continuous, real-time measurements of a range of environmental parameters along the length of a fibre optic cable. In this article, we review the recently emerged applications of DOFS techniques in physical oceanography and offer a perspective on the technology's potential for future growth within the field. The introduction of DOFS to physical oceanography is contextualised with a brief history of the technology, which spun off primarily from the use of seafloor-laid optical fibres for telecommunications purposes. The key components and underpinning physics of a DOFS system are outlined and, on their basis, the suite of variables that are observable with DOFS are discussed. The implementation factors of DOFS, which include trade-offs between measurement accuracy and spatio-temporal resolutions and ranges, are also examined. The physical oceanographic applications of DOFS to date are then illustrated with case examples of four distinct DOFS techniques: distributed temperature sensing (DTS), which can provide ocean temperature observations; distributed static strain sensing (DSS) and distributed acoustic sensing (DAS), which are sensitive to temperature, cable strain and strain-associated variables, such as pressure and ocean velocity; and ultra-long-range observations of ocean currents with optical interferometry. The forthcoming prospects of DOFS in physical oceanography are considered, and are proposed to include new fibre optic-based approaches to sense ocean salinity and measure through the water column. We conclude with reflections on the future role of DOFS within the Global Ocean Observing System, and highlight the opportunities provided by the existing world-wide network of seafloor-laid optical fibres.
Naveira Garabato, Alberto C. [Univ. of Southampton↗
Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning
Understanding the dynamics of nonequilibrium quantum many-body systems is an important research topic in a wide range of fields across condensed matter physics, quantum optics, and high-energy physics. However, numerical studies of large-scale nonequilibrium phenomena in realistic materials face serious challenges due to intrinsic high-dimensionality of quantum many-body problems and the absence of time-invariance. The nonequilibrium properties of many-body systems can be described by the dynamics of the correlator, or the Green's function of the system, whose time evolution is given by a high-dimensional system of integro-differential equations, known as the Kadanoff–Baym equations (KBEs). The time-convolution term in KBEs, which needs to be recalculated at each time step, makes it difficult to perform long-time numerical simulation. In this paper, we develop an operator-learning framework based on recurrent neural networks (RNNs) to address this challenge. We utilize RNNs to learn the nonlinear mapping between Green's functions and convolution integrals in KBEs. By using the learned operators as a surrogate model in the KBE solver, we obtain a general machine-learning scheme for predicting the dynamics of nonequilibrium Green's functions. Besides significant savings per each time step, the new methodology reduces the temporal computational complexity from $O(N_t^3)$ to $O(N_t)$ where N t is the number of steps taken in a simulation, thereby making it possible to study large many-body problems which are currently infeasible with conventional KBE solvers. Through various numerical examples, we demonstrate the effectiveness of the operator-learning based approach in providing accurate predictions of physical observables such as the reduced density matrix and time-resolved photoemission spectra. Moreover, our framework exhibits clear numerical convergence and can be easily parallelized, thereby facilitating many possible further developments and applications.
97 MATHEMATICS AND COMPUTING↗
Efficient simulation of optical spectra via machine learning and physical decomposition of environmental effects
Simulations of optical spectra can provide key insights to aid experimental interpretation of electronic excitation phenomena. For chromophores in the condensed phase, these spectra, which incorporate the coupling between electronic excitation and molecular and solvent nuclear motions, can be simulated using excitation energies obtained from molecular dynamics simulations of the chromophore and solvent. Here, we present a hybrid scheme that exploits machine learning and physically informed spectral densities to show that as few as 25 ground and excited state energetic gradient calculations can be used to construct models that accurately predict environment-influenced vibronic coupling in optical spectra. We demonstrate our approach for the green fluorescent protein chromophore in water and the cresyl violet chromophore in methanol. We show that our hybrid approach, employing a machine learning model for the high-frequency spectral density and an ab initio parameterized Debye spectral density for the low-frequency, results in a systematic improvement of the optical absorption lineshape, leading to a simple machine learning scheme that can be used for the simulation of spectral densities and optical spectra.
Snider, Andrew [Univ. of California, Merced, CA (U↗
Non-linear enhancement of ultrafast X-ray diffraction through transient resonances
Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale.
47 OTHER INSTRUMENTATION↗
A renewable double plasma mirror for Petawatt-class lasers
Exceptional pulse contrast can be critical for ultraintense laser experiments, particularly when using solid density targets, and their use is becoming widespread. However, current plasma mirror technology is becoming inadequate for the new generation of high repetition rate, high power lasers now available. We describe a novel double plasma mirror configuration based on renewable, free standing, ultrathin liquid crystal films tested at the BELLA Petawatt Laser Center. Although operating at a repetition rate of several shots per minute, this system can be scaled to a high repetition rate exceeding 1 Hz and represents an important step towards enabling sustained, continuous operation of plasma mirrors. We demonstrate an improvement of two to three orders of magnitude in contrast and a total throughput of 80%. We present the first measurements of a beam reflected from a single or double plasma mirror system using a wavefront sensor, showing a well preserved wavefront and spatial mode. Finally, we introduce a model that predicts the total throughput through this double plasma mirror. This is the first model that accurately predicts the peak reflectivity of a plasma mirror when given the laser temporal profile.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Virtual Beamline++: full-chain optical modeling for modern laser design and operation
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Physics - Solid state physics, Mathematics and Com↗
Quantum Wrapper Networking for Entanglement Management and Control in Transparent Optical Quantum Networks
The overarching goal of this three-year project was to design and experimentally demonstrate a quantum wrapper networking (QWN) protocol and architecture for entanglement management and control in coexisted classical-quantum networks, facilitating a global quantum Internet. In QWN, the quantum payload (qubits) is wrapped with classical bits as a header. The classical bits facilitate end-to-end transport of the quantum payload without having to read or alter the quantum data payload at intermediate switches and routers.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Optical Alignment with X-ray Sources Using Counter Propagating Laser Beams
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73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Enhanced Carbon Dioxide Uptake in Drilled Hollow Core Fibers for Raman Spectroscopy
Fiber-based Raman spectroscopy enhances the Raman signal by maximizing the overlap of the optical field and the gas species. However, filling the hollow-core fiber (HCF) with gas requires time that is dependent on the fiber core diameter, fiber length, and pressure of the gas. At ambient pressure, the fiber gas uptake is driven by diffusion into the fiber ends, severely limiting the response time of the system. By laser drilling access holes to the core along the length of the fiber, the uptake time of the gas is reduced, improving the system response time. In this work, we study the carbon dioxide (CO 2 ) sensor dynamics based on Raman signal intensity generated in HCFs. The signal intensity versus gas concentration is characterized by controlling the CO 2 concentration in the surrounding environment of the fiber. Next, we characterize the gas uptake time in HCFs as a function of fiber length. Finally, we optimize the access hole configuration along the fiber, demonstrating reduced sensor uptake time by a factor of three.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optical Alignment with X-ray Sources Using Counter Propagating Laser Beams
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73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Next-generation neutron detection using a 6 Li glass scintillator composite
Neutron detectors are crucial in fundamental science, nuclear security, safeguards, and civil applications. 3 He-filled gas proportional counters are the gold standard for thermal neutron detection, prized for their efficiency, neutron/gamma discrimination, and stability; however, the scarcity of 3 He has prompted the search for alternatives. Here, we introduce a neutron detector design based on a scintillating composite consisting of 6 Li glass scintillator particles dispersed in an organic matrix. A detector consisting of this scintillating composite, photomultiplier tubes (PMTs) for optical detection, and electronics for reading out the PMT signal in both pulse and current modes was prototyped and characterized using various neutron and gamma sources. The prototype achieves a measured intrinsic detection efficiency of 6.70 ± 0.01%, a die-away time of 10.3 ± 0.1 μs, a negligible gamma misidentification probability, and response linearity up to at least 3.7 × 10 6 incident neutrons/s established via a cross-calibration technique. This detector holds the potential to outperform traditional 3 He-gas-based neutron detection systems, offering a viable alternative amidst the ongoing 3 He shortage and promising advancements in neutron detection technology.
47 OTHER INSTRUMENTATION↗
Halide perovskite-polymer composite film for bright and stable light-emitting devices
Stability is the primary hindrance for the application of halide perovskite material in light-emitting devices, solar cells, and other devices. In this work, halide perovskite and polymer composite film have been prepared for stable and bright light-emitting devices. Pure-phase Cs4PbBr6 crystals have been synthesized, and their photoluminescence (PL) properties and fluorescence lifetimes have been investigated. The Cs 4 PbBr 6 crystals exhibited high uniformity but underwent rapid photodegradation under light irradiation. To address this issue, we prepared bright light-emitting devices using composite of Cs 4 PbBr 6 crystals and polyethylene oxide (PEO) as the emission layer. The aim was to improve the optical and physical properties of halide perovskites, such as photodegradation and stability. PEO, with its excellent film-forming ability, created a uniform and dense film on the halide perovskite surface, filling microscopic defects and providing a protective barrier. FTIR, morphology, and PL analyses confirmed the protective role of the halide perovskite and polymer composite film. The composite film light-emitting devices demonstrated improved stability and higher PL brightness, with a peak brightness approaching 3 × 10 8 cd/m 2 , which was approximately 75% higher than the pure halide perovskite devices.
Composite film↗
Conducting polymer-based electrochemical sensors: Progress, challenges, and future perspectives
Conducting polymers are promising due to their unique properties, such as excellent electrical and optical properties, physical and chemical stability, high conductivity, and effective redox properties with high-temperature stability and biocompatibility. Due to these properties, conducting polymers are useful in diverse applications like sensors, batteries, oil industries, biosensors, biomedicines, catalysis, cancer treatment, etc. This review article aims to discuss the recent trends and analysis of conducting polymer-based electrochemical sensors in diverse areas with all required sensor characteristics, such as the derived limit of detection, utilized techniques for the sensing analysis and derived linear dynamic range with the stability of the sensors. Conducting polymers and their nanocomposites-based electrochemical sensors have demonstrated exceptional capabilities towards detecting various biomolecules, heavy metals, pesticides, and viruses like SARS-COV-2. Incorporation of redox mediators, use of conducting hydrogels, and molecular imprinting are promising strategies for better performance of the derived sensor. The article has demonstrated the existing challenges and limitations and provided solutions in the field. In the future, conducting polymers-based electrochemical sensors can be utilized in wearable sensors and integrated with IoT devices for better reach in real-time applications. They can also be made more accessible with precise control and data output by following specific methodologies. Utilizing green and sustainable conducting polymers can be crucial in advancing eco-friendly practices in the future. Conducting polymer-based electrochemical sensors has affectivity in neurochemical and pathogen sensing, which is essential for brain function and mental health.
42 ENGINEERING↗
Collection of fluorescence from an ion using trap-integrated photonics
Spontaneously emitted photons are entangled with the electronic and nuclear degrees of freedom of the emitting atom, so interference and measurement of these photons can entangle separate matter-based quantum systems as a resource for quantum information processing. Since confinement in a single-mode facilitates the photon interference needed for generating entanglement, the dipole emission patterns relevant in spontaneous emission present a mode-matching challenge. Current demonstrations rely on bulk photon-collection and manipulation optics that suffer from large component size and system-to-system variability—factors that impede scaling to the large numbers of entangled pairs needed for quantum information processing. To address these limitations, we demonstrate a collection method that enables passive phase stability, straightforward photonic manipulation, and intrinsic reproducibility. Specifically, we engineer a waveguide-integrated grating to couple photons emitted from a trapped ion into a single optical mode within a microfabricated ion-trap chip. Using the integrated collection optic, we characterize the collection efficiency, image the ion, and detect the ion’s quantum state. The integrated optic covers 2.18% of the solid angle and collects 1.97 ± 0.3% of the spontaneously emitted light incident on the grating for a total collection efficiency of 0.043% into a single-mode waveguide. This proof-of-principle demonstration lays the foundation for leveraging the inherent stability and reproducibility of integrated photonics to create, manipulate, and measure multipartite quantum states in arrays of quantum emitters.
Optical physics↗