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Entangled multiphoton is an ideal resource for quantum information technology. Here, narrow-bandwidth hyper-entangled quadphoton is theoretically demonstrated by quantizing degenerate Zeeman sub states through spontaneous eight-wave mixing (EWM) in a hot 85Rb. Polarization-based energy-time entanglement (output) under multiple polarized dressings is presented in detail with uncorrelated photons and Raman scattering suppressed. High-dimensional entanglement is contrived by passive non-Hermitian characteristic, and EWM-based quadphoton is genuine quadphoton with quadripartite entanglement. High quadphoton production rate is achieved from co-action of four strong input fields, and electromagnetically induced transparency (EIT) slow light effect. Atomic passive non-Hermitian characteristic provides the system with acute coherent tunability around exceptional points (EPs). The results unveil multiple coherent channels (~8) inducing oscillations with multiple periods (~19) in quantum correlations, and high-dimensional (~8) four-body entangled quantum network (capacity ~65536). Coexistent hyper and high-dimensional entanglements facilitate high quantum information capacity. The system can be converted among three working states under regulating passive non-Hermitian characteristic via triple polarized dressing. The research provides a promising approach for applying hyper-entangled multiphoton to tunable quantum networks with high information capacity, whose multi-partite entanglement and multiple-degree-of-freedom properties help optimize the accuracy of quantum sensors.

This study is an overview of the atomic data and opacity computations performed by the Atomic Physics and Astrophysics Unit of Mons University in the context of kilonova emission following neutron star mergers, in both the photospheric and nebular phases. In this work, as a sample case, we focus on a specific lanthanide ion, namely Er III. As far as the LTE photospheric phase of the kilonova ejecta is concerned, we present our calculations using both a theoretical method (the pseudo-relativistic Hartree-Fock method, HFR) and a statistical approach (the Resolved Transition Array approach, RTA) to obtain the atomic data required to estimate the Er III expansion opacity for typical conditions expected in kilonova ejecta one day after the merger. In order to draw the limitations of both of our strategies, the results obtained using the latter are compared, and a calibration procedure of the HFR atomic data in this context is also discussed. Concerning the kilonova ejecta nebular phase, atomic parameters that characterize forbidden lines in Er III are calculated using HFR as well as another computational approach, namely the Multiconfiguration Dirac–Hartree–Fock (MCDHF) method. The potential detection of such lines in late-phase kilonova spectra is then discussed. Graphical abstract

Electromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still insufficient for natural control. Recent advancements in deep learning have shown tremendous progress in biosignal processing. Multiple architectures have been proposed yielding high accuracies (>95%) for offline analysis, yet the delay caused due to optimization of the system remains a challenge for its real-time application. From this arises a need for optimized deep learning architecture based on fine-tuned hyper-parameters. Although the chance of achieving convergence is random, however, it is important to observe that the performance gain made is significant enough to justify extra computation. In this study, the convolutional neural network (CNN) was implemented to decode hand gestures from the sEMG data recorded from 18 subjects to investigate the effect of hyper-parameters on each hand gesture. Results showed that the learning rate set to either 0.0001 or 0.001 with 80-100 epochs significantly outperformed (p < 0.05) other considerations. In addition, it was observed that regardless of network configuration some motions (close hand, flex hand, extend the hand and fine grip) performed better (83.7% ± 13.5%, 71.2% ± 20.2%, 82.6% ± 13.9% and 74.6% ± 15%, respectively) throughout the course of study. So, a robust and stable myoelectric control can be designed on the basis of the best performing hand motions. With improved recognition and uniform gain in performance, the deep learning-based approach has the potential to be a more robust alternative to traditional machine learning algorithms.

For many years we have known that dust in the form of a dusty-molecular torus is responsible for the obscuration in active galactic nuclei (AGN) at large viewing angles and, thus, for the widely used phenomenological classification of AGN. Recently, we gained new observational and theoretical insights into the geometry of the torus region and the role of dust in the dynamics of emerging outflows and failed winds. We will briefly touch on all these aspects and provide a more detailed update of our dust-based model (FRADO—Failed Radiatively Accelerated Dusty Outflow) capable of explaining the processes of formation of Balmer lines in AGN. Graphic abstract

Biological molecular machines enable chemical transformations, assembly, replication and motility, but most distinctively drive chemical systems out of-equilibrium to sustain life 1 , 2 . In such processes, nanometre-sized machines produce molecular energy carriers by driving endergonic equilibrium reactions. However, transforming the work performed by artificial nanomachines 3 – 5 into chemical energy remains highly challenging. Here, we report a light-fuelled small-molecule ratchet capable of driving a coupled chemical equilibrium energetically uphill. By bridging two imine 6 – 9 macrocycles with a molecular motor 10 , 11 , the machine forms crossings and consequently adopts several distinct topologies by either a thermal (temporary bond-dissociation) or photochemical (unidirectional rotation) pathway. While the former will relax the machine towards the global energetic minimum, the latter increases the number of crossings in the system above the equilibrium value. Our approach provides a blueprint for coupling continuous mechanical motion performed by a molecular machine with a chemical transformation to reach an out-of-equilibrium state. An artificial molecular machine was designed by coupling a chemical equilibrium to a photoresponsive molecular motor. Upon light illumination, the rotary movement of the motor performs work on the chemical equilibrium generating a far-from-equilibrium state.

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024 (Second Terrestrial Very-Long-Baseline Atom Interferometry Workshop, Imperial College, April 2024), building on the initial discussions during the inaugural workshop held at CERN in March 2023 (First Terrestrial Very-Long-Baseline Atom Interferometry Workshop, CERN, March 2023). Like the summary of the first workshop (Abend et al. in AVS Quantum Sci. 6:024701, 2024), this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions (Memorandum of Understanding for the Terrestrial Very Long Baseline Atom Interferometer Study).

Significance: 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence is currently used for image-guided glioma resection. Typically, this widefield imaging method highlights the bulk of high-grade gliomas, but it underperforms at the infiltrating edge where PpIX fluorescence is not visible to the eyes. Fluorescence lifetime imaging (FLIm) has the potential to detect PpIX fluorescence below the visible detection threshold. Moreover, simultaneous acquisition of time-resolved nicotinamide adenine (phosphate) dinucleotide [NAD(P)H] fluorescence may provide metabolic information from the tumor environment to further improve overall tumor detection. Aim: We investigate the ability of pulse sampling, fiber-based FLIm to simultaneously image PpIX and NAD(P)H fluorescence of glioma infiltrative margins in patients. Approach: A mesoscopic fiber-based point-scanning FLIm device (355 nm pulses) was used to simultaneously resolve the fluorescence decay of PpIX (629/53 nm) and NAD(P)H (470/28 nm). The FLIm device enabled data acquisition at room light and rapid (<33  ms) augmentation of FLIm parameters on the surgical field-of-view. FLIm measurements from superficial tumors and tissue areas around the resection margins were performed on three glioblastoma patients in vivo following inspection of PpIX visible fluorescence with a conventional neurosurgical microscope. Microbiopsies were collected from FLIm imaged areas for histopathological evaluation. Results: The average lifetime from PpIX and NAD(P)H fluorescence distinguished between tumor and surrounding tissue. FLIm measurements of resection margins presented a range of PpIX and NAD(P)H lifetime values (τPpIX       ∼  3 to 14 ns, τNAD(P)H  =  3 to 6 ns) associated with unaffected tissue and areas of low-density tumor infiltration. Conclusions: Intraoperative FLIm could simultaneously detect the emission of PpIX and NAD(P)H from patients in vivo during craniotomy procedures. This approach doubles as a clinical tool to identify tumor areas while performing tissue resection and as a research tool to study tumor microenvironmental changes in vivo. Intraoperative FLIm of 5-ALA-induced PpIX and tissue autofluorescence makes a promising surgical adjunct to guide tumor resection surgery.

Size, shape, overall composition, and surface functionality largely determine the properties and applications of metal nanoparticles. Aside from well-defined metal clusters, their composition is often estimated assuming a quasi-spherical shape of the nanoparticle core. With decreasing diameter of the assumed circumscribed sphere, particularly in the range of only a few nanometers, the estimated nanoparticle composition increasingly deviates from the real composition, leading to significant discrepancies between anticipated and experimentally observed composition, properties, and characteristics. We here assembled a compendium of tables, models, and equations for thiol-protected gold nanoparticles that will allow experimental scientists to more accurately estimate the composition of their gold nanoparticles using TEM image analysis data. The estimates obtained from following the routines described here will then serve as a guide for further analytical characterization of as-synthesized gold nanoparticles by other bulk (thermal, structural, chemical, and compositional) and surface characterization techniques. While the tables, models, and equations are dedicated to gold nanoparticles, the composition of other metal nanoparticle cores with face-centered cubic lattices can easily be estimated simply by substituting the value for the radius of the metal atom of interest. Graphical abstract

Compact Michelson interferometers are well positioned to replace existing displacement sensors in the readout of seismometers and suspension systems, such as those used in contemporary gravitational-wave detectors. Here, we continue our previous investigation of a customised compact displacement sensor built by SmarAct that operates on the principle of deep frequency modulation. The focus of this paper is the linearity of this device and its subsequent impact on sensitivity. We show the three primary sources of nonlinearity that arise in the sensor: residual ellipticity, intrinsic distortion of the Lissajous figure, and distortion caused by exceeding the velocity limit imposed by the demodulation algorithm. We verify the theoretical models through an experimental demonstration, where we show the detrimental impact that these nonlinear effects have on device sensitivity. Finally, we simulate the effect that these nonlinearities are likely to have if implemented in the readout of the Advanced LIGO suspensions and show that the noise from nonlinearities should not dominate across the key sub-10 Hz frequency band.