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Boundary conforming coordinates are commonly used in plasma physics to describe the geometry of toroidal domains, for example, in three-dimensional magnetohydrodynamic equilibrium solvers. The magnetohydrodynamic equilibrium configuration can be approximated with an inverse map, defining nested surfaces of constant magnetic flux. For equilibrium solvers that solve for this inverse map iteratively, the initial guess for the inverse map must be well defined and invertible. Even if magnetic islands are to be included in the representation, boundary conforming coordinates can still be useful, for example to parametrize the interface surfaces in multi-region, relaxed magnetohydrodynamics. Given a fixed boundary shape, finding a valid boundary conforming mapping can be challenging, especially for the non-convex boundaries from recent developments in stellarator optimization. In this work, we propose a new algorithm to construct such a mapping, by solving two Dirichlet-Laplace problems via a boundary integral method. We can prove that the generated harmonic map is always smooth and has a smooth inverse. Furthermore, we can find a discrete approximation of the mapping that preserves this property.

After the discovery of a cross-luminescence (CL) in BaF2 in 1982, a large number of CL scintillators were investigated. However, no CL scintillator superior to BaF2 has been discovered, and the research of CL scintillators has subsided. Recent technological development in medical imaging and high-energy physics created a new demand for ultra-fast scintillators further supported by the development of UV-sensitive semiconductor photodetectors. As a consequence, renewed interest in CL scintillators appeared. To satisfy the requirements of fast timing applications high photo-detection efficiency, e. i. a good spectral match between the scintillator and photodetector must be achieved. Cesium-based ternary chlorides could provide a red-shift (~1.5 eV) of CL towards the sensitive region of the photodetector (PMT or SiPM) while keeping light output and timing characteristics comparable to BaF2., Comment: 10 pages, 13 figures, 56 references

Novel red-emitting scintillator Li$_2$MnCl$_4$ is proposed as a candidate for thermal neutron detection. It features high Li content, low density, low effective atomic number, and emission in red-NIR region. These characteristics make it an interesting candidate for long distance neutron detection in harsh enviroments e. g. decomisioning of nuclear powerplants. The absorption spectrum is thoroughly investigated in the scope of Tanabe-Sugano diagram. Luminescence mechanism in the undoped Li$_2$MnCl$_4$ is studied in depth. Doping by Eu$^{2+}$ and Ce$^{3+}$ is introduced as a trial to improve the scintillation efficiency. We show in the Eu$^{2+}$ and Ce$^{3+}$ doped Li$_2$MnCl$_4$ that luminescence mechanism involves energy transfer from the dopants to Mn$^{2+}$, and propose the local lattice distortion around the dopant and a possible charge compensation mechanisms., Comment: 8 pages, 10 figures, 2 tables, 26 references

Fast emitting polymeric scintillators are requested in advanced applications where high-speed detectors with large signal-to-noise ratio are needed. However, their low density implies a weak stopping power of high energy radiations, thus a limited light output and sensitivity. To enhance their performances, polymeric scintillators can be loaded with dense nanoparticles (NPs). We investigate the properties of a series of polymeric scintillators by means of photoluminescence and scintillation spectroscopy, comparing standard scintillators with a composite system loaded with dense hafnium dioxide (HfO2) NPs. The nanocomposite shows a scintillation yield enhancement of +100% with unchanged time response. We provide for the first time an interpretation of this effect, pointing out the local effect of NPs in the generation of emissive states upon interaction with the ionizing radiation. The obtained results indicate that coupling of fast conjugated emitters with optically inert dense NPs could allow to surpass the actual limits of pure polymeric scintillators., Comment: 14 pages, 4 figures

Energy transfer between different mechanical degrees of freedom in atom-molecule collisions has been widely studied and largely understood. However, systems involving spins remain less explored, especially with a state-to-state precision. Here, we directly observed the energy transfer from atomic hyperfine to molecular rotation in the $^{87}$Rb ($|F_a,M_{F_a}\rangle = |2,2\rangle$) + $^{40}$K$^{87}$Rb (in the rovibronic ground state $N=0$) $\longrightarrow$ Rb ($ |1,1\rangle$) + KRb ($N=0,1,2$) exothermic collision. We probed the quantum states of the collision products using resonance-enhanced multi-photon ionization followed by time-of-flight mass spectrometry. We also carried out state-of-the-art quantum scattering calculations, which rigorously take into account the coupling between the spin and rotational degrees of freedom at short range, and assume that the KRb monomer can be treated as a rigid rotor moving on a single potential energy surface. The calculated product rotational state distribution deviates from the observations even after extensive tuning of the atom-molecule potential energy surface, suggesting that vibrational degrees of freedom and conical intersections play an important part in ultracold Rb + KRb collisions. Additionally, our ab initio calculations indicate that spin-rotation coupling is dramatically enhanced near a conical intersection, which is energetically accessible at short range. The observations confirm that spin is coupled to mechanical rotation at short range and establish a benchmark for future theoretical studies.

Learned video compression methods already outperform VVC in the low-delay (LD) case, but the random-access (RA) scenario remains challenging. Most works on learned RA video compression either use HEVC as an anchor or compare it to VVC in specific test conditions, using RGB-PSNR metric instead of Y-PSNR and avoiding comprehensive evaluation. Here, we present an end-to-end learned video codec for random access that combines training on long sequences of frames, rate allocation designed for hierarchical coding and content adaptation on inference. We show that under common test conditions (JVET-CTC), it achieves results comparable to VTM (VVC reference software) in terms of YUV-PSNR BD-Rate on some classes of videos, and outperforms it on almost all test sets in terms of VMAF BD-Rate. On average it surpasses open LD and RA end-to-end solutions in terms of VMAF and YUV BD-Rates.

Digital systems are growing in importance and computing hardware is growing more heterogeneous. Hardware design, however, remains laborious and expensive, in part due to the limitations of conventional hardware description languages (HDLs) like VHDL and Verilog. A longstanding research goal has been programming hardware like software, with high-level languages that can generate efficient hardware designs. This paper describes Kanagawa, a language that takes a new approach to combine the programmer productivity benefits of traditional High-Level Synthesis (HLS) approaches with the expressibility and hardware efficiency of Register-Transfer Level (RTL) design. The language's concise syntax, matched with a hardware design-friendly execution model, permits a relatively simple toolchain to map high-level code into efficient hardware implementations., Comment: Accepted to PLDI'24

In this paper, we show that transferring knowledge from other domains of video understanding combined with large-scale learning can improve robustness of Video Object Segmentation (VOS) under complex circumstances. Namely, we focus on integrating scene global motion knowledge to improve large-scale semi-supervised Video Object Segmentation. Prior works on VOS mostly rely on direct comparison of semantic and contextual features to perform dense matching between current and past frames, passing over actual motion structure. On the other hand, Optical Flow Estimation task aims to approximate the scene motion field, exposing global motion patterns which are typically undiscoverable during all pairs similarity search. We present WarpFormer, an architecture for semi-supervised Video Object Segmentation that exploits existing knowledge in motion understanding to conduct smoother propagation and more accurate matching. Our framework employs a generic pretrained Optical Flow Estimation network whose prediction is used to warp both past frames and instance segmentation masks to the current frame domain. Consequently, warped segmentation masks are refined and fused together aiming to inpaint occluded regions and eliminate artifacts caused by flow field imperfects. Additionally, we employ novel large-scale MOSE 2023 dataset to train model on various complex scenarios. Our method demonstrates strong performance on DAVIS 2016/2017 validation (93.0% and 85.9%), DAVIS 2017 test-dev (80.6%) and YouTube-VOS 2019 validation (83.8%) that is competitive with alternative state-of-the-art methods while using much simpler memory mechanism and instance understanding logic.

The recent works on Video Object Segmentation achieved remarkable results by matching dense semantic and instance-level features between the current and previous frames for long-time propagation. Nevertheless, global feature matching ignores scene motion context, failing to satisfy temporal consistency. Even though some methods introduce local matching branch to achieve smooth propagation, they fail to model complex appearance changes due to the constraints of the local window. In this paper, we present DeVOS (Deformable VOS), an architecture for Video Object Segmentation that combines memory-based matching with motion-guided propagation resulting in stable long-term modeling and strong temporal consistency. For short-term local propagation, we propose a novel attention mechanism ADVA (Adaptive Deformable Video Attention), allowing the adaption of similarity search region to query-specific semantic features, which ensures robust tracking of complex shape and scale changes. DeVOS employs an optical flow to obtain scene motion features which are further injected to deformable attention as strong priors to learnable offsets. Our method achieves top-rank performance on DAVIS 2017 val and test-dev (88.1%, 83.0%), YouTube-VOS 2019 val (86.6%) while featuring consistent run-time speed and stable memory consumption

The usage of a GaAsP (gallium arsenide phosphide) photomultiplier for microscopical imaging allows the evaluation of low-light luminescent objects. We designed a setup for collecting a confocal microscopic image signal, which is divided into 14 equal-sized input channels. The division is achieved with a beamsplitter and two fiber bundles consisting of seven fibers each. Re-imaging the confocal pinhole by such a densely packed fiber bundle permits the utilization of a photon re-localization approach to overcome the optical resolution limit. The center fiber creates a real-time image, while the outer fibers enable a higher-resolution image via an image scanning microscope (ISM) signal calculation. The fiber bundles are enclosed in a fused silica capillary and are drawn out to create one solid fiber bundle. During the drawing process, the fiber bundles are tapered down to an outer diameter size of 400 {\mu}m, with each fiber having a less than 0.3 Airy unit diameter. For the photomultiplier interface, all fibers of both fiber bundles are integrated into a v-groove array, with each fiber representing a detection input, which is followed by projection optics for imaging onto the multichannel detector. The resulting confocal super-resolution microscope is suitable for the application of time-correlated single photon counting (TCSPC) techniques such as fluorescence lifetime imaging (FLIM), time-resolved anisotropy, or F\"orster resonance energy transfer (FRET) imaging.

Complete quantum control of a stationary quantum bit embedded in a quantum emitter is crucial for photonic quantum information technologies. Recently, the orbital degree of freedom in optically active quantum dots has emerged as a promising candidate. However, the essential ability to perform arbitrary rotations on orbital qubits remains elusive. Here, we demonstrate arbitrary rotation of a hole orbital qubit with direct phase control using picosecond optical pulses. This is achieved by successfully inducing stimulated Raman transitions within $\Lambda$ systems coupled via radiative Auger processes. The new capability enables direct control of polar and azimuth angles of the Bloch vector without requiring timed precession. Our results establish orbital states in solid-state quantum emitters as a viable resource for applications in high-speed quantum information processing., Comment: Manuscript with 7 pages and 4 figures plus Supplementary Material comprising 9 pages and 10 figures

Coherent superpositions and entanglement are hallmarks of quantum mechanics, but they are fragile and can easily be perturbed by their environment. Selected isolated physical systems can maintain coherence and generate entanglement using well-controlled interactions. Chemical reactions, where bonds break and form, are highly dynamic quantum processes. A fundamental question is whether coherence can be preserved in chemical reactions and then harnessed to generate entangled products. Here we investigate this question by studying the 2KRb $\rightarrow$ K$_2$ + Rb$_2$ reaction at 500 nK, focusing on the the nuclear spin degrees of freedom. We prepare the initial nuclear spins in KRb in an entangled state and characterize the preserved coherence in nuclear spin wavefunction after the reaction. The data are consistent with full coherence at the end of the reaction. This suggests that entanglement can be prepared within the reactants, followed by a chemical reaction that produces separate, entangled molecules. We additionally demonstrate control of the reaction product state distribution by deliberately decohering the reactants., Comment: 14 pages, 7 figures

The construction of a large-scale quantum internet requires quantum repeaters containing multiple entangled photon sources with identical wavelengths. Semiconductor quantum dots can generate entangled photon pairs deterministically with high fidelity. However, realizing wavelength-matched quantum-dot entangled photon sources faces two difficulties: the non-uniformity of emission wavelength and exciton fine-structure splitting induced fidelity reduction. Typically, these two factors are not independently tunable, making it challenging to achieve simultaneous improvement. In this work, we demonstrate wavelength-tunable entangled photon sources based on droplet-etched GaAs quantum dots through the combined use of AC and quantum-confined Stark effects. The emission wavelength can be tuned by ~1 meV while preserving an entanglement fidelity f exceeding 0.955(1) in the entire tuning range. Based on this hybrid tuning scheme, we finally demonstrate multiple wavelength-matched entangled photon sources with f>0.919(3), paving a way towards robust and scalable on-demand entangled photon sources for quantum internet and integrated quantum optical circuits., Comment: Main text: 11 pages, 6 figures, Supplementary information: 7 pages, 6 figures, 2 tables

A spin-photon interface should operate with both coherent photons and a coherent spin to enable cluster-state generation and entanglement distribution. In high-quality devices, self-assembled GaAs quantum dots are near-perfect emitters of on-demand coherent photons. However, the spin rapidly decoheres via the magnetic noise arising from the host nuclei. Here, we address this drawback by implementing an all-optical nuclear-spin cooling scheme on a GaAs quantum dot. The electron-spin coherence time increases 156-fold from $T_2^*$ = 3.9 ns to 0.608 $\mu$s. The cooling scheme depends on a non-collinear term in the hyperfine interaction. The results show that such a term is present even though the strain is low and no external stress is applied. Our work highlights the potential of optically-active GaAs quantum dots as fast, highly coherent spin-photon interfaces.

We present the white paper developed during the QEYSSat 2.0 study, which was undertaken between June 2021 and March 2022. The study objective was to establish a technology road-map for a Canada-wide quantum network enabled by satellites. We survey the state-of-art in quantum communication technologies, identify the main applications and architectures, review the technical readiness levels and technology bottlenecks and identify a future mission scenario. We report the findings of a dedicated one-day workshop that included Canadian stakeholders from government, industry and academia to gather inputs and insights for the applications and technical road-map. We also provide an overview of the Quantum EncrYption and Science Satellite (QEYSSat) mission expected to launch in 2024-2025 and its anticipated outcomes. One of the main outcomes of this study is that developing the main elements for a Canada-wide quantum internet will have the highest level of impact, which includes Canada-wide entanglement distribution and teleportation. We present and analyze a possible future mission ('QEYSSat 2.0') that would enable a long range quantum teleportation across Canada as an important step towards this vision., Comment: 108 pages, 38 figures, white paper to be submitted to CJP

Improved miniaturization capabilities for complex fisheye camera systems have recently led to the introduction of many compact 360-degree cameras on the consumer technology market. Designed primarily for recreational photography, several manufacturers have decided to allow users access to raw imagery for further editing flexibility, thereby offering data at sensor level that can be directly exploited for absolute-light quantification. In this study, we demonstrate methodologies to carefully calibrate a consumer-grade 360-degree camera for radiometry use. The methods include linearity analysis, geometric calibration, assessment of the illumination fall-off across the image plane, spectral-response determination, absolute spectral-radiance calibration, immersion factor determination and dark-frame analysis. Accuracy of the calibration was validated by a real-world experiment comparing sky radiance measurements with a co-localized Compact Optical Profiling System (C-OPS, Biospherical Instruments Inc.), which gave mean unbiased percentage differences of less than 21.1 %. Using the photon-transfer technique, we calculated that this camera consisting of two fisheyes with a 182$^\circ$ field of view in air (152$^\circ$ in water) has a limit of detection of at least $4.6 \times 10^{-7}$ $\mathrm{W \cdot sr^{-1} \cdot m^{-2} \cdot nm^{-1}}$ in its three spectral channels. This technology, with properly stored calibration data, may benefit researchers from multiple scientific areas interested in radiometric geometric light-field study. While some of these radiometric calibration methods are complex or costly, this work opens up possibilities for easy-to-use, inexpensive, and accessible radiance cameras.

Coherently driven semiconductor quantum dots are one of the most promising platforms for non-classical light sources and quantum logic gates which form the foundation of photonic quantum technologies. However, to date, coherent manipulation of single charge carriers in quantum dots is limited mainly to their lowest orbital states. Ultrafast coherent control of high-orbital states is obstructed by the demand for tunable terahertz pulses. To break this constraint, we demonstrate an all-optical method to control high-orbital states of a hole via stimulated Auger process. The coherent nature of the Auger process is proved by Rabi oscillation and Ramsey interference. Harnessing this coherence further enables the investigation of single-hole relaxation mechanism. A hole relaxation time of 161 ps is observed and attributed to the phonon bottleneck effect. Our work opens new possibilities for understanding the fundamental properties of high-orbital states in quantum emitters and developing new types of orbital-based quantum photonic devices., Comment: Manuscript with 14 pages and 6 figures plus supplementary Information comprising 15 pages and 14 figures. Nature Nanotechnology (24 July 2023)

Medical image segmentation often requires segmenting multiple elliptical objects on a single image. This includes, among other tasks, segmenting vessels such as the aorta in axial CTA slices. In this paper, we present a general approach to improving the semantic segmentation performance of neural networks in these tasks and validate our approach on the task of aorta segmentation. We use a cascade of two neural networks, where one performs a rough segmentation based on the U-Net architecture and the other performs the final segmentation on polar image transformations of the input. Connected component analysis of the rough segmentation is used to construct the polar transformations, and predictions on multiple transformations of the same image are fused using hysteresis thresholding. We show that this method improves aorta segmentation performance without requiring complex neural network architectures. In addition, we show that our approach improves robustness and pixel-level recall while achieving segmentation performance in line with the state of the art., Comment: Accepted to 64th International Symposium ELMAR-2022, Zadar, Croatia

Atrial fibrillation (AF) is a cardiovascular disease identified as one of the main risk factors for stroke. The majority of strokes due to AF are caused by clots originating in the left atrial appendage (LAA). LAA occlusion is an effective procedure for reducing stroke risk. Planning the procedure using pre-procedural imaging and analysis has shown benefits. The analysis is commonly done by manually segmenting the appendage on 2D slices. Automatic LAA segmentation methods could save an expert's time and provide insightful 3D visualizations and accurate automatic measurements to aid in medical procedures. Several semi- and fully-automatic methods for segmenting the appendage have been proposed. This paper provides a review of automatic LAA segmentation methods on 3D and 4D medical images, including CT, MRI, and echocardiogram images. We classify methods into heuristic and model-based methods, as well as into semi- and fully-automatic methods. We summarize and compare the proposed methods, evaluate their effectiveness, and present current challenges in the field and approaches to overcome them.

The ability to perform high-precision optical measurements is paramount to science and engineering. Laser interferometry enables interaction-free sensing with a precision ultimately limited by shot noise. Quantum optical sensors can surpass this limit, but single- or multi-photon schemes are challenged by low experimental sampling rates, while squeezed-light approaches require complex optical setups and sophisticated time gating. Here, we introduce a simple method that infers optical phase shifts through standard intensity measurements while still maintaining the quantum advantage in the measurement precision. Capitalising on the robustness and high sampling rates of our device, we implement a quantum optical microphone in the audio band. Its performance is benchmarked against a classical laser microphone in a standardised medically-approved speech recognition test on 45 subjects. We find that quantum-recorded words improve the speech recognition threshold by $-0.57\, \text{dB}_{\text{SPL}}$, thus making the quantum advantage audible. Not only do these results open the door towards applications in quantum nonlinear interferometry, but they also show that quantum phenomena can be experienced by humans., Comment: 8 pages, 4 figures