arXiv subjects

Sushil Sharma

Publications and source records attributed to Sushil Sharma.

At least 19 recordsLinked to original sources

arXiv2026

Design and optimization of the NSLS-II lattice with complex bend replacement

The demand for brighter photon beams has driven the development of diffraction-limited storage rings with ultralow electron beam emittance. A complex bend (CB) lattice was recently proposed as an approach for the future NSLS-II upgrade. As a step toward this upgrade, NSLS-II plans to replace two existing electromagnetic dipoles with permanent-magnet CBs, providing the first experimental demonstration of the CB concept in a storage ring. This paper presents the linear optics design, nonlinear optimization, and machine error evaluation of the modified NSLS-II lattice. The optimized lattice provides sufficient dynamic and momentum apertures for off-axis injection and routine operation and can be corrected with the existing NSLS-II correction scheme. Scraper measurements near the planned CB installation location validate the beam aperture requirements used in the CB design.

physics.acc-ph↗

arXiv2026

Experimental determination of the Dalitz plot for positronium decay using the J-PET detection system

We present the first measurements of the Dalitz plot for ortho-positronium annihilation to three photons. Our measurements, accurate to about 3% statistical and 2-3% systematic uncertainty in angular representation over almost the entire available phase space, were performed using the Jagiellonian Positron Emission Tomograph (J-PET) based on organic scintillator strips. Until now, the Dalitz plot for the three-body positronium decay has been poorly explored. The new measurements presented here are consistent with both the leading-order and next-to-leading order QED predictions for the Dalitz plot.

nucl-ex↗

arXiv2026

Roadmap Towards Quantum Entanglement Positron Emission Tomography (QE-PET)

Annihilation photons are quantum entangled in their polarization, a property that is not accessible in state-of-the-art clinical Positron Emission Tomography (PET). This roadmap describes the current status of research in the emerging field of quantum entanglement applications involving these photons for medical diagnosis. It outlines the underlying physics phenomena and the development of detector systems that can serve as a foundation for future Quantum Entanglement PET (QE-PET) scanners. These scanners will be capable of utilizing the entanglement between annihilation photons by measuring their Compton scattering on electrons. This roadmap comprises up-to-date experimental results on the study of quantum entanglement and the decoherence of annihilation photons, alongside the current theoretical understanding of these phenomena. The methods and detector technologies described herein are being developed (i) in order to enhance standard PET imaging by suppressing random coincidences in the reconstruction of annihilation site density distributions, (ii) in order to establish the degree of quantum entanglement as a diagnostic biomarker for tissue pathology and oxygenation, and (iii) in order to elaborate a method for pH imaging. Whether entanglement-based imaging and pH mapping can be successfully translated into clinical practice remains an open question and a subject of exciting ongoing research. This roadmap serves as an invitation to the scientific community to join this burgeoning field.

physics.med-ph↗

arXiv2026

First-in-human quantum entanglement imaging

Annihilation photons are quantum-entangled in polarization, a phenomenon that has not been exploited in medical diagnostics so far. We present the first in vivo imaging of the degree of quantum entanglement of photons originating from positron-electron annihilation within a human subject. This study utilized the Jagiellonian Positron Emission Tomography (J-PET) scanner, constructed from plastic scintillators. In plastics, annihilation photons interact primarily via the Compton effect, which provides simultaneous information regarding the photon interaction position and time, as well as the photon polarization plane. The patient was injected with a DOTA-TATE radiopharmaceutical labeled with the $^{68}$Ga radionuclide. Using the J-PET scanner, we determined the image of the radiopharmaceutical uptake and, simultaneously, the image of the degree of quantum entanglement. The latter was determined from the relative angle between the polarization planes of the annihilation photons. The values of the degree of quantum entanglement extracted for the liver and the spleen are smaller than those predicted for maximally entangled two-photon states, yet larger than expected for separable photons. This demonstration opens new perspectives for the application of quantum entanglement in clinical diagnostics.

physics.med-ph↗

arXiv2026

A Conjugate Bayesian Framework for Fast 3D Positronium Lifetime Estimation with a Partial System Matrix

Background: Positronium lifetime imaging extends conventional positron emission tomography by using the time interval between positron emission and annihilation as an additional contrast mechanism. Voxel-wise lifetime estimation in fully three-dimensional settings is computationally difficult because the number of feasible detector-time channels grows rapidly, whereas only a small subset is observed in practice. We developed a scalable statistical framework for three-dimensional positronium lifetime estimation based on a time-of-flight-aware partial system matrix restricted to observed detector-time channels, combined with posterior event-to-voxel weighting and a conjugate Gamma--Exponential update for closed-form voxel-wise effective-rate estimation. Results: Restricting the forward model to observed detector-time channels reduced memory and computational requirements while preserving the Poisson data model for retained detected triple coincidences. In simulated data with 4056 voxels, the analytic Bayesian estimator required 2.76 s versus 74.46 s for 10 L-BFGS-B iterations on the same CPU while accurately recovering the effective-rate map. In a triple-coincidence dataset acquired with a J-PET prototype scanner and a NEMA image-quality phantom, a 234 375-voxel effective-rate map was estimated in approximately 3 s from about $3.64\times10^5$ retained events. Conclusions: Restricting the system matrix to observed detector-time channels makes fully three-dimensional positronium lifetime estimation computationally practical for sparse triple-coincidence data. The proposed posterior-weighted conjugate update provides a fast and stable single-component surrogate estimator of voxel-wise effective lifetime for large-scale three-dimensional positronium lifetime imaging.

physics.med-ph↗

arXiv2026

First ex-vivo positronium imaging of tissues with modular J-PET scanner using $^{44}$Sc radionuclide

This study presents the first ex-vivo positronium imaging of human tissues using the modular J-PET scanner with the $^{44}$Sc radionuclide. The $^{44}$Sc isotope was produced via the $^{44}$Ca(p, n)$^{44}$Sc nuclear reaction and used to perform positronium imaging of phantom composed of human adipose tissue, cardiac myxoma tissue, thrombi blood clot, and also porous polymer XAD4, and a certified reference material (CRM) made from fused silica. The experiment demonstrates the suitability of $^{44}$Sc as a positron source for positronium imaging. The performance of J-PET for positronium imaging with $^{44}$Sc was validated by proper reconstruction of the mean orthopositronium lifetime for CRM material and XAD-4 polymer. The mean ortho-positronium (oPs) lifetimes determined for adipose tissue, cardiac myxoma tissues and thrombi were consistent with results of previous experiments. The study highlights the potential $^{44}$Sc radionuclide for positronium lifetime imaging (PLI).

physics.med-ph↗

arXiv2026

Feasibility study of the positronium lifetime imaging with the Biograph Vision Quadra and J-PET tomographs

Background: After its first ex-vivo and in-vivo demonstration, Positronium Lifetime Imaging (PLI) has received considerable interest as a potential new diagnostic biomarker. High sensitivity Positron Emission Tomography (PET) systems are needed for PLI since it requires simultaneous registration of annihilation photons and prompt gamma. In this simulation-based study, a~feasibility of PLI with the long axial field-of-view Biograph Vision Quadra (Quadra) and the Total Body J-PET scanner was investigated. Methods: The study was performed using the GATE software. Background radiation, present within the Quadra tomograph, was added to the simulation. First, the optimal placement of the energy window for the registration of the prompt gamma was investigated. Next, the organ-wise sensitivity of Quadra was calculated for the $^{68}$Ga, $^{44}$Sc, $^{22}$Na and $^{124}$I radioisotopes. Finally, the sensitivity for the scandium isotope was compared to the sensitivities obtainable with the Total Body J-PET scanner, as well as with the modular J-PET prototype. Results: The PLI sensitivities for the Quadra with the background radiation are estimated to 9.22(3), 10.46(4), 5.91(3), and 15.39(4) cps/kBq for the $^{44}$Sc, $^{68}$Ga, $^{22}$Na and $^{124}$I radioisotopes, respectively. The highest sensitivity was obtained when the energy window for the deexcitation photon is adjacent to the energy window for the annihilation photons. The determined PLI sensitivities with Quadra and the Total Body J-PET are in the order of sensitivities of standard PET imaging with the short axial field-of-view ($\sim$20 cm) PET scanners. Conclusion: The organ-wise PLI sensitivity of Quadra has been computed for the $^{68}$Ga, $^{44}$Sc, $^{22}$Na and $^{124}$I radioisotopes. A sensitivity gain by a factor of 150 was estimated relative to the modular J-PET system previously used for the first in-vivo PLI.

physics.med-ph↗

arXiv2025

First Positronium Lifetime Imaging using $^{52}$Mn and $^{55}$Co with a plastic-based PET scanner

Positronium Lifetime Imaging (PLI) extends positron emission tomography by using the lifetime of positronium atoms as a probe of tissue molecular architecture. In this work, we report the first PLI measurements performed with $^{52}$Mn and $^{55}$Co using the modular J-PET. Four samples were studied in each experiment: two Certified Reference Materials (polycarbonate and fused silica) and two human tissues (cardiac myxoma and adipose). The selection of PLI events was based on the registration of two 511~keV annihilation photons and one prompt gamma in triple coincidence. From the resulting lifetime spectra we extracted the mean ortho-positronium lifetime $\tau_{\text{oPs}}$ and the mean positron lifetime $\Delta T_{\text{mean}}$ for each sample. The measured values of $\tau_{\text{oPs}}$ in polycarbonate using both isotopes matches well with the certified reference values. Furthermore, $^{55}$Co reproduced identical results for fused-silica measurements at their respective uncertainty levels. In contrast, measurements with $^{52}$Mn in fused silica show a minor deviation, which could be caused by the Parafilm spacer. In myxoma and adipose tissue, the reduced $\tau_{\text{oPs}}$ values are mainly linked to the long storage history of the samples rather than to the choice of isotope. Comparing peak-to-background ratios and spectral purity, $^{55}$Co provides cleaner PLI data under the same experimental conditions. Although $^{52}$Mn offers a longer half-life and a multi gamma cascade enhancing $\beta^{+}$ + $\gamma$ coincidences, but at the expense of higher background. In this study, we demonstrate that the applied selection criteria on the data measured with the modular J-PET can be used for PLI studies even with radionuclides with complex decay patterns.

physics.med-ph↗

arXiv2025

First positronium imaging using $^{44}$Sc with the J-PET scanner: a case study on the NEMA-Image Quality phantom

Positronium Lifetime Imaging (PLI), an emerging extension of conventional positron emission tomography (PET) imaging, offers a novel window for probing the submolecular properties of biological tissues by imaging the mean lifetime of the positronium atom. Currently, the method is under rapid development in terms of reconstruction and detection systems. Recently, the first in vivo PLI of the human brain was performed using the J-PET scanner utilizing the $^{68}$Ga isotope. However, this isotope has limitations due to its comparatively low prompt gamma yields, which is crucial for positronium lifetime measurement. Among alternative radionuclides, $^{44}$Sc stands out as a promising isotope for PLI, characterized by a clinically suitable half-life (4.04 hours) emitting 1157 keV prompt gamma in 100% cases after the emission of the positron. This study reports the first experimental demonstration of PLI with $^{44}$Sc, carried out on a NEMA-Image Quality (IQ) phantom using the Modular J-PET tomograph-the first plastic scintillators-based PET scanner.

physics.med-ph↗

arXiv2025

Positronium Imaging: History, Current Status, and Future Perspectives

Positronium imaging was recently proposed to image the properties of positronium atoms in the patient body. Positronium properties depend on the size of intramolecular voids and oxygen concentration; therefore, they deliver information different and complementary to the anatomic, morphological, and metabolic images. Thus far, the mean ortho-positronium lifetime imaging has been at the center of research interest. The first ex vivo and in vivo positronium lifetime images of humans have been demonstrated with the dedicated J-PET scanner enabling simultaneous registration of annihilation photons and prompt gamma from ${\beta^{+} \gamma}$ emitters. Annihilation photons are used to reconstruct the annihilation place and time while prompt gamma is used to reconstruct the time of positronium formation. This review describes recent achievements in the translation of positronium imaging into clinics. The first measurements of positronium lifetime in humans with commercial PET scanners modernized to register triple coincidences are reported. The in vivo observations of differences in ortho-positronium lifetime between tumor and healthy tissues and between different oxygen concentrations are discussed. So far, the positronium lifetime measurements in humans were completed with clinically available ${^{68}\text{Ga}}$, ${^{82}\text{Rb}}$, and ${^{124}\text{I}}$ radionuclides. Status and challenges in developing positronium imaging on a way to a clinically useful procedure are presented and discussed.

physics.med-ph↗

arXiv2025

Minimizing Occlusion Effect on Multi-View Camera Perception in BEV with Multi-Sensor Fusion

Autonomous driving technology is rapidly evolving, offering the potential for safer and more efficient transportation. However, the performance of these systems can be significantly compromised by the occlusion on sensors due to environmental factors like dirt, dust, rain, and fog. These occlusions severely affect vision-based tasks such as object detection, vehicle segmentation, and lane recognition. In this paper, we investigate the impact of various kinds of occlusions on camera sensor by projecting their effects from multi-view camera images of the nuScenes dataset into the Bird's-Eye View (BEV) domain. This approach allows us to analyze how occlusions spatially distribute and influence vehicle segmentation accuracy within the BEV domain. Despite significant advances in sensor technology and multi-sensor fusion, a gap remains in the existing literature regarding the specific effects of camera occlusions on BEV-based perception systems. To address this gap, we use a multi-sensor fusion technique that integrates LiDAR and radar sensor data to mitigate the performance degradation caused by occluded cameras. Our findings demonstrate that this approach significantly enhances the accuracy and robustness of vehicle segmentation tasks, leading to more reliable autonomous driving systems.

cs.CV↗

arXiv2024

Velocity Driven Vision: Asynchronous Sensor Fusion Birds Eye View Models for Autonomous Vehicles

Fusing different sensor modalities can be a difficult task, particularly if they are asynchronous. Asynchronisation may arise due to long processing times or improper synchronisation during calibration, and there must exist a way to still utilise this previous information for the purpose of safe driving, and object detection in ego vehicle/ multi-agent trajectory prediction. Difficulties arise in the fact that the sensor modalities have captured information at different times and also at different positions in space. Therefore, they are not spatially nor temporally aligned. This paper will investigate the challenge of radar and LiDAR sensors being asynchronous relative to the camera sensors, for various time latencies. The spatial alignment will be resolved before lifting into BEV space via the transformation of the radar/LiDAR point clouds into the new ego frame coordinate system. Only after this can we concatenate the radar/LiDAR point cloud and lifted camera features. Temporal alignment will be remedied for radar data only, we will implement a novel method of inferring the future radar point positions using the velocity information. Our approach to resolving the issue of sensor asynchrony yields promising results. We demonstrate velocity information can drastically improve IoU for asynchronous datasets, as for a time latency of 360 milliseconds (ms), IoU improves from 49.54 to 53.63. Additionally, for a time latency of 550ms, the camera+radar (C+R) model outperforms the camera+LiDAR (C+L) model by 0.18 IoU. This is an advancement in utilising the often-neglected radar sensor modality, which is less favoured than LiDAR for autonomous driving purposes.

cs.RO↗

arXiv2024

MapsTP: HD Map Images Based Multimodal Trajectory Prediction for Automated Vehicles

Predicting ego vehicle trajectories remains a critical challenge, especially in urban and dense areas due to the unpredictable behaviours of other vehicles and pedestrians. Multimodal trajectory prediction enhances decision-making by considering multiple possible future trajectories based on diverse sources of environmental data. In this approach, we leverage ResNet-50 to extract image features from high-definition map data and use IMU sensor data to calculate speed, acceleration, and yaw rate. A temporal probabilistic network is employed to compute potential trajectories, selecting the most accurate and highly probable trajectory paths. This method integrates HD map data to improve the robustness and reliability of trajectory predictions for autonomous vehicles.

cs.CV↗

arXiv2024

Surround-View Fisheye Optics in Computer Vision and Simulation: Survey and Challenges

In this paper, we provide a survey on automotive surround-view fisheye optics, with an emphasis on the impact of optical artifacts on computer vision tasks in autonomous driving and ADAS. The automotive industry has advanced in applying state-of-the-art computer vision to enhance road safety and provide automated driving functionality. When using camera systems on vehicles, there is a particular need for a wide field of view to capture the entire vehicle's surroundings, in areas such as low-speed maneuvering, automated parking, and cocoon sensing. However, one crucial challenge in surround-view cameras is the strong optical aberrations of the fisheye camera, which is an area that has received little attention in the literature. Additionally, a comprehensive dataset is needed for testing safety-critical scenarios in vehicle automation. The industry has turned to simulation as a cost-effective strategy for creating synthetic datasets with surround-view camera imagery. We examine different simulation methods (such as model-driven and data-driven simulations) and discuss the simulators' ability (or lack thereof) to model real-world optical performance. Overall, this paper highlights the optical aberrations in automotive fisheye datasets, and the limitations of optical reality in simulated fisheye datasets, with a focus on computer vision in surround-view optical systems.

cs.CV↗

arXiv2024

Discrete symmetries tested at 10$^{-4}$ precision using linear polarization of photons from positronium annihilations

Discrete symmetries play an important role in particle physics with violation of CP connected to the matter-antimatter imbalance in the Universe. We report the most precise test of P, T and CP invariance in decays of ortho-positronium, performed with methodology involving polarization of photons from these decays. Positronium, the simplest bound state of an electron and positron, is of recent interest with discrepancies reported between measured hyperfine energy structure and theory at the level of $10^{-4}$ signaling a need for better understanding of the positronium system at this level. We test discrete symmetries using photon polarizations determined via Compton scattering in the dedicated J-PET tomograph on an event-by-event basis and without the need to control the spin of the positronium with an external magnetic field, in contrast to previous experiments. Our result is consistent with QED expectations at the level of 0.0007 and one standard deviation.

hep-ph↗

arXiv2023

BEVSeg2TP: Surround View Camera Bird's-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction

Trajectory prediction is, naturally, a key task for vehicle autonomy. While the number of traffic rules is limited, the combinations and uncertainties associated with each agent's behaviour in real-world scenarios are nearly impossible to encode. Consequently, there is a growing interest in learning-based trajectory prediction. The proposed method in this paper predicts trajectories by considering perception and trajectory prediction as a unified system. In considering them as unified tasks, we show that there is the potential to improve the performance of perception. To achieve these goals, we present BEVSeg2TP - a surround-view camera bird's-eye-view-based joint vehicle segmentation and ego vehicle trajectory prediction system for autonomous vehicles. The proposed system uses a network trained on multiple camera views. The images are transformed using several deep learning techniques to perform semantic segmentation of objects, including other vehicles, in the scene. The segmentation outputs are fused across the camera views to obtain a comprehensive representation of the surrounding vehicles from the bird's-eye-view perspective. The system further predicts the future trajectory of the ego vehicle using a spatiotemporal probabilistic network (STPN) to optimize trajectory prediction. This network leverages information from encoder-decoder transformers and joint vehicle segmentation.

cs.CV↗

arXiv2023

Optimizing Ego Vehicle Trajectory Prediction: The Graph Enhancement Approach

Predicting the trajectory of an ego vehicle is a critical component of autonomous driving systems. Current state-of-the-art methods typically rely on Deep Neural Networks (DNNs) and sequential models to process front-view images for future trajectory prediction. However, these approaches often struggle with perspective issues affecting object features in the scene. To address this, we advocate for the use of Bird's Eye View (BEV) perspectives, which offer unique advantages in capturing spatial relationships and object homogeneity. In our work, we leverage Graph Neural Networks (GNNs) and positional encoding to represent objects in a BEV, achieving competitive performance compared to traditional DNN-based methods. While the BEV-based approach loses some detailed information inherent to front-view images, we balance this by enriching the BEV data by representing it as a graph where relationships between the objects in a scene are captured effectively.

cs.CV↗

arXiv2023

Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety

Autonomous vehicles require accurate and reliable short-term trajectory predictions for safe and efficient driving. While most commercial automated vehicles currently use state machine-based algorithms for trajectory forecasting, recent efforts have focused on end-to-end data-driven systems. Often, the design of these models is limited by the availability of datasets, which are typically restricted to generic scenarios. To address this limitation, we have developed a synthetic dataset for short-term trajectory prediction tasks using the CARLA simulator. This dataset is extensive and incorporates what is considered complex scenarios - pedestrians crossing the road, vehicles overtaking - and comprises 6000 perspective view images with corresponding IMU and odometry information for each frame. Furthermore, an end-to-end short-term trajectory prediction model using convolutional neural networks (CNN) and long short-term memory (LSTM) networks has also been developed. This model can handle corner cases, such as slowing down near zebra crossings and stopping when pedestrians cross the road, without the need for explicit encoding of the surrounding environment. In an effort to accelerate this research and assist others, we are releasing our dataset and model to the research community. Our datasets are publicly available on https://github.com/sharmasushil/Navigating-Uncertainty-Trajectory-Prediction .

cs.CV↗