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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Local characterization of hindered Brownian motion by using digital video microscopy and 3D particle tracking

In this article we present methods for measuring hindered Brownian motion in the confinement of complex 3D geometries using digital video microscopy. Here we discuss essential features of automated 3D particle tracking as well as diffusion data analysis. By introducing local mean squared displacement-vs-time curves, we are able to simultaneously measure the spatial dependence of diffusion coefficients, tracking accuracies and drift velocities. Such local measurements allow a more detailed and appropriate description of strongly heterogeneous systems as opposed to global measurements. Finite size effects of the tracking region on measuring mean squared displacements are also discussed. The use of these methods was crucial for the measurement of the diffusive behavior of spherical polystyrene particles (505 nm diameter) in a microfluidic chip. The particles explored an array of parallel channels with different cross sections as well as the bulk reservoirs. For this experiment we present the measurement of local tracking accuracies in all three axial directions as well as the diffusivity parallel to the channel axis while we observed no significant flow but purely Brownian motion. Finally, the presented algorithm is suitable also for tracking of fluorescently labeled particles and particles driven by an external force, e.g., electrokinetic or dielectrophoretic forces.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Test beam demonstration of silicon microstrip modules with transverse momentum discrimination for the future CMS tracking detector

A new CMS Tracker is under development for operation at the High Luminosity LHC from 2026 onwards. It includes an outer tracker based on dedicated modules that will reconstruct short track segments, called stubs, using spatially coincident clusters in two closely spaced silicon sensor layers. These modules allow the rejection of low transverse momentum track hits and reduce the data volume before transmission to the first level trigger. The inclusion of tracking information in the trigger decision is essential to limit the first level trigger accept rate. A customized front-end readout chip, the CMS Binary Chip (CBC), containing stub finding logic has been designed for this purpose. A prototype module, equipped with the CBC chip, has been constructed and operated for the first time in a 4 GeemVem/emc positron beam at DESY. The behaviour of the stub finding was studied for different angles of beam incidence on a module, which allows an estimate of the sensitivity to transverse momentum within the future CMS detector. A sharp transverse momentum threshold around 2 emVem/emc was demonstrated, which meets the requirement to reject a large fraction of low momentum tracks present in the LHC environment on-detector. This is the first realistic demonstration of a silicon tracking module that is able to select data, based on the particle's transverse momentum, for use in a first level trigger at the LHC . The results from this test are described here.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Muon track reconstruction in a segmented bolometric array using multi-objective optimization

Recent advances in segmented solid-state detector arrays for rare-event searches have allowed the technology to approach the ton-scale in detector mass and the scale of meters in size. Often focused around searches for neutrinoless double-beta decay or direct dark matter detection, such experiments also have the capability to search for exotic particles that leave track-like signatures across their volume. However, the segmented nature of such detector arrays often sets the spatial resolution and makes the problem of reconstructing track-like paths non-trivial. Here, in this paper, we present an algorithm that improves reconstruction of track-like events in segmented detectors using multi-objective optimization — a computational technique that optimizes more than one cost function at a time without specifying a quantitative weighting between them. Such a technique allows the reconstruction of tracks through a detector and the determination of path-lengths through individual elements. When combined with the reconstructed energy depositions in each element this allows for a calculation of the stopping power of track-like particles and opens the door to searches for particles with abnormal stopping power like monopoles or lightly-ionizing particles (LIPs). Results are presented which evaluate the precision of the reconstruction tools as they currently stand against Monte Carlo generated data. The algorithm is presented in the context of the CUORE experiment, but has applications to other segmented calorimeter detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Track reconstruction as a service for collider physics

Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms have been adapted to run on massively parallel coprocessors, such as graphics processing units (GPUs), to reduce processing time. Nevertheless, challenges remain in fully harnessing the computational capacity of coprocessors in a scalable and non-disruptive manner. This paper proposes an inference-as-a-service approach for particle tracking in high energy physics experiments. To evaluate the efficacy of this approach, two distinct tracking algorithms are tested: Patatrack, a rule-based algorithm, and Exa.TrkX, a machine learning-based algorithm. The as-a-service implementations show enhanced GPU utilization and can process requests from multiple CPU cores concurrently without increasing per-request latency. The impact of data transfer is minimal and insignificant compared to running on local coprocessors. This approach greatly improves the computational efficiency of charged particle tracking, providing a solution to the computing challenges anticipated in the High-Luminosity LHC era.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Description and Performance of Track and Primary-Vertex Reconstruction with the CMS Tracker

A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For tbar t events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of p(T) > 0.9GeV is 94% for pseudorapidities of |η| < 0.9 and 85% for 0.9 < |η| < 2.5. The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of p(T) = 100GeV emitted at |η| < 1.4, the resolutions are approximately 2.8% in p(T), and respectively, 10μm and 30μm in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10–12μm in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Quantum tracking control of the orientation of symmetric-top molecules

The goal of quantum tracking control is to identify shaped fields to steer observable expectation values along designated time-dependent tracks. The fields are determined via an iteration-free procedure, which is based on inverting the underlying dynamical equations governing the controlled observables. In this paper, we generalize the ideas in [Phys. Rev. A 98, 043429 (2018)] to the task of orienting symmetric top molecules in three dimensions. To this end, we derive equations for the control fields capable of directly tracking the expected value of the three-dimensional dipole orientation vector along a desired path in time. In conclusion, we show this framework can be utilized for tracking the orientation of linear molecules as well, and present numerical illustrations of these principles for symmetric-top tracking control problems.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Search for the jet-induced diffusion wake in the quark-gluon plasma via measurements of jet-track correlations in photon-jet events in Pb+Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with the ATLAS detector

This paper presents a measurement of jet-track correlations in photon-jet events, using 1.72 nb −1 of Pb+Pb data at $\sqrt{s_{NN}}$ = 5.02TeV recorded with the ATLAS detector at the LHC. Events with energetic photon-jet pairs are selected, where the photon and jet are approximately back-to-back in azimuth. The angular correlation between jets and charged-particle tracks with transverse momentum (𝑝 T ) in the range 0.5–2.0 GeV in the hemisphere opposite to the jet, |Δ⁢𝜙(jet,track)|>𝜋/2, is measured as a function of their relative pseudorapidity difference, |Δ⁢𝜂(jet,track)|. In central Pb+Pb collisions, these correlations are predicted to be sensitive to the diffusion wake in the quark-gluon plasma resulting from the lost energy of high-𝑝T partons traversing the plasma, with a characteristic modification as a function of |Δ⁢𝜂(jet,track)|. The correlations are examined with different selections on the jet-to-photon 𝑝 T ratio to select events with different degrees of energy loss. No diffusion wake signal is observed within the current sensitivity and upper limits at 95% confidence level on the diffusion wake amplitude are reported.

heavy flavor physics↗
DOE OSTI2024

Leading order track functions in a hot and dense QGP

We study the modifications to the fragmentation pattern of partons into charged particles in the presence of a hot and dense quark gluon plasma. To this end, we analyze the perturbative renormalization group equations of the track functions, which describe the energy fraction carried by charged hadrons. Focusing on pure Yang-Mills theory, we compute the lowest-order moments of the medium-modified track functions, which are found to be sensitive to the reduced phase space for emissions in the medium and to energy loss. We use the extracted moments to calculate the energy energy correlator (EEC) on tracks in the collinear limit. The EEC on medium-evolved tracks does not differ qualitatively from the EEC on vacuum tracks despite being sensitive to the color decoherence transition and suppressing the distribution due to quenching, as seen in other jet observables. Published by the American Physical Society 2024

Barata, João (ORCID:0000000342864555)↗
DOE OSTI2017

Target tracking via recursive Bayesian state estimation in radar networks

Modern cognitive radar networks incorporating intelligent and cognitive support-modules can actively adjust the radar-target geometry and optimally select a subset of radars to track the target of interest. Based on the theories of dynamic graphical models (DGM) and recursive Bayesian state estimation (RBSE), we propose a framework for single target tracking in mobile and cooperative radar networks, jointly considering path planning and radar selection. We formulate the tracking procedure as two iterative steps: (i) solving a combinatorial problem based on the expected cross-entropy measure to select the optimal subset of radars and their locations, and (ii) tracking the target using RBSE technique. We simulate the proposed framework using an illustrative example in 2-D space and demonstrate the tracking performance.

Xiang, Yijian↗
DOE OSTI2019

Iterative Learning Control for High-Speed Rosette Trajectory Tracking

We demonstrate high-speed tracking of a selfrepeating non-raster scan AFM pattern known as rosette. To generate this pattern, the lateral axes of the scanner trace a sum of two sinusoids with different frequencies but identical amplitudes. A feedback controller is combined with an iterative learning controller (ILC) to track this repetitive pattern. The feedback controller is designed based on the internal model principle and incorporates the fundamental reference frequencies. The ILC eliminates the repeating deterministic disturbances that appear in the tracking error. To verify the efficacy of the control approach, an experiment is conducted using a two degrees-of-freedom microelectromechanical system nanopositioner to track a rosette pattern sequentially at the rate= of five frames per second. The experimental results show that the root-mean-square value of tracking error has been reduced by more than 50% owing to the ILC

42 ENGINEERING↗
DOE OSTI2015

Dithering Digital Ripple Correlation Control for Photovoltaic Maximum Power Point Tracking

This study demonstrates a new method for rapid and precise maximum power point tracking in photovoltaic (PV) applications using dithered PWM control. Constraints imposed by efficiency, cost, and component size limit the available PWM resolution of a power converter, and may in turn limit the MPP tracking efficiency of the PV system. In these scenarios, PWM dithering can be used to improve average PWM resolution. In this study, we present a control technique that uses ripple correlation control (RCC) on the dithering ripple, thereby achieving simultaneous fast tracking speed and high tracking accuracy. Moreover, the proposed method solves some of the practical challenges that have to date limited the effectiveness of RCC in solar PV applications. We present a theoretical derivation of the principles behind dithering digital ripple correlation control, as well as experimental results that show excellent tracking speed and accuracy with basic hardware requirements.

Barth, C↗
DOE OSTI2017

Nested Tracking Graphs

Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to each other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We show the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multilevel Robustness for 2D Vector Field Feature Tracking, Selection and Comparison

Abstract Critical point tracking is a core topic in scientific visualization for understanding the dynamic behaviour of time‐varying vector field data. The topological notion of robustness has been introduced recently to quantify the structural stability of critical points, that is, the robustness of a critical point is the minimum amount of perturbation to the vector field necessary to cancel it. A theoretical basis has been established previously that relates critical point tracking with the notion of robustness, in particular, critical points could be tracked based on their closeness in stability, measured by robustness, instead of just distance proximity within the domain. However, in practice, the computation of classic robustness may produce artifacts when a critical point is close to the boundary of the domain; thus, we do not have a complete picture of the vector field behaviour within its local neighbourhood. To alleviate these issues, we introduce a multilevel robustness framework for the study of 2D time‐varying vector fields. We compute the robustness of critical points across varying neighbourhoods to capture the multiscale nature of the data and to mitigate the boundary effect suffered by the classic robustness computation. We demonstrate via experiments that such a new notion of robustness can be combined seamlessly with existing feature tracking algorithms to improve the visual interpretability of vector fields in terms of feature tracking, selection and comparison for large‐scale scientific simulations. We observe, for the first time, that the minimum multilevel robustness is highly correlated with physical quantities used by domain scientists in studying a real‐world tropical cyclone dataset. Such an observation helps to increase the physical interpretability of robustness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Convolutional networks for vehicle track segmentation

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

4D tumor centroid tracking using orthogonal 2D dynamic MRI: Implications for radiotherapy planning

Purpose: Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited “snapshot” in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.Methods: 2D balanced steady-state free precession MRI was acquired continuously over 9–14 min at approximately 4 Hz in three healthy volunteers using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm{sup 2} with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.Results: Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.Conclusions: The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Suitability of markerless EPID tracking for tumor position verification in gated radiotherapy

Purpose: To maximize the benefits of respiratory gated radiotherapy (RGRT) of lung tumors real-time verification of the tumor position is required. This work investigates the feasibility of markerless tracking of lung tumors during beam-on time in electronic portal imaging device (EPID) images of the MV therapeutic beam. Methods: EPID movies were acquired at ∼2 fps for seven lung cancer patients with tumor peak-to-peak motion ranges between 7.8 and 17.9 mm (mean: 13.7 mm) undergoing stereotactic body radiotherapy. The external breathing motion of the abdomen was synchronously measured. Both datasets were retrospectively analyzed inPortalTrack, an in-house developed tracking software. The authors define a three-step procedure to run the simulations: (1) gating window definition, (2) gated-beam delivery simulation, and (3) tumor tracking. First, an amplitude threshold level was set on the external signal, defining the onset of beam-on/-off signals. This information was then mapped onto a sequence of EPID images to generate stamps of beam-on/-hold periods throughout the EPID movies in PortalTrack, by obscuring the frames corresponding to beam-off times. Last, tumor motion in the superior-inferior direction was determined on portal images by the tracking algorithm during beam-on time. The residual motion inside the gating window as well as target coverage (TC) and the marginal target displacement (MTD) were used as measures to quantify tumor position variability. Results: Tumor position monitoring and estimation from beam's-eye-view images during RGRT was possible in 67% of the analyzed beams. For a reference gating window of 5 mm, deviations ranging from 2% to 86% (35% on average) were recorded between the reference and measured residual motion. TC (range: 62%–93%; mean: 77%) losses were correlated with false positives incidence rates resulting mostly from intra-/inter-beam baseline drifts, as well as sudden cycle-to-cycle fluctuations in exhale positions. Both phenomena can lead to considerable deviations (with MTD values up to a maximum of 7.8 mm) from the intended tumor position, and in turn may result in a marginal miss. The difference between tumor traces determined within the gating window against ground truth trajectory maps was 1.1 ± 0.7 mm on average (range: 0.4–2.3 mm). Conclusions: In this retrospective analysis of motion data, it is demonstrated that the system is capable of determining tumor positions in the plane perpendicular to the beam direction without the aid of fiducial markers, and may hence be suitable as an online verification tool in RGRT. It may be possible to use the tracking information to enable on-the-fly corrections to intra-/inter-beam variations by adapting the gating window by means of a robotic couch.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-194: Dynamic Tumor Tracking End-To-End Testing Using a 4D Thorax Phantom and EBT3 Films

Purpose: To quantify the Vero linac dosimetric accuracy of the tumor dynamic tracking treatment using EBT3 film embedded in a 4D thorax phantom. Methods: A dynamic thorax phantom with tissue equivalent materials and a film insert were used in this study. The thorax phantom was scanned in 4DCT mode with a viscoil embedded in its film insert composed of lung equivalent material. Dynamic tracking planning was performed using the 50% phase CT set with 5 conformal beams at gantry angles of 330, 15, 60, 105 and 150 degrees. Each field is a 3cm by 3cm square centered at viscoil since there was no solid mass target. Total 3 different 1–2cos4 motion profiles were used with varied motion magnitude and cycle frequency. Before treatment plan irradiation, a 4D motion model of the target was established using a series of acquired fluoroscopic images and infrared markers motion positions. During irradiation, fluoroscopic image monitoring viscoil motion was performed to verify model validity. The irradiated films were scanned and the dose maps were compared to the planned Monte Carlo dose distributions. Gamma analyses using 3%–3mm, 2%–3mm, 3%–2mm, 2%–2mm criteria were performed and presented. Results: For each motion pattern, a 4D motion model was built successfully and the target tracking performance was verified with fluoroscopic monitoring of the viscoil motion and its model predicted locations. The film gamma analysis showed the average pass rates among the 3 motion profiles are 98.14%, 96.2%, 91.3% and 85.61% for 3%–3mm, 2%–3mm, 3%–2mm, 2%–2mm criteria. Conclusion: Target dynamic tracking was performed using patient-like breathing patterns in a 4D thorax phantom with EBT3 film insert and a viscoil. There was excellent agreement between acquired and planned dose distributions for all three target motion patterns. This study performed end-to-end testing and verified the treatment accuracy of tumor dynamic tracking.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-E-17A-11: Tracking Tumor’s Boundary in MV Image Sequences for Image-Guided Radiation Therapy

Purpose: To develop a level set method (LSM)-based algorithm to track the tumor’s boundary in MV image sequences for image-guided radiation therapy (IGRT). Method: Four MV image sequences, each of which consists of 100 frames at frame rate of 7.5 Hz, are acquired by using the electronic portal imaging device (EPID) (Varian Medical Systems, Pal Alto, USA) during the treatment of lung cancer. In the first frame of each sequence, we roughly delineate an initial contour of the target tumor by hand. Using a LSM-based algorithm, the initial contour can automatically shape itself to fit the tumor, and eventually detect the tumor’s boundary. We then employ the tumor’s boundary obtained from the previous frame as the initial contour in the subsequent frame, so that the LSM-based method can drive this initial contour to the tumor’s boundary quickly and fulfill a tracking task. Results: The proposed method has been evaluated on four MV image sequences. The mean tracking errors were 0.23, 0.29, 0.37, and 1.18 mm, and their corresponding standard deviations were 0.97, 0.75, 1.2 and 1.48 mm, respectively. Conclusion: Compared with conventional tumor tracking techniques, the proposed system is capable not only of tracking the tumor’s position, but also of detecting the tumor’s boundary varying with the respiration during the treatment. Considering current radiation therapy technique, for example, dynamical multi-leaf collimator (DMLC) has been widely applied in clinical treatment, this study indicates the potential for significant accuracy improvement in radiation therapy. This work was partially supported by a research grant from Varian Medical Systems (Palo Alto, California)

60 APPLIED LIFE SCIENCES↗