5 research outputs found
Investigating the IBEX Ribbon Structure a Solar Cycle Apart
A Ribbon of enhanced energetic neutral atom (ENA) emissions was discovered by
the Interstellar Boundary Explorer (IBEX) in 2009, redefining our understanding
of the heliosphere boundaries and the physical processes occurring at the
interstellar interface. The Ribbon signal is intertwined with that of a
globally distributed flux (GDF) that spans the entire sky. To a certain extent,
Ribbon separation methods enabled examining its evolution independent of the
underlying GDF. Observations over a full solar cycle revealed the Ribbon's
evolving nature, with intensity variations closely tracking those of the solar
wind (SW) structure after a few years delay accounting for the SW-ENA recycling
process. In this work, we examine the Ribbon structure, namely, its ENA fluxes,
angular extent, width, and circularity properties for two years, 2009 and 2019,
representative of the declining phases of two adjacent solar cycles. We find
that, (i) the Ribbon ENA fluxes have recovered in the nose direction and south
of it down to ~ 25{\deg} (for energies below 1.7 keV) and not at mid and high
ecliptic latitudes; (ii) The Ribbon width exhibits significant variability as a
function of azimuthal angle; (iii) Circularity analysis suggests that the 2019
Ribbon exhibits a statistically consistent radius with that in 2009. The
Ribbon's partial recovery is aligned with the consensus of a heliosphere with
its closest point being southward of the nose region. The large variability of
the Ribbon width as a function of Azimuth in 2019 compared to 2009 is likely
indicative of small-scale processes within the Ribbon.Comment: 5 figure
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Mixing Interstellar Clouds Surrounding the Sun
On its journey through the Galaxy, the Sun passes through diverse regions of the interstellar medium. High-resolution spectroscopic measurements of interstellar absorption lines in spectra of nearby stars show absorption components from more than a dozen warm partially ionized clouds within 15 pc of the Sun. The two nearest clouds—the Local Interstellar Cloud (LIC) and Galactic (G) cloud—move toward each other. Their bulk heliocentric velocities can be compared with the interstellar neutral helium flow velocity obtained from space-based experiments. We combine recent results from Ulysses, IBEX, and STEREO observations to find a more accurate estimate of the velocity and temperature of the very local interstellar medium. We find that, contrary to the widespread viewpoint that the Sun resides inside the LIC, the locally observed velocity of the interstellar neutral helium is consistent with a linear combination of the velocities of the LIC and G cloud, but not with either of these two velocities. This finding shows that the Sun travels through a mixed-cloud interstellar medium composed of material from both these clouds. Interactions between these clouds explain the substantially higher density of the interstellar hydrogen near the Sun and toward stars located within the interaction region of these two clouds. The observed asymmetry of the interstellar helium distribution function also supports this interaction. The structure and equilibrium in this region require further studies using in situ and telescopic observations.
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Real-Time Parallel-Serial LiDAR-Based Localization Algorithm with Centimeter Accuracy for GPS-Denied Environments
In this paper, we introduce a real-time parallel-serial algorithm for autonomous robot positioning for GPS-denied, dark environments, such as caves and mine galleries. To achieve a good complexity-accuracy trade-off, we fuse data from light detection and ranging (LiDAR) and an inertial measurement unit (IMU). The proposed algorithm’s main novelty is that, unlike in most algorithms, we apply an extended Kalman filter (EKF) to each LiDAR scan point and calculate the location relative to a triangular mesh. We also introduce three implementations of the algorithm: serial, parallel, and parallel-serial. The first implementation verifies the correctness of our innovative approach, but is too slow for real-time execution. The second approach implements a well-known parallel data fusion approach, but is still too slow for our application. The third and final implementation of the presented algorithm along with the state-of-the-art GPU data structures achieves real-time performance. According to our experimental findings, our algorithm outperforms the reference Gaussian mixture model (GMM) localization algorithm in terms of accuracy by a factor of two