LASP Science Seminars

LASP Science Seminars

LASP seminars are generally held every Thursday at 4:00 PM on Zoom and in person.
If you are interested in attending, please contact Jem Averyt to be added to the mailing list.

We are currently seeking speakers for our Fall 2022 seminar series. If you or a colleague would like to give a seminar, please contact one of our Science Seminar Committee members:

Kevin McGouldrick (Planetary)
Min Deng (Earth Atmosphere)
Hadi Madanian (Space Physics)
David Wilson (Solar/Stellar)

Upcoming Science Seminars

August 18, 2022
SPSC W-120 & Zoom
The Dispersal of Gas in Circumstellar Disks Based on Observations of H_2 in the FUV
Laura Flagg (Cornell University)
Planets form in circumstellar disks. However, the main component of these disks, H_2, is extremely hard to detect. We have developed a new technique that increases our sensitivity to warm H_2 emission in medium resolution FUV...

Past Science Seminars

August 4, 2022
LASP – Space Science Building, SPSC - W120 & Zoom
The Pragmatic Interstellar Probe Study: Completion and Results
Dr. Ralph McNutt (APL)

Interstellar Probe is a scientific mission to capture a unified view of our heliosphere and its surroundings in interstellar space. To study both scientific and engineering aspects of such a mission an internal Johns Hopkins Applied Physics Laboratory (JHU/APL) team and a large number of external and unpaid volunteers were assembled via a set of four annual workshops from 2018 through 2021. The resulting 498-page study published online. This large strategic mission concept is now one of many under consideration for development and flight by the Solar and Space Physics Decadal Survey starting up now in the United States.

Zoom Info:
If you’re interested in attending, please contact Jem Averyt to be added to the mailing list.

Address Info:
LASP – Space Science Building
3665 Discovery Drive, Boulder, CO 80303

July 7, 2022
SPSC-W120 and Zoom
Synthesis and Characterization of Polypyrrole-Coated Anthracene Microparticles: A New Synthetic Mimic for Polyaromatic Hydrocarbon-based Cosmic Dust
Prof. Steven P. Armes (Department of Chemistry, University of Sheffield)

Polyaromatic hydrocarbons (PAHs) are found throughout the Universe. The ubiquity of these organic molecules means that they are of considerable interest in the context of cosmic dust, which typically travel at hypervelocities (> 1 km s-1) within our Solar System. However, studying such fast-moving micrometer-sized particles in laboratory-based experiments requires suitable synthetic mimics. Herein we use ball-milling to produce microparticles of anthracene, which is the simplest member of the PAH family. Size control can be achieved by varying the milling time in the presence of a suitable anionic commercial polymeric dispersant (Morwet D-425). These anthracene microparticles are then coated with a thin overlayer of polypyrrole (PPy), which is an air-stable organic conducting polymer. The uncoated and PPy-coated anthracene microparticles are characterized in terms of their particle size, surface morphology and chemical structure using optical microscopy, scanning electron microscopy, laser diffraction, aqueous electrophoresis, FT-IR spectroscopy, Raman microscopy and XPS. Finally, such microparticles can be accelerated up to hypervelocities using a Light Gas Gun. Moreover, studies of impact craters indicate carbon debris so they are expected to serve as the first synthetic mimic for PAH-based cosmic dust.

June 2, 2022
W-120 & Zoom
Janus: A NASA SIMPLEx mission to explore two NEO Binary Asteroid
D.J. Scheeres, Distinguished Professor, Smead Aerospace Engineering Sciences Department (University of Colorado)
The Janus mission was selected in 2019 as a NASA SIMPLEx mission to be launched in August of 2022 with the NASA Discovery mission Psyche. Janus will send two spacecraft, each of which will fly by...
May 26, 2022
Quest for finding Acoustic Sources on the Solar Surface: Deep Learning in DKIST era
Shah M Bahauddin (LASP)
The solar acoustic oscillations are likely stochastically excited by convective dynamics in the solar photosphere, though few direct observations of individual source events have been made and their detailed characteristics are still unknown. Wave source identification...

The solar acoustic oscillations are likely stochastically excited by convective dynamics in the solar photosphere, though few direct observations of individual source events have been made and their detailed characteristics are still unknown. Wave source identification requires measurements that can reliably discriminate the local wave signal from the background convective motions and resonant modal power. This is quite challenging as these ’noise’ contributions have amplitudes several orders of magnitude greater than the sources and the propagating wave fields they induce. In this talk, I will discuss how we can filter and identify these sources in simulated photospheres and in observation as well. The development of this technique leveraged the application of deep learning algorithm as well as the upcoming Daniel K. Inouye Solar Telescope (DKIST)’s high-resolution, fast cadence capabilities. Using the filtering technique developed, we have uncovered previously unknown properties of the acoustic emission process and their possible characteristic dynamics both in below (upper convection zone) and above (chromosphere/corona) atmosphere. We believe the technique will have important applications in chromospheric wave-studies and may lead to new investigations in high-resolution local-helioseismology.

May 23, 2022
Zoom and SPSC W120
Filling in the Gaps: Soft X-ray Polarimetry Development at MIT
Sarah Trowbridge Heine (MIT)
X-rays are produced in some of the hottest and most extreme environments in the universe.  Many telescopes, most notably the Chandra X-ray Observatory, have helped us learn a great deal about these sources through imaging and spectroscopy...
April 28, 2022
Subsurface Ocean Detection in Icy Worlds Using Magnetic Induction
Corey Cochrane (JPL)
Many moons in the solar system are thought to potentially harbor hidden oceans based on the features observed at their surfaces. However, the best evidence for the existence of subsurface oceans arises from interpretation of magnetic...
April 28, 2022
4:00 PM
Application of Machine Learning for the Analysis of Velocity Distribution Functions and Plasma Waves
Daniel Vech (LASP)

The first half of this talk will focus on using unsupervised machine learning for the purpose of wave analysis. The available magnetic field data from the terrestrial magnetosphere, solar wind and planetary magnetospheres exceeds over 1 million hours. Identifying plasma waves in these large data sets is a time consuming and tedious process. We propose a solution to this problem. We demonstrate how Self-Organizing Maps can be used for rapid data reduction and identification of plasma waves in large data sets. We use 72,000 fluxgate and 110,000 search coil magnetic field power spectra from the Magnetospheric Multiscale Mission and show how the Self-Organizing Map sorts the power spectra into groups based on their shape. Organizing the data in this way makes it very straightforward to identify power spectra with similar properties and therefore this technique greatly reduces the need for manual inspection of the data. We suggest that Self-Organizing Maps offer a time effective and robust technique, which can significantly accelerate the processing of magnetic field data and discovery of new wave forms.

The second half of the talk will focus on the analysis of velocity distribution functions (VDFs). The analysis of the thermal part of VDFs is fundamentally important for understanding the kinetic physics that governs the evolution and dynamics of space plasmas. However, calculating the proton core, beam, and alpha-particle parameters for large data sets of VDFs is a time-consuming and computationally demanding process that always requires supervision by a human expert. We developed a machine learning tool that can extract proton core, beam, and alpha-particle parameters using images (2D grid consisting pixel values) of VDFs. A database of synthetic VDFs was generated, which was used to train a convolutional neural network that infers bulk speed, thermal speed, and density for all three particle populations. We generated a separate test data set of synthetic VDFs that we used to compare and quantify the predictive power of the neural network and a fitting algorithm. The neural network achieves significantly smaller root-mean-square errors to infer proton core, beam, and alpha-particle parameters than a traditional fitting algorithm.

April 21, 2022
Zoom and SPSC W120
PILOT: Plasma Imaging, LOcal measurement, and Tomographic Experiment, a Mission Concept for Transformational Multi-scale Observations of Cold Plasma Dynamics in Earth’s Magnetosphere
David Malaspina (LASP)
Magnetospheric physics has a massive problem: we have not yet determined the fundamental processes that govern plasma mass and energy flow through the terrestrial magnetosphere, nor the degree to which these flows regulate key magnetospheric subsystems....
April 20, 2022
Astronomy and Space in Australia
Brad Carter (USQ’s Institute for Advanced Engineering and Space Sciences)
Australian astronomy is a story of indigenous peoples and cultures, colonial exploration and observatories, national research institutions, and international collaborations. Australia’s role in the space age has been limited but the advent of an Australian Space...
April 14, 2022
Past and Future Exploration of Enceladus and Europa: an Icy Dust Analyzer Perspective
Frank Postberg (Freie Universität Berlin)
Enceladus has become the iconic example of an active icy moon where the subsurface ocean cryo-volcanically communicates with the surface and in fact the surrounding space. In the first part of the talk, the main findings...

Enceladus has become the iconic example of an active icy moon where the subsurface ocean cryo-volcanically communicates with the surface and in fact the surrounding space. In the first part of the talk, the main findings from the Cosmic Dust Analyzer (CDA) and other instruments about Enceladus after the end of the Cassini mission are presented. In the second part, the preparations for future missions to Enceladus and Europa are discussed from the perspective of dust analyzer instrumentation, like LASP’s Surface Dust Analyzer (SUDA) onboard the Europa Clipper mission.