41 pages, 14 figures, 1 table - Submitted to The Planetary Science Journal (PSJ) - After 2nd review
Grain-grain collisions shape the 3-dimensional size and velocity distribution of the inner Zodiacal Cloud and the impact rates of dust on inner planets, yet they remain the least understood sink of zodiacal dust grains. For the first time, we combine the collisional grooming method combined with a dynamical meteoroid model of Jupiter-family comets (JFCs) that covers four orders of magnitude in particle diameter to investigate the consequences of grain-grain collisions in the inner Zodiacal Cloud. We compare this model to a suite of observational constraints from meteor radars, the Infrared Astronomical Satellite (IRAS), mass fluxes at Earth, and inner solar probes, and use it to derive the population and collisional strength parameters for the JFC dust cloud. We derive a critical specific energy of $Q^*_D=5\times10^5 \pm 4\times10^5 R_\mathrm{met}^{-0.24}$ J kg$^{-1}$ for particles from Jupiter-family comet particles, making them 2-3 orders of magnitude more resistant to collisions than previously assumed. We find that the differential power law size index $-4.2\pm0.1$ for particles generated by JFCs provides a good match to observed data. Our model provides a good match to the mass production rates derived from the Parker Solar Probe observations and their scaling with the heliocentric distance. The higher resistance to collisions of dust particles might have strong implications to models of collisions in solar and exo-solar dust clouds. The migration via Poynting-Roberson drag might be more important for denser clouds, the mass production rates of astrophysical debris disks might be overestimated, and the mass of the source populations might be underestimated. Our models and code are freely available online.
The physics of solar flares occurring on the Sun is highly complex and far from fully understood. However, observations show that solar eruptions are associated with the intense kilogauss fields of active regions, where free energies are stored with field-aligned electric currents. With the advent of high-quality data sources such as the Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), recent works on solar flare forecasting have been focusing on data-driven methods. In particular, black box machine learning and deep learning models are increasingly adopted in which underlying data structures are not modeled explicitly. If the active regions indeed follow the same laws of physics, there should be similar patterns shared among them, reflected by the observations. Yet, these black box models currently used in the literature do not explicitly characterize the heterogeneous nature of the solar flare data, within and between active regions. In this paper, we propose two finite mixture models designed to capture the heterogeneous patterns of active regions and their associated solar flare events. With extensive numerical studies, we demonstrate the usefulness of our proposed method for both resolving the sample imbalance issue and modeling the heterogeneity for rare energetic solar flare events.
To appear in the Bulletin of the American Astronomical Society (see DOI); 13 pages, 6 figures
13 pages, 12 figures, submitted to MNRAS
26 pages, 8 figures
27 pages, 15 figures, 1 table, submitted to ApJ, comments welcome!!!
8 pages, 2 figures; Submitted to A&A
Accepted for publication in MNRAS. 15 pages, 10 figures, 4 tables (+ Appendices). Full version of tables 1 and 2 included
Submitted to A&A. Comments are welcome
Resubmitted to ApJ Letters. Python notebook and data files are available at this https URL
31 pages, 19 figures, submitted to ApJ
Submitted to Astronomy&Astrophysics, 16 pages, 3 figures, 4 tables
21 pages, 13 figures; accepted for publication in ApJ
PhD thesis, 309 pages (Submitted 16 Sep 2023, defended 9 Nov 2023)
15 pages, 9 Figures, accepted for publication in MNRAS
63 pages, 29 figures, 3 tables; submitted to Astrophysics and Space Science (Ap&SS), 2022 Astronomy Prize Awardees Collection
6 pages, 4 figures. Submitted for publication on MNRAS
Accepted to The Astrophysical Journal Letters
19 pages, 10 figures, accepted for publication in Astronomical Journal
Accepted for publication in A&A
20 pages, 25 figures, accepted for MNRAS
16 pages, 10 figures
16 pages, 11 figures. Accepted for publication in the Monthly Notices of the Royal Astronomical Society
Accepted for publication in Monthly Notices of the Royal Astronomical Society, 9 Pages, 8 figures, 3 tables
17 pages, 7 figures. Accepted for publication in ApJ
10 pages, 2 figures
Accepted by ApJ, 24 pages, 14 figures, 5 tables
25 pages, 10 figures, submitted to Journal of Cosmology and Astroparticle Physics
23 pages, 15 Figures + 7 Figures in appendix. Accepted for publication in Astronomy & Astrophysics
Accepted for publication in MNRAS
12 pages, 5 figures, submitted to A&A
5 pages + references, 1 table and 3 figures, codes can be found at this https URL and chains can be found at this https URL
31 pages, 1 table, 2 figures, accepted to Astronomical and Astrophysical Transactions
Accepted for publication in Astronomische Nachrichten
Accepted for publication in Astronomy & Astrophysics
14 pages (9 pages of text), 10 figures. For the associated code, please see this https URL
22 pages, 21 figures, accepted for publication by ApJ
Accepted for publication in Monthly Notices of the Royal Astronomical Society
15 pages, 13 figures
Submitted to PASP
Submitted to A&A Letters. Comments are welcome
14 pages, 13 figures. Accepted to ApJ
9 pages, 4 figures; Accepted for publication in MNRAS
49 pages, 13 figures, contribution to 1st Training School of the COST Action COSMIC WISPers (CA21106). Comments on technical or citation issues welcome!
37 pages, 18 figures
Accepted for publication in JOSS (The Journal of Open-Source Software)