Accepted Cycle 24 Theory Proposals

Proposal Number	Subject Category	PI Name	Title
24200412	STARS AND WD	Christopher Russell	Is Mk 34 the most massive binary star system? A dynamic modeling effort afforded by Chandra
24300063	WD BINARIES AND CV	Shazrene Mohamed	A Comprehensive Theoretical View of Recurrent Novae from Quiescence to Outburst
24400024	BH AND NS BINARIES	Jason Dexter	X-ray Binaries from the Inside Out: Simulations of Accretion Disk Truncation and Collapse
24500428	SN, SNR AND ISOLATED NS	Amy Gall	Implementing Experimental Ionization and Recombination Rates for Supernovae Abundance Analysis
24800110	CLUSTERS OF GALAXIES	Yuan Li	PROBING CLUSTER PLASMA PHYSICS WITH SIMULATIONS OF JELLYFISH TAILS
24800323	CLUSTERS OF GALAXIES	Congyao Zhang	Sloshing-driven turbulence in the ICM: unique properties and their X-ray measurements
24800341	CLUSTERS OF GALAXIES	Daisuke Nagai	A Photon Point Cloud Machine Learning Approach for Galaxy Cluster X-ray Mass Estimation

Subject Category: STARS AND WD

Proposal Number: 24200412

Title: Is Mk 34 the most massive binary star system? A dynamic modeling effort afforded by Chandra

PI Name: Christopher Russell

Mk 34 is a WNh+WNh system that is potentially the most massive binary known. Chandra has spent 2 Ms observing the system throughout its orbital phase, which shows phase-varying X-ray emission consistent with other long-period binaries. Unknown about the system is its inclination, which thus prevents a definitive mass measurement from being made. However, the phase-dependent absorption of the thermal X-ray emission is subject to the system inclination, thereby making an independent measurement of the system inclination possible. We aim for a series of hydrodynamic simulations and radiative transfer calculations that leverage the Chandra observations to determine the inclination of the system, thereby determining the fundamental parameter of the masses in Mk 34.

Subject Category: WD BINARIES AND CV

Proposal Number: 24300063

Title: A Comprehensive Theoretical View of Recurrent Novae from Quiescence to Outburst

PI Name: Shazrene Mohamed

Novae are bright explosions resulting from thermonuclear runaway on the surface of an accreting white dwarf. Detailed theoretical and observational studies (with over 2.4 Ms of Chandra data) have demonstrated that they are outstanding interstellar laboratories that test a wide range of astrophysical phenomena, including real-time cosmic accelerators. Our systematic study of recurrent novae, systems with multiple observed outbursts, will include detailed modeling of the accretion phase, producing physically motivated circumstellar structures within which the explosions occur. Three modes of outburst will be tested. The results will give us a more comprehensive view, from quiescence to outburst, of the shock energetics, structure and properties of the ejecta and circumstellar medium.

Subject Category: BH AND NS BINARIES

Proposal Number: 24400024

Title: X-ray Binaries from the Inside Out: Simulations of Accretion Disk Truncation and Collapse

PI Name: Jason Dexter

X-ray observations of accreting black holes in binary systems show distinct soft (thermal) and hard (power-law) spectral states. The power-law component is attributed to a corona whose properties evolve with luminosity and whose physical origin remains uncertain. We propose to carry out a thorough study of corona formation using MHD simulations in a black hole spacetime including two-temperature physics of electron and ion coupling and magnetic stresses, which may promote disk truncation and collapse. We will make predictions for disk structure and dissipation as functions of mass accretion rate and disk magnetization, providing a mapping between X-ray binary phenomenology and theoretical models of accretion flows.

Subject Category: SN, SNR AND ISOLATED NS

Proposal Number: 24500428

Title: Implementing Experimental Ionization and Recombination Rates for Supernovae Abundance Analysis

PI Name: Amy Gall

Spectral models of supernova remnants require reliable underlying atomic data, including Ionization (I) and recombination (R) rates, to accurately extract properties such as age, abundance, and temperature. While experimental cross sections and rates are available, models rely on theoretical calculations with unknown uncertainties, with discrepancies between experimental and theoretical rates on the order of 10%. We propose to make direct use of the extensive published experimental I&R rates by 1.) critically evaluating available datasets, 2.) transforming discrete experimental datapoints into useful rate coefficients with uncertainties, 3.)incorporating the rates into XSPEC non-equilibrium models, and 4.) examining where better experiments/theories will benefit the community the most.

Subject Category: CLUSTERS OF GALAXIES

Proposal Number: 24800110

Title: PROBING CLUSTER PLASMA PHYSICS WITH SIMULATIONS OF JELLYFISH TAILS

PI Name: Yuan Li

Chandra observations have revealed spectacular X-ray tails associated with galaxies falling into galaxy clusters. The tails are subject to Kelvin-Helmholtz instability as they interact with the surrounding hot plasma. The details of this interaction can reveal crucial information about the effective plasma viscosity and conductivity, which are largely unknown. We will perform a set of high-resolution numerical simulations to study jellyfish tails. This study will be the first systematic exploration including all relevant physical processes: radiative cooling, viscosity, conduction and magnetic fields. We will compare our simulations with Chandra observations of tail density, temperature and metallicity distributions to put constraints on effective transport coefficients of the hot plasma.

Subject Category: CLUSTERS OF GALAXIES

Proposal Number: 24800323

Title: Sloshing-driven turbulence in the ICM: unique properties and their X-ray measurements

PI Name: Congyao Zhang

Turbulence plays a vital role in the intracluster medium. It could prevent gas from cooling in cluster cores, promote gas mixing, and excite diffuse radio emission. In observations, gas bulk motions masquerade as turbulence and bias its measurements. In this study, we aim to tackle this problem for sloshing motions that are nearly universal in cool-core clusters. We propose to utilize numerically a self-similar model of sloshing process in galaxy clusters to separate the sloshing-driven turbulence and gas bulk motions unambiguously. Using this model, we will (1) comprehend how turbulence is developed, distributed, and dissipated in the sloshing process, and (2) explore various strategies of measuring genuine turbulence when combining high-resolution Chandra imaging and XRISM spectral data.

Subject Category: CLUSTERS OF GALAXIES

Proposal Number: 24800341

Title: A Photon Point Cloud Machine Learning Approach for Galaxy Cluster X-ray Mass Estimation

PI Name: Daisuke Nagai

The mass distribution of galaxy clusters is directly connected to the cosmology. However, estimation of cluster masses is currently limited by the bias and intrinsic scatter in cluster observable-mass relations. Modern machine learning (ML) methods, when applied to mock cluster observations from state-of-the-art simulations, have been recently used to reduce mass uncertainties relative to scaling relations. In this work, we propose to utilize a novel `point cloud'-based ML approach for estimating cluster masses. By using the support distribution machine algorithm, we aim to produce a more robust estimator of cluster mass by developing a model that exploits the full multi-dimensional photon information content (detector positions and energies) available in Chandra observations.