2019
DOI: 10.1029/2018je005871
|View full text |Cite
|
Sign up to set email alerts
|

MESSENGER Gamma Ray Spectrometer and Epithermal Neutron Hydrogen Data Reveal Compositional Differences Between Mercury's Hot and Cold Poles

Abstract: The presence of hydrogen, most likely in the form of water ice, is well established in Mercury's permanently shaded polar craters. But lower concentrations that may exist away from the poles have not previously been well constrained. In this work we use data from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) Gamma‐Ray and Neutron Spectrometer to produce the first map of the absolute hydrogen abundance in Mercury's northern hemisphere. We find a mean abundance of ppm … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
7
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
6
1

Relationship

4
3

Authors

Journals

citations
Cited by 7 publications
(10 citation statements)
references
References 44 publications
3
7
0
Order By: Relevance
“…The MCNPX-modeled neutron fluxes were processed using a code that transports neutrons from the top of the atmosphere to the spacecraft, accounting for gravitationally-bound neutrons on ballistic trajectories (Feldman et al, 1989), Doppler-shifting of neutron energy due to the spacecraft velocity relative to Venus (Feldman et al, 1986), and the angle-and energy-dependent neutron detection efficiency of the LG sensors (Lawrence et al, 2010). This simulation toolkit was developed and validated using Mercury flyby (Lawrence et al, 2010) and orbital (Lawrence et al, 2013(Lawrence et al, , 2017Wilson et al, 2019) datasets. Figure 1 plots the time-series of neutron rate measurements made with the NS LG1 and LG2 detectors.…”
Section: Main Textmentioning
confidence: 99%
“…The MCNPX-modeled neutron fluxes were processed using a code that transports neutrons from the top of the atmosphere to the spacecraft, accounting for gravitationally-bound neutrons on ballistic trajectories (Feldman et al, 1989), Doppler-shifting of neutron energy due to the spacecraft velocity relative to Venus (Feldman et al, 1986), and the angle-and energy-dependent neutron detection efficiency of the LG sensors (Lawrence et al, 2010). This simulation toolkit was developed and validated using Mercury flyby (Lawrence et al, 2010) and orbital (Lawrence et al, 2013(Lawrence et al, , 2017Wilson et al, 2019) datasets. Figure 1 plots the time-series of neutron rate measurements made with the NS LG1 and LG2 detectors.…”
Section: Main Textmentioning
confidence: 99%
“…The effects varying neutron lifetimes would have on the neutron count rate is shown by simulated count rates (colored traces) in Figure 4c. The details of how these simulated count rates were implemented is described in various prior studies [4,7,11,18,20,21], with the foundational algorithms given by [14]. Neutron lifetime effects manifest as count-rate variations for different tn values when thermal neutrons are detected prior to the rotation.…”
Section: Measurement Implementationmentioning
confidence: 99%
“…In addition, for any given scenario, the exact spacecraft composition and mass distribution may not be fully known. Nevertheless, full simulations of MESSENGER NS data showed that relative uncertainties of ~<0.5% were achievable when neutron arrival angles were restricted to directions that did not travel through the full spacecraft material [7,18,20,21,34]. However, a dedicated space-based neutron lifetime experiment would strive to have a smaller spacecraft that is more easily modeled, thus achieving more uniform accuracies for all orientations.…”
Section: Background Signalsmentioning
confidence: 99%
“…Many of these elements were mapped by MESSENGER during its 4-year orbital mission [e.g. [29][30][31][32][33]; consequently we have a good understanding of Mercury's composition on large scales. For the Mercury flyby, a set of models with different neutron lifetimes but constant composition were generated.…”
Section: Using Messenger Data To Measure τNmentioning
confidence: 99%