Gamma Ray Spectroscopy of the Martian Subsurface

Frances Charlwood

SURE Student

August 2006

Introduction

• The production of gamma rays from the Martian subsurface

• GRS onboard Mars Odyssey • Extraction of GRS data from Mars Odyssey• Solar flare interactions with the planet• Regional intensities of U, Th decay chain

gammas

Incident radiation upon the Martian surface

• Galactic cosmic rays (GCR) are the major excitation mechanism for the emission of gamma rays from a planetary surface and have an energy range 0.1-10GeV

• Incident particles produce showers of secondary particles, ~10 secondary neutrons with energy 0.1-20MeV per incident particle.

• Secondary charged particles are subject to ionisation shortly after their production whereas neutrons traverse the surface layers until they interact with nearby nuclei or are emitted from the surface

Courtesy of NASA

Production of gamma rays from the Martian subsurface

• Radioactive elements in the subsurface decay releasing gamma rays down the U, Th, K decay chains

• Inelastic scattering mechanisms: (n,nγ) of high energy GCR particles with subsurface nuclei. This causes prompt gamma emissions, the excited nucleus decaying to a lower level after ~1ps. Usually it is the first excited level which is occupied, and for the process to occur the particle has to have energy greater than this state to conserve momentum in the nucleus.

• Neutron capture mechanisms: (n,γ) with neutrons of thermal energies (less than ~0.1eV). A neutron is absorbed into an excited state of a nucleus and on its decay releases gamma rays. This requires high capture cross sections.

Background Continuum

• Typical emission spectrum shows a background continuum on which lie the gamma emission peaks associated with different elements

• Origin of background important in peak fitting procedures

The continuum arises from the following:

• Bremstrahlung radiation of incoming high energy particles

• Above 8MeV, mainly due to charged particle interactions with the detector

• At lower energies, mainly due to scattered gamma rays, losing a fraction of their energy to the atmosphere, regolith or detector itself

Typical Corrected Gamma Ray Spectrum

1

10

100

1000

10000

100000

0 2000 4000 6000 8000 10000 12000

Energy (keV)

log

Co

un

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2001 Mars Odyssey• Mission objectives: to map

the elemental composition of the surface, hydrogen abundance in the shallow subsurface, seasonal changes in CO2 frost thickness

• Gamma Subsystem (GSS) located on the Gamma Sensor Head

Courtesy of NASA

• GSS counts gamma rays with its large single crystal n-type ultrahigh purity Ge solid state detector.

• Hole-electron pairs created by an incoming gamma ray are channelled towards the respective semiconductor electrodes.

• A Pulse Height Analyser bins the counts from gamma events according to energy. The GSS has 16384 channels to store the energy spectrum over a range of 0-10MeV.

Aims over the 6 week project

• Extract GRS spectral data using provided java code

• Fit the background around the gamma emission peaks so areas and intensities can be determined using IDL

• Study how solar flare particles affect the background and emission peaks in the gamma ray spectrum over a flare period

• Study decay gammas in the U, Th chains over 5 degree latitude bands over the Odyssey mission period

GRS data extraction• Each individual energy spectra has a ~19.7s collection interval and individual spectra

have to be summed to make the number of counts statistically significant and to see the individual gamma peaks.

• The Corrected Gamma Spectra (CGS) datasets were used for the analysis of spectra over a solar flare period. Individual spectra were summed to give the equivalent of a days’ worth of data.

• The Summed Gamma Spectra (SGS) were used for the U, Th decay chain gamma analysis. This spectra is available as summed data over selected latitude and longitude regions and over longer time periods. 5 degree latitude bands were investigated.

• CGS and SGS datasets are raw gamma spectra products corrected for gain, offset and non-linearity. A spectrum shifting algorithm is used to re-bin the counts in each spectrum and align the channels to a common energy scale so these energy spectra are directly comparable.

• These data sets and associated Java code are available on line at the GRS data Node, University of Arizona or Geosciences Node, NASA.

Difficulties Encountered

• Java code provided by GRS data node for spectrum extraction

• No Previous Programming Experience

• Supplied Java jar – No Spectrum extraction

• Supplied Java Packages byte to float conversion – incorrect !

• Inconsistent Format specification

• Data Node offline for days

• Initial response from University of Arizona was slow, but useful later on

• Period where the detector was shut down by a solar flare and bad codes especially over solar flare periods.

• Initial focus on Hydrogen peak which requires months of summed data

Solar Flares• Solar flare events were studied as

their particle interactions with the Martian surface could lead to enhanced gamma peaks creating a pulsed effect over that period

• Originate in active regions of the Sun which are generally associated with sunspots

• Generated in compact structures at the top of coronal loops liberating up to 1MeV in the form of plasma

• Ejections can be large as 1-10 billion tonnes and can take more than a day to pass a planetary object

2410 Wm

•Several flares per day can occur at or near the solar maximum of the 11 year solar cycle

• Flares produce enhanced effects of the solar wind containing higher energy particles

• X class flares are the most intense with the highest peak flux ( ) in the soft X-ray region

2410 Wm

Effects of a solar flare on the background

continuum • Solar flare events raise the

count rates increasing the amount of dead time in the detector. The continuum levels and detector leakage current are also increased.

• Rapid increase in gamma ray flux at the start of a flare period, then slow decay over the preceding few days.

• Flare events produce enhanced gamma peaks through additional reaction mechanisms such as the (p,p) reaction.

Peak Fitting Procedures in IDL

• Michelle Skidmore developed a mathematical gamma ray peak fitting procedure in IDL

• The background around the peak was subtracted off by fitting a power law to the spectra

• A Gaussian was fitted to the peak and the area underneath was integrated to calculate the intensity

• Area of the peak was sometimes hard to determine due to the uncertainty in the shape of the peak, location of continuum, or if a peak was close to a larger peak.

Intensity of the Oxygen peak for a flare period in September 2005

• Enhanced intensities in the Oxygen peak are seen a few days after the actual X-class flares on the 9th and 10th September

• Lower peak flux flares do not noticeably effect the intensity of the Oxygen peak

• Further study required with other flare periods and other elements which are involved in inelastic scattering processes

Intensity of the Oxygen γ=6.129MeV peak for days in September 2005

Intensity of the Hydrogen peak for a flare period in September 2005

Intensity of the γ=2.223MeV Hydrogen peak for days throughout September 2005

Flare Classification

dd/09/2005 C M X

1 0 0 0

2 0 0 0

3 0 0 0

4 1 0 0

5 1 0 0

6 2 1 0

7 4 0 1

8 5 2 1

9 7 5 3

10 3 3 2

11 5 3 0

12 9 4 0

13 9 1 2

14 8 1 0

15 12 2 1

16 6 3 0Courtesy of NOAA, Space Environment Center

•Detector flooded over the main flare period (9th and 10th September.. Enhanced peak on the 13th September.

•Require 100 days of summed data to get 10% precision on the hydrogen peak

Cou

nts

Detection of Radon as a geochemical probe for water

• Indirectly detecting radon is important because it could be a possible method for analysing the distribution of water ice in the subsurface for depths in the range of 1-100m (Sabroux et al., 2003).

• Radon is produced by the radioactive decay of Uranium which is relatively abundant in rocks on Mars, embedding itself in nearby mineral grain. In regions containing water, radon is slowed post production. The loss of energy causes radon to diffuse out up to the surface, travelling up to 20m despite its short half life.

• The intensity of the radon gamma rays were too low to be seen above the background in GRS energy spectra

• Gamma rays from decay products further down the Uranium chain could be analysed, which would give an indicator of the amount of radon released from the surface.

Courtesy of New Scientist

Regional Intensities of U, Th decay gammas

• More intense gamma activity from the polar regions which start at around 55 degrees latitude

Intensities of U,Th decay gamma rays across latitude bands of 5 degree thickness

0.00E+00

5.00E-08

1.00E-07

1.50E-07

2.00E-07

2.50E-07

3.00E-07

3.50E-07

-100 -80 -60 -40 -20 0 20 40 60 80 100

Midpoint of Latitude Band

Inte

nsi

ty

214Pbγ=351.932keV

214Bi γ=609.312keV

214Biγ=1120.287keV

214Biγ=1764.494keV

208Tlγ=583.191keV

Comparison with global distribution of water ice

• More water ice found at the polar regions

• Possible correlation between release of radon by indirect detection of decay gammas further down the U, Th chains

• Another reason for more intense

gamma activity in the polar regions due to water ice mixed into Martian soil, making it less dense. In these regions, gamma ray emission from the surface is therefore increased due to the additional presence of Hydrogen.

• Further study required with smaller regions at equatorial and polar regions and analysing more decay gammas in the decay chain above and below radon

Courtesy of University of Arizona

Conclusion• Studied interactions of gamma rays with the Martian

surface• Extracted energy spectra from Mars Odyssey GRS• Sharply increased gamma intensities for Oxygen

(γ=6.129MeV) in the event of a solar flare, indicates potential for using flares as pulsed neutron sources

• Polar regions show higher intensity of U, Th decay gamma rays than equatorial regions, correlating with distribution of water ice on Mars from Odyssey High Energy Neutron Detector

Acknowledgements:

Richard Ambrosi and Michelle Skidmore, University of Leicester

GRS team, University of Arizona