Compositional And Physical Characterizations Of NEOs From VNIR Spectroscopy Michael J. Gaffey 1,3 Paul A. Abell 2,3 Paul S. Hardersen 1,3 1 Department of Space Studies, Univ. of North Dakota 2 Planetary Astronomy Group, NASA JSC 3 Visiting astronomer - NASA Infrared Telescope Facility (IRTF)

VNIR Characterizations Composition / Mineralogy → Intrinsic density → Intrinsic strength → General albedo Albedo [for many/most observed NEOs] –Size (albedo combined with visual magnitude) –Volume from size and axial ratio (lightcurve)

Derived Properties Estimated Mass –Volume x Int. density x porosity fudge factor Actual Mass –From observations of binary NEOs Bulk Density –Mass / Volume Strength –Porosity from bulk density / intrinsic density –High porosity → Weak rubble pile –Low porosity → Relative strong solid body –Metallic body → Very strong

Different Analysis Concepts Taxonomic classification –Grouping by shared observation characteristics –S-, C-, M-, E-, A-, V-taxons Curve matching –Comparison to catalog of sample spectra Diagnostic spectral parameters –Extraction of diagnostic mineral parameters –Interpretation using crystal field theory and laboratory calibrations

Limits of Taxonomic Classifications Group diverse materials together –If two asteroids are different taxonomic types, they are very probably different materials. However if they are the same taxonomic type there is no assurance that they are composed of similar materials. Sensitive to space weathering effects –Spectral slopes –Absorption band depths

S CV3/CO3 OC Prim. Achon. Diff. Ol-rich Diff. Px-rich Diff. Ol-Px Mix CB/CH + NiFe Metal Compositional Diversity of the S-Taxon

S CV3/CO3 OC Prim. Achon. Diff. Ol-rich Diff. Px-rich Diff. Ol-Px Mix CB/CH + NiFe Metal S(VII) S(IV) S(I) S(IV)

KEY Weak – Mod. Weak Mod. Weak - Mod. Strong Mod. Strong Strong S CV3/CO3 OC Prim. Achon. Diff. Ol-rich Diff. Px-rich Diff. Ol-Px Mix CB/CH + NiFe Metal Strengths of the S-Taxon Lithologies

KEY ~3 – 3.5 gm/cm 3 ~4.5 – 5.5 gm/cm 3 ~6 - 8 gm/cm 3 S CV3/CO3 OC Prim. Achon. Diff. Ol-rich Diff. Px-rich Diff. Ol-Px Mix CB/CH + NiFe Metal Densities of the S-Taxon Lithologies

M Hyd. Sil. NiFe Metal with Fe-Sil. NiFe Metal w/o Fe-Sil. M Hyd. Sil. NiFe Metal with Fe-Sil. NiFe Metal w/o Fe-Sil. KEYWeak Mod. Strong Strong KEY ~2.5 – 3 gm/cm 3 ~5 – 7.5 gm/cm 3 ~ gm/cm 3 Strength and Densities with the M-Taxon

V Diogenite Howardite Eucrite Polymict Eucrite V-Taxon Densities are similar KEY Mod. Weak Mod. Strong

A Pallasite Dunite A-Taxon Mod. Weak – Mod. Strong Very Strong  ~ 3.5 g/cm 3  ~ g/cm 3

Limits to Curve Matching Limited set of comparison material –Variables Mineral type and abundances Mineral compositions Petrology Space weathering Contamination / terrestrial weathering –Tens of thousands of permutations What constitutes a good match? –Minimize deviations? –Spectral intervals are not equally important

Purported “best match” between asteroid 21 Lutetia and CV3 Chondrite Vigarano. When is a mis-match critical? The absence of these features in the asteroid spectrum eliminates this option!

The Meteorite sample is a slab of the L6 ordinary chondrite, Pervomaisky. The mis-match near 1  m – if real – would rule out any such assemblage. NEO match to Ordinary Chondrite?

Limits to Diagnostic Parameters Requires high quality spectra with continuous coverage across telluric water vapor absorptions Parameter extraction methodologies are not standardized More interpretive calibrations are needed Existing interpretive calibrations must be regularly evaluated and upgraded as needed

Diagnostic Parameter Methodology - I Instrumentation –Low resolution ( /  ~ 100 – 200) spectrograph (e.g., IRTF SpeX) –NIR (~0.7 – 2.5  m) coverage is critical VNIR (~0.4 – 2.5  m) desirable –High dry observing site is needed Reasonable signal through the 1.4 & 1.9  m telluric water vapor bands

Raw Flux versus Wavelength [SpeX Instrument] H 2 O Vapor absorptions Even in the 1.4 and 1.9  m regions significant flux is being detected.

Unsmoothed, unedited average spectrum. This should be the current expectation for NIR asteroid spectra. Current State-of-the-Art H2OH2O H2OH2O Hardersen et al. (2004) 1459 MagnyaV mag = 15.7

Spectra with Serious Problems in the 1.4 & 1.9  m Telluric Features V mags = Are these problems due to fainter objects or shorter integrations? Citation is intentionally omitted

Can these problems be ameliorated by smoothing? Smoothing will only work if the “spikiness” is due random noise in the spectra.

0.05 airmass difference Exposure = 60 sec V Mag = 12.4 What is the nature of these variations? Simple Asteroid / Standard Star Ratio

Effects of Channel Shifts Much of the “noise” is actually an interference pattern due to small offsets in the location of the dispersed spectrum onto the detector array. +1 Channel Offset -1 Channel Offset Raw Flux Data

Extinction correction with channel offsets Most of the “noise” in the 1.4 & 1.9  m regions was not random, but due to uncorrected channel offsets

Effects of Uncorrected 0.5 Channel Offset -0.5 Chan Chan. Correct A small offset produces major deviations in Band II

Implications for Analysis Irrespective of the analysis technique Curve matching Gaussian fitting Parameter extraction Interpretations would differ for these spectra.

Correction Process The interference pattern identifies the presence of an offset. Channel offset is determined for each set of observations relative to a chosen reference set. Offsets are derived by using the steep edge of the 1.4  m atmospheric water vapor feature. Offsets should be established to ~ pixels. Pixel offset corrections are applied to the raw standard star spectra prior to calculation of the extinction coefficients (or their use in ratios). Pixel offset corrections are applied to the raw object spectra prior to extinction corrections.

Correction for Atmospheric Absorptions In as far as possible extinction corrections should be based on objective rather than subjective criteria. Extinction corrections should be derived from standard star observations throughout the night. Use of average extinction coefficients should be avoided.

In a stable homogeneous atmosphere, the log of the transmitted flux decreases linearly with atmospheric path length (airmass) Beer’s Law (Beer-Lambert Law)

Real Observations Most nights do not satisfy the requirements for “A”. Sky conditions commonly vary during the night, and at Mauna Kea (at least), there is often an invisible orographic cloud over and downwind of the summit. [Case B]

Orographic cloud produced by airflow over a mountain © Sharon Gerig / Roma Stock Wind Flow

Commonly the data indicates that different extinction coefficients are required for different parts of the night Pre-meridian observations Post-meridian observations

One should expect high quality spectra for NEOs down to V Mag ~ 17.

(5660) 1974 MA Band I Center: 1.02±0.01μm Band II Center: 2.0±0.01μm Band Area Ratio: 0.06±0.006 Reddy et al. (2006)