NeoWISE Data:
IR observations of asteroids provide valuable information. Myhrvold conducted a comparative study of asteroid surveys, including NeoWISE, NeoCam, B612, JPL’s CubeSat project, LSST, and others.

NeoWISE Data in the PDS System:
NeoWISE data is available in the PDS system. Discrepancies exist between the original papers and the PDS data: 3,700 asteroids from the original papers are missing in the PDS. 1,200 asteroids in the PDS are not present in the original papers. PDS data offers additional information, but it differs from the original papers.

Multiple Models and Band Combinations in NeoWISE Data:
NeoWISE employed various models and band combinations. 10 different models and several combinations of the four WISE bands (W1, W2, W3, W4) were used. Approximately 45% of the new WISE results are based on the Near Earth Asteroid Thermal Model (NETAM).

STM-Like Models:
55% of Neowise asteroid thermal models resemble the standard thermal model (STM) developed in the late 1970s and early 1980s. STM involves fixing a parameter called the beaming parameter.

Fully Thermal Bands:
About 44% of observations have fully thermal bands, with the W3 and W4 bands emitting at long enough wavelengths to be thermal at typical asteroid temperatures. The W1 and W2 bands contain reflected sunlight, making their interpretation more challenging.

Partial and Single-Band Models:
1% of models are partial, and 51% are based on a single band. Single-band models require assumptions and estimations, making them highly dependent on those assumptions.

Model Codes and Assumptions:
The PDS version of Neomyos results includes a model code indicating the fitted parameters. D represents fitted diameter, V represents fitted visible band albedo, and IR represents fitted IR albedo. The code also shows band information and typical reflected sunlight for different emissivities.

Reflected Sunlight and Thermal Emissivity:
The W1 band consists primarily of reflected sunlight, while the W2 band contains a mixture of reflected sunlight and thermal emission. The W3 and W4 bands are dominated by thermal emission due to limited reflected sunlight.

IR Albedo Assumptions:
About 69,000 results assume a relationship between IR albedo and visible band albedo, with a constant factor A. Different groups use different A values, even for the same asteroid groups like main belt asteroids and near-Earth asteroids.

Scattered Plot of IR Albedo vs. Visible Band Albedo:
A scattered plot of IR albedo versus visible band albedo for main belt asteroids shows no clear linear relationship. A linear relationship between these parameters is not a good assumption for modeling.

Independent Determination of Parameters:
When multiple bands are available, parameters like IR albedo and visible band albedo are determined independently through curve fitting. However, the diameter, which is derived from IR modeling and visible band absolute magnitude, is not entirely independent.

Limited Independent Albedo Determinations:
Very few asteroids have visible albedo independently determined without assumptions, primarily through radar, stellar occultations, and observations of Ceres.

Data Issues and Assumptions:
Linear assumptions about the IR albedo and ADA (albedo parameter) have limitations and can lead to discrepancies. Assumptions about the beaming parameter (in the NITA model) vary widely, affecting the accuracy of results. Only a small portion (3%) of NEOWISE data remains after discarding data due to various criteria, including a 40% rule for observations in each band. The 40% rule may discard valuable data, especially for fainter bands, due to the sensitivity of sensors and asteroid brightness.

Diameter Discrepancies:
Some published diameters match to the nearest meter for asteroids measured by radar occultation spacecraft (ROAS), raising concerns about the accuracy of modeled diameters. Nine results in the PDS compilation had copied diameters, suggesting that the diameters were not determined through modeling. Copying diameters from other sources introduces uncertainty since the accuracy of those sources cannot be verified.

Observational Errors:
Overlapping observations in the Y-space data allow for the estimation of instrumental errors. Statistical analysis reveals significant discrepancies between consecutive measurements, with some exceeding 8 sigma. The error estimates provided by the Y’s pipeline are often poor, as they are based on small sample sizes and estimated from photon statistics.

WISE Mission Design and Asteroid Observations:
WISE was designed for multiple co-added frames, providing accurate asteroid observations. Single-exposure observations for asteroids introduced significant errors. Using maximum likelihood estimation with incorrect sigma values can lead to over-constrained fits.

Error Analysis Assumptions and Limitations:
The error analysis assumed a normal distribution with the WISE sigma. Using a chi-square fitting method can be misleading due to the asteroid’s light curve variations. Light curve variations are typically larger than single measurement errors, affecting the accuracy of chi-square fitting.

Data Fitting Results:
Many of the fitted curves missed the data points, with 30% of single-band results failing to align with the data. Even when all data points were included, only 60% of the fits successfully aligned with the data. This highlights the limitations of single-band observations and the challenges of curve fitting with incorrect error assumptions.

Residual Analysis and Flux Calculations:
Residual analysis showed that even when curves missed data points, they were evenly distributed, indicating accurate flux calculations. The residuals were centered around zero, confirming the correctness of flux calculations.

Geometric Albedo Definition and Error Analysis:
The geometric albedo definition involves asteroid diameter, absolute magnitude H, and the parameter h. Analyzing the absolute and proportional errors revealed that most data points were accurate, with a small subset of around 14,000-15,000 observations showing discrepancies. The source of these discrepancies could be incorrect diameter or albedo values, but the exact cause remains uncertain.

NEOWISE Data Analysis Uncertainties:
Over 100% errors in PV and diameter were found, indicating causes beyond diameter and albedo variations.

Systematic and Random Errors:
Systematic error of about 5% exists, along with a random error roughly twice the claimed 10% or possibly 1.5 times.

Data Accuracy and Limitations:
Radar occultations and spacecraft data provide diameters, but not all band combinations have good statistics. For W1234, there are 435 cases, while for W3, there are only 17, leading to uncertainties. Systematic errors vary, with some bands having low errors and others having higher errors.

Replicating Neowise Analysis:
There may be some double counting of asteroids observed in different phases and bands. Extracting fluxes from published data and performing curve fits can be done, but the exact analysis of the original study could not be replicated.

Data Correlation and Model Distribution:
There is a correlation between model and diameter, with certain regions showing clusters of colors due to varying visibility of asteroids.

Unresolved Issues and Potential:
The analysis of Neowise data is still an unsolved problem with much more interesting data to be explored. Replicating the analysis in a more open manner would allow for diverse searches and identification of fast tumblers and other interesting objects.

Asteroids Models and Spectral Changes:
A tumbling asteroid model shows that the spectrum becomes a black body when rotating in two directions. Fast tumblers and other unique objects can be identified from Neowise data.

Nemesis Hypothesis:
In the past, there was speculation about a “Nemesis” object, possibly a red dwarf star, causing the extinction of the dinosaurs. Later, it was discovered that there was no evidence for a red dwarf, and the Nemesis hypothesis was discarded.

Tyche Hypothesis:
Matisse and Whitmire proposed the existence of an object called “Tyche” as a potential new Nemesis. The speaker was involved in processing data to search for Tyche.

NEOWISE Data:
The speaker obtained a fellowship from NASA to work with NEOWISE data. They are searching for objects that might have been overlooked, specifically objects that could have caused the dinosaur extinction.

Collaboration:
The speaker expresses willingness to collaborate with others, including Nathan Myhrvold, on analyzing NEOWISE data.

Planet Nine:
The speaker mentions the possibility of finding Planet Nine in the NEOWISE data.

Dark Matter Hypothesis:
Lisa Randall, a physicist, proposed that dark matter might have caused the extinction of the dinosaurs.

Mechanism for Extinction:
The various hypotheses discussed in the presentation seek to provide a mechanism for explaining the asteroid impact that caused the dinosaur extinction. The Nemesis hypothesis suggests that it perturbed the Oort cloud, leading to the release of comets and asteroids.

Impactors and Nemesis:
There are two hypotheses for the cause of the Chicxulub impact: one suggests a perturbation in the ORC cloud, while the other proposes a collision in the Baptistina family 160 million years ago. Bill Botke’s recent research suggests that the bombardment rate may have been lower in the past, and craters on Earth are not missing but never occurred.

Nemesis and Mass Extinctions:
The idea of Nemesis as a cause for mass extinctions gained traction after the Alvarez hypothesis linking an asteroid impact to the dinosaur extinction. The original basis for Nemesis was the Fourier series analysis of extinction data, suggesting a quasi-periodic pattern.

Data Analysis of Asteroid Observations:
Asteroid data analysis typically involves fitting for diameter, visible albedo, and infrared albedo, with additional parameters like the beaming parameter and sub-solar temperature. The conventional approach of using a ratio for sub-solar temperature is not ideal, and it’s better to fit for sub-solar temperature and diameter directly. Kirchhoff’s law should be respected when analyzing infrared albedo to ensure consistency with emissivity.

Data Availability and Analysis Potential:
About 44% of asteroid observations have enough data to allow for a good analysis, including those with W3 and W4 bands. For observations with only W1 and W2 bands, a Kirchhoff’s Law-respecting framework can be used, but the errors are higher.