SU-EARTHSYS11 MAY182026
Last edited: May 5, 2026There’s So Much Oil in the Ground
oil
“Fossilized Sunshine” photosynthesis => plant elements => preserved sedimentary rocks.
- small critters
- phytoplankton
- plant matter
maturation process
Carbon-rich organic features, deposited. Increased pressure. Eventually compressed into…
kerogen
A solid, seminary rock that’s carbon rich. With enough pressure, carbons join up and then you get a chain.
Oil: C16H34, C7H16 etc.
increase pressure
….oil gets squeezed out from the kerogen, and then density differences makes it rise.
knowledgebase testing page
Last edited: May 5, 2026A memo from the administrators at Metropolis Health System, in response to a nationwide blood shortage, asked the care teams and doctors at all of their hospitals to be particularly conservative and judicious in how they used blood products because of the critical shortage. Phoebe, a 17-year-old girl, is being treated for leukemia at Metro Hospital, which is part of the health system. She has gone through several rounds of chemotherapy, but has not responded to the treatment.
SU-EARTHSYS11 APR292026
Last edited: May 5, 2026orogeny
crust is folded and deformed by lateral compression to form a mountain range
deformation
types of deformation—
- displacement: stuff slip
- rotation
- distortion: metaphoric stresses
topography
features we see at the surface, in the verticle sense
relief
difference between highest and lowest points in an areao
mountain forming and plate boundaries
convergent bounaries
Subduction mountain building: volcanic arc behind
collisional orogones
continenant to continent convergence
2026-04-23
Last edited: April 4, 2026Alex's Defense
Last edited: April 4, 2026We need to figure out good aways of modeling/representing uncertainty.
unifying principle
- data: samples / distribution
- representation: simplify / keep what matters
- control: convex / gradient / MPC
Different things requires different techniques but broadly the structure.
contributions
- factor models of covariance
- 1d projections of distributions and distribution shaping
- informational representation: conditioning + shrinking horizon reoptimization
factor model
Suppose someone hands you a model for returns:
\begin{equation} r \approx F_{\text{base}} s + \varepsilon, s \sim \mathcal{N}\qty(0, \Omega_{\text{base}}), \epsilon \sim \mathcal{N}\qty(0, D_{\text{base}}) \end{equation}
