Deep Learning Models for Planetary Seismicity Detection

Research in planetary seismology is fundamentally constrained by a lack of data. Seismo-logical science products of future missions can typically only be informed by theoretical signal/noise characteristics of the environment or likely Earth-analogues. Although objectives can be re-assessed after some initial data-collection upon lander arrival, transfer of high-resolution data back to Earth is costly on lander power usage. Over the last several years, development of GPU computing techniques and open-source high-level APIs have led to rapid advances in deep learning within the fields of computer vision, natural language processing, and collaborative filtering. These techniques are actively being adapted in seismology for a variety of tasks, including: earthquake detection, seismic phase discrimination, and ground-motion prediction. Until the recent detection of mars quakes during the Mars InSight mission, the only other measurements of seismicity recorded outside of Earth was on the Moon during the Apollo missions between 1969 to 1977. These unique data sets have been periodically revisited using new seismological methods, including ambient noise interferometry and Hidden Markov Models. Our objective is to develop a deep learning seismic detector and use it to catalog moonquakes from the Apollo 17 Lunar Seismic Profiling Experiment (LSPE) and compare the results with those obtained by other methods. Additionally, we will assess the accuracy tradeoff between using a training set of lunar data and one composed of Earth seismicity. In this document, we present preliminary results using a prototype classifier trained on a small set of earthquakes that was able to obtain detections for LSPE moonquakes with a greater accuracy than a recent study using Hidden Markov Models

Checkerboard order in the t--J model on the square lattice

We propose that the inhomogeneous patterns seen by STM in some underdoped superconducting cuprates could be related to a bond-order-wave instability of the staggered flux state, one of the most studied "normal" state proposed to compete with the d-wave RVB superconductor. A checkerboard pattern is obtained by a Gutzwiller renormalized mean-field theory of the t-J model for doping around 1/8. It is found that the charge modulation is always an order of magnitude smaller than the bond-order modulations. This is confirmed by an exact optimization of the wavefunction by a variational Monte Carlo scheme. The numerical estimates of the order parameters are however found to be strongly reduced w.r.t their mean-field values

The use of multispectral sensing techniques to detect ponderosa pine trees under stress from insect or pathogenic organisms Annual progress report

Ground and aerial imaging techniques to detect tree damage caused by bark beetles in forested area

Integral representations combining ladders and crossed-ladders

We use the worldline formalism to derive integral representations for three classes of amplitudes in scalar field theory: (i) the scalar propagator exchanging N momenta with a scalar background field (ii) the "half-ladder" with N rungs in x - space (iii) the four-point ladder with N rungs in x - space as well as in (off-shell) momentum space. In each case we give a compact expression combining the N! Feynman diagrams contributing to the amplitude. As our main application, we reconsider the well-known case of two massive scalars interacting through the exchange of a massless scalar. Applying asymptotic estimates and a saddle-point approximation to the N-rung ladder plus crossed ladder diagrams, we derive a semi-analytic approximation formula for the lowest bound state mass in this model.Comment: 39 pages, 10 pdf figure

The use of multispectral sensing techniques to detect Ponderosa pine trees under stress from insect or pathogenic organisms

Multispectral sensing techniques for ground and airborne detection of Ponderosa pine trees under stress from insect or pathogenic organism

Inventory of forest and rangeland resources, including forest stress

The author has identified the following significant results. Road systems being developed within the Manitou, Colorado area for human habitation are readily discernible on the S192 normal-color photographs. These are dirt roads, some of which are about 20 feet wide. These data should provide the District Ranger of the Pike National Forest required information on the size and extent of these developing areas, information which he does not now have but is required for total management of the District

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report