Randomness-efficient curve sampling

Curve samplers are sampling algorithms that proceed by viewing the domain as a vector space over a finite field, and randomly picking a low-degree curve in it as the sample. Curve samplers exhibit a nice property besides the sampling property: the restriction of low-degree polynomials over the domain to the sampled curve is still low-degree. This property is often used in combination with the sampling property and has found many applications, including PCP constructions, local decoding of codes, and algebraic PRG constructions.

The randomness complexity of curve samplers is a crucial parameter for its applications. It is known that (non-explicit) curve samplers using O(log N + log(1/δ)) random bits exist, where N is the domain size and δ is the confidence error. The question of explicitly constructing randomness-efficient curve samplers was first raised in [TU06] where they obtained curve samplers with near-optimal randomness complexity.

In this thesis, we present an explicit construction of low-degree curve samplers with optimal randomness complexity (up to a constant factor) that sample curves of degree (m log_q(1/δ))^O(1) in F_q^m. Our construction is a delicate combination of several components, including extractor machinery, limited independence, iterated sampling, and list-recoverable codes.

Filtering N.M.R. spectra

Methods of filtering an n.m.r. spectrum which can improve the resolution by as much as a factor of ten are examined. They include linear filters based upon an information theory approach and non-linear filters based upon a statistical approach. The appropriate filter is determined by the nature of the problem. Once programmed on a digital computer they are both simple to use.

These filters are applied to some examples from ¹³C and ¹⁵N n.m.r. spectra.

Measurements of mantle velocities of P waves with a large array

A large array has been used to investigate the P-wave velocity structure of the lower mantle. Linear array processing methods are reviewed and a method of nonlinear processing is presented. Phase velocities, travel times, and relative amplitudes of P waves have been measured with the large array at the Tonto Forest Seismological Observatory in Arizona for 125 earthquakes in the distance range of 30 to 100 degrees. Various models are assumed for the upper 771 km of the mantle and the Wiechert-Herglotz method applied to the phase velocity data to obtain a velocity depth structure for the lower mantle. The phase velocity data indicates the presence of a second-order discontinuity at a depth of 840 km, another at 1150 km, and less pronounced discontinuities at 1320, 1700 and 1950 km. Phase velocities beyond 85 degrees are interpreted in terms of a triplication of the phase velocity curve, and this results in a zone of almost constant velocity between depths of 2670 and 2800 km. Because of the uncertainty in the upper mantle assumptions, a final model cannot be proposed, but it appears that the lower mantle is more complicated than the standard models and there is good evidence for second-order discontinuities below a depth of 1000 km. A tentative lower bound of 2881 km can be placed on the depth to the core. The importance of checking the calculated velocity structure against independently measured travel times is pointed out. Comparisons are also made with observed PcP times and the agreement is good. The method of using measured values of the rate of change of amplitude with distances shows promising results.