Colliding and Moving Bose-Einstein Condensates: Studies of superfluidity and optical tweezers for condensate transport

In this thesis, two different sets of experiments are described. The first is an exploration of the microscopic superfluidity of dilute gaseous Bose- Einstein condensates. The second set of experiments were performed using transported condensates in a new BEC apparatus. Superfluidity was probed by moving impurities through a trapped condensate. The impurities were created using an optical Raman transition, which transferred a small fraction of the atoms into an untrapped hyperfine state. A dramatic reduction in the collisions between the moving impurities and the condensate was observed when the velocity of the impurities was close to the speed of sound of the condensate. This reduction was attributed to the superfluid properties of a BEC. In addition, we observed an increase in the collisional density as the number of impurity atoms increased. This enhancement is an indication of bosonic stimulation by the occupied final states. This stimulation was observed both at small and large velocities relative to the speed of sound. A theoretical calculation of the effect of finite temperature indicated that collision rate should be enhanced at small velocities due to thermal excitations. However, in the current experiments we were insensitive to this effect. Finally, the factor of two between the collisional rate between indistinguishable and distinguishable atoms was confirmed. A new BEC apparatus that can transport condensates using optical tweezers was constructed. Condensates containing 10-15 million sodium atoms were produced in 20 s using conventional BEC production techniques. These condensates were then transferred into an optical trap that was translated from the ‘production chamber’ into a separate vacuum chamber: the ‘science chamber’. Typically, we transferred 2-3 million condensed atoms in less than 2 s. This transport technique avoids optical and mechanical constrainsts of conventional condensate experiments and allows for the possibility of novel experiments. In the first experiments using transported BEC, we loaded condensed atoms from the optical tweezers into both macroscopic and miniaturized magnetic traps. Using microfabricated wires on a silicon chip, we observed excitation-less propagation of a BEC in a magnetic waveguide. The condensates fragmented when brought very close to the wire surface indicating that imperfections in the fabrication process might limit future experiments. Finally, we generated a continuous BEC source by periodically replenishing a condensate held in an optical reservoir trap using fresh condensates delivered using optical tweezers. More than a million condensed atoms were always present in the continuous source, raising the possibility of realizing a truly continuous atom lase.

Automatically Recovering Geometry and Texture from Large Sets of Calibrated Images

Three-dimensional models which contain both geometry and texture have numerous applications such as urban planning, physical simulation, and virtual environments. A major focus of computer vision (and recently graphics) research is the automatic recovery of three-dimensional models from two-dimensional images. After many years of research this goal is yet to be achieved. Most practical modeling systems require substantial human input and unlike automatic systems are not scalable. This thesis presents a novel method for automatically recovering dense surface patches using large sets (1000's) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Essentially, the problem is to find corresponding points in each of the images. Once a correspondence has been established, calculating its three-dimensional position is simply a matter of geometry. Long baseline images improve the accuracy. Short baseline images and the large number of images greatly simplifies the correspondence problem. The initial stage of the algorithm is completely local and scales linearly with the number of images. Subsequent stages are global in nature, exploit geometric constraints, and scale quadratically with the complexity of the underlying scene. We describe techniques for: 1) detecting and localizing surface patches; 2) refining camera calibration estimates and rejecting false positive surfels; and 3) grouping surface patches into surfaces and growing the surface along a two-dimensional manifold. We also discuss a method for producing high quality, textured three-dimensional models from these surfaces. Some of the most important characteristics of this approach are that it: 1) uses and refines noisy calibration estimates; 2) compensates for large variations in illumination; 3) tolerates significant soft occlusion (e.g. tree branches); and 4) associates, at a fundamental level, an estimated normal (i.e. no frontal-planar assumption) and texture with each surface patch.

A System for Representing and Using Real-World Knowledge

This report describes a knowledge-base system in which the information is stored in a network of small parallel processing elements ??de and link units ??ich are controlled by an external serial computer. This network is similar to the semantic network system of Quillian, but is much more tightly controlled. Such a network can perform certain critical deductions and searches very quickly; it avoids many of the problems of current systems, which must use complex heuristics to limit and guided their searches. It is argued (with examples) that the key operation in a knowledge-base system is the intersection of large explicit and semi-explicit sets. The parallel network system does this in a small, essentially constant number of cycles; a serial machine takes time proportional to the size of the sets, except in special cases.

Thread Scheduling Mechanisms for Multiple-Context Parallel Processors

Scheduling tasks to efficiently use the available processor resources is crucial to minimizing the runtime of applications on shared-memory parallel processors. One factor that contributes to poor processor utilization is the idle time caused by long latency operations, such as remote memory references or processor synchronization operations. One way of tolerating this latency is to use a processor with multiple hardware contexts that can rapidly switch to executing another thread of computation whenever a long latency operation occurs, thus increasing processor utilization by overlapping computation with communication. Although multiple contexts are effective for tolerating latency, this effectiveness can be limited by memory and network bandwidth, by cache interference effects among the multiple contexts, and by critical tasks sharing processor resources with less critical tasks. This thesis presents techniques that increase the effectiveness of multiple contexts by intelligently scheduling threads to make more efficient use of processor pipeline, bandwidth, and cache resources. This thesis proposes thread prioritization as a fundamental mechanism for directing the thread schedule on a multiple-context processor. A priority is assigned to each thread either statically or dynamically and is used by the thread scheduler to decide which threads to load in the contexts, and to decide which context to switch to on a context switch. We develop a multiple-context model that integrates both cache and network effects, and shows how thread prioritization can both maintain high processor utilization, and limit increases in critical path runtime caused by multithreading. The model also shows that in order to be effective in bandwidth limited applications, thread prioritization must be extended to prioritize memory requests. We show how simple hardware can prioritize the running of threads in the multiple contexts, and the issuing of requests to both the local memory and the network. Simulation experiments show how thread prioritization is used in a variety of applications. Thread prioritization can improve the performance of synchronization primitives by minimizing the number of processor cycles wasted in spinning and devoting more cycles to critical threads. Thread prioritization can be used in combination with other techniques to improve cache performance and minimize cache interference between different working sets in the cache. For applications that are critical path limited, thread prioritization can improve performance by allowing processor resources to be devoted preferentially to critical threads. These experimental results show that thread prioritization is a mechanism that can be used to implement a wide range of scheduling policies.

Evaluation of sets of oriented and non-oriented receptive fields as local descriptors

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.