Asymptotic scaling in the two-dimensional O(3) Nonlinear sigma model: a Monte Carlo study on parallel computers

We investigate the 2d O(3) model with the standard action by Monte Carlo simulation at couplings β up to 2.05. We measure the energy density, mass gap and susceptibility of the model, and gather high statistics on lattices of size L ≤ 1024 using the Floating Point Systems T-series vector hypercube and the Thinking Machines Corp.'s Connection Machine 2. Asymptotic scaling does not appear to set in for this action, even at β = 2.10, where the correlation length is 420. We observe a 20% difference between our estimate m/Λ^─_(Ms) = 3.52(6) at this β and the recent exact analytical result . We use the overrelaxation algorithm interleaved with Metropolis updates and show that decorrelation time scales with the correlation length and the number of overrelaxation steps per sweep. We determine its effective dynamical critical exponent to be z' = 1.079(10); thus critical slowing down is reduced significantly for this local algorithm that is vectorizable and parallelizable.

We also use the cluster Monte Carlo algorithms, which are non-local Monte Carlo update schemes which can greatly increase the efficiency of computer simulations of spin models. The major computational task in these algorithms is connected component labeling, to identify clusters of connected sites on a lattice. We have devised some new SIMD component labeling algorithms, and implemented them on the Connection Machine. We investigate their performance when applied to the cluster update of the two dimensional Ising spin model.

Finally we use a Monte Carlo Renormalization Group method to directly measure the couplings of block Hamiltonians at different blocking levels. For the usual averaging block transformation we confirm the renormalized trajectory (RT) observed by Okawa. For another improved probabilistic block transformation we find the RT, showing that it is much closer to the Standard Action. We then use this block transformation to obtain the discrete β-function of the model which we compare to the perturbative result. We do not see convergence, except when using a rescaled coupling β_E to effectively resum the series. For the latter case we see agreement for m/ Λ^─_(Ms) at , β = 2.14, 2.26, 2.38 and 2.50. To three loops m/Λ^─_(Ms) = 3.047(35) at β = 2.50, which is very close to the exact value m/ Λ^─_(Ms) = 2.943. Our last point at β = 2.62 disagrees with this estimate however.

Wireless parylene-based retinal implant

The degeneration of the outer retina usually causes blindness by affecting the photoreceptor cells. However, the ganglion cells, which consist of optic nerves, on the middle and inner retina layers are often intact. The retinal implant, which can partially restore vision by electrical stimulation, soon becomes a focus for research. Although many groups worldwide have spent a lot of effort on building devices for retinal implant, current state-of-the-art technologies still lack a reliable packaging scheme for devices with desirable high-density multi-channel features. Wireless flexible retinal implants have always been the ultimate goal for retinal prosthesis. In this dissertation, the reliable packaging scheme for a wireless flexible parylene-based retinal implants has been well developed. It can not only provide stable electrical and mechanical connections to the high-density multi-channel (1000+ channels on 5 mm × 5 mm chip area) IC chips, but also survive for more than 10 years in the human body with corrosive fluids.

The device is based on a parylene-metal-parylene sandwich structure. In which, the adhesion between the parylene layers and the metals embedded in the parylene layers have been studied. Integration technology for high-density multi-channel IC chips has also been addressed and tested with dummy and real 268-channel and 1024-channel retinal IC chips. In addition, different protection schemes have been tried in application to IC chips and discrete components to gain the longest lifetime. The effectiveness has been confirmed by the accelerated and active lifetime soaking test in saline solution. Surgical mockups have also been designed and successfully implanted inside dog's and pig's eyes. Additionally, the electrodes used to stimulate the ganglion cells have been modified to lower the interface impedance and shaped to better fit the retina. Finally, all the developed technologies have been applied on the final device with a dual-metal-layer structure.

Neural network design for switching network control

A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.

Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.

Zn-VI/Cu2O Heterojunctions for Earth-Abundant Photovoltaics

The need for sustainable energy production motivates the study of photovoltaic materials, which convert energy from sunlight directly into electricity. This work has focused on the development of Cu₂O as an earth-abundant solar absorber due to the abundance of its constituent elements in the earth's crust, its suitable band gap, and its potential for low cost processing. Crystalline wafers of Cu₂O with minority carrier diffusion lengths on the order of microns can be manufactured in a uniquely simple fashion — directly from copper foils by thermal oxidation. Furthermore, Cu₂O has an optical band gap of 1.9 eV, which gives it a detailed balance energy conversion efficiency of 24.7% and the possibility for an independently connected Si/Cu₂O dual junction with a detailed balance efficiency of 44.3%.

However, the highest energy conversion efficiency achieved in a photovoltaic device with a Cu₂O absorber layer is currently only 5.38% despite the favorable optical and electronic properties listed above. There are several challenges to making a Cu₂O photovoltaic device, including an inability to dope the material, its relatively low chemical stability compared to other oxides, and a lack of suitable heterojunction partners due to an unusually small electron affinity. We have addressed the low chemical stability, namely the fact that Cu₂O is an especially reactive oxide due to its low enthalpy of formation (ΔH_f⁰ = -168.7 kJ/mol), by developing a novel surface preparation technique. We have addressed the lack of suitable heterojunction partners by investigating the heterojunction band alignment of several Zn-VI materials with Cu₂O. Finally, We have addressed the typically high series resistance of Cu₂O wafers by developing methods to make very thin, bulk Cu₂O, including devices on Cu₂O wafers as thin as 20 microns. Using these methods we have been able to achieve photovoltages over 1 V, and have demonstrated the potential of a new heterojunction material, Zn(O,S).

Isotope shift studies in the rare earths and lead

Isotope shifts of K_α1 x-ray transitions were measured for the Neodymium isotopes Nd 142, 143, 144, 145, 146, 148 and 150, the Samarium isotopes Sm 147, 148, 149, 150, 152 and 154, the Gadolinium isotopes Gd 154, 155, 156, 157, 158 and 160, the Dysprosium isotopes Dy 162 and 164, the Erbium isotopes Er 166, 168 and 170, the Hafnium isotopes Hf 178 and 180 and the Lead isotopes Pb 204, 206, 207 and 208. A curved crystal Cauchois spectrometer was used. The analysis of the measurement furnished the variation of the mean square charge radius of the nucleus, δ˂r²˃, for 23 isotope pairs. The experimental results were compared with theoretical values from nuclear models. Combining the x-ray shifts and the optical shifts in Nd and Sm yielded the optical mass shifts. An anomaly was observed in the odd-even shifts when the optical and the x-ray shifts were plotted against each other.