Ultrasound tomography using pyroelectric and piezoelectric sensors

Acoustic absorption is one of several quantities which can differentiate healthy breast tissue from cancerous tissue. In order to accurately quantify the acoustic absorption, the sensor system must be able to accurately distinguish acoustic power loss due to absorption from other modes of attenuation. Traditional piezoelectric sensors are susceptible to phase-cancellation artifacts due to their directional signal response, and thus pyroelectric ultrasound sensors, which have a much flatter directional response, have been suggested as an alternate measurement device for improved absorption reconstructions in ultrasound tomography (UST). In this thesis we investigate the use of pyroelectric phase-insensitive sensors in UST — the thesis is divided into two parts. In the first part we present a model for a pyroelectric ultrasound sensor and investigate its directional response and sensitivity properties. The model’s time-series response and directional response are compared to real-world measurements to confirm accuracy. The second part focuses on the inverse problem aspect of ultrasound tomography, where we consider various reconstruction methods and sensor geometries to determine which situations can benefit from phase-insensitive data for acoustic absorption reconstruction. Reconstructions for both phase-insensitive as well as phase-sensitive sensors are analysed, with future work considerations for combined sensor systems

Phase-insensitive versus phase-sensitive ultrasound absorption tomography in the frequency domain

The sensitivity of phase-sensitive detectors, such as piezoelectric detectors, becomes increasingly directional as the detector element size increases. In contrast, pyroelectric sensors, which are phase-insensitive, retain their omni-directionality even for large element sizes, although they have significantly poorer temporal resolution. This study uses numerical models to examine whether phase-insensitive detectors can be used advantageously in ultrasound tomography, specifically absorption tomography, when the number of detectors is sparse. We present measurement models for phase-sensitive and phase-insensitive sensors and compare the quality of the absorption reconstructions between these sensor types based on relative error and image contrast metrics. We perform the inversion using synthetic data with a Jacobian-based linearized matrix inversion approach

Detection of cloud type using ground-based measurements of global shortwave radiation and cloud base height

Peer reviewe

Reaction coordinate approach to non-Markovian dynamics in the spin-boson model

The fundamental building blocks of quantum computers, called qubits, can be physically realized through any quantum system that is restricted to two possible states. The power of qubits arises from their ability to be in a superposition of these two states, allowing for the development of quantum algorithms that are impossible for classical computers. However, interactions with the surrounding environment destroy the superposition in a process called decoherence, which makes it important to find ways to model these interactions and mitigate them. In this thesis we derive a non-Markovian master equation for the spin-boson model, with a time-dependent two-level system, using the reaction coordinate representation. We show numerically that in the superconducting qubit regime this master equation maintains the positivity of the density operator for relevant parameter ranges, and is able to model non-Markovian effects between the system and the environment. We also compare the reaction coordinate master equation to a Markovian master equation with parameters taken from real superconducting qubits. We demonstrate that the Markovian master equation fails to capture the system–bath correlations for short times, and in many cases overestimates relaxation and coherence times. Finally, we test how a time-dependent bias affects the evolution of the two-level system. The bias is assumed to be constant with an additive term arising from an externally applied time-dependent plane wave control field. We show that an amplitude, angular frequency, and phase shift for the plane wave can be chosen such that the control field improves the coherence time of the two-level system

Clouds over Hyytiälä, Finland : an algorithm to classify clouds based on solar radiation and cloud base height measurements

We developed a simple algorithm to classify clouds based on global radiation and cloud base height measured by pyranometer and ceilometer, respectively. We separated clouds into seven different classes (stratus, stratocumulus, cumulus, nimbostratus, altocumulus + altostratus, cirrus + cirrocumulus + cirrostratus and clear sky + cirrus). We also included classes for cumulus and cirrus clouds causing global radiation enhancement, and we classified multilayered clouds, when captured by the ceilometer, based on their height and characteristics (transmittance, patchiness and uniformity). The overall performance of the algorithm was nearly 70% when compared with classification by an observer using total-sky images. The performance was best for clouds having well-distinguishable effects on solar radiation: nimbostratus clouds were classified correctly in 100% of the cases. The worst performance corresponds to cirriform clouds (50 %). Although the overall performance of the algorithm was good, it is likely to miss the occurrences of high and multilayered clouds. This is due to the technical limits of the instrumentation: the vertical detection range of the ceilometer and occultation of the laser pulse by the lowest cloud layer. We examined the use of clearness index, which is defined as a ratio between measured global radiation and modeled radiation at the top of the atmosphere, as an indicator of clear-sky conditions. Our results show that cumulus, altocumulus, altostratus and cirriform clouds can be present when the index indicates clear-sky conditions. Those conditions have previously been associated with enhanced aerosol formation under clear skies. This is an important finding especially in the case of low clouds coupled to the surface, which can influence aerosol population via aerosol-cloud interactions. Overall, caution is required when the clearness index is used in the analysis of processes affected by partitioning of radiation by clouds.Peer reviewe