Microwave background constraints on inflationary parameters

We use a compilation of cosmic microwave anisotropy data (including the recent VSA, CBI and Archeops results), supplemented with an additional constraint on the expansion rate, to directly constrain the parameters of slow-roll inflation models. We find good agreement with other papers concerning the cosmological parameters, and display constraints on the power spectrum amplitude from inflation and the first two slow-roll parameters, finding in particular that $\epsilon_1 < 0.057$. The technique we use for parametrizing inflationary spectra may become essential once the data quality improves significantly.Comment: 6 pages LaTeX file with figures incorporated. Major revisions including incorporation of new datasets (CBI and Archeops). Slow-roll inflation module for use with the CAMB program can be found at http://astronomy.cpes.susx.ac.uk/~sleach/inflation

Measuring the primordial power spectrum: principal component analysis of the cosmic microwave background

We implement and investigate a method for measuring departures from scale-invariance, both scale-dependent as well as scale-free, in the primordial power spectrum of density perturbations using cosmic microwave background (CMB) Cℓ data and a principal component analysis (PCA) technique. The primordial power spectrum is decomposed into a dominant scale-invariant Gaussian adiabatic component plus a series of orthonormal modes whose detailed form only depends the noise model for a particular CMB experiment. However, in general these modes are localized across wavenumbers with 0.01 < k < 0.2 Mpc−1 displaying rapid oscillations on scales corresponding the acoustic peaks where the sensitivity to primordial power spectrum is greatest. The performance of this method is assessed using simulated data for the Planck satellite, and the full cosmological plus power spectrum parameter space is integrated out using Markov Chain Monte Carlo. As a proof of concept we apply this data-compression technique to the current CMB data from Wilkinson Microwave Anisotropy Probe (WMAP), ACBAR, CBI, VSA and Boomerang. We find no evidence for the breaking of scale-invariance from measurements of four PCA mode amplitudes, which is translated to a constraint on the scalar spectral index nS(k0= 0.04 Mpc−1) = 0.94 ± 0.04 in accordance with WMAP studie

From the production of primordial perturbations to the end of inflation

In addition to generating the appropriate perturbation power spectrum, an inflationary scenario must take into account the need for inflation to end subsequently. In the context of single-field inflation models where inflation ends by breaking of the slow-roll condition, we constrain the first and second derivatives of the inflaton potential using this additional requirement. We compare this with current observational constraints from the primordial spectrum and discuss several issues relating to our results.Comment: RevTex4, 6 pages, 7 figures. To match version accepted by PR

Analysis of Hardware Accelerated Deep Learning and the Effects of Degradation on Performance

As convolutional neural networks become more prevalent in research and real world applications, the need for them to be faster and more robust will be a constant battle. This thesis investigates the effect of degradation being introduced to an image prior to object recognition with a convolutional neural network. As well as experimenting with methods to reduce the degradation and improve performance. Gaussian smoothing and additive Gaussian noise are both analyzed degradation models within this thesis and are reduced with Gaussian and Butterworth masks using unsharp masking and smoothing, respectively. The results show that each degradation is disruptive to the performance of YOLOv3, with Gaussian smoothing producing a mean average precision of less than 20% and Gaussian noise producing a mean average precision as low as 0%. Reduction methods applied to the data give results of 1%-21% mean average precision increase over the baseline, varying based on the degradation model. These methods are also applied to an 8-bit quantized implementation of YOLOv3, which is intended to run on a Xilinx ZCU104 FPGA, which showed to be as robust as the oating point network, with results within 2% mean average precision of the oating point network. With the ZCU104 being able to process images of 416x416 at 25 frames per second which is comparable to a NVIDIA 2080 RTX, FPGAs are a viable solution to computing object detection on the edge. In conclusion, this thesis shows that degradation causes performance of a convolutional neural network (quantized and oating point) to lose accuracy to a level that the network is unable to accurately predict objects. However, the degradation can be reduced, and in most cases can elevate the performance of the network by using computer vision techniques to reduce the noise within the image

Dear Wife : the Civil War letters of Chester K. Leach

Occasional paper (University of Vermont. Center for Research on Vermont) ; no. 20

The WMAP normalization of inflationary cosmologies

We use the three-year WMAP observations to determine the normalization of the matter power spectrum in inflationary cosmologies. In this context, the quantity of interest is not the normalization marginalized over all parameters, but rather the normalization as a function of the inflationary parameters n and r with marginalization over the remaining cosmological parameters. We compute this normalization and provide an accurate fitting function. The statistical uncertainty in the normalization is 3 percent, roughly half that achieved by COBE. We use the k-l relation for the standard cosmological model to identify the pivot scale for the WMAP normalization. We also quote the inflationary energy scale corresponding to the WMAP normalization.Comment: 4 pages RevTex4 with two figure

Effect of ethanol and iso-octane blends on isolated low-temperature heat release in a spark ignition engine

Low-temperature heat release (LTHR) is of interest for its potential to help control autoignition in advanced compression ignition (ACI) engines and mitigate knock in spark ignition (SI) engines. Previous studies have identified and investigated LTHR in both ACI and SI engines before the main high-temperature heat release (HTHR) event and, more recently, LTHR in isolation has been demonstrated in SI engines by appropriately curating the in-cylinder thermal state during compression and disabling the spark discharge. Ethanol is an increasingly common component of market fuel blends, owing to its renewable sources. In this work, the effect of adding ethanol to iso-octane (2,2,4-trimethylpentane) blends on their LTHR behavior is demonstrated. Tests were run on a motored single-cylinder engine elevated inlet air temperatures and pressures were adjusted to realize LTHR from blends of iso-octane and ethanol without entering the HTHR regime. The blends were tested with inlet temperatures of 40°C–140°C at equivalence ratios of 0.5, 0.67, and 1.0 with boosted (1.5 barA) conditions. The measured LTHR decreased with increasing ethanol content for all conditions tested; iso-octane–ethanol blends with above 20% ethanol content (by volume) showed minimal LTHR under engine conditions. These net effects resulted from the combination of thermal effects (charge cooling) and chemical effects (reactivity changes at low temperatures). The effect of temperature, pressure, fuel composition, and equivalence ratio on ignition delay times calculated from chemical kinetic modeling are presented alongside pressure–temperature trajectories of the in-cylinder gases to explain the trends. The underlying cause of the trends is explained by using a sensitivity analysis to determine the contribution of each reaction within the chemical kinetic mechanism to first-stage ignition, revealing the effect of introducing ethanol on the OH radical pool and resulting LTHR intensity

Low temperature heat release and ϕ-sensitivity characteristics of iso-octane/air mixtures

Chemical energy release from high octane number fuels via low temperature heat release (LTHR) can help develop high-efficiency gasoline engines by promoting ultra-lean combustion in spark ignition engines and improving combustion control in gasoline compression ignition engines. A recently developed experimental technique that permits isolated LTHR investigations in motored engines was used to characterize the LTHR behavior of iso-octane/air mixtures ranging in strength from ϕ≈0.02 to 1.6 at multiple inlet temperature conditions (60 to 120°C). LTHR changes were studied by observing variations in exhaust CO emissions and exhaust temperature increase. Observed heat release results were explained using cylinder mixture pressure-temperature histories alongside supporting chemical kinetics modeling estimates of mixture reactivity in the form of chemical ignition delay (ID) time. The effects of fuel enrichment on iso-octane/air mixture reactivity were found to be non-uniform and dependent on mixtures’ thermal state trajectories in the LTHR ID peninsula. LTHR intensity measurements were used to discuss changes in mixture ϕ−sensitivity at different engine inlet conditions. It was shown that by appropriately adjusting mixture thermal conditions via charge cooling from direct fuel injection and intake air heating, reactivity enhancements could be exploited maximally; and strong, positive, linear ϕ−sensitivity of around 10 J per 0.1 increase in ϕ could be realized across a wide range of equivalence ratios from 0.05–1.2. It was also found that dominance of charge cooling effects at rich conditions resulted in negative and zero ϕ−sensitivity regions

Constraining slow-roll inflation with WMAP and 2dF

We constrain slow-roll inflationary models using the recent WMAP data combined with data from the VSA, CBI, ACBAR and 2dF experiments. We find the slow-roll parameters to be $0 < \epsilon_1 < 0.032$ and $\epsilon_2 + 5.0 \epsilon_1 = 0.036 \pm 0.025$. For inflation models $V \propto \phi^{\alpha}$ we find that $\alpha< 3.9, 4.3$ at the 2$\sigma$ and $3\sigma$ levels, indicating that the $\lambda\phi^4$ model is under very strong pressure from observations. We define a convergence criterion to judge the necessity of introducing further power spectrum parameters such as the spectral index and running of the spectral index. This criterion is typically violated by models with large negative running that fit the data, indicating that the running cannot be reliably measured with present data.Comment: 8 pages RevTeX4 file with six figures incorporate