Deep near-infrared spectroscopy of high-redshift galaxies: the physical growth of passive systems

The assembly history of massive galaxies is one of the most important aspects of galaxy formation and evolution. Although we have a broad idea of what physical processes govern the early phases of galaxy evolution, there are still many open questions. In this thesis I demonstrate the crucial role that spectroscopy can play in a physical understanding of galaxy evolution. I present deep near-infrared spectroscopy for a sample of high-redshift galaxies, from which I derive important physical properties and their evolution with cosmic time. I take advantage of the recent arrival of efficient near-infrared detectors to target the rest-frame optical spectra of z > 1 galaxies, from which many physical quantities can be derived. After illustrating the applications of near-infrared deep spectroscopy with a study of star-forming galaxies, I focus on the evolution of massive quiescent systems.

Most of this thesis is based on two samples collected at the W. M. Keck Observatory that represent a significant step forward in the spectroscopic study of z > 1 quiescent galaxies. All previous spectroscopic samples at this redshift were either limited to a few objects, or much shallower in terms of depth. Our first sample is composed of 56 quiescent galaxies at 1 < z < 1.6 collected using the upgraded red arm of the Low Resolution Imaging Spectrometer (LRIS). The second consists of 24 deep spectra of 1.5 < z < 2.5 quiescent objects observed with the Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE). Together, these spectra span the critical epoch 1 < z < 2.5, where most of the red sequence is formed, and where the sizes of quiescent systems are observed to increase significantly.

We measure stellar velocity dispersions and dynamical masses for the largest number of z > 1 quiescent galaxies to date. By assuming that the velocity dispersion of a massive galaxy does not change throughout its lifetime, as suggested by theoretical studies, we match galaxies in the local universe with their high-redshift progenitors. This allows us to derive the physical growth in mass and size experienced by individual systems, which represents a substantial advance over photometric inferences based on the overall galaxy population. We find a significant physical growth among quiescent galaxies over 0 < z < 2.5 and, by comparing the slope of growth in the mass-size plane dlogR_e/dlogM_∗ with the results of numerical simulations, we can constrain the physical process responsible for the evolution. Our results show that the slope of growth becomes steeper at higher redshifts, yet is broadly consistent with minor mergers being the main process by which individual objects evolve in mass and size.

By fitting stellar population models to the observed spectroscopy and photometry we derive reliable ages and other stellar population properties. We show that the addition of the spectroscopic data helps break the degeneracy between age and dust extinction, and yields significantly more robust results compared to fitting models to the photometry alone. We detect a clear relation between size and age, where larger galaxies are younger. Therefore, over time the average size of the quiescent population will increase because of the contribution of large galaxies recently arrived to the red sequence. This effect, called progenitor bias, is different from the physical size growth discussed above, but represents another contribution to the observed difference between the typical sizes of low- and high-redshift quiescent galaxies. By reconstructing the evolution of the red sequence starting at z ∼ 1.25 and using our stellar population histories to infer the past behavior to z ∼ 2, we demonstrate that progenitor bias accounts for only half of the observed growth of the population. The remaining size evolution must be due to physical growth of individual systems, in agreement with our dynamical study.

Finally, we use the stellar population properties to explore the earliest periods which led to the formation of massive quiescent galaxies. We find tentative evidence for two channels of star formation quenching, which suggests the existence of two independent physical mechanisms. We also detect a mass downsizing, where more massive galaxies form at higher redshift, and then evolve passively. By analyzing in depth the star formation history of the brightest object at z > 2 in our sample, we are able to put constraints on the quenching timescale and on the properties of its progenitor.

A consistent picture emerges from our analyses: massive galaxies form at very early epochs, are quenched on short timescales, and then evolve passively. The evolution is passive in the sense that no new stars are formed, but significant mass and size growth is achieved by accreting smaller, gas-poor systems. At the same time the population of quiescent galaxies grows in number due to the quenching of larger star-forming galaxies. This picture is in agreement with other observational studies, such as measurements of the merger rate and analyses of galaxy evolution at fixed number density.

Digital Quantum Rabi and Dicke Models in Superconducting Circuits

We propose the analog-digital quantum simulation of the quantum Rabi and Dicke models using circuit quantum electrodynamics (QED). We find that all physical regimes, in particular those which are impossible to realize in typical cavity QED setups, can be simulated via unitary decomposition into digital steps. Furthermore, we show the emergence of the Dirac equation dynamics from the quantum Rabi model when the mode frequency vanishes. Finally, we analyze the feasibility of this proposal under realistic superconducting circuit scenarios.

Life-stage recruitment models for Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) on Georges Bank

Ichthyoplankton surveys have been used to provide an independent estimate of adult spawning biomass of commercially exploited species and to further our understanding of the recruitment processes in the early life stages. However, predicting recruitment has been difficult because of the complex interaction of physical and biological processes operating at different spatial and temporal scales that can occur at the different life stages. A model of first-year life-stage recruitment was applied to Georges Bank Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) stocks over the years 1977–2004 by using environmental and densitydependent relationships. The best lifestage mortality relationships for eggs, larvae, pelagic juveniles, and demersal juveniles were first determined by hindcasting recruitment estimates based on egg and larval abundance and mortality rates derived from two intensive sampling periods, 1977–87 and 1995–99. A wind-driven egg mortality relationship was used to estimate losses due to transport off the bank, and a wind-stress larval mortality relationship was derived from feeding and survival studies. A simple metric for the density-dependent effects of Atlantic cod was used for both Atlantic cod and haddock. These life stage proxies were then applied to the virtual population analysis (VPA) derived annual egg abundances to predict age-1 recruitment. Best models were determined from the correlation of predicted and VPA-derived age-1 abundance. The larval stage was the most quantifiable of any stage from surveys, whereas abundance estimates of the demersal juvenile stage were not available because of undersampling. Attempts to forecast recruitment from spawning stock biomass or egg abundance, however, will always be poor because of variable egg survival.

Digital Quantum Simulation of Spin Models with Circuit Quantum Electrodynamics

Systems of interacting quantum spins show a rich spectrum of quantum phases and display interesting many-body dynamics. Computing characteristics of even small systems on conventional computers poses significant challenges. A quantum simulator has the potential to outperform standard computers in calculating the evolution of complex quantum systems. Here, we perform a digital quantum simulation of the paradigmatic Heisenberg and Ising interacting spin models using a two transmon-qubit circuit quantum electrodynamics setup. We make use of the exchange interaction naturally present in the simulator to construct a digital decomposition of the model-specific evolution and extract its full dynamics. This approach is universal and efficient, employing only resources that are polynomial in the number of spins, and indicates a path towards the controlled simulation of general spin dynamics in superconducting qubit platforms.

On the Stability and Equilibrium Points of Multistaged SI (n) R Epidemic Models

This paper relies on the concept of next generation matrix defined ad hoc for a new proposed extended SEIR model referred to as SI(n)R-model to study its stability. The model includes n successive stages of infectious subpopulations, each one acting at the exposed subpopulation of the next infectious stage in a cascade global disposal where each infectious population acts as the exposed subpopulation of the next infectious stage. The model also has internal delays which characterize the time intervals of the coupling of the susceptible dynamics with the infectious populations of the various cascade infectious stages. Since the susceptible subpopulation is common, and then unique, to all the infectious stages, its coupled dynamic action on each of those stages is modeled with an increasing delay as the infectious stage index increases from 1 to n. The physical interpretation of the model is that the dynamics of the disease exhibits different stages in which the infectivity and the mortality rates vary as the individual numbers go through the process of recovery, each stage with a characteristic average time.

Physical modelling of large area 4H-SiC PiN diodes

The recent developments in SiC PiN diode research mean that physics-based models that allow accurate, rapid prediction of switching and conduction performance and resulting converter losses will soon be required. This is especially the case given the potential for very high voltage converters to be used for enabling distributed and renewable power generation. In this work an electro-thermal compact model of a 4.5 kV silicon carbide PiN diode has been developed for converter loss modelling in Simulink. Good matching of reverse recovery has been achieved between 25 and 200 °C. The I-V characteristics of the P+ anode contact have been shown to be significant in obtaining good matching for the forward characteristics of the diode, requiring further modelling work in this area. © 2009 IEEE.

Physical and numerical modeling of horizontal gas-hydrate wells

Methane hydrate, which is usually found under deep seabed or permafrost zones, is a potential energy resource for future years. Depressurization of horizontalwells bored in methane hydrate layer is considered as one possible method for hydrate dissociation and methane extraction from the hosting soil. Since hydrate is likely to behave as a bonding material to sandy soils, supported well construction is necessary to avoid wellcollapse due to the loss of the apparent cohesion during depressurization. This paper describes both physical and numerical modeling of such horizontal support wells. The experimental part involves depressurization of small well models in a large pressure cell, while the numerical part simulates the corresponding problem. While the experiment models simulate only gas saturated initial conditions, the numerical analysis simulates both gas-saturated and more realistic water-saturated conditions based on effective stress coupled flow-deformation formulation of these three phases. © 2006 Taylor & Francis Group, London.

Perceptual thresholds for acoustical guitar models

Synthesised acoustic guitar sounds based on a detailed physical model are used to provide input for psychoacoustical testing. Thresholds of perception are found for changes in the main parameters of the model. Using a three-alternative forced-choice procedure, just-noticeable differences are presented for changes in frequency and damping of the modes of the guitar body, and also for changes in the tension, bending stiffness and damping parameters of the strings. These are compared with measured data on the range of variation of these parameters in a selection of guitars. © S. Hirzel Verlag © EAA.

Physical modelling of flexible retaining walls under seismic actions

A series of dynamic centrifuge tests on reduced scale models of flexible retaining structures were conducted on the Turner beam centrifuge at the Schofield Centre of the University of Cambridge. The paper illustrates the main results of the experimental work in terms of observed amplifications of ground motion and mobilised shear stiffness and damping ratio for all tests. The experimental results for one test on a pair of cantilevered walls in dense sand are also presented in terms of measured bending moments and horizontal displacements of the walls during (maximum values) and at the end of (residual values) each seismic event. Finally, the experimental data are discussed in the light of the results obtained from dynamic numerical analyses of the behaviour of cantilevered walls under real seismic actions. © 2010 Taylor & Francis Group, London.

Dynamic centrifuge tests on shallow tunnel models in dry sand

In the framework of the Italian research project ReLUIS-DPC, a set of centrifuge tests were carried out at the Schofield Centre in Cambridge (UK) to investigate the seismic behaviour of tunnels. Four samples of dry sand were prepared at different densities, in which a small scale model of circular tunnel was inserted, instrumented with gauges measuring hoop and bending strains. Arrays of accelerometers in the soil and on the box allowed the amplification of ground motion to be evaluated; LVDTs measured the soil surface settlement. This paper describes the main results of this research, showing among others the evolution of the internal forces during the model earthquakes at significant locations along the tunnel lining. © 2010 Taylor & Francis Group, London.

Use of automatic sand pourers for loose sand models

The consistency of laboratory sand model preparation for physical testing is a fundamental criterion in representing identical geotechnical issues at prototype scale. This objective led to the development of robotic apparatus to eliminate the non-uniformity in manual pouring. Previous studies have shown consistent sand models with high relative density between 50 to 90% produced by the automatic moving-hopper sand pourer at the University of Cambridge, based primarily on a linear correlation to flow rate. However, in the case of loose samples, the influence of other parameters, particularly the drop height, becomes more apparent. In this paper, findings on the effect of flow rate and drop height are discussed in relation to the layer thickness and relative density of loose sand samples. Design charts are presented to illustrate their relationships. The effect of these factors on different sand types is also covered to extend the use of the equipment. © 2010 Taylor & Francis Group, London.

Model based control for closed loop testing of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts and prediction of the resulting engine transient response. The latter often requires closed loop control over the model to ensure operation within physical limits and tracking of reference signals. For this purpose, a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). As an example this study is focused on the transient response of a light-duty car Diesel engine. For the cases examined the proposed controller implementation gives a more systematic procedure than other ad-hoc approaches that require considerable tuning effort. © 2012 IFAC.

Effects of the biodiesel fuel physical properties on the swirl stabilised spray combustion characteristics

An increasin g interest in biofuel applications in modern engines requires a better understanding of biodiesel combustion behaviour. Many numerical studies have been carried out on unsteady combustion of biodiesel in situations similar to diesel engines, but very few studies have been done on the steady combustion of biodiesel in situations similar to a gas turbine combustor environment. The study of biodiesel spray combustion in gas turbine applications is of special interest due to the possible use of biodiesel in the power generation and aviation industries. In modelling spray combustion, an accurate representation of the physical properties of the fuel is a first important step, since spray formation is largely influenced by fuel properties such as viscosity, density, surface tension and vapour pressure. In the present work, a calculated biodiesel properties database based on the measured composition of Fatty Acid Methyl Esters (FAME) has been implemented in a multi-dimensional Computational Fluid Dynamics (CFD) spray simulation code. Simulations of non-reacting and reacting atmospheric-pressure sprays of both diesel and biodiesel have been carried out using a spray burner configuration for which experimental data is available. A pre-defined droplet size probability density function (pdf) has been implemented together with droplet dynamics based on phase Doppler anemometry (PDA) measurements in the near-nozzle region. The gas phase boundary condition for the reacting spray cases is similar to that of the experiment which employs a plain air-blast atomiser and a straight-vane axial swirler for flame stabilisation. A reaction mechanism for heptane has been used to represent the chemistry for both diesel and biodiesel. Simulated flame heights, spray characteristics and gas phase velocities have been found to compare well with the experimental results. In the reacting spray cases, biodiesel shows a smaller mean droplet size compared to that of diesel at a constant fuel mass flow rate. A lack of sensitivity towards different fuel properties has been observed based on the non-reacting spray simulations, which indicates a need for improved models of secondary breakup. By comparing the results of the non-reacting and reacting spray simulations, an improvement in the complexity of the physical modelling is achieved which is necessary in the understanding of the complex physical processes involved in spray combustion simulation. Copyright © 2012 SAE International.