Suppression of Classical and Quantum Radiation Pressure Noise via Electro-Optic Feedback

We present theoretical results that demonstrate a new technique to be used to improve the sensitivity of thermal noise measurements: intra-cavity intensity stabilisation. It is demonstrated that electro-optic feedback can be used to reduce intra-cavity intensity fluctuations, and the consequent radiation pressure fluctuations, by a factor of two below the quantum noise limit. We show that this is achievable in the presence of large classical intensity fluctuations on the incident laser beam. The benefits of this scheme are a consequence of the sub-Poissonian intensity statistics of the field inside a feedback loop, and the quantum non-demolition nature of radiation pressure noise as a readout system for the intra-cavity intensity fluctuations.Comment: 4 pages, 1 figur

Multilevel convergence analysis of multigrid-reduction-in-time

This paper presents a multilevel convergence framework for multigrid-reduction-in-time (MGRIT) as a generalization of previous two-grid estimates. The framework provides a priori upper bounds on the convergence of MGRIT V- and F-cycles, with different relaxation schemes, by deriving the respective residual and error propagation operators. The residual and error operators are functions of the time stepping operator, analyzed directly and bounded in norm, both numerically and analytically. We present various upper bounds of different computational cost and varying sharpness. These upper bounds are complemented by proposing analytic formulae for the approximate convergence factor of V-cycle algorithms that take the number of fine grid time points, the temporal coarsening factors, and the eigenvalues of the time stepping operator as parameters. The paper concludes with supporting numerical investigations of parabolic (anisotropic diffusion) and hyperbolic (wave equation) model problems. We assess the sharpness of the bounds and the quality of the approximate convergence factors. Observations from these numerical investigations demonstrate the value of the proposed multilevel convergence framework for estimating MGRIT convergence a priori and for the design of a convergent algorithm. We further highlight that observations in the literature are captured by the theory, including that two-level Parareal and multilevel MGRIT with F-relaxation do not yield scalable algorithms and the benefit of a stronger relaxation scheme. An important observation is that with increasing numbers of levels MGRIT convergence deteriorates for the hyperbolic model problem, while constant convergence factors can be achieved for the diffusion equation. The theory also indicates that L-stable Runge-Kutta schemes are more amendable to multilevel parallel-in-time integration with MGRIT than A-stable Runge-Kutta schemes.Comment: 26 pages; 17 pages Supplementary Material

ISO 15859 Propellant and Fluid Specifications: A Review and Comparison with Military and NASA Specifications

This work presents an overview of the International Organization for Standardization (ISO) 15859 International Standard for Space Systems Fluid Characteristics, Sampling and Test Methods Parts 1 through 13 issued in June 2004. These standards establish requirements for fluid characteristics, sampling, and test methods for 13 fluids of concern to the propellant community and propellant characterization laboratories: oxygen, hydrogen, nitrogen, helium, nitrogen tetroxide, monomethylhydrazine, hydrazine, kerosene, argon, water, ammonia, carbon dioxide, and breathing air. A comparison of the fluid characteristics, sampling, and test methods required by the ISO standards to the current military and NASA specifications, which are in use at NASA facilities and elsewhere, is presented. Many ISO standards composition limits and other content agree with those found in the applicable parts of NASA SE-S-0073, NASA SSP 30573, military performance standards and details, and Compressed Gas Association (CGA) commodity specifications. The status of a current project managed at NASA Johnson Space Center White Sands Test Facility (WSTF) to rewrite these documents is discussed

Implicit Decomposition for Write-Efficient Connectivity Algorithms

The future of main memory appears to lie in the direction of new technologies that provide strong capacity-to-performance ratios, but have write operations that are much more expensive than reads in terms of latency, bandwidth, and energy. Motivated by this trend, we propose sequential and parallel algorithms to solve graph connectivity problems using significantly fewer writes than conventional algorithms. Our primary algorithmic tool is the construction of an $o(n)$-sized "implicit decomposition" of a bounded-degree graph $G$ on $n$ nodes, which combined with read-only access to $G$ enables fast answers to connectivity and biconnectivity queries on $G$. The construction breaks the linear-write "barrier", resulting in costs that are asymptotically lower than conventional algorithms while adding only a modest cost to querying time. For general non-sparse graphs on $m$ edges, we also provide the first $o(m)$ writes and $O(m)$ operations parallel algorithms for connectivity and biconnectivity. These algorithms provide insight into how applications can efficiently process computations on large graphs in systems with read-write asymmetry

A Cost-based Optimizer for Gradient Descent Optimization

As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a specific form. Furthermore, these optimization problems can be efficiently solved using variations of the gradient descent (GD) algorithm. Thus, to decouple a user specification of an ML task from its execution, a key component is a GD optimizer. We propose a cost-based GD optimizer that selects the best GD plan for a given ML task. To build our optimizer, we introduce a set of abstract operators for expressing GD algorithms and propose a novel approach to estimate the number of iterations a GD algorithm requires to converge. Extensive experiments on real and synthetic datasets show that our optimizer not only chooses the best GD plan but also allows for optimizations that achieve orders of magnitude performance speed-up.Comment: Accepted at SIGMOD 201

Spatiotemporal effects of logging and fire on tall, wet temperate eucalypt forest birds

Forests globally are subject to disturbances such as logging and fire that create complex temporal variation in spatial patterns of forest cover and stand age. However, investigations that quantify temporal changes in biodiversity in response to multiple forms of disturbance in space and time are relatively uncommon. Over a 10-yr period, we investigated the response of bird species to spatiotemporal changes in forest cover associated with logging and wildfire in the mountain ash (Eucalyptus regnans) forests of southeastern Australia. Specifically, we examined how bird occurrence changed with shifts in the proportion of area burned or logged in a 4.5 km radius surrounding our 88 long-term field survey sites, each measuring 1 ha in size. Overall species richness was greatest in older forest patches, but declined as the amount of fire around each site increased. At the individual species level, 31 of the 37 bird species we modeled exhibited a negative response to the amount of fire in the surrounding landscape, while one species responded positively to fire. Only nine species exhibited signs of recovery in the 6 yr of surveys following the fire. Five species were more likely to be detected as the proportion of logged forest surrounding a site increased, suggesting a possible "concentration effect" with displaced birds moving into unlogged areas following harvesting of adjacent areas. We also identified relationships between the coefficients of life history attributes and spatiotemporal changes in forest cover and stand age. Large-bodied birds and migratory species were associated with landscapes subject to large amounts of fire in 2009. There were associations between old growth stands and small-bodied bird species and species that were not insectivores. Our study shows that birds in mountain ash forests are strongly associated with old growth stands and exhibit complex, time-dependent, and species-specific responses to landscape disturbance. Despite logging and fire both being high-severity perturbations, no bird species exhibited similar responses to fire and logging in the landscape surrounding our sites. Thus, species responses to one kind of landscape-scale disturbance are not readily predictable based on an understanding of the responses to another kind of (albeit superficially similar) disturbance.Threatened Species Recovery Hub of the National Environmental Science Program, Parks Victoria, and Victorian Government Department of Environment, Land, Water and Plannin

Energetics as a lens to understanding aquatic insect's responses to changing temperature, dissolved oxygen and salinity regimes

Contains fulltext : 225050.pdf (publisher's version ) (Open Access)8 p

Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis

Diagnosis and prognosis of cancer is informed by the architecture inherent in cancer patient tissue sections. This architecture is typically identified by pathologists, yet advances in computational image analysis facilitate quantitative assessment of this structure. In this article we develop a spatial point process approach in order to describe patterns in cell distribution within tissue samples taken from colorectal cancer (CRC) patients. In particular, our approach is centered on the Palm intensity function. This leads to taking an approximate-likelihood technique in fitting point processes models. We consider two Neyman-Scott point processes and a void process, fitting these point process models to the CRC patient data. We find that the parameter estimates of these models may be used to quantify the spatial arrangement of cells. Importantly, we observe characteristic differences in the spatial arrangement of cells between patients who died from CRC and those alive at follow-up