Michael A. Burr

An intuitive approach to measuring protein surface curvature.

A natural way to measure protein surface curvature is to generate the least squares fitted (LSF) sphere to a surface patch and use the radius as the curvature measure. While the concept is simple, the sphere‐fitting problem is not trivial and known means of protein surface curvature measurement use alternative schemes that are arguably less straightforward to interpret. We have developed an approach to solve the LSF sphere problem by turning the sphere‐fitting problem into a solvable plane‐fitting problem using a transformation known as geometric inversion. The approach works on any arbitrary surface patch, and returns a radius of curvature that has direct physical interpretation. Additionally, it is flexible in its ability to find the curvature of an arbitrary surface patch, and the “resolution” can be adjusted to highlight atomic features or larger features such as peptide binding sites. We include examples of applying the method to visualization of peptide recognition pockets and protein conformational change, as well as a comparison with a commonly used solid‐angle curvature method showing that the LSF method produces more pronounced curvature results. Proteins 2005.

SqFreeEVAL: An (almost) optimal real-root isolation algorithm

Let f be a univariate polynomial with real coefficients, f@?R[X]. Subdivision algorithms based on algebraic techniques (e.g., Sturm or Descartes methods) are widely used for isolating the real roots of f in a given interval. In this paper, we consider a simple subdivision algorithm whose primitives are purely numerical (e.g., function evaluation). The complexity of this algorithm is adaptive because the algorithm makes decisions based on local data. The complexity analysis of adaptive algorithms (and this algorithm in particular) is a new challenge for computer science. In this paper, we compute the size of the subdivision tree for the SqFreeEVAL algorithm. The SqFreeEVAL algorithm is an evaluation-based numerical algorithm which is well-known in several communities. The algorithm itself is simple, but prior attempts to compute its complexity have proven to be quite technical and have yielded sub-optimal results. Our main result is a simple O(d(L+lnd)) bound on the size of the subdivision tree for the SqFreeEVAL algorithm on the benchmark problem of isolating all real roots of an integer polynomial f of degree d and whose coefficients can be written with at most L bits. Our proof uses two amortization-based techniques: first, we use the algebraic amortization technique of the standard Mahler-Davenport root bounds to interpret the integral in terms of d and L. Second, we use a continuous amortization technique based on an integral to bound the size of the subdivision tree. This paper is the first to use the novel analysis technique of continuous amortization to derive state of the art complexity bounds.

Continuous amortization and extensions

Subdivision-based algorithms recursively subdivide an input region until the smaller subregions can be processed. It is a challenge to analyze the complexity of such algorithms because the work they perform is not uniform across the input region. Continuous amortization was introduced in Burr et al. (2009) as a way to bound the complexity of subdivision-based algorithms. The main features of this new technique are that (1) the technique can be applied, uniformly, to a variety of subdivision-based algorithms, (2) the technique considers a function directly related to the subdivision-based algorithm under consideration, and (3) the output of the technique is often explicitly expressed in terms of the intrinsic complexity of the problem instance.In this paper, the theory of continuous amortization is generalized and applied in several directions. The theory is generalized (1) to allow the domain to be higher dimensional or an abstract measure space, (2) to allow more general subdivisions than bisections, and (3) to bound the value of general functions on the regions of the final partition. The theory is applied to seven examples of subdivision-based algorithms. These applications include (1) bounding the number of subdivisions performed by algorithms for isolating real and complex roots of polynomials, (2) bounding the bit-complexity of subdivision-based algorithms for isolating the real roots of polynomials, and (3) bounding the expected run-time of an algorithm for approximating a biased coin. In each of these applications, by using continuous amortization, we achieve or improve the best-known complexity bounds.

The Complexity of an Adaptive Subdivision Method for Approximating Real Curves

We present the first complexity analysis of the algorithm by Plantinga and Vegter for approximating real implicit curves and surfaces. This approximation algorithm certifies the topological correctness of the output using both subdivision and interval arithmetic. In practice, it has been seen to be quite efficient; our goal is to quantify this efficiency. We focus on the subdivision step (and not the approximation step) of the Plantinga and Vegter algorithm. We begin by extending the subdivision step to arbitrary dimensions. We provide a priori worst-case bounds on the complexity of this algorithm both in terms of the number of subregions constructed and the bit complexity for the construction. Then, we use continuous amortization to derive adaptive bounds on the complexity of the subdivided region. We also provide examples showing our bounds are tight.

An Approach for Certifying Homotopy Continuation Paths: Univariate Case

Homotopy continuation is a well-known method in numerical root-finding. Recently, certified algorithms for homotopy continuation based on Smales alpha-theory have been developed. This approach enforces very strong requirements at each step, leading to small step sizes. In this paper, we propose an approach that is independent of alpha-theory. It is based on the weaker notion of well-isolated approximations to the roots. We apply it to univariate polynomials and provide experimental evidence of its feasibility.