Certified Roundoff Error Bounds Using Semidefinite Programming.

Roundoff errors cannot be avoided when implementing numerical programs with finite precision. The ability to reason about rounding is especially important if one wants to explore a range of potential representations, for instance for FPGAs or custom hardware implementation. This problem becomes challenging when the program does not employ solely linear operations as non-linearities are inherent to many interesting computational problems in real-world applications. Existing solutions to reasoning are limited in the presence of nonlinear correlations between variables, leading to either imprecise bounds or high analysis time. Furthermore, while it is easy to implement a straightforward method such as interval arithmetic, sophisticated techniques are less straightforward to implement in a formal setting. Thus there is a need for methods which output certificates that can be formally validated inside a proof assistant. We present a framework to provide upper bounds on absolute roundoff errors. This framework is based on optimization techniques employing semidefinite programming and sums of squares certificates, which can be formally checked inside the Coq theorem prover. Our tool covers a wide range of nonlinear programs, including polynomials and transcendental operations as well as conditional statements. We illustrate the efficiency and precision of this tool on non-trivial programs coming from biology, optimization and space control. Our tool produces more precise error bounds for 37 percent of all programs and yields better performance in 73 percent of all programs

Semidefinite approximations of projections and polynomial images of semialgebraic sets

Given a compact semialgebraic set S of R^n and a polynomial map f from R^n to R^m, we consider the problem of approximating the image set F = f(S) in R^m. This includes in particular the projection of S on R^m for n greater than m. Assuming that F is included in a set B which is simple (e.g. a box or a ball), we provide two methods to compute certified outer approximations of F. Method 1 exploits the fact that F can be defined with an existential quantifier, while Method 2 computes approximations of the support of image measures.The two methods output a sequence of superlevel sets defined with a single polynomial that yield explicit outer approximations of F. Finding the coefficients of this polynomial boils down to computing an optimal solution of a convex semidefinite program. We provide guarantees of strong convergence to F in L^1 norm on B, when the degree of the polynomial approximation tends to infinity. Several examples of applications are provided, together with numerical experiments

Satisfiability Modulo Transcendental Functions via Incremental Linearization

In this paper we present an abstraction-refinement approach to Satisfiability Modulo the theory of transcendental functions, such as exponentiation and trigonometric functions. The transcendental functions are represented as uninterpreted in the abstract space, which is described in terms of the combined theory of linear arithmetic on the rationals with uninterpreted functions, and are incrementally axiomatized by means of upper- and lower-bounding piecewise-linear functions. Suitable numerical techniques are used to ensure that the abstractions of the transcendental functions are sound even in presence of irrationals. Our experimental evaluation on benchmarks from verification and mathematics demonstrates the potential of our approach, showing that it compares favorably with delta-satisfiability /interval propagation and methods based on theorem proving

Local human impacts disrupt relationships between benthic reef assemblages and environmental predictors

Human activities are changing ecosystems at an unprecedented rate, yet large-scale studies into how local human impacts alter natural systems and interact with other aspects of global change are still lacking. Here we provide empirical evidence that local human impacts fundamentally alter relationships between ecological communities and environmental drivers. Using tropical coral reefs as a study system, we investigated the influence of contrasting levels of local human impact using a spatially extensive dataset spanning 62 outer reefs around inhabited Pacific islands. We tested how local human impacts (low versus high determined using a threshold of 25 people km−2 reef) affected benthic community (i) structure, and (ii) relationships with environmental predictors using pre-defined models and model selection tools. Data on reef depth, benthic assemblages, and herbivorous fish communities were collected from field surveys. Additional data on thermal stress, storm exposure, and market gravity (a function of human population size and reef accessibility) were extracted from public repositories. Findings revealed that reefs subject to high local human impact were characterised by relatively more turf algae (>10% higher mean absolute coverage) and lower live coral cover (9% less mean absolute coverage) than reefs subject to low local human impact, but had similar macroalgal cover and coral morphological composition. Models based on spatio-physical predictors were significantly more accurate in explaining the variation of benthic assemblages at sites with low (mean adjusted-R2 = 0.35) rather than high local human impact, where relationships became much weaker (mean adjusted-R2 = 0.10). Model selection procedures also identified a distinct shift in the relative importance of different herbivorous fish functional groups in explaining benthic communities depending on the local human impact level. These results demonstrate that local human impacts alter natural systems and indicate that projecting climate change impacts may be particularly challenging at reefs close to higher human populations, where dependency and pressure on ecosystem services are highest

A formal proof of the Kepler conjecture

This article describes a formal proof of the Kepler conjecture on dense sphere packings in a combination of the HOL Light and Isabelle proof assistants. This paper constitutes the official published account of the now completed Flyspeck project

Beta decay of the Tz=-2 nucleus 64Se and its descendants

International audience; The beta decay of the Tz=-2 nucleus 64Se has been studied in a fragmentation reaction at RIKEN-Nishina Center. 64Se is the heavies Tz=-2 nucleus that decays to bound states in the daughter nucleus and the heaviest case where the mirror reaction 64Zn(3He,t)64Ga on the Tz=+2 64Zn stable target exists and can be compared. Beta-delayed gamma and proton radiation is reported for the 64Se and 64As cases. New levels have been observed in 64As, 64Ge (N=Z), 63Ge and 63Ga. The associated T1/2 values have been obtained

Certified roundoff error bounds using semidefinite programming

Roundoff errors cannot be avoided when implementing numerical programs with finite precision. The ability to reason about rounding is especially important if one wants to explore a range of potential representations, for instance, for FPGAs or custom hardware implementations. This problem becomes challenging when the program does not employ solely linear operations as non-linearities are inherent to many interesting computational problems in real-world applications. Existing solutions to reasoning possibly lead to either inaccurate bounds or high analysis time in the presence of nonlinear correlations between variables. Furthermore, while it is easy to implement a straightforward method such as interval arithmetic, sophisticated techniques are less straightforward to implement in a formal setting. Thus there is a need for methods that output certificates that can be formally validated inside a proof assistant. We present a framework to provide upper bounds on absolute roundoff errors of floating-point nonlinear programs. This framework is based on optimization techniques employing semidefinite programming and sums of squares certificates, which can be checked inside the Coq theorem prover to provide formal roundoff error bounds for polynomial programs. Our tool covers a wide range of nonlinear programs, including polynomials and transcendental operations as well as conditional statements. We illustrate the efficiency and precision of this tool on non-trivial programs coming from biology, optimization, and space control. Our tool produces more accurate error bounds for 23% of all programs and yields better performance in 66% of all programs

EXACT OPTIMIZATION VIA SUMS OF NONNEGATIVE CIRCUITS AND SUMS OF AM/GM EXPONENTIALS

International audienceWe provide two hybrid numeric-symbolic optimization algorithms, computing exact sums of nonnegative circuits (SONC) and sums of arithmetic-geometric-exponentials (SAGE) decompositions. Moreover, we provide a hybrid numeric-symbolic decision algorithm for polynomials lying in the interior of the SAGE cone. Each framework , inspired by previous contributions of Parrilo and Peyrl, is a rounding-projection procedure. For a polynomial lying in the interior of the SAGE cone, we prove that the decision algorithm terminates within a number of arithmetic operations, which is polynomial in the degree and number of terms of the input, and singly exponential in the number of variables. We also provide experimental comparisons regarding the implementation of the two optimization algorithms

Semidefinite Approximations of Reachable Sets for Discrete-time Polynomial Systems

International audienceWe consider the problem of approximating the reachable set of a discrete-time polynomial system from a semialgebraic set of initial conditions under general semi-algebraic set constraints. Assuming inclusion in a given simple set like a box or an ellipsoid, we provide a method to compute certified outer approximations of the reachable set. The proposed method consists of building a hierarchy of relaxations for an infinite-dimensional moment problem. Under certain assumptions, the optimal value of this problem is the volume of the reachable set and the optimum solution is the restriction of the Lebesgue measure on this set. Then, one can outer approximate the reachable set as closely as desired with a hierarchy of super level sets of increasing degree polynomials. For each fixed degree, finding the coefficients of the polynomial boils down to computing the optimal solution of a convex semidefinite program. When the degree of the polynomial approximation tends to infinity, we provide strong convergence guarantees of the super level sets to the reachable set. We also present some application examples together with numerical results

On Exact Polya and Putinar's Representations

19 pages, 4 algorithms, 3 tablesInternational audienceWe consider the problem of finding exact sums of squares (SOS) decompositions for certain classes of non-negative multivariate polynomials, relying on semidefinite programming (SDP) solvers. We start by providing a hybrid numeric-symbolic algorithm computing exact rational SOS decompositions for polynomials lying in the interior of the SOS cone. It computes an approximate SOS decomposition for a perturbation of the input polynomial with an arbitrary-precision SDP solver. An exact SOS decomposition is obtained thanks to the perturbation terms. We prove that bit complexity estimates on output size and runtime are both polynomial in the degree of the input polynomial and simply exponential in the number of variables. Next, we apply this algorithm to compute exact Polya and Putinar's representations respectively for positive definite forms and positive polynomials over basic compact semi-algebraic sets. We also compare the implementation of our algorithms with existing methods in computer algebra including cylindrical algebraic decomposition and critical point method