Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSemialgebraic Invariant Synthesis for the Kannan-Lipton Orbit Problem
85
0
0.0
(
0
)
Added by
Amaury Pouly
Publication date
2017
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
The emph{Orbit Problem} consists of determining, given a linear transformation $A$ on $mathbb{Q}^d$, together with vectors $x$ and $y$, whether the orbit of $x$ under repeated applications of $A$ can ever reach $y$. This problem was famously shown to be decidable by Kannan and Lipton in the 1980s. In this paper, we are concerned with the problem of synthesising suitable emph{invariants} $mathcal{P} subseteq mathbb{R}^d$, emph{i.e.}, sets that are stable under $A$ and contain $x$ and not $y$, thereby providing compact and versatile certificates of non-reachability. We show that whether a given instance of the Orbit Problem admits a semialgebraic invariant is decidable, and moreover in positive instances we provide an algorithm to synthesise suitable invariants of polynomial size. It is worth noting that the existence of emph{semilinear} invariants, on the other hand, is (to the best of our knowledge) not known to be decidable.
rate research
Read More
The Semialgebraic Orbit Problem is a fundamental reachability question that arises in the analysis of discrete-time linear dynamical systems such as automata, Markov chains, recurrence sequences, and linear while loops. An instance of the problem comprises a dimension $dinmathbb{N}$, a square matrix $Ainmathbb{Q}^{dtimes d}$, and semialgebraic source and target sets $S,Tsubseteq mathbb{R}^d$. The question is whether there exists $xin S$ and $ninmathbb{N}$ such that $A^nx in T$. The main result of this paper is that the Semialgebraic Orbit Problem is decidable for dimension $dleq 3$. Our decision procedure relies on separation bounds for algebraic numbers as well as a classical result of transcendental number theory---Bakers theorem on linear forms in logarithms of algebraic numbers. We moreover argue that our main result represents a natural limit to what can be decided (with respect to reachability) about the orbit of a single matrix. On the one hand, semialgebraic sets are arguably the largest general class of subsets of $mathbb{R}^d$ for which membership is decidable. On the other hand, previous work has shown that in dimension $d=4$, giving a decision procedure for the special case of the Orbit Problem with singleton source set $S$ and polytope target set $T$ would entail major breakthroughs in Diophantine approximation.
For Boolean satisfiability problems, the structure of the solution space is characterized by the solution graph, where the vertices are the solutions, and two solutions are connected iff they differ in exactly one variable. In 2006, Gopalan et al. studied connectivity properties of the solution graph and related complexity issues for CSPs, motivated mainly by research on satisfiability algorithms and the satisfiability threshold. They proved dichotomies for the diameter of connected components and for the complexity of the st-connectivity question, and conjectured a trichotomy for the connectivity question. Recently, we were able to establish the trichotomy [arXiv:1312.4524]. Here, we consider connectivity issues of satisfiability problems defined by Boolean circuits and propositional formulas that use gates, resp. connectives, from a fixed set of Boolean functions. We obtain dichotomies for the diameter and the two connectivity problems: on one side, the diameter is linear in the number of variables, and both problems are in P, while on the other side, the diameter can be exponential, and the problems are PSPACE-complete. For partially quantified formulas, we show an analogous dichotomy.
Limits on the number of satisfying assignments for CNS instances with n variables and m clauses are derived from various inequalities. Some bounds can be calculated in polynomial time, sharper bounds demand information about the distribution of the number of unsatisfied clauses. Quite generally, the number of satisfying assignments involve variance and mean of this distribution. For large formulae, m>>1, bounds vary with 2**n/n, so they may be of use only for instances with a large number of satisfying assignments.
We reflect on programming with complicated effects, recalling an undeservingly forgotten alternative to monadic programming and checking to see how well it can actually work in modern functional languages. We adopt and argue the position of factoring an effectful program into a first-order effectful DSL with a rich, higher-order macro system. Not all programs can be thus factored. Although the approach is not general-purpose, it does admit interesting programs. The effectful DSL is likewise rather problem-specific and lacks general-purpose monadic composition, or even functions. On the upside, it expresses the problem elegantly, is simple to implement and reason about, and lends itself to non-standard interpretations such as code generation (compilation) and abstract interpretation. A specialized DSL is liable to be frequently extended; the experience with the tagless-final style of DSL embedding shown that the DSL evolution can be made painless, with the maximum code reuse. We illustrate the argument on a simple but representative example of a rather complicated effect -- non-determinism, including committed choice. Unexpectedly, it turns out we can write interesting non-deterministic programs in an ML-like language just as naturally and elegantly as in the functional-logic language Curry -- and not only run them but also statically analyze, optimize and compile. The richness of the Meta Language does, in reality, compensate for the simplicity of the effectful DSL. The key idea goes back to the origins of ML as the Meta Language for the Edinburgh LCF theorem prover. Instead of using ML to build theorems, we now build (DSL) programs.
It is well known that the containment problem (as well as the equivalence problem) for semilinear sets is $log$-complete in $Pi_2^p$. It had been shown quite recently that already the containment problem for multi-dimensional linear sets is $log$-complete in $Pi_2^p$ (where hardness even holds for a unary encoding of the numerical input parameters). In this paper, we show that already the containment problem for $1$-dimensional linear sets (with binary encoding of the numerical input parameters) is $log$-hard (and therefore also $log$-complete) in $Pi_2^p$. However, combining both restrictions (dimension $1$ and unary encoding), the problem becomes solvable in polynomial time.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
