Deciding the consistency of non-linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings

We present a new algorithm for determining the satisfiability of conjunctions of non-linear polynomial constraints over the reals, which can be used as a theory solver for satisfiability modulo theory (SMT) solving for non-linear real arithmetic. The algorithm is a variant of Cylindrical Algebraic Decomposition (CAD) adapted for satisfiability, where solution candidates (sample points) are constructed incrementally, either until a satisfying sample is found or sufficient samples have been sampled to conclude unsatisfiability. The choice of samples is guided by the input constraints and previous conflicts. The key idea behind our new approach is to start with a partial sample; demonstrate that it cannot be extended to a full sample; and from the reasons for that rule out a larger space around the partial sample, which build up incrementally into a cylindrical algebraic covering of the space. There are similarities with the incremental variant of CAD, the NLSAT method of Jovanovic and de Moura, and the NuCAD algorithm of Brown; but we present worked examples and experimental results on a preliminary implementation to demonstrate the differences to these, and the benefits of the new approach

Satisfiability Modulo Finite Fields

We study satisfiability modulo the theory of finite fields and give a decision procedure for this theory. We implement our procedure for prime fields inside the cvc5 SMT solver. Using this theory, we con- struct SMT queries that encode translation validation for various zero knowledge proof compilers applied to Boolean computations. We evalu- ate our procedure on these benchmarks. Our experiments show that our implementation is superior to previous approaches (which encode field arithmetic using integers or bit-vectors)

Secretome Analysis of Mesenchymal Stem Cell Factors Fostering Oligodendroglial Differentiation of Neural Stem Cells In Vivo

Mesenchymal stem cell (MSC)-secreted factors have been shown to significantly promote oligodendrogenesis from cultured primary adult neural stem cells (aNSCs) and oligodendroglial precursor cells (OPCs). Revealing underlying mechanisms of how aNSCs can be fostered to differentiate into a specific cell lineage could provide important insights for the establishment of novel neuroregenerative treatment approaches aiming at myelin repair. However, the nature of MSC-derived differentiation and maturation factors acting on the oligodendroglial lineage has not been identified thus far. In addition to missing information on active ingredients, the degree to which MSC-dependent lineage instruction is functional in vivo also remains to be established. We here demonstrate that MSC-derived factors can indeed stimulate oligodendrogenesis and myelin sheath generation of aNSCs transplanted into different rodent central nervous system (CNS) regions, and furthermore, we provide insights into the underlying mechanism on the basis of a comparative mass spectrometry secretome analysis. We identified a number of secreted proteins known to act on oligodendroglia lineage differentiation. Among them, the tissue inhibitor of metalloproteinase type 1 (TIMP-1) was revealed to be an active component of the MSC-conditioned medium, thus validating our chosen secretome approach

Cylindrical algebraic decomposition for nonlinear arithmetic problems

Satisfiability modulo theories solving is a technology to solve logically encoded problems for many applications like verification, testing, or planning. Among the many theories that are considered within this logical framework, nonlinear real arithmetic stands out as particularly challenging, yet decidable and sufficiently well understood from a mathematical perspective. The most prominent approach that can decide upon nonlinear real questions in a complete way is the cylindrical algebraic decomposition method. We explore the usage of the cylindrical algebraic decomposition method for satisfiability modulo theories solving, both theoretically and experimentally. This method is commonly understood as an almost atomic procedure that gathers information about an algebraic problem and then allows to answer all kinds of questions about this algebraic problem afterward. We essentially break up this method into smaller components that we can then process in varying order to derive the particular piece of information - whether the problem is satisfiable or unsatisfiable - allowing to avoid some amount of computations. As this method often exhibits doubly exponential running time, these savings can be very significant in practice. We furthermore embed this method in the regular satisfiability modulo theories framework where the cylindrical algebraic method is faced with a sequence of problems that are “related” in the sense that they usually share large parts of their problem statements. We devise different approaches to retain information from a previous run so that it can be reused when the problem is only “extended” as well as purging now obsolete information if the problem is “reduced”. These variants change in how much information can be reused, the granularity of the information that is removed, and how much bookkeeping needs to be done. This integration is then enhanced with techniques that are more or less well-known in the computer algebra community, for example, different projection operators, equational constraints, or employing the so-called resultant rule. Furthermore, we present novel features necessary for an efficient embedding in the satisfiability modulo theories frame-work like infeasible subset computations and early termination as well as extensions to integer problems and optimization problems. We then turn to an alternative approach to satisfiability modulo theories solving that is commonly called model-constructing satisfiability calculus. The core idea of this framework is to integrate the theory reasoning, in particular the construction of a theory model, tightly with the Boolean reasoning. The most popular theory reasoning engine is again based on the cylindrical algebraic decomposition method, though we focus on the overall framework here. We start with our own variant of the model-constructing satisfiability calculus and discuss some general insights and changes compared to current implementations. We then proceed to present a whole series of reasoning engines for arithmetic problems and show how a proper (though still naive) combination of those serves to significantly improve a practical solver. We also show how the tight integration into the Boolean reasoning allows for novel strategies for notoriously hard problems like the theory variable ordering or expedient cooperation between the Boolean and the theory reasoning. Finally, we consider the theoretical relation of the model-constructing satisfiability calculus to other proof systems, in particular, the aforementioned regular satisfiability modulo theories solving. Under certain assumptions - that turn out to be instructive in and of themselves - we show that they are equivalent with respect to their proof complexity and even establish what we call “algorithmic equivalency” afterward