Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Series Preface * Preface to the Third Edition * 1 Linear Systems * 2 Nonlinear Systems: Local Theory * 3 Nonlinear Systems: Global Theory * 4 Nonlinear Systems: Bifurcation Theory * References * Index

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Differential Equations and Dynamical Systems

In this provocative book, Barwise and Perry tackle the slippery subject of \"meaning, \" a subject that has long vexed linguists, language philosophers, and logicians.

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Situations and Attitudes.

Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts of AI technologies on society. In this paper we discuss one such potential impact: the problem of accidents in machine learning systems, defined as unintended and harmful behavior that may emerge from poor design of real-world AI systems. We present a list of five practical research problems related to accident risk, categorized according to whether the problem originates from having the wrong objective function ("avoiding side effects" and "avoiding reward hacking"), an objective function that is too expensive to evaluate frequently ("scalable supervision"), or undesirable behavior during the learning process ("safe exploration" and "distributional shift"). We review previous work in these areas as well as suggesting research directions with a focus on relevance to cutting-edge AI systems. Finally, we consider the high-level question of how to think most productively about the safety of forward-looking applications of AI.

Concrete Problems in AI Safety

Deep neural networks have emerged as a widely used and effective means for tackling complex, real-world problems. However, a major obstacle in applying them to safety-critical systems is the great difficulty in providing formal guarantees about their behavior. We present a novel, scalable, and efficient technique for verifying properties of deep neural networks (or providing counter-examples). The technique is based on the simplex method, extended to handle the non-convex Rectified Linear Unit (ReLU) activation function, which is a crucial ingredient in many modern neural networks. The verification procedure tackles neural networks as a whole, without making any simplifying assumptions. We evaluated our technique on a prototype deep neural network implementation of the next-generation airborne collision avoidance system for unmanned aircraft (ACAS Xu). Results show that our technique can successfully prove properties of networks that are an order of magnitude larger than the largest networks verified using existing methods.

Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

This paper presents a uniform substitution calculus for differential game logic (dGL). Church's uniform substitutions substitute a term or formula for a function or predicate symbol everywhere. After generalizing them to differential game logic and allowing for the substitution of hybrid games for game symbols, uniform substitutions make it possible to only use axioms instead of axiom schemata, thereby substantially simplifying implementations. Instead of subtle schema variables and soundness-critical side conditions on the occurrence patterns of logical variables to restrict infinitely many axiom schema instances to sound ones, the resulting axiomatization adopts only a finite number of ordinary dGL formulas as axioms, which uniform substitutions instantiate soundly. This paper proves soundness and completeness of uniform substitutions for the monotone modal logic dGL. The resulting axiomatization admits a straightforward modular implementation of dGL in theorem provers.

Uniform Substitution for Differential Game Logic

This chapter leaves the realm of cyber-physical systems whose differential equations are solvable in closed form.Without closed-form solvable differential equations, the continuous dynamics of cyber-physical systems becomes much more challenging. The change is as noticeable and significant as the change from singleshot control systems to systems with an unbounded number of interactions in a control loop. All of a sudden, we can no longer pretend each differential equation could be replaced by an explicit representation of a function that describes the resulting state at time t along with a quantifier for t. Instead, differential equations have to be handled implicitly based on their actual dynamics as opposed to their solution. This leads to a remarkable shift in perspective opening up a new world of fascination in the continuous dynamical aspects of cyber-physical systems, and it begins by ascribing an entirely new meaning to primes in cyber-physical system models.

Differential Equations & Differential Invariants

We formalize the univariate fragment of Ben-Or, Kozen, and Reif's (BKR) decision procedure for first-order real arithmetic in Isabelle/HOL. BKR's algorithm has good potential for parallelism and was designed to be used in practice. Its key insight is a clever recursive procedure that computes the set of all consistent sign assignments for an input set of univariate polynomials while carefully managing intermediate steps to avoid exponential blowup from naively enumerating all possible sign assignments (this insight is fundamental for both the univariate case and the general case). Our proof combines ideas from BKR and a follow-up work by Renegar that are well-suited for formalization. The resulting proof outline allows us to build substantially on Isabelle/HOL's libraries for algebra, analysis, and matrices. Our main extensions to existing libraries are also detailed.

A Verified Decision Procedure for Univariate Real Arithmetic with the BKR Algorithm

Formal verification techniques are used routinely in finite-state digital circuits. Theorem proving is also used successfully for infinite-state discrete systems. But many safety-critical computers are actually embedded in physical systems. Hybrid systems [1] model complex physical systems as dynamical systems with interacting discrete transitions and continuous evolutions along differential equations. They arise frequently in many application domains, including aviation, automotive, railway, and robotics. There is a well-understood theory for proving programs. But what about complex physical systems? How can we prove that a hybrid system works as expected, e.g., an aircraft does not crash into another one? This talk illustrates the complexities and pitfalls of hybrid systems verification. It describes a theoretical and practical foundation for deductive verification of hybrid systems called differential dynamic logic (dL). The proof calculus for this logic is interesting from a theoretical perspective, because it is a complete axiomatization of hybrid systems relative to differential equations. The approach is of considerable practical interest too. Its implementation in the theorem prover KeYmaera [7] has been used successfully to verify collision avoidance properties in the European Train Control System [8] and air traffic control systems [6]. The number of dimensions and nonlinearities in they hybrid dynamics of these systems is surprisingly tricky such that they are still out of scope for other verification tools. This talk is based on recent work [2, 3, 4]. More comprehensive details can be found in a corresponding book [5].

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Real Analysis for Complex Systems

This paper introduces a uniform substitution calculus for $\mathsf{dL}_\text{CHP}$, the dynamic logic of communicating hybrid programs. Uniform substitution enables parsimonious prover kernels by using axioms instead of axiom schemata. Instantiations can be recovered from a single proof rule responsible for soundness-critical instantiation checks rather than being spread across axiom schemata in side conditions. Even though communication and parallelism reasoning are notorious for necessitating subtle soundness-critical side conditions, uniform substitution when generalized to $\mathsf{dL}_\text{CHP}$ manages to limit and isolate their conceptual overhead. Since uniform substitution has proven to simplify the implementation of hybrid systems provers substantially, uniform substitution for $\mathsf{dL}_\text{CHP}$ paves the way for a parsimonious implementation of theorem provers for hybrid systems with communication and parallelism.

André Platzer

Papers

Uniform Substitution for Differential Game Logic

Differential Equations & Differential Invariants

A Verified Decision Procedure for Univariate Real Arithmetic with the BKR Algorithm

Real Analysis for Complex Systems

Uniform Substitution for Dynamic Logic with Communicating Hybrid Programs