Addressing business agility challenges with enterprise systems

It is clear that systems agility (i.e., having a responsive IT infrastructure that can be changed quickly to meet changing business needs) has become a critical component of organizational agility. However, skeptics continue to suggest that, despite the benefits enterprise system packages provide, they are constraining choices for firms faced with agility challenges. The reason for this skepticism is that the tight integration between different parts of the business that enables many enterprise systems\u27 benefits also increases the systems\u27 complexity, and this increased complexity, say the skeptics, increases the difficulty of changing systems when business needs change. These persistent concerns motivated us to conduct a series of interviews with business and IT managers in 15 firms to identify how they addressed, in total, 57 different business agility challenges. Our analysis suggests that when the challenges involved an enterprise system, firms were able to address a high percentage of their challenges with four options that avoid the difficulties associated with changing the complex core system: capabilities already built-in to the package but not previously used, leveraging globally consistent integrated data already available, using add-on systems available on the market that easily interfaced with the existing enterprise system, and vendor provided patches that automatically updated the code. These findings have important implications for organizations with and without enterprise system architectures

The Complexity of Translationally Invariant Spin Chains with Low Local Dimension

We prove that estimating the ground state energy of a translationally-invariant, nearest-neighbour Hamiltonian on a 1D spin chain is QMAEXP-complete, even for systems of low local dimension (roughly 40). This is an improvement over the best previously-known result by several orders of magnitude, and it shows that spin-glass-like frustration can occur in translationally-invariant quantum systems with a local dimension comparable to the smallest-known non-translationally-invariant systems with similar behaviour. While previous constructions of such systems rely on standard models of quantum computation, we construct a new model that is particularly well-suited for encoding quantum computation into the ground state of a translationally-invariant system. This allows us to shift the proof burden from optimizing the Hamiltonian encoding a standard computational model to proving universality of a simple model. Previous techniques for encoding quantum computation into the ground state of a local Hamiltonian allow only a linear sequence of gates, hence only a linear (or nearly linear) path in the graph of all computational states. We extend these techniques by allowing significantly more general paths, including branching and cycles, thus enabling a highly efficient encoding of our computational model. However, this requires more sophisticated techniques for analysing the spectrum of the resulting Hamiltonian. To address this, we introduce a framework of graphs with unitary edge labels. After relating our Hamiltonian to the Laplacian of such a unitary labelled graph, we analyse its spectrum by combining matrix analysis and spectral graph theory techniques

Reversible Computation: Extending Horizons of Computing

This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first