New Dependencies of Hierarchies in Polynomial Optimization

We compare four key hierarchies for solving Constrained Polynomial Optimization Problems (CPOP): Sum of Squares (SOS), Sum of Diagonally Dominant Polynomials (SDSOS), Sum of Nonnegative Circuits (SONC), and the Sherali Adams (SA) hierarchies. We prove a collection of dependencies among these hierarchies both for general CPOPs and for optimization problems on the Boolean hypercube. Key results include for the general case that the SONC and SOS hierarchy are polynomially incomparable, while SDSOS is contained in SONC. A direct consequence is the non-existence of a Putinar-like Positivstellensatz for SDSOS. On the Boolean hypercube, we show as a main result that Schm\"udgen-like versions of the hierarchies SDSOS*, SONC*, and SA* are polynomially equivalent. Moreover, we show that SA* is contained in any Schm\"udgen-like hierarchy that provides a O(n) degree bound.Comment: 26 pages, 4 figure

The Communicative Informativeness and Efficiency of Connected Discourse by Adults With Aphasia Under Structured and Conversational Sampling Conditions

Measuring communicative informativeness under conversational discourse conditions is perhaps the most valid means of determining the interpersonal verbal communication abilities of aphasic adults. Nevertheless, the data derived from such analyses are expensive to collect and subject to unknown sources of variablity. In this study, samples of connected discourse were obtained from 20 aphasic subjects under narrative and conversational sampling conditions to determine the extent to which they were related on measures of communicative informativeness. Results revealed that subjects produced significantly greater percentages of informative words [i.e., correct information units (Nicholas & Brookshire, 1993b)] under conversational discourse conditions, but that the percentage of correct information units produced during narrative discourse tasks could be used to predict performance under conversational conditions with a high degree of accuracy

Static-Memory-Hard Functions, and Modeling the Cost of Space vs. Time

A series of recent research starting with (Alwen and Serbinenko, STOC 2015) has deepened our understanding of the notion of memory-hardness in cryptography — a useful property of hash functions for deterring large-scale password-cracking attacks — and has shown memory-hardness to have intricate connections with the theory of graph pebbling. Definitions of memory-hardness are not yet unified in the somewhat nascent field of memory-hardness, however, and the guarantees proven to date are with respect to a range of proposed definitions. In this paper, we observe two significant and practical considerations that are not analyzed by existing models of memory-hardness, and propose new models to capture them, accompanied by constructions based on new hard-to-pebble graphs. Our contribution is two-fold, as follows. First, existing measures of memory-hardness only account for dynamic memory usage (i.e., memory read/written at runtime), and do not consider static memory usage (e.g., memory on disk). Among other things, this means that memory requirements considered by prior models are inherently upper-bounded by a hash function’s runtime; in contrast, counting static memory would potentially allow quantification of much larger memory requirements, decoupled from runtime. We propose a new definition of static-memory-hard function (SHF) which takes static memory into account: we model static memory usage by oracle access to a large preprocessed string, which may be considered part of the hash function description. Static memory requirements are complementary to dynamic memory requirements: neither can replace the other, and to deter large-scale password-cracking attacks, a hash function will benefit from being both dynamic memory-hard and static-memory-hard. We give two SHF constructions based on pebbling. To prove static-memory-hardness, we define a new pebble game (“black-magic pebble game”), and new graph constructions with optimal complexity under our proposed measure. Moreover, we provide a prototype implementation of our first SHF construction (which is based on pebbling of a simple “cylinder” graph), providing an initial demonstration of practical feasibility for a limited range of parameter settings. Secondly, existing memory-hardness models implicitly assume that the cost of space and time are more or less on par: they consider only linear ratios between the costs of time and space. We propose a new model to capture nonlinear time-space trade-offs: e.g., how is the adversary impacted when space is quadratically more expensive than time? We prove that nonlinear tradeoffs can in fact cause adversaries to employ different strategies from linear tradeoffs. Finally, as an additional contribution of independent interest, we present an asymptotically tight graph construction that achieves the best possible space complexity up to log log n-factors for an existing memory-hardness measure called cumulative complexity in the sequential pebbling model

Thermal barrier coatings on surfaces with micro-machined roughness profiles

Thermal barrier coating systems are used to enhance the temperature resistance of hot section components in gas turbines. The coatings protect the underlying nickel based components and consist of the bond coat (BC) the thermal barrier coating (TBC) and a thermally grown oxide (TGO) between the BC and TBC. The coating systems fail in service at or near the TBC/TGO interface. To study the failure mechanisms a simplified coating system is introduced which consists of a MCrAlY bond-coat material as the substrate, a TGO, and ayttria-stabilised zirconia TBC as a topcoat. The TBC is applied by atmospheric plasma spraying on top of specimens with defined roughness profiles, manufactured by a micromachining process. The main advantage of micro-machining is a defined interfacial roughness between the TBC and the BC in contrast to sandblasted specimens. Furthermore, a FEM simulation of the coating system was developed which approximates the interface by sinusoidal functions. This simplified model system and additional FEM calculations show the influence of varying the interfacial roughness between the BC and the TBC