Lifshitz flows in IIB and dual field theories

We construct solutions describing flows between AdS and Lifshitz spacetimes in IIB supergravity. We find that flows from AdS5 can approach either AdS3 or Lifshitz3 in the IR depending on the values of the deformation from AdS5. Surprisingly, the choice between AdS and Lifshitz IR depends only on the value of the deformation, not on its character; the breaking of the Lorentz symmetry in the flows with Lifshitz IR is spontaneous. We find that the values of the deformation which lead to flows to Lifshitz make the UV field theory dual to the AdS5 geometry unstable, so that these flows do not offer an approach to defining the field theory dual to the Lifshitz spacetime

Sensory, motor, and emotion associations for landscape concepts differ across neighbouring speech communities

A long-standing debate centres around our mental representation of landscape: is it experienced in largely the same way across all humans or is it shaped to some extent by cultural and linguistic experience? Previous research supporting differences across cultures has often relied on introspection or qualitative ethnolinguistic methods. Departing from this, we collected systematic sensory, motor, and emotion ratings for different landscape terms from 289 native speakers of German, English and French. The results show that speakers within and across groups agree to a large extent in their ratings of landscape terms, particularly in their sensory and motor associations. However, there is cultural shaping too. This suggests more caution is required when extrapolating findings about landscape understandings and preferences across cultures and languages

Conceptualizing landscapes through anguage: the role of native language and expertise in the representation of waterbody related terms

Landscapes are essential to human life: they provide a multitude of material (food, water, pollination) and nonmaterial (beauty, tranquility, recreation) values. Their importance is enshrined in international conventions and treaties, committing signatories to protecting, monitoring, and managing all landscapes. Yet, relatively little is known about how people conceptualize “landscape” and its constituents. There is emerging evidence that conceptualizations of landscape entities may influence landscape management. This in turn raises the question as to how people speaking different languages, and with differing levels of expertise, may differ in conceptualizing landscape domains as a whole. In this paper, we investigated how people conceptualize landscape-related terms in a specific domain—waterbodies—by comparing German and English-speaking experts and nonexperts. We identified commonly used waterbody terms in sustainability discourses in both languages, and used those terms to collect sensory, motor, and affective ratings from participants. Speakers of all groups appear to conceptualize the domain of waterbody terms in comparable ways. Nevertheless, we uncovered subtle differences across languages for nonexperts. For example, there were differences in which waterbodies were associated with calm happiness in each language. In addition, olfaction seemingly plays a role in English speakers’ conceptualization of waterbodies, but not German speakers. Taken together, this suggests the ways in which people relate to landscape although shared in many respects may also be shaped in part by their specific language and culture

The DLPS: A New Framework for Benchmarking Blockchains

Distributed Ledger Technologies (DLT) promise to revolutionize business ecosystems by permitting secure transactions without intermediaries. A widely recognized challenge that inhibits the uptake of DLT is scalability and performance. Hence, quantifying key metrics such as throughput and latency is crucial for designing DLT-based infrastructures, applications, and ecosystems. However, current benchmarking frameworks for blockchains do not cover the whole benchmarking process; impeding transparent comparisons of different DLT networks. In this paper, we present the Distributed Ledger Performance Scan (DLPS), an open-source framework for end-to-end performance characterizations of blockchains, addressing the need to transparently and automatically evaluate the performance of highly customizable configurations. We describe our new framework and argue that it significantly improves existing DLT benchmarking solutions. To demonstrate the capabilities of the DLPS, we also summarize the main results obtained from a series of experiments that we have conducted with it, giving a first comprehensive comparison of essential scalability properties of several commonly used enterprise blockchains

Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK

Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e.g., regarding model ansatzes, data sets, training techniques, and hyper-parameters selection. The QUantum computing Application benchmaRK (QUARK) framework simplifies and standardizes benchmarking studies for quantum computing applications. Here, we propose several extensions of QUARK to include the ability to evaluate the training and deployment of quantum generative models. We describe the updated software architecture and illustrate its flexibility through several example applications: (1) We trained different quantum generative models using several circuit ansatzes, data sets, and data transformations. (2) We evaluated our models on GPU and real quantum hardware. (3) We assessed the generalization capabilities of our generative models using a broad set of metrics that capture, e.g., the novelty and validity of the generated data.Comment: 10 pages, 10 figure