Device-independent tests of quantum measurements

We consider the problem of characterizing the set of input-output correlations that can be generated by an arbitrarily given quantum measurement. Our main result is to provide a closed-form, full characterization of such a set for any qubit measurement, and to discuss its geometrical interpretation. As applications, we further specify our results to the cases of real and complex symmetric, informationally complete measurements and mutually unbiased bases of a qubit, in the presence of isotropic noise. Our results provide the optimal device-independent tests of quantum measurements.Comment: 5 + 2 pages, no figure

Amsterdam

Contains fulltext : 127768.pdf (publisher's version ) (Open Access

A comparison of machine learning and rule-based approaches for text mining in the archaeology domain, across three languages

Archaeology is a destructive process in which the evidence primarily becomes written documentation. As such, the archaeological domain creates huge amounts of text, from books and scholarly articles to unpublished ‘grey literature’ fieldwork reports. We are experiencing a significant increase in archaeological investigations and easy access to the information hidden in these texts is a substantial problem for the archaeological field, which has been identified as early as 2005 (Falkingham 2005). In the Netherlands alone, it is estimated that 4,000 new grey literature reports are being created each year, as well as numerous books, papers and monographs. Furthermore, as research – such as desk based assessments – are increasingly being carried out online remotely, these documents need to be made more easily Findable, Accessible, Interoperable and Reusable. Making these documents searchable and analysing them is a time consuming task when done by hand, and will often lack consistency. Text mining provides methods for disclosing information in large text collections, allowing researchers to locate (parts of) texts relevant to their research questions, as well as being able to identify patterns of past behaviour in these reports. Furthermore, it enables resources to be searched in meaningful ways using semantic interoperable vocabularies and domain ontologies to answer questions on what, where and when. The EXALT project at Leiden University is working on creating a semantic search engine for archaeology in and around the Netherlands, indexing all available, open-access texts, which includes Dutch, English and German language documents. In this context, we are systematically researching and comparing different methods for extracting information from archaeological texts, in these 3 languages. The specific task we are looking at is Named Entity Recognition (NER), which is to find and recognise certain concepts in text, e.g. artefacts, time periods, places, etc. In the archaeology domain, the task of entity recognition is particularly specialised and determined by domain semantics that pose challenges to conventional NER. We develop text mining applications tailored to the archaeological domain and in this process we will compare a rule-based knowledge driven approach (using GATE), a ‘traditional’ machine learning method (Conditional Random Fields), and a deep learning method (BERT). Previous studies have investigated different applications of text mining in archaeological literature (Richards et al. 2015), but this often occurred at a relatively small scale, in isolated case studies, or as proof-of-concept type work. With this study, we are comparing multiple methods in multiple languages, and we aim to contribute to guidelines and good practice for text mining in archaeology. Specifically, we will compare not only the overall accuracy of each approach, but also the time, digital literacy, hardware, and labelled data needed to run each method. We also pay attention to the energy usage and CO2 output of these machine learning models and the impact on climate change, something that’s particularly poignant during the ongoing energy crisis. Besides these more practical aspects, we also aim to describe some general properties of the way we write about archaeology, and how writing in a particular language can make knowledge transfer (and by extension, NER) easier or more difficult

Polar Codes for CQ Channels: Decoding via Belief-Propagation with Quantum Messages

This paper considers the design and decoding of polar codes for general classical-quantum (CQ) channels. It focuses on decoding via belief-propagation with quantum messages (BPQM) and, in particular, the idea of paired-measurement BPQM (PM-BPQM) decoding. Since the PM-BPQM decoder admits a classical density evolution (DE) analysis, one can use DE to design a polar code for any CQ channel and then efficiently compute the trade-off between code rate and error probability. We have also implemented and tested a classical simulation of our PM-BPQM decoder for polar codes. While the decoder can be implemented efficiently on a quantum computer, simulating the decoder on a classical computer actually has exponential complexity. Thus, simulation results for the decoder are somewhat limited and are included primarily to validate our theoretical results

Collaborative governance

Collaborative governance (CG) refers to a mode of policy and service delivery that shifts away from government- or market-centric settings to a setting in which public, private nonprofit, and private business actors are jointly involved in and accountable for policymaking and service delivery to create public value that could otherwise not be achieved. This mode has arisen as a result of societal issues’ becoming increasingly “wicked,” lacking consensus about what the exact nature of the problem is and what the appropriate solutions are (e.g., migration and refugees, climate change, poverty). These CG networks can often be fragmented and deprived of resources as part of increased fiscal stress, stimulating the search for cross-boundary arrangements for policy and management. Consequently, both practitioners and academics explore how more and better collaboration between semi-autonomous actors with different interests and resources can be achieved in efforts to tackle wicked issues. CG refers to a trend, an era, a practice, a paradigm, and a holistic framework. While there are variations in the way scholars conceptualize or define it as a model, some common features can be discerned. CG is about identifying/being aware of/dealing with the initial conditions of collaboration and the broader context or system in which cross-sectoral governance is situated. We seek ways of structuring and institutionalizing the collaboration in smart and effective ways that are deemed critical to achieving success and performance. The intentional and deliberative design and implementation of CG arrangements can result from deeper awareness of process and structure, as well as requiring active and smart management strategies and leadership roles to be used and played, while acknowledging the importance of being aware of downsides, risks, and constraints in doing so. Effective CG must be accountable, it must lead to public value and effective outcomes, and, in many countries, it must be democratically legitimate