Quantum Hamiltonian Learning Using Imperfect Quantum Resources

Identifying an accurate model for the dynamics of a quantum system is a vexing problem that underlies a range of problems in experimental physics and quantum information theory. Recently, a method called quantum Hamiltonian learning has been proposed by the present authors that uses quantum simulation as a resource for modeling an unknown quantum system. This approach can, under certain circumstances, allow such models to be efficiently identified. A major caveat of that work is the assumption of that all elements of the protocol are noise-free. Here, we show that quantum Hamiltonian learning can tolerate substantial amounts of depolarizing noise and show numerical evidence that it can tolerate noise drawn from other realistic models. We further provide evidence that the learning algorithm will find a model that is maximally close to the true model in cases where the hypothetical model lacks terms present in the true model. Finally, we also provide numerical evidence that the algorithm works for non-commuting models. This work illustrates that quantum Hamiltonian learning can be performed using realistic resources and suggests that even imperfect quantum resources may be valuable for characterizing quantum systems.Comment: 16 pages 11 Figure

Mennocostal Musings: Poetic Inquiry and Performance in Narrative Research

My narrative research investigates the writing of two critically-acclaimed Canadian Mennonite authors. My methods include interviews with the authors and narrative analysis of their works. I also use a less conventional method, that of writing poetry. Through writing poems about my mennocostal (Mennonite and Pentecostal) background, I am coming to new understandings of my self, my past experiences, and my writing-research practices. In turn, these insights help me better understand some experiences and writing practices of my research subjects, as well as what the scholarly literature says about such practices. I research how writing personal narratives can be an act of inquiry—how it can help the writer construct new understandings about her self and her topic. While studying how writing can be inquiry, I practice writing as inquiry. I also perform the poetic data from my research. In this article, I perform some poems through audio files (http://natashagwiebe.googlepages.com/poeticperformances) and give examples of how writing them is making me a better researcher. Along the way, I mention how participating in poetic performances as a listener and performer has helped shape my poetic inquiry and engendered new insights into my narrative research. I conclude by situating my poetic inquiry as performative research. URN: urn:nbn:de:0114-fqs080242

Mennonites, the Apocalypse, and the Appeal of the Walking Dead

Over the past 15 years, the story of a world devastated by the walking dead has increasingly captured our attention through movies, television, and literature. The fictional narrative of zombie apocalypse has also shaped activities of government agencies, not-for-profits, and universities. Why is this narrative captivating? How might we be using it to navigate large-scale or personal challenges? This paper suggests some answers, bringing together zombie studies, narrative theory, and Mennonite studies to do so

Miriam Toews’ A Complicated Kindness: Restorying the Russian Mennonite Diaspora

A literary critique is presented wherein the author examines the novel “A Complicated Kindness,” by Miriam Toew as a restorying of the Russian Mennonite diaspora. The prominence of the diaspora in Canadian Mennonite discourse is referenced, and the personal narrative approach used in Toew’s novel is discussed as a method of connecting readers to the Mennonite experience

Tax Expenditures to Limit the Growth of Carbon Emissions in Canada: Identification and Evaluation

Unlike the U.S., which relies heavily on tax expenditures as instruments of energy and climate change policy, Canada has introduced very few such tax expenditures, relying instead on voluntary initiatives, direct subsidies, and limited regulatory measures to limit carbon emissions. This paper identifies and evaluates the most prominent tax expenditures in Canada to limit the growth of carbon emissions. As background to this inquiry, Part II reviews Canadian experience with carbon emissions over the last two decades and the limited government response to this growing problem. Part III identifies the most prominent tax expenditures that Canadian governments have introduced in order limit the growth of carbon emissions. Part IV evaluates these tax expenditures as spending programs and tax measures, concluding that they are vulnerable to many of the traditional criticisms levied against tax expenditures. As a result, the paper concludes, if Canadian governments are to continue to utilize tax expenditures to help fight climate change, they should pay closer attention to the insights of tax expenditure analysis and design these policy instruments accordingly

Semantic Sentiment Analysis of Twitter Data

Internet and the proliferation of smart mobile devices have changed the way information is created, shared, and spreads, e.g., microblogs such as Twitter, weblogs such as LiveJournal, social networks such as Facebook, and instant messengers such as Skype and WhatsApp are now commonly used to share thoughts and opinions about anything in the surrounding world. This has resulted in the proliferation of social media content, thus creating new opportunities to study public opinion at a scale that was never possible before. Naturally, this abundance of data has quickly attracted business and research interest from various fields including marketing, political science, and social studies, among many others, which are interested in questions like these: Do people like the new Apple Watch? Do Americans support ObamaCare? How do Scottish feel about the Brexit? Answering these questions requires studying the sentiment of opinions people express in social media, which has given rise to the fast growth of the field of sentiment analysis in social media, with Twitter being especially popular for research due to its scale, representativeness, variety of topics discussed, as well as ease of public access to its messages. Here we present an overview of work on sentiment analysis on Twitter.Comment: Microblog sentiment analysis; Twitter opinion mining; In the Encyclopedia on Social Network Analysis and Mining (ESNAM), Second edition. 201