2,208 research outputs found
Quantum phase transition and fractional excitations in a topological insulator thin film with Zeeman and excitonic masses
We study the zero-temperature phase diagram and fractional excitation when a
thin film of 3D topological insulator has two competing masses: T- symmetric
exciton condensation and T- breaking Zeeman effect. Two topologically distinct
phases are identified: in one, the quasiparticles can be viewed as in a quantum
spin Hall phase, and in the other a quantum anomalous Hall phase. The vortices
of the exciton order parameter can carry fractional charge and statistics of
electrons in both phases. When the system undergoes the quantum phase
transition between these two phases, the charges, statistics and the number of
fermionic zero mode of the excitonic vortices are also changed. We derive the
effective field theory for vortices and external gauge field by directly
integrating out fermions and present an explicit wave function for the
fermionic zero mode localized at the excitonic vortices with or without orbital
magnetic field. The quantum phase transition can be measured by optical Faraday
or Kerr effect experiments, and in closing we discuss the conditions required
to create the excitonic condensate.Comment: 8 pages, 3 figures, accepted version, editorial suggestio
Dyon condensation in topological Mott insulators
We consider quantum phase transitions out of topological Mott insulators in
which the ground state of the fractionalized excitations (fermionic spinons) is
topologically non-trivial. The spinons in topological Mott insulators are
coupled to an emergent compact U(1) gauge field with a so-called "axion" term.
We study the confinement transitions from the topological Mott insulator to
broken symmetry phases, which may occur via the condensation of dyons. Dyons
carry both "electric" and "magnetic" charges, and arise naturally in this
system because the monopoles of the emergent U(1) gauge theory acquires gauge
charge due to the axion term. It is shown that the dyon condensate, in general,
induces simultaneous current and bond orders. To demonstrate this, we study the
confined phase of the topological Mott insulator on the cubic lattice. When the
magnetic transition is driven by dyon condensation, we identify the bond order
as valence bond solid order and the current order as scalar spin chirality
order. Hence, the confined phase of the topological Mott insulator is an exotic
phase where the scalar spin chirality and the valence bond order coexist and
appear via a single transition. We discuss implications of our results for
generic models of topological Mott insulators.Comment: 14 pages, accepted to the New Journal of Physic
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Comparison of First-Line Dual Combination Treatments in Hypertension: Real-World Evidence from Multinational Heterogeneous Cohorts.
Background and objectives: 2018 ESC/ESH Hypertension guideline recommends 2-drug combination as initial anti-hypertensive therapy. However, real-world evidence for effectiveness of recommended regimens remains limited. We aimed to compare the effectiveness of first-line anti-hypertensive treatment combining 2 out of the following classes: angiotensin-converting enzyme (ACE) inhibitors/angiotensin-receptor blocker (A), calcium channel blocker (C), and thiazide-type diuretics (D).Methods: Treatment-naïve hypertensive adults without cardiovascular disease (CVD) who initiated dual anti-hypertensive medications were identified in 5 databases from US and Korea. The patients were matched for each comparison set by large-scale propensity score matching. Primary endpoint was all-cause mortality. Myocardial infarction, heart failure, stroke, and major adverse cardiac and cerebrovascular events as a composite outcome comprised the secondary measure.Results: A total of 987,983 patients met the eligibility criteria. After matching, 222,686, 32,344, and 38,513 patients were allocated to A+C vs. A+D, C+D vs. A+C, and C+D vs. A+D comparison, respectively. There was no significant difference in the mortality during total of 1,806,077 person-years: A+C vs. A+D (hazard ratio [HR], 1.08; 95% confidence interval [CI], 0.97-1.20; p=0.127), C+D vs. A+C (HR, 0.93; 95% CI, 0.87-1.01; p=0.067), and C+D vs. A+D (HR, 1.18; 95% CI, 0.95-1.47; p=0.104). A+C was associated with a slightly higher risk of heart failure (HR, 1.09; 95% CI, 1.01-1.18; p=0.040) and stroke (HR, 1.08; 95% CI, 1.01-1.17; p=0.040) than A+D.Conclusions: There was no significant difference in mortality among A+C, A+D, and C+D combination treatment in patients without previous CVD. This finding was consistent across multi-national heterogeneous cohorts in real-world practice
Towards an Inclusive and Accessible Metaverse
The push towards a Metaverse is growing, with companies such as Meta developing their own interpretation of what it should look like. The Metaverse at its conceptual core promises to remove boundaries and borders, becoming a decentralised entity for everyone to use - forming a digital virtual layer over our own "real"world. However, creation of a Metaverse or "new world"presents the opportunity to create one which is inclusive and accessible to all. This challenge is explored and discussed in this workshop, with an aim of understanding how to create a Metaverse which is open and inclusive to people with physical and intellectual disabilities, and how interactions can be designed in a way to minimise disadvantage. The key outcomes of this workshop outline new opportunities for improving accessibility in the Metaverse, methodologies for designing and evaluating accessibility, and key considerations for designing accessible Metaverse environments and interactions
The blind spots of interdisciplinarity in addressing grand challenges
When implemented effectively, interdisciplinary research can produce practical impact towards addressing societal “grand challenges” while also generating novel conceptual insights that advance theory. However, despite decades of calls for interdisciplinarity, research communities continue to become more siloed and less impactful. This paper aims to highlight the obstacles to interdisciplinary work contained within the accounting community, specifically those associated
with Interdisciplinary Accounting Research (IAR). We argue that, in order to overcome these obstacles and produce more effective and impactful interdisciplinary work, we require four IAR practices: Problem-solving, Public engagement, Professionalism and Performance Revision. Our purpose is to identify challenges as well as solutions that reduce the friction that accounting academics experience when collaborating with scholars outside their research discipline, especially when it concerns addressing grand challenges
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Recently, using a powerful proprietary Large Language Model (LLM) (e.g.,
GPT-4) as an evaluator for long-form responses has become the de facto
standard. However, for practitioners with large-scale evaluation tasks and
custom criteria in consideration (e.g., child-readability), using proprietary
LLMs as an evaluator is unreliable due to the closed-source nature,
uncontrolled versioning, and prohibitive costs. In this work, we propose
Prometheus, a fully open-source LLM that is on par with GPT-4's evaluation
capabilities when the appropriate reference materials (reference answer, score
rubric) are accompanied. We first construct the Feedback Collection, a new
dataset that consists of 1K fine-grained score rubrics, 20K instructions, and
100K responses and language feedback generated by GPT-4. Using the Feedback
Collection, we train Prometheus, a 13B evaluator LLM that can assess any given
long-form text based on customized score rubric provided by the user.
Experimental results show that Prometheus scores a Pearson correlation of 0.897
with human evaluators when evaluating with 45 customized score rubrics, which
is on par with GPT-4 (0.882), and greatly outperforms ChatGPT (0.392).
Furthermore, measuring correlation with GPT-4 with 1222 customized score
rubrics across four benchmarks (MT Bench, Vicuna Bench, Feedback Bench, Flask
Eval) shows similar trends, bolstering Prometheus's capability as an evaluator
LLM. Lastly, Prometheus achieves the highest accuracy on two human preference
benchmarks (HHH Alignment & MT Bench Human Judgment) compared to open-sourced
reward models explicitly trained on human preference datasets, highlighting its
potential as an universal reward model. We open-source our code, dataset, and
model at https://kaistai.github.io/prometheus/.Comment: ICLR 202
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