Weak magnetism phenomena in heavy-fermion superconductors: selected μ\muSR studies

The behavior of the so-called weak moment antiferromagnetic states, observed in the heavy-fermion superconductors UPt$_3$ and URu$_2$Si$_2$, is discussed in view of recent $\mu$SR results obtained as function of control parameters like chemical substitution and external pressure. In UPt$_3$, the Pd substitution for Pt reveals the dynamical character of the weak moment order. On the other hand, $\mu$SR measurements performed on samples in which Th substitutes U suggest that crystallographic disorder on the magnetic sites deeply affects the fluctuation timescale. In URu$_2$Si$_2$, a phase separation between the so-called hidden order state, present at ambient pressure, and an antiferromagnetic state, occurring under pressure, is observed. In view of the pressure-temperature phase diagram obtained by $\mu$SR, it is deduced that the respective order parameters have different symmetries.Comment: To appear in: J. Phys.: Cond. Matte

Inferring Networks of Substitutable and Complementary Products

In a modern recommender system, it is important to understand how products relate to each other. For example, while a user is looking for mobile phones, it might make sense to recommend other phones, but once they buy a phone, we might instead want to recommend batteries, cases, or chargers. These two types of recommendations are referred to as substitutes and complements: substitutes are products that can be purchased instead of each other, while complements are products that can be purchased in addition to each other. Here we develop a method to infer networks of substitutable and complementary products. We formulate this as a supervised link prediction task, where we learn the semantics of substitutes and complements from data associated with products. The primary source of data we use is the text of product reviews, though our method also makes use of features such as ratings, specifications, prices, and brands. Methodologically, we build topic models that are trained to automatically discover topics from text that are successful at predicting and explaining such relationships. Experimentally, we evaluate our system on the Amazon product catalog, a large dataset consisting of 9 million products, 237 million links, and 144 million reviews.Comment: 12 pages, 6 figure

Adding a Stick to the Carrot? The Interaction of Bonuses and Fines

In this paper we report on a principal-agent experiment where the principal can choose whether to rely on an unenforcable bonus contract or to combine the bonus contract with a fine if the agent’s effort falls below a minimum standard. We show that most principals do not use the fine and that the pure bonus contract is more efficient than the combined contract. Our experiment suggests that principals who are less fair are more likely to choose a combined contract and less likely to actually pay the announced bonus. This offers a new explanation for why explicit and implicit incentives are substitutes rather than complements