Non-Threshold Quantum Secret Sharing Schemes in the Graph State Formalism

In a recent work, Markham and Sanders have proposed a framework to study quantum secret sharing (QSS) schemes using graph states. This framework unified three classes of QSS protocols, namely, sharing classical secrets over private and public channels, and sharing quantum secrets. However, most work on secret sharing based on graph states focused on threshold schemes. In this paper, we focus on general access structures. We show how to realize a large class of arbitrary access structures using the graph state formalism. We show an equivalence between $[[n,1]]$ binary quantum codes and graph state secret sharing schemes sharing one bit. We also establish a similar (but restricted) equivalence between a class of $[[n,1]]$ Calderbank-Shor-Steane (CSS) codes and graph state QSS schemes sharing one qubit. With these results we are able to construct a large class of quantum secret sharing schemes with arbitrary access structures.Comment: LaTeX, 6 page

Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing

Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing information-theoretic exploration strategies for learning GP-based environmental field maps adopt the non-Markovian problem structure and consequently scale poorly with the length of history of observations. Hence, it becomes computationally impractical to use these strategies for in situ, real-time active sampling. To ease this computational burden, this paper presents a Markov-based approach to efficient information-theoretic path planning for active sampling of GP-based fields. We analyze the time complexity of solving the Markov-based path planning problem, and demonstrate analytically that it scales better than that of deriving the non-Markovian strategies with increasing length of planning horizon. For a class of exploration tasks called the transect sampling task, we provide theoretical guarantees on the active sampling performance of our Markov-based policy, from which ideal environmental field conditions and sampling task settings can be established to limit its performance degradation due to violation of the Markov assumption. Empirical evaluation on real-world temperature and plankton density field data shows that our Markov-based policy can generally achieve active sampling performance comparable to that of the widely-used non-Markovian greedy policies under less favorable realistic field conditions and task settings while enjoying significant computational gain over them.Comment: 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Extended version with proofs, 11 page

The Effect of Corporate Break-ups on Information Asymmetry: A Market Microstructure Analysis

This paper investigates the information environment during and after a corporate break-up utilizing direct measures of information asymmetry developed in the market microstructure literature. The analysis is based on all corporate break-ups in the United States in the period 1995-2005. The results document that information asymmetry declines significantly as a result of a break-up. However, this reduction takes place not at the time of its announcement or its completion, but after it has been fully consummated. At the same time, not all investors are equally affected, but informed investors who generate private information by skilled analysis of public information come to play a more important role compared to traditional corporate insiders. This might explain why financial advisors promote break-ups among their corporate clients, as they are likely beneficiaries. The positive stock-market reaction to break-up announcements is significantly related to reductions in insider-related information asymmetry, indicating that the advantage of skilled information analysts does not offset the overall improvement in the information environment due to a break-up.Spin-off, Divestiture, Information asymmetry

Informed Trading, Information Asymmetry and Pricing of Information Risk: Empirical Evidence from the NYSE

We analyze commonality in informed trading across stocks, and how informed trading varies with the structural and trading characteristics of a firm. We thereby isolate the residual level of informed trading that is unrelated to commonality, trading characteristics, and structural charac-teristics and analyze this measure with respect to its characteristics and pricing relevance. We find evidence of commonality in informed trading, and a systematic dependence of the level of informed trading on firm characteristics, such as, tick size, the existence of options, and the size of the ownership stake of outside parties. Most importantly, we find that the residual level of in-formed trading is the component of informed trading most strongly related to required returns. This indicates that an important part of the information risk premium is related to the inability to differentiate between price fluctuations that are caused by changes in fundamental value from random price moves.Market microstructure; Common factors; Risk factors; Asymmetric information

A rapid and convergent synthesis of the integrastatin core

The tetracyclic core of the integrastatin natural products has been prepared in a convergent and rapidmanner. Our strategy relies upon a palladium(II)-catalyzed oxidative cyclization to form the central [3.3.1]-dioxabicycle of the natural product core. Overall, the core has been completed in only 4 linear steps from known compounds