Deterministic 1-k routing on meshes with applications to worm-hole routing

In $1$-$k$ routing each of the $n^2$ processing units of an $n \times n$ mesh connected computer initially holds $1$ packet which must be routed such that any processor is the destination of at most $k$ packets. This problem reflects practical desire for routing better than the popular routing of permutations. $1$-$k$ routing also has implications for hot-potato worm-hole routing, which is of great importance for real world systems. We present a near-optimal deterministic algorithm running in \sqrt{k} \cdot n / 2 + \go{n} steps. We give a second algorithm with slightly worse routing time but working queue size three. Applying this algorithm considerably reduces the routing time of hot-potato worm-hole routing. Non-trivial extensions are given to the general $l$-$k$ routing problem and for routing on higher dimensional meshes. Finally we show that $k$-$k$ routing can be performed in \go{k \cdot n} steps with working queue size four. Hereby the hot-potato worm-hole routing problem can be solved in \go{k^{3/2} \cdot n} steps

Successive normalization of rectangular arrays

Standard statistical techniques often require transforming data to have mean $0$ and standard deviation $1$. Typically, this process of "standardization" or "normalization" is applied across subjects when each subject produces a single number. High throughput genomic and financial data often come as rectangular arrays where each coordinate in one direction concerns subjects who might have different status (case or control, say), and each coordinate in the other designates "outcome" for a specific feature, for example, "gene," "polymorphic site" or some aspect of financial profile. It may happen, when analyzing data that arrive as a rectangular array, that one requires BOTH the subjects and the features to be "on the same footing." Thus there may be a need to standardize across rows and columns of the rectangular matrix. There arises the question as to how to achieve this double normalization. We propose and investigate the convergence of what seems to us a natural approach to successive normalization which we learned from our colleague Bradley Efron. We also study the implementation of the method on simulated data and also on data that arose from scientific experimentation.Comment: Published in at http://dx.doi.org/10.1214/09-AOS743 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org). With Correction

Gate fidelity fluctuations and quantum process invariants

We characterize the quantum gate fidelity in a state-independent manner by giving an explicit expression for its variance. The method we provide can be extended to calculate all higher order moments of the gate fidelity. Using these results we obtain a simple expression for the variance of a single qubit system and deduce the asymptotic behavior for large-dimensional quantum systems. Applications of these results to quantum chaos and randomized benchmarking are discussed.Comment: 13 pages, no figures, published versio

Evolving controllers for simulated car racing

This paper describes the evolution of controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different controller architectures were compared, based on neural networks, force fields and action sequences. The controllers use either egocentric (first person), Newtonian (third person) or no information about the state of the car (open-loop controller). The only controller that is able to evolve good racing behaviour is based on a neural network acting on egocentric inputs

A high-throughput, quantitative cell-based screen for efficient tailoring of RNA device activity

Recent advances have demonstrated the use of RNA-based control devices to program sophisticated cellular functions; however, the efficiency with which these devices can be quantitatively tailored has limited their broader implementation in cellular networks. Here, we developed a high-efficiency, high-throughput and quantitative two-color fluorescence-activated cell sorting-based screening strategy to support the rapid generation of ribozyme-based control devices with user-specified regulatory activities. The high-efficiency of this screening strategy enabled the isolation of a single functional sequence from a library of over 106 variants within two sorting cycles. We demonstrated the versatility of our approach by screening large libraries generated from randomizing individual components within the ribozyme device platform to efficiently isolate new device sequences that exhibit increased in vitro cleavage rates up to 10.5-fold and increased in vivo activation ratios up to 2-fold. We also identified a titratable window within which in vitro cleavage rates and in vivo gene-regulatory activities are correlated, supporting the importance of optimizing RNA device activity directly in the cellular environment. Our two-color fluorescence-activated cell sorting-based screen provides a generalizable strategy for quantitatively tailoring genetic control elements for broader integration within biological networks

Stochastic uncoupled dynamics and Nash equilibrium

In this paper we consider dynamic processes, in repeated games, that are subject to the natural informational restriction of uncoupledness. We study the almost sure convergence to Nash equilibria, and present a number of possibility and impossibility results. Basically, we show that if in addition to random moves some recall is introduced, then successful search procedures that are uncoupled can be devised. In particular, to get almost sure convergence to pure Nash equilibria when these exist, it su±ces to recall the last two periods of play.Uncoupled, Nash equilibrium, stochastic dynamics, bounded recall