Searching for Signatures of Cosmic Superstrings in the CMB

Because cosmic superstrings generically form junctions and gauge theoretic strings typically do not, junctions may provide a signature to distinguish between cosmic superstrings and gauge theoretic cosmic strings. In cosmic microwave background anisotropy maps, cosmic strings lead to distinctive line discontinuities. String junctions lead to junctions in these line discontinuities. In turn, edge detection algorithms such as the Canny algorithm can be used to search for signatures of strings in anisotropy maps. We apply the Canny algorithm to simulated maps which contain the effects of cosmic strings with and without string junctions. The Canny algorithm produces edge maps. To distinguish between edge maps from string simulations with and without junctions, we examine the density distribution of edges and pixels crossed by edges. We find that in string simulations without Gaussian noise (such as produced by the dominant inflationary fluctuations) our analysis of the output data from the Canny algorithm can clearly distinguish between simulations with and without string junctions. In the presence of Gaussian noise at the level expected from the current bounds on the contribution of cosmic strings to the total power spectrum of density fluctuations, the distinction between models with and without junctions is more difficult. However, by carefully analyzing the data the models can still be differentiated.Comment: 15 page

Peer-to-Peer Secure Multi-Party Numerical Computation Facing Malicious Adversaries

We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and reputation, monitoring and other tasks, where the computing nodes is expected to preserve the privacy of their inputs while performing a joint computation of a certain function. Although there is a rich literature in the field of distributed systems security concerning secure multi-party computation, in practice it is hard to deploy those methods in very large scale Peer-to-Peer networks. In this work, we try to bridge the gap between theoretical algorithms in the security domain, and a practical Peer-to-Peer deployment. We consider two security models. The first is the semi-honest model where peers correctly follow the protocol, but try to reveal private information. We provide three possible schemes for secure multi-party numerical computation for this model and identify a single light-weight scheme which outperforms the others. Using extensive simulation results over real Internet topologies, we demonstrate that our scheme is scalable to very large networks, with up to millions of nodes. The second model we consider is the malicious peers model, where peers can behave arbitrarily, deliberately trying to affect the results of the computation as well as compromising the privacy of other peers. For this model we provide a fourth scheme to defend the execution of the computation against the malicious peers. The proposed scheme has a higher complexity relative to the semi-honest model. Overall, we provide the Peer-to-Peer network designer a set of tools to choose from, based on the desired level of security.Comment: Submitted to Peer-to-Peer Networking and Applications Journal (PPNA) 200

Labour supply and skills demands in fashion retailing

If, as Adam Smith once famously suggested, Britain was a nation of shopkeepers then it is now a nation of shopworkers. Retail is now a significant part of the UK economy, accounting for £256 billion in sales and one-third of all consumer spending (Skillsmart, 2007). It is the largest private sector employer in the UK, employing 3m workers, or 1 in 10 of the working population. For future job creation in the UK economy retail is also similarly prominent and the sector is expected to create a further 250,000 jobs to 2014 (Skillsmart, 2007). The centrality of retail to economic success and job creation is apparent in other advanced economies. For example, within the US, retail sales is the occupation with the largest projected job growth in the period 2004-2014 (Gatta et al., 2009) and in Australia retail accounts for 1 in 6 workers (Buchanan et al., 2003). Within the UK these workers are employed in approximately 290,000 businesses, encompassing large and small organizations and also a number of sub-sectors. This variance suggests that retail should not be regarded as homogenous in its labour demands. Hart et al. (2007) note how skill requirements and the types of workers employed may differ across the sector. This chapter further opens up this point, providing an analysis of the labour supply and skills demands for the sub-sectors of clothing, footwear and leather goods, which are described by Skillsmart (2007: 48) as being 'significant categories in UK retailing'

Sampling-based Algorithms for Optimal Motion Planning

During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics Researc

Seeing Tree Structure from Vibration

Humans recognize object structure from both their appearance and motion; often, motion helps to resolve ambiguities in object structure that arise when we observe object appearance only. There are particular scenarios, however, where neither appearance nor spatial-temporal motion signals are informative: occluding twigs may look connected and have almost identical movements, though they belong to different, possibly disconnected branches. We propose to tackle this problem through spectrum analysis of motion signals, because vibrations of disconnected branches, though visually similar, often have distinctive natural frequencies. We propose a novel formulation of tree structure based on a physics-based link model, and validate its effectiveness by theoretical analysis, numerical simulation, and empirical experiments. With this formulation, we use nonparametric Bayesian inference to reconstruct tree structure from both spectral vibration signals and appearance cues. Our model performs well in recognizing hierarchical tree structure from real-world videos of trees and vessels.Comment: ECCV 2018. The first two authors contributed equally to this work. Project page: http://tree.csail.mit.edu

Accidental Pinhole and Pinspeck Cameras

We identify and study two types of “accidental” images that can be formed in scenes. The first is an accidental pinhole camera image. The second class of accidental images are “inverse” pinhole camera images, formed by subtracting an image with a small occluder present from a reference image without the occluder. Both types of accidental cameras happen in a variety of different situations. For example, an indoor scene illuminated by natural light, a street with a person walking under the shadow of a building, etc. The images produced by accidental cameras are often mistaken for shadows or interreflections. However, accidental images can reveal information about the scene outside the image, the lighting conditions, or the aperture by which light enters the scene.National Science Foundation (U.S.) (CAREER Award 0747120)United States. Office of Naval Research. Multidisciplinary University Research Initiative (N000141010933)National Science Foundation (U.S.) (CGV 1111415)National Science Foundation (U.S.) (CGV 0964004

How brains make decisions

This chapter, dedicated to the memory of Mino Freund, summarizes the Quantum Decision Theory (QDT) that we have developed in a series of publications since 2008. We formulate a general mathematical scheme of how decisions are taken, using the point of view of psychological and cognitive sciences, without touching physiological aspects. The basic principles of how intelligence acts are discussed. The human brain processes involved in decisions are argued to be principally different from straightforward computer operations. The difference lies in the conscious-subconscious duality of the decision making process and the role of emotions that compete with utility optimization. The most general approach for characterizing the process of decision making, taking into account the conscious-subconscious duality, uses the framework of functional analysis in Hilbert spaces, similarly to that used in the quantum theory of measurements. This does not imply that the brain is a quantum system, but just allows for the simplest and most general extension of classical decision theory. The resulting theory of quantum decision making, based on the rules of quantum measurements, solves all paradoxes of classical decision making, allowing for quantitative predictions that are in excellent agreement with experiments. Finally, we provide a novel application by comparing the predictions of QDT with experiments on the prisoner dilemma game. The developed theory can serve as a guide for creating artificial intelligence acting by quantum rules.Comment: Latex file, 20 pages, 3 figure

Canny Algorithm, Cosmic Strings and the Cosmic Microwave Background

We describe a new code to search for signatures of cosmic strings in cosmic microwave anisotropy maps. The code implements the Canny Algorithm, an edge detection algorithm designed to search for the lines of large gradients in maps. Such a gradient signature which is coherent in position space is produced by cosmic strings via the Kaiser-Stebbins effect. We test the power of our new code to set limits on the tension of the cosmic strings by analyzing simulated data with and without cosmic strings. We compare maps with a pure Gaussian scale-invariant power spectrum with maps which have a contribution of a distribution of cosmic strings obeying a scaling solution. The maps have angular scale and angular resolution comparable to what current and future ground-based small-scale cosmic microwave anisotropy experiments will achieve. We present tests of the codes, indicate the limits on the string tension which could be set with the current code, and describe various ways to refine the analysis. Our results indicate that when applied to the data of ongoing cosmic microwave experiments such as the South Pole Telescope project, the sensitivity of our method to the presence of cosmic strings will be more than an order of magnitude better than the limits from existing analyses.Comment: 19 pp, 14 figures; v4. minor corrections, as appears in journa

A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks

Autonomous agents must learn to collaborate. It is not scalable to develop a new centralized agent every time a task's difficulty outpaces a single agent's abilities. While multi-agent collaboration research has flourished in gridworld-like environments, relatively little work has considered visually rich domains. Addressing this, we introduce the novel task FurnMove in which agents work together to move a piece of furniture through a living room to a goal. Unlike existing tasks, FurnMove requires agents to coordinate at every timestep. We identify two challenges when training agents to complete FurnMove: existing decentralized action sampling procedures do not permit expressive joint action policies and, in tasks requiring close coordination, the number of failed actions dominates successful actions. To confront these challenges we introduce SYNC-policies (synchronize your actions coherently) and CORDIAL (coordination loss). Using SYNC-policies and CORDIAL, our agents achieve a 58% completion rate on FurnMove, an impressive absolute gain of 25 percentage points over competitive decentralized baselines. Our dataset, code, and pretrained models are available at https://unnat.github.io/cordial-sync .Comment: Accepted to ECCV 2020 (spotlight); Project page: https://unnat.github.io/cordial-syn