A Cluster Bootstrap for Two-Loop MHV Amplitudes

We apply a bootstrap procedure to two-loop MHV amplitudes in planar N=4 super-Yang-Mills theory. We argue that the mathematically most complicated part (the $\Lambda^2 B_2$ coproduct component) of the n-particle amplitude is uniquely determined by a simple cluster algebra property together with a few physical constraints (dihedral symmetry, analytic structure, supersymmetry, and well-defined collinear limits). We present a concise, closed-form expression which manifests these properties for all n.Comment: v2: a few comments adde

Liquidity when it matters : QE and Tobin’s q

When financial markets freeze in fear, borrowing costs for solvent governments may fall towards zero in a flight to quality – but credit-worthy private borrowers can be starved of external funding. In Kiyotaki and Moore (2008), where liquidity crisis is captured by the effective rationing of private credit, tightening credit constraints have direct effects on investment. If prices are sticky, the effects on aggregate demand can be pronounced – as reported by FRBNY for the US economy using a calibrated DSGE-style framework modified to include such frictions. In such an environment, two factors stand out. First the recycling of credit flows by central banks can dramatically ease credit-rationing faced by private investors: this is the rationale for Quantitative Easing. Second, revenue-neutral fiscal transfers aimed at would-be investors can have similar effects. We show these features in a stripped- down macro model of inter-temporal optimisation subject to credit constraints

An analytic result for the two-loop seven-point MHV amplitude in N=4 SYM

We describe a general algorithm which builds on several pieces of data available in the literature to construct explicit analytic formulas for two-loop MHV amplitudes in N=4 super-Yang-Mills theory. The non-classical part of an amplitude is built from $A_3$ cluster polylogarithm functions; classical polylogarithms with (negative) cluster X-coordinate arguments are added to complete the symbol of the amplitude; beyond-the-symbol terms proportional to $\pi^2$ are determined by comparison with the differential of the amplitude; and the overall additive constant is fixed by the collinear limit. We present an explicit formula for the seven-point amplitude $R_7^{(2)}$ as a sample application.Comment: 17 pages, 1 figure; v2: minor changes; v3: added a section with some background materia

Assertion and transparent self-knowledge

We argue that honesty in assertion requires non-empirical knowledge that what one asserts is what one believes. Our argument proceeds from the thought that to assert honestly, one must follow and not merely conform to the norm ‘Assert that p only if you believe that p’. Furthermore, careful consideration of cases shows that the sort of doxastic self-knowledge required for following this norm cannot be acquired on the basis of observation, inference, or any other form of detection of one’s own doxastic states. It is, as we put it, transparent rather than empirical self-knowledge

Optimal Dynamic Nonlinear Income Taxes with No Commitment

We wish to study optimal dynamic nonlinear income taxes. Do real world taxes share some of their features? What policy prescriptions can be made? We study a two period model, where the consumers and government each have separate budget constraints in the two periods, so income cannot be transferred between periods. Labor supply in both periods is chosen by the consumers. The government has memory, so taxes in the first period are a function of first period labor income, whereas taxes in the second period are a function of both first and second period labor income. The government cannot commit to future taxes. Time consistency is thus imposed as a requirement. The main results of the paper show that time consistent incentive compatible two period taxes involve separation of types in the first period and a differentiated lump sum tax in the second period, provided that the discount rate is high or utility is separable between labor and consumption. In the natural extension of the Diamond (1998) model with quasi-linear utility functions to two periods, an equivalence of dynamic and static optimal taxes is demonstrated, and a necessary condition for the top marginal tax rate on first period income is found.Optimal Income Taxation; Time Consistency; Incentive Compatibility; Sequential Information Revelation; Optimal Dynamic Taxation

Universal Reinforcement Learning Algorithms: Survey and Experiments

Many state-of-the-art reinforcement learning (RL) algorithms typically assume that the environment is an ergodic Markov Decision Process (MDP). In contrast, the field of universal reinforcement learning (URL) is concerned with algorithms that make as few assumptions as possible about the environment. The universal Bayesian agent AIXI and a family of related URL algorithms have been developed in this setting. While numerous theoretical optimality results have been proven for these agents, there has been no empirical investigation of their behavior to date. We present a short and accessible survey of these URL algorithms under a unified notation and framework, along with results of some experiments that qualitatively illustrate some properties of the resulting policies, and their relative performance on partially-observable gridworld environments. We also present an open-source reference implementation of the algorithms which we hope will facilitate further understanding of, and experimentation with, these ideas.Comment: 8 pages, 6 figures, Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17

Alignment of cryo-EM movies of individual particles by optimization of image translations

Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the specimen, due both to instabilities in the microscope specimen stage and electron beam-induced movement. Unlike specimen stage drift, beam-induced movement is not always homogeneous within an image. Local correlation in the trajectories of nearby particles suggests that beam-induced motion is due to deformation of the ice layer. Algorithms have already been described that can correct movement for large regions of frames and for > 1 MDa protein particles. Another algorithm allows individual < 1 MDa protein particle trajectories to be estimated, but requires rolling averages to be calculated from frames and fits linear trajectories for particles. Here we describe an algorithm that allows for individual < 1 MDa particle images to be aligned without frame averaging or linear trajectories. The algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-EM.Comment: 11 pages, 4 figure