The Foil: Capture-Avoiding Substitution With No Sharp Edges

Correctly manipulating program terms in a compiler is surprisingly difficult because of the need to avoid name capture. The rapier from "Secrets of the Glasgow Haskell Compiler inliner" is a cutting-edge technique for fast, stateless capture-avoiding substitution for expressions represented with explicit names. It is, however, a sharp tool: its invariants are tricky and need to be maintained throughout the whole compiler that uses it. We describe the foil, an elaboration of the rapier that uses Haskell's type system to enforce the rapier's invariants statically, preventing a class of hard-to-find bugs, but without adding any run-time overheads.Comment: Presented at IFL 202

Firefly Monte Carlo: Exact MCMC with Subsets of Data

Markov chain Monte Carlo (MCMC) is a popular and successful general-purpose tool for Bayesian inference. However, MCMC cannot be practically applied to large data sets because of the prohibitive cost of evaluating every likelihood term at every iteration. Here we present Firefly Monte Carlo (FlyMC) an auxiliary variable MCMC algorithm that only queries the likelihoods of a potentially small subset of the data at each iteration yet simulates from the exact posterior distribution, in contrast to recent proposals that are approximate even in the asymptotic limit. FlyMC is compatible with a wide variety of modern MCMC algorithms, and only requires a lower bound on the per-datum likelihood factors. In experiments, we find that FlyMC generates samples from the posterior more than an order of magnitude faster than regular MCMC, opening up MCMC methods to larger datasets than were previously considered feasible.Engineering and Applied Science

Flash Memory: Photochemical Imprinting of Neuronal Action Potentials onto a Microbial Rhodopsin

We developed a technique, “flash memory”, to record a photochemical imprint of the activity state—firing or not firing—of a neuron at a user-selected moment in time. The key element is an engineered microbial rhodopsin protein with three states. Two nonfluorescent states, D1 and D2, exist in a voltage-dependent equilibrium. A stable fluorescent state, F, is reached by a photochemical conversion from D2. When exposed to light of a wavelength λwrite, population transfers from D2 to F, at a rate determined by the D1 ⇌ D2 equilibrium. The population of F maintains a record of membrane voltage which persists in the dark. Illumination at a later time at a wavelength λread excites fluorescence of F, probing this record. An optional third flash at a wavelength λreset converts F back to D2, for a subsequent write–read cycle. The flash memory method offers the promise to decouple the recording of neural activity from its readout. In principle, the technique may enable one to generate snapshots of neural activity in a large volume of neural tissue, e.g., a complete mouse brain, by circumventing the challenge of imaging a large volume with simultaneous high spatial and high temporal resolution. The proof-of-principle flash memory sensors presented here will need improvements in sensitivity, speed, brightness, and membrane trafficking before this goal can be realized

Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming

We present a novel programming language design that attempts to combine the clarity and safety of high-level functional languages with the efficiency and parallelism of low-level numerical languages. We treat arrays as eagerly-memoized functions on typed index sets, allowing abstract function manipulations, such as currying, to work on arrays. In contrast to composing primitive bulk-array operations, we argue for an explicit nested indexing style that mirrors application of functions to arguments. We also introduce a fine-grained typed effects system which affords concise and automatically-parallelized in-place updates. Specifically, an associative accumulation effect allows reverse-mode automatic differentiation of in-place updates in a way that preserves parallelism. Empirically, we benchmark against the Futhark array programming language, and demonstrate that aggressive inlining and type-driven compilation allows array programs to be written in an expressive, "pointful" style with little performance penalty.Comment: 31 pages with appendix, 11 figures. A conference submission is still under revie

Timekeeping with electron spin states in diamond

Frequency standards based on atomic states, such as Rb or Cs vapors, or single-trapped ions, are the most precise measures of time. Here we propose and analyze a precision oscillator approach based upon spins in a solid-state system, in particular, the nitrogen-vacancy defect in single-crystal diamond. We show that this system can have stability approaching portable atomic standards and is readily incorporable as a chip-scale device. Using a pulsed spin-echo technique, we anticipate an Allan deviation of σy=10−7τ−1/2 limited by thermally-induced strain variations; in the absence of such thermal fluctuations, the system is limited by spin dephasing and harbors an Allan deviation nearing ∼10−12τ−1/2. Potential improvements based upon advanced diamond material processing, temperature stabilization, and nanophotonic engineering are discussed.Physic

Convolutional Networks on Graphs for Learning Molecular Fingerprints.

We introduce a convolutional neural network that operates directly on graphs. These networks allow end-to-end learning of prediction pipelines whose inputs are graphs of arbitrary size and shape. The architecture we present generalizes standard molecular feature extraction methods based on circular fingerprints. We show that these data-driven features are more interpretable, and have better predictive performance on a variety of tasks.Chemistry and Chemical Biolog

All-optical electrophysiology in mammalian neurons using engineered microbial rhodopsins

All-optical electrophysiology—spatially resolved simultaneous optical perturbation and measurement of membrane voltage—would open new vistas in neuroscience research. We evolved two archaerhodopsin-based voltage indicators, QuasAr1 and QuasAr2, which show improved brightness and voltage sensitivity, have microsecond response times and produce no photocurrent. We engineered a channelrhodopsin actuator, CheRiff, which shows high light sensitivity and rapid kinetics and is spectrally orthogonal to the QuasArs. A coexpression vector, Optopatch, enabled cross-talk–free genetically targeted all-optical electrophysiology. In cultured rat neurons, we combined Optopatch with patterned optical excitation to probe back-propagating action potentials (APs) in dendritic spines, synaptic transmission, subcellular microsecond-timescale details of AP propagation, and simultaneous firing of many neurons in a network. Optopatch measurements revealed homeostatic tuning of intrinsic excitability in human stem cell–derived neurons. In rat brain slices, Optopatch induced and reported APs and subthreshold events with high signal-to-noise ratios. The Optopatch platform enables high-throughput, spatially resolved electrophysiology without the use of conventional electrodes