23 research outputs found

    EXPRES I. HD~3651 an Ideal RV Benchmark

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    The next generation of exoplanet-hunting spectrographs should deliver up to an order of magnitude improvement in radial velocity precision over the standard 1 m/s state of the art. This advance is critical for enabling the detection of Earth-mass planets around Sun-like stars. New calibration techniques such as laser frequency combs and stabilized etalons ensure that the instrumental stability is well characterized. However, additional sources of error include stellar noise, undetected short-period planets, and telluric contamination. To understand and ultimately mitigate error sources, the contributing terms in the error budget must be isolated to the greatest extent possible. Here, we introduce a new high cadence radial velocity program, the EXPRES 100 Earths program, which aims to identify rocky planets around bright, nearby G and K dwarfs. We also present a benchmark case: the 62-d orbit of a Saturn-mass planet orbiting the chromospherically quiet star, HD 3651. The combination of high eccentricity (0.6) and a moderately long orbital period, ensures significant dynamical clearing of any inner planets. Our Keplerian model for this planetary orbit has a residual RMS of 58 cm/s over a ∼6\sim 6 month time baseline. By eliminating significant contributors to the radial velocity error budget, HD 3651 serves as a standard for evaluating the long term precision of extreme precision radial velocity (EPRV) programs.Comment: 11 pages, 6 figures, accepted for publication in Astronomical Journa

    Identifying exoplanets with deep learning. IV. Removing stellar activity signals from radial velocity measurements using neural networks

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    Funding: This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (SCORE grant agreement No. 851555). A.C.C. acknowledges support from the Science and Technology Facilities Council (STFC) consolidated grant No. ST/R000824/1 and UKSA grant ST/R003203/1. R.D.H. is funded by the UK Science and Technology Facilities Council (STFC)’s Ernest Rutherford Fellowship (grant number ST/V004735/1). M.P. acknowledges financial support from the ASI-INAF agreement No. 2018-16-HH.0. A.M. acknowledges support from the senior Kavli Institute Fellowships.Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine-learning techniques such as linear regression and neural networks can effectively remove the activity signals (due to starspots/faculae) from RV observations. Previous efforts focused on carefully filtering out activity signals in time using modeling techniques like Gaussian process regression. Instead, we systematically remove activity signals using only changes to the average shape of spectral lines, and use no timing information. We trained our machine-learning models on both simulated data (generated with the SOAP 2.0 software) and observations of the Sun from the HARPS-N Solar Telescope. We find that these techniques can predict and remove stellar activity both from simulated data (improving RV scatter from 82 to 3 cm s−1) and from more than 600 real observations taken nearly daily over 3 yr with the HARPS-N Solar Telescope (improving the RV scatter from 1.753 to 1.039 m s−1, a factor of ∼1.7 improvement). In the future, these or similar techniques could remove activity signals from observations of stars outside our solar system and eventually help detect habitable-zone Earth-mass exoplanets around Sun-like stars.Publisher PDFPeer reviewe

    An Extreme Precision Radial Velocity Pipeline: First Radial Velocities from EXPRES

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    The EXtreme PREcision Spectrograph (EXPRES) is an environmentally stabilized, fiber-fed, R=137,500R=137,500, optical spectrograph. It was recently commissioned at the 4.3-m Lowell Discovery Telescope (LDT) near Flagstaff, Arizona. The spectrograph was designed with a target radial-velocity (RV) precision of 30 cm s−1\mathrm{~cm~s^{-1}}. In addition to instrumental innovations, the EXPRES pipeline, presented here, is the first for an on-sky, optical, fiber-fed spectrograph to employ many novel techniques---including an "extended flat" fiber used for wavelength-dependent quantum efficiency characterization of the CCD, a flat-relative optimal extraction algorithm, chromatic barycentric corrections, chromatic calibration offsets, and an ultra-precise laser frequency comb for wavelength calibration. We describe the reduction, calibration, and radial-velocity analysis pipeline used for EXPRES and present an example of our current sub-meter-per-second RV measurement precision, which reaches a formal, single-measurement error of 0.3 m s−1\mathrm{~m~s^{-1}} for an observation with a per-pixel signal-to-noise ratio of 250. These velocities yield an orbital solution on the known exoplanet host 51 Peg that matches literature values with a residual RMS of 0.895 m s−1\mathrm{~m~s^{-1}}

    Shard Systems: Scalable, Robust and Persistent Multi-Agent Path Finding with Performance Guarantees

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    Modern multi-agent robotic systems increasingly require scalable, robust and persistent Multi-Agent Path Finding (MAPF) with performance guarantees. While many MAPF solvers that provide some of these properties exist, none provides them all. To fill this need, we propose a new MAPF framework, the shard system. A shard system partitions the workspace into geographic regions, called shards, linked by a novel system of buffers. Agents are routed optimally within a shard by a local controller to local goals set by a global controller. The buffer system novelly allows shards to plan with perfect parallelism, providing scalability. A novel global controller algorithm can rapidly generate an inter-shard routing plan for thousands of agents while minimizing the traffic routed through any shard. A novel workspace partitioning algorithm produces shards small enough to replan rapidly. These innovations allow a shard system to adjust its routing plan in real time if an agent is delayed or assigned a new goal, enabling robust, persistent MAPF. A shard system's local optimality and optimized inter-shard routing bring the sum-of-costs of its solutions to single-shot MAPF problems to < 20-60% of optimal on a diversity of workspaces. Its scalability allows it to plan paths for 1000s of agents in seconds. If any of their goals change or move actions fails, a shard system can replan in under a second

    Conserving California fish … Extension approaches applied to contentious marine-fisheries management issues

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    We describe three creative collaborations between the California Sea Grant Extension Program (SGEP), the California Department of Fish and Game, the fishing industry and university researchers to improve marine fisheries management in California. These collaborations involved difficult and long-standing issues at a time when many fisheries are declining. The cases studied highlight SGEP's involvement in (1) implementing California's comprehensive marine-life management legislation, (2) helping the sea urchin industry identify goals and techniques to achieve them, and (3) using extension methodologies to enhance socioeconomic research related to management of the Dungeness crab fishery. Critical components of SGEP methods were trust, independence and nonadvo-cacy, a science-based approach, and effective communication. These characteristics are seldom found together among diverse participants involved in contentious fisheries-management situations. We demonstrate how extension programs can partner with constituents and agencies to improve the management and research process; this approach can be applied to the broad range of natural-resource issues facing the state
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