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India's first robotic eye for time domain astrophysics: the GROWTH-India telescope

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arXiv 2022年

作者： Kumar, Harsh Bhalerao, Varun Anupama, G.C. Barway, Sudhanshu Basu, Judhajeet Deshmukh, Kunal De, Kishalay Dutta, Anirban Fremling, Christoffer Iyer, Hrishikesh Jassani, Adeem Joharle, Simran Karambelkar, Viraj Khandagale, Maitreya Krishna, K. Adithya Kulkarni, Sumeet Mate, Sujay Patil, Atharva Phanindra, D.V.S. Samantaray, Subham Sharma, Kritti Sharma, Yashvi Shenoy, Vedant Singh, Avinash Srivastava, Shubham Swain, Vishwajeet Waratkar, Gaurav Angchuk, Dorje Dorjay, Padma Dorjai, Tsewang Gyalson, Tsewang Jorphail, Sonam Mahay, Tashi Thsering Norbu, Rigzin Sharma, Tarun Kumar Stanzin, Jigmet Stanzin, Tsewang Stanzin, Urgain Department of Physics Indian Institute of Technology Bombay Powai400 076 India Indian Institute of Astrophysics 2nd Block 100 Feet Rd Koramangala Bangalore560 034 India Department of Metallurgical Engineering and Materials Science Indian Institute of Technology Bombay Powai Mumbai400076 India Department of Physics and Astronomy Texas Tech University PO Box 41051 LubbockTX79409 United States Division of Physics Mathematics and Astronomy California Institute of Technology PasadenaCA91125 United States MIT-Kavli Institute for Astrophysics and Space Research 77 Massachusetts Ave. CambridgeMA02139 United States Pondicherry University R.V. Nagar Kalapet Puducherry605014 India Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Fergusson College Shivajinagar Maharashtra Pune411 004 India Heidelberg University Grabengasse 1 Heidelberg 691 17 Germany 204 Lewis Hall The University of Mississippi OxfordMS38677 United States Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai400005 India Graduate Institute of Astronomy National Central University 32001 Taiwan Department of Mechanical Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India Hiroshima Astrophysical Science Center Hiroshima University Hiroshima Higashi-Hiroshima739-8526 Japan Astrophysics Research Centre School of Mathematics and Physics Queen's University Belfast BelfastBT7 1NN United Kingdom 194 101 India Physikalisches Institut Universität zu Köln Zülpicher Strasse 77 Cologne50937 Germany

We present the design and performance of the GROWTH-India telescope, a 0.7 m robotic telescope dedicated to time domain astronomy. The telescope is equipped with a 4k back-illuminated camera gives a 0.82◦ field of view and a sensitivity of mg' ∼20.5 in 5-min exposures. Custom software handle observatory operations: attaining high on-sky observing efficiencies ( 80%) and allowing rapid response to targets of opportunity. The data processing pipelines are capable of performing PSF photometry as well as image subtraction for transient searches. We also present an overview of the GROWTH-India telescope's contributions to the studies of Gamma-ray Bursts, the electromagnetic counterparts to gravitational wave sources, supernovae, novae and solar system objects. Copyright © 2022, The Authors. All rights reserved.

关键词： Telescopes

The threshold for SDP-refutation of random regular NAE-3SAT

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arXiv 2018年

作者： Deshpande, Yash Montanari, Andrea O’Donnell, Ryan Schramm, Tselil Sen, Subhabrata MIT Department of Mathematics Department of Electrical Engineering Department of Statistics Stanford University Computer Science Department Carnegie Mellon University Harvard University MIT Microsoft Research NE MIT Department of Mathematics

Unlike its cousin 3SAT, the NAE-3SAT (not-all-equal-3SAT) problem has the property that spectral/SDP algorithms can efficiently refute random instances when the constraint density is a large constant (with high probability). But do these methods work immediately above the "satisfiability threshold", or is there still a range of constraint densities for which random NAE-3SAT instances are unsatisfiable but hard to refute? We show that the latter situation prevails, at least in the context of random regular instances and SDP-based refutation. More precisely, whereas a random d-regular instance of NAE-3SAT is easily shown to be unsatisfiable (whp) once d ≥ 8, we establish the following sharp threshold result regarding efficient refutation: If d 13.5 then even the most basic spectral algorithm refutes satisfiability (whp). Copyright © 2018, The Authors. All rights reserved.

关键词： Formal logic

Thwarting Adversarial Examples: An L0-Robust Sparse Fourier Transform

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arXiv 2018年

作者： Bafna, mitali Murtagh, Jack Vyas, Nikhil School of Engineering & Applied Sciences Harvard University CambridgeMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States

We give a new algorithm for approximating the Discrete Fourier transform of an approximately sparse signal that has been corrupted by worst-case L0 noise, namely a bounded number of coordinates of the signal have been corrupted arbitrarily. Our techniques generalize to a wide range of linear transformations that are used in data analysis such as the Discrete Cosine and Sine transforms, the Hadamard transform, and their high-dimensional analogs. We use our algorithm to successfully defend against well known L0 adversaries in the setting of image classification. We give experimental results on the Jacobian-based Saliency Map Attack (JSMA) and the Carlini Wagner (CW) L0 attack on the MNIST and Fashion-MNIST datasets as well as the Adversarial Patch on the ImageNet dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Discrete Fourier transforms

Contact Model Fusion for Event-Based Locomotion in Unstructured Terrains

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Contact Model Fusion for Event-Based Locomotion in Unstructu...

IEEE International Conference on Robotics and Automation

作者： Gerardo Bledt Patrick M. Wensing Sam Ingersoll Sangbae Kim Department of Electrical Engineering and Computer Science MIT Cambridge MA USA Department of Aerospace and Mechanical Engineering University of Notre Dame Notre Dame IN USA Department of Mechanical Engineering MIT Cambridge MA 02139 USA Department of Mechanical Engineering MIT Cambridge MA USA

As legged robots are sent into unstructured environments, the ability to robustly manage contact transitions will be a critical skill. This paper introduces an approach to probabilistically fuse contact models, managing uncertainty in terrain geometry, dynamic modeling, and kinematics to improve the robustness of contact initiation at touchdown. A discrete-time extension of the generalized-momentum disturbance observer is presented to increase the accuracy of proprioceptive force control estimates. This information is fused with other contact priors under a framework of Kalman Filtering to increase robustness of the method. This approach results in accurate contact detection with 99.3% accuracy and a small 4 - 5ms delay. Using this new detector, an Event-Based Finite State Machine is implemented to deal with unexpected early and late contacts. This allows the robot to traverse cluttered environments by modifying the control actions for each individual leg based on the estimated contact state rather than adhering to a rigid time schedule regardless of actual contact state. Experiments with the mit Cheetah 3 robot show the success of both the detection algorithm, as well as the Event-Based FSM while making unexpected contacts during trotting.

关键词： Legged locomotion Robot sensing systems Force Disturbance observers Robustness

Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

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arXiv 2018年

作者： Dalca, Adrian V. Balakrishnan, Guha Guttag, John Sabuncu, Mert R. Computer Science and Artificial Intelligence Lab MIT United States Martinos Center for Biomedical Imaging Massachusetts General Hospital Hms School of Electrical and Computer Engineering Cornell University

Traditional deformable registration techniques achieve im-pressive results and offer a rigorous theoretical treatment, but are com-putationally intensive since they solve an optimization problem for each image pair. Recently, learning-based methods have facilitated fast registra-tion by learning spatial deformation functions. However, these approaches use restricted deformation models, require supervised labels, or do not guarantee a diffeomorphic (topology-preserving) registration. Further-more, learning-based registration tools have not been derived from a probabilistic framework that can offer uncertainty estimates. In this paper, we present a probabilistic generative model and derive an un-supervised learning-based inference algorithm that makes use of recent developments in convolutional neural networks (CNNs). We demonstrate our method on a 3D brain registration task, and provide an empirical analysis of the algorithm. Our approach results in state of the art accu-racy and very fast runtimes, while providing diffeomorphic guarantees and uncertainty estimates. Our implementation is available online at https://***/voxelmorph/voxelmorph. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

Publisher Correction: Machine learning for genetics-based classification and treatment response prediction in cancer of unknown primary

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Nature medicine 2024年第2期30卷 607页

作者： Intae Moon Jaclyn LoPiccolo Sylvan C Baca Lynette M Sholl Kenneth L Kehl Michael J Hassett David Liu Deborah Schrag Alexander Gusev Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA. Division of Population Sciences Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Center for Functional Cancer Epigenetics Dana-Farber Cancer Institute Boston MA USA. Department of Pathology Brigham and Women's Hospital Harvard Medical School Boston MA USA. The Broad Institute of MIT & Harvard Cambridge MA USA. Memorial Sloan Kettering Cancer Center New York City NY USA. Division of Population Sciences Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA. alexander_gusev@dfci.harvard.edu. The Broad Institute of MIT & Harvard Cambridge MA USA. alexander_gusev@dfci.harvard.edu. Division of Genetics Brigham and Women's Hospital and Harvard Medical School Boston MA USA. alexander_gusev@dfci.harvard.edu.

Medical image imputation from image collections

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arXiv 2018年

作者： Dalca, Adrian V. Bouman, Katherine L. Freeman, William T. Rost, Natalia S. Sabuncu, Mert R. Golland, Polina Computer Science and Artificial Intelligence Lab Martinos Center for Biomedical Imaging General Hospital HMS Massachusetts United States Computer Science and Artificial Intelligence Lab MIT Computer Science and Artificial Intelligence Lab MIT and Google School of Electrical and Computer Engineering Meinig School of Biomedical Engineering Cornell University Department of Neurology Massachusetts General Hospital HMS United States

We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large data sets of clinical images contain a wealth of information, time constraints during acquisition result in sparse scans that fail to capture much of the anatomy. These characteristics often render computational analysis impractical as many image analysis algorithms tend to fail when applied to such images. Highly specialized algorithms that explicitly handle sparse slice spacing do not generalize well across problem domains. In contrast, we aim to enable application of existing algorithms that were originally developed for high resolution research scans to significantly undersampled scans. We introduce a generative model that captures fine-scale anatomical structure across subjects in clinical image collections and derive an algorithm for filling in the missing data in scans with large inter-slice spacing. Our experimental results demonstrate that the resulting method outperforms state-of-the-art upsampling super-resolution techniques, and promises to facilitate subsequent analysis not previously possible with scans of this quality. Our implementation is freely available at https://***/adalca/papago. Copyright © 2018, The Authors. All rights reserved.

关键词： Optical resolving power

CHIME/FRB Outriggers: KKO Station System and Commissioning Results

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arXiv 2024年

作者： Lanman, Adam E. Andrew, Shion Lazda, Mattias Shah, Vishwangi Amiri, Mandana Balasubramanian, Arvind Bandura, Kevin Boyle, P.J. Brar, Charanjot Carlson, Mark Cliche, Jean-François Gusinskaia, Nina Hendricksen, Ian T. Kaczmarek, J.F. Landecker, Tom Leung, Calvin McKinven, Ryan Mena-Parra, Juan Milutinovic, Nikola Nimmo, Kenzie Pearlman, Aaron B. Renard, Andre Rahman, Mubdi Shaw, J. Richard Siegel, Seth R. Smegal, Rick J. Cassanelli, Tomas Chatterjee, Shami Curtin, Alice P. Dobbs, Matt Dong, Fengqiu Adam Halpern, Mark Hopkins, Hans Kaspi, Victoria M. Khairy, Kholoud Masui, Kiyoshi W. Meyers, Bradley W. Michilli, Daniele Petroff, Emily Pinsonneault-Marotte, Tristan Pleunis, Ziggy Rafiei-Ravandi, Masoud Shin, Kaitlyn Smith, Kendrick Vanderlinde, Keith Zegmott, Tarik J. Department of Physics McGill University 3600 rue University MontréalQCH3A 2T8 Canada Trottier Space Institute McGill University 3550 rue University MontréalQCH3A 2A7 Canada MIT Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Department of Physics and Astronomy University of British Columbia 6224 Agricultural Road VancouverBCV6T 1Z1 Canada Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai400005 India Lane Department of Computer Science and Electrical Engineering 1220 Evansdale Drive PO Box 6109 MorgantownWV26506 United States Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV26505 United States Canadian Institute for Theoretical Astrophysics 60 St. George Street TorontoONM5S 3H8 Canada CSIRO Space & Astronomy Parkes Observatory P.O. Box 276 ParkesNSW2870 Australia Dominion Radio Astrophysical Observatory Herzberg Research Centre for Astronomy and Astrophysics National Research Council Canada PO Box 248 PentictonBCV2A 6J9 Canada Department of Astronomy University of California Berkeley BerkeleyCA94720 United States McGill Space Institute Canada FRQNT Sidrat Research 124 Merton Street Suite 507 TorontoONM4S 2Z2 Canada Perimeter Institute for Theoretical Physics 31 Caroline Street N WaterlooONN25 2YL Canada Department of Electrical Engineering Universidad de Chile Av. Tupper 2007 Santiago8370451 Chile Cornell Center for Astrophysics and Planetary Science Cornell University IthacaNY148

Localizing fast radio bursts (FRBs) to their host galaxies is an essential step to better understanding their origins and using them as cosmic probes. The CHIME/FRB Outrigger program aims to add VLBI-localization capabilities to CHIME, such that FRBs may be localized to tens of milliarcsecond precision at the time of their discovery, more than sufficient for host galaxy identification. The first-built outrigger telescope is the k’niPatn k’l͜stk’masqt outrigger (KKO), located 66 kilometers west of CHIME. Cross-correlating KKO with CHIME can achieve arcsecond precision along the baseline axis while avoiding the worst effects of the ionosphere. Since the CHIME — KKO baseline is mostly East/West, this improvement is mostly in right ascension. This paper presents measurements of KKO’s performance throughout its commissioning phase, as well as a summary of its design and function. We demonstrate KKO’s capabilities as a standalone instrument by producing full-sky images, mapping the angular and frequency structure of the primary beam, and measuring feed positions. To demonstrate the localization capabilities of the CHIME — KKO baseline, we collected five separate observations each for a set of twenty bright pulsars, and aimed to measure their positions to within 5 arcseconds. All of these pulses were successfully localized to within this specification. The next two outriggers are expected to be commissioned in 2024, and will enable subarcsecond localizations for approximately hundreds of FRBs each year. © 2024, CC BY.

关键词： Cosmology

One-way travel-time inverted ultra-short baseline localization for low-cost autonomous underwater vehicles

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One-way travel-time inverted ultra-short baseline localizati...

2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Rypkema, Nicholas R. Fischell, Erin M. Schmidt, Henrik Electrical Engineering and Computer Science Department MIT CambridgeMA02139 United States Mechanical Engineering Department MIT CambridgeMA02139 United States

ISBN: (纸本)9781509046331

This paper presents an acoustic localization system for small and low-cost autonomous underwater vehicles (AUVs). Accurate and robust localization for low-cost AUVs would lower the barrier toward multi-AUV research in river and ocean environments. However, these AUVs introduce size, power, and cost constraints that prevent the use of conventional AUV sensors and acoustic positioning systems, adding great difficulty to the problem of underwater localization. Our system uses a single acoustic transmitter placed at a reference point and is acoustically passive on the AUV, reducing cost and power use, and enabling multi-AUV localization. The AUV has an ultra-short baseline (USBL) receiver array that uses one-way travel-time (OWTT) and phased-array beamforming to calculate range, azimuth, and inclination to the transmitter, providing an instantaneous estimate of the vehicle location. This estimate is fed to a particle filter and graph-based smoothing algorithm to generate a consistent AUV trajectory. We describe the complete processing pipeline of our system, and present results based on experiments using a low-cost AUV. To the authors' knowledge, this work constitutes the first practical demonstration of the feasibility of OWTT inverted USBL navigation for AUVs. © 2017 IEEE.

关键词： Autonomous underwater vehicles