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arXiv 2022年

作者： Jelescu, Ileana O. Grussu, Francesco Ianus, Andrada Hansen, Brian Barrett, Rachel L.C. Aggarwal, Manisha Michielse, Stijn Nasrallah, Fatima Syeda, Warda Wang, Nian Veraart, Jelle Roebroeck, Alard Bagdasarian, Andrew F. Eichner, Cornelius Sepehrband, Farshid Zimmermann, Jan Soustelle, Lucas Bowman, Christien Tendler, Benjamin C. Hertanu, Andreea Jeurissen, Ben Verhoye, Marleen Frydman, Lucio de Looij, Yohan van Hike, David Dunn, Jeff F. Miller, Karla Landman, Bennett A. Shemesh, Noam Anderson, Adam McKinnon, Emilie Farquharson, Shawna Acqua, Flavio Dell Pierpaoli, Carlo Drobnjak, Ivana Leemans, Alexander Harkins, Kevin D. Descoteaux, Maxime Xu, Duan Huang, Hao Santin, Mathieu D. Grant, Samuel C. Obenaus, Andre Kim, Gene S. Wu, Dan Le Bihan, Denis Blackband, Stephen J. Ciobanu, Luisa Fieremans, Els Bai, Ruiliang Leergaard, Trygve B. Zhang, Jiangyang Dyrby, Tim B. Johnson, G. Allan Cohen-Adad, Julien Budde, Matthew D. Schilling, Kurt G. Department of Radiology Lausanne University Hospital University of Lausanne Lausanne Switzerland CIBM Center for Biomedical Imaging Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland Radiomics Group Vall d’Hebron Institute of Oncology Vall d’Hebron Barcelona Hospital Campus Barcelona Spain Queen Square MS Centre Queen Square Institute of Neurology Faculty of Brain Sciences University College London London United Kingdom Champalimaud Research Champalimaud Foundation Lisbon Portugal Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Department of Neuroimaging Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom NatBrainLab Department of Forensics and Neurodevelopmental Sciences Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States Maastricht University Medical Center Maastricht Netherlands The Queensland Brain Institute The University of Queensland Queensland Australia Melbourne Neuropsychiatry Centre The University of Melbourne ParkvilleVIC Australia Department of Radiology and Imaging Sciences Indiana University IN United States Stark Neurosciences Research Institute Indiana University School of Medicine IN United States Center for Biomedical Imaging NYU Grossman School of Medicine New YorkNY United States Faculty of psychology and Neuroscience Maastricht University Maastricht Netherlands Department of Chemical & Biomedical Engineering FAMU-FSU College of Engineering Florida State University TallahasseeFL United States Center for Interdisciplinary Magnetic Resonance National HIgh Magnetic Field Laboratory TallahasseeFL United States Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany USC Stevens Neuroimaging and Informatics Instit

Small-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected recommendations and guidelines from the diffusion community, on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We then give guidelines for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including pre-processing, model-fitting, and tractography. Finally, we provide an online resource which lists publicly available preclinical dMRI datasets and software packages, to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. While we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal herein is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge. © 2022, CC BY-NC-ND.

关键词： Invertebrates

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Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 2 — Ex vivo imaging: added value and acquisition

arXiv

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arXiv 2022年

作者： Schilling, Kurt G. Grussu, Francesco Ianus, Andrada Hansen, Brian Howard, Amy F.D. Barrett, Rachel L.C. Aggarwal, Manisha Michielse, Stijn Nasrallah, Fatima Syeda, Warda Wang, Nian Veraart, Jelle Roebroeck, Alard Bagdasarian, Andrew F. Eichner, Cornelius Sepehrband, Farshid Zimmermann, Jan Soustelle, Lucas Bowman, Christien Tendler, Benjamin C. Hertanu, Andreea Jeurissen, Ben Verhoye, Marleen Frydman, Lucio de Looij, Yohan van Hike, David Dunn, Jeff F. Miller, Karla Landman, Bennett A. Shemesh, Noam Anderson, Adam McKinnon, Emilie Farquharson, Shawna Acqua, Flavio Dell Pierpaoli, Carlo Drobnjak, Ivana Leemans, Alexander Harkins, Kevin D. Descoteaux, Maxime Xu, Duan Huang, Hao Santin, Mathieu D. Grant, Samuel C. Obenaus, Andre Kim, Gene S. Wu, Dan Le Bihan, Denis Blackband, Stephen J. Ciobanu, Luisa Fieremans, Els Bai, Ruiliang Leergaard, Trygve B. Zhang, Jiangyang Dyrby, Tim B. Allan Johnson, G. Cohen-Adad, Julien Budde, Matthew D. Jelescu, Ileana O. Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN United States Vanderbilt University Institute of Imaging Science Vanderbilt University NashvilleTN United States Radiomics Group Vall d’Hebron Institute of Oncology Vall d’Hebron Barcelona Hospital Campus Barcelona Spain Queen Square MS Centre Queen Square Institute of Neurology Faculty of Brain Sciences University College London London United Kingdom Champalimaud Research Champalimaud Foundation Lisbon Portugal Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Department of Bioengineering Imperial College London London United Kingdom FMRIB Centre Wellcome Centre for Integrative Neuroimaging Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom Department of Neuroimaging Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom NatBrainLab Department of Forensics and Neurodevelopmental Sciences Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States Maastricht University Medical Center Maastricht Netherlands The Queensland Brain Institute The University of Queensland Queensland Australia Melbourne Neuropsychiatry Centre The University of Melbourne ParkvilleVIC Australia Department of Radiology and Imaging Sciences Indiana University IN United States Stark Neurosciences Research Institute Indiana University School of Medicine IN United States Center for Biomedical Imaging NYU Grossman School of Medicine New YorkNY United States Faculty of psychology and Neuroscience Maastricht University Maastricht Netherlands Department of Chemical & Biomedical Engineering FAMU-FSU College of Engineering Florida State University TallahasseeFL United States Center for Interdisciplinary Magnetic Re

The value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher signal-to-noise ratio (SNR) and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents "Part 2" of a 3-part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge. © 2022, CC BY.

关键词： Image acquisition

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Spectrum management and the impact of RFI on science sensors 15

Spectrum management and the impact of RFI on science sensors

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15th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment, MicroRad 2018

作者： Cruz-Pol, Sandra Van Zee, Liese Kassim, Namir Blackwell, William Le Vine, David Scott, Agnes Emerson, Darrel Gergely, Tomas Lovell, Amy MOran, James Ransom, Scott Siqueira, Paul Electrical and Computer Enqineerinq Department University of Puerto Rico Mayaguez Puerto Rico Astronomy Department Indiana U. United States Electrical Engineering Department MIT Lincoln Lab United States CORF United States Radio Astronomy Naval Research Lab United States Passive Remote Sensing NASA Goddard Space Flight Center United States Dept. of Physics and Astronomy Agnes Scott CoHege United States Harvard-Smithsonian Center for Astrophysics United States National Radio Astronomy Observatory United States Electrical and Computer Engineering Department U. Massachusetts Amherst United States

ISBN: (纸本)9781538650158

The ever-increasing demand for the radio frequency (RF) spectrum is transforming radio regulations at national and international levels at an increasingly frenzied pace. Observations collected with radio-astronomy and Earth remote sensing instruments can easily be rendered unusable due to Radio Frequency Interference (RFI) whether it is from out-of-band (OOBE) or spurious emissions in the bands used by these sensors. The RFI could originate from a single transmitter or the aggregate effects of a collection of many transmitting sources using the same frequency (e.g. spurious radiation from a poorly designed TV receiver) or different frequencies, e.g., OOBE. The aggregate case is particularly problematic because the collective signal can be indistinguishable from natural radiation. The Committee on Radio Frequencies (CORF) is a standing committee of the United States' National Academy of Sciences (NAS), that represents the scientific users of the radio spectrum at national and international fora. This paper will present a brief overview of spectrum management within the USA and the role of CORF. It will also describe some of the important issues to be dealt with at thr World Radiocommunication Conference-2019 (WRC19) and their potential impact on radio astronomy and passive remote sensing. © 2018 IEEE.

关键词： Remote sensing

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A complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy

arXiv

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arXiv 2019年

作者： Tavakoli, Meysam Shahri, Reza Pourreza Pourreza, Hamidreza Mehdizadeh, Alireza Banaee, Touka Bahreini Toosi, Mohammad Hosein Electrical Engineering Department University of Texas Dallas United States Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Medical Physics Center for research in Medical Physics and biomedical Engineering-Image processing lab Shiraz University of Medical Sciences Shiraz Iran Ophthalmic Research Center Khatam-Al-Anbia Hospital Mashhad University of Medical Sciences Eye Image Analysis Research Group MUMS Ferdowsi University of Mashhad Medical Physics Mashhad University of Medical Sciences Department of Medical Physics School of Medicine Dept. of Physics PS-145- Oklahoma State University Stillwater Oklahoma United States

Early detection of microaneurysms (MAs), the first sign of Diabetic Retinopathy (DR), is an essential first step in automated detection of DR to prevent vision loss and blindness. This study presents a novel and different algorithm for automatic detection of MAs in fluorescein angiography (FA) fundus images, based on Radon transform (RT) and multi-overlapping windows. This project addresses a novel method, in detection of retinal land marks and lesions to diagnose the DR. At the first step, optic nerve head (ONH) was detected and masked. In preprocessing stage, top-hat transformation and averaging filter were applied to remove the background. In main processing section, firstly, we divided the whole preprocessed image into sub-images and then segmented and masked the vascular tree by applying RT in each sub-image. After detecting and masking retinal vessels and ONH, MAs were detected and numbered by using RT and appropriated thresholding. The results of the proposed method were evaluated reported on three different retinal images databases, the Mashhad Database with 120 FA fundus images, Second Local Database from Tehran with 50 FA retinal images and a part of Retinopathy Online Challenge (ROC) database with 22 images. Automated DR detection demonstrated a sensitivity and specificity of 94% and 75% for Mashhad database and 100% and 70% for the Second Local Database respectively. Copyright © 2019, The Authors. All rights reserved.

关键词： computer aided diagnosis

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Multiline orthogonal scanning temporal focusing (mosTF) microscopy for scattering reduction in high-speed in vivo brain imaging

arXiv

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arXiv 2019年

作者： Xue, Yi Boivin, Josiah R. Wadduwage, Dushan N. Park, Jong Kang Nedivi, Elly So, Peter T.C. Dept. of Mechanical Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 Singapore Laser Biomedical Research Center Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 Singapore Picower Institute Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States Dept. of Biological Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 Singapore Dept. of Biology Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 Singapore Dept. of Brain and Cognitive Sciences Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States Center for Advanced Imaging Faculty of Arts and Sciences Harvard University CambridgeMA02138 Dept. of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States

Temporal focusing two-photon microscopy enables high resolution imaging of fine structures in vivo over a large volume. A limitation of temporal focusing is that signal-to-background ratio and resolution degrade rapidly with increasing imaging dept.. This degradation originates from the scattered emission photons are widely distributed resulting in a strong background. We have developed Multiline Orthogonal Scanning Temporal Focusing (mosTF) microscopy that overcomes this problem. mosTF captures a sequence of images at each scan location of the excitation line, followed by a reconstruction algorithm reassigns scattered photons back to the correct scan position. We demonstrate mosTF by acquiring mice neuronal images in vivo. Our results show remarkably improvements with mosTF for in vivo brain imaging while maintaining its speed advantage. Copyright © 2019, The Authors. All rights reserved.

关键词： Photons

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Preserving location privacy in mobile Edge computing

arXiv

引用

arXiv 2018年

作者： Zhang, Hongli Wang, Yuhang Du, Xiaojiang Guizani, Mohsen Research Center of Computer Network and Information Security Technology Harbin Institute of Technology Harbin150001 China Dept. of Computer and Information Sciences Temple University PhiladelphiaPA19122 United States Dept. of Electrical and Computer Engineering University of Idaho MoscowID United States

The burgeoning technology of Mobile Edge Computing is attracting the traditional LBS and LS to deploy due to its nature characters such as low latency and location awareness. Although this transplant will avoid the location privacy threat from the central cloud provider, there still exists the privacy concerns in the LS of MEC scenario. Location privacy threat arises during the procedure of the fingerprint localization, and the previous studies on location privacy are ineffective because of the different threat model and information semantic. To address the location privacy in MEC environment, we designed LoPEC, a novel and effective scheme for protecting location privacy for the MEC devices. By the proper model of the RAN access points, we proposed the noise-addition method for the fingerprint data, and successfully induce the attacker from recognizing the real location. Our evaluation proves that LoPEC effectively prevents the attacker from obtaining the user's location precisely in both single-point and trajectory scenarios. Copyright © 2018, The Authors. All rights reserved.

关键词： Location based services

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A Large Scale Magneto-ionic Fluctuation in the Local Environment of Periodic Fast Radio Burst Source, FRB 20180916B

arXiv

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arXiv 2022年

作者： McKinven, Ryan Gaensler, B.M. Michilli, D. Masui, K. Kaspi, V.M. Bhardwaj, M. Cassanelli, T. Chawla, P. Dong, F. Adam Fonseca, E. Leung, C. Li, D.Z. Ng, C. Patel, C. Petroff, E. Pearlman, A.B. Pleunis, Z. Rafiei-Ravandi, M. Rahman, M. Sand, K.R. Shin, K. Scholz, P. Stairs, I.H. Smith, K. Su, J. Tendulkar, S. Department of Physics McGill University 3600 rue University MontréalQCH3A 2T8 Canada McGill Space Institute McGill University 3550 rue University MontréalQCH3A 2A7 Canada Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Department of Physics Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Mit Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Dept. of Physics and Astronomy 6224 Agricultural Road VancouverBCV6T 1Z1 Canada 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 Department of Physics and Astronomy West Virginia University P.O. Box 6315 MorgantownWV26506 United States Cahill Center for Astronomy and Astrophysics California Institute of Technology 1216 E California Boulevard PasadenaCA91125 United States Sidrat Research PO Box 73527 RPO Wychwood TorontoONM6C 4A7 Canada Perimeter Institute for Theoretical Physics 31 Caroline Street N WaterlooONN2L 2Y5 Canada Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai400005 India National Centre for Radio Astrophysics Post Bag 3 Ganeshkhind Pune411007 India

Fast radio burst (FRB) source 20180916B exhibits a 16.33-day periodicity in its burst activity. It is as of yet unclear what proposed mechanism produces the activity, but polarization information is a key diagnostic. Here, we report on the polarization properties of 44 bursts from FRB 20180916B detected between 2018 December and 2021 December by CHIME/FRB, the FRB project on the Canadian Hydrogen Intensity Mapping Experiment the Canadian Hydrogen Intensity Mapping Experiment. In contrast to previous observations, we find significant variations in the Faraday rotation measure (RM) of FRB 20180916B. Over the nine month period 2021 April-2021 December we observe an apparent secular increase in RM of ∼ 50 radm-2(a fractional change of over 40%) that is accompanied by a possible drift of the emitting band to lower frequencies. This interval displays very little variation in the dispersion measure (ΔDM 0.8 pc cm-3) which indicates that the observed RM evolution is likely produced from coherent changes in the Faraday-active medium's magnetic field. Burst-to-burst RM variations appear unrelated to the activity cycle phase. The degree of linear polarization of our burst sample ( 80%) is consistent with the negligible depolarization expected for this source in the 400-800 MHz bandpass of CHIME. FRB 20180916B joins other repeating FRBs in displaying substantial RM variations between bursts. This is consistent with the notion that repeater progenitors may be associated with young stellar populations by their preferential occupation of dynamic magnetized environments commonly found in supernova remnants, pulsar wind nebulae or near high mass stellar companions. © 2022, CC BY.

关键词： Hydrogen

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Generative-Discriminative basis learning framework to predict clinical severity from resting state functional MRI Data

arXiv

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arXiv 2018年

作者： D'Souza, Niharika Shimona Nebe, Mary Beth Wymbs, Nicholas Mostofsky, Stewart Venkataraman, Archana Dept. of Electrical and Computer Engineering Johns Hopkins University United States Center for Neurodevelopmental Medicine and Research Kennedy Krieger Institute Dept. of Neurology Johns Hopkins School of Medicine United States Dept. of Pediatrics Johns Hopkins School of Medicine United States

We propose a matrix factorization technique that decom-poses the resting state fMRI (rs-fMRI) correlation matrices for a patient population into a sparse set of representative subnetworks, as modeled by rank one outer products. The subnetworks are combined using pa-tient specific non-negative coecients;these coecients are also used to model, and subsequently predict the clinical severity of a given patient via a linear regression. Our generative-discriminative framework is able to exploit the structure of rs-fMRI correlation matrices to capture group level e ects, while simultaneously accounting for patient variability. We employ ten fold cross validation to demonstrate the predictive power of our model on a cohort of fifty eight patients diagnosed with Autism Spectrum Disorder. Our method outperforms classical semi-supervised frameworks, which perform dimensionality reduction on the correlation features followed by non-linear regression to predict the clinical scores. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Biphoton shaping with cascaded entangled-photon sources

arXiv

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arXiv 2019年

作者： Riazi, Arash Chen, Changjia Zhu, Eric Y. Gladyshev, Alexey V. Kazansky, Peter G. Sipe, J.E. Qian, L. Dept. of Electrical and Computer Engineering University of Toronto 10 King’s College Rd. TorontoM5S 3G4 Canada 2Fibre Optics Research Center Russian Academy of Sciences 38 Vavilov Street Moscow119333 Russia Optoelectronics Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom Dept. of Physics University of Toronto 60 St. George St. TorontoM5S 1A7 Canada

Quantum entanglement is an integral part of quantum optics and has been exploited in areas such as computation, cryptography and metrology. The entanglement between photons can be present in various degrees of freedom (DOFs), and even the simplest bi-partite systems can occupy a large Hilbert space. Therefore, it is desirable to exploit this multi-dimensional space for various quantum applications by fully controlling the properties of the entangled photons in multiple DOFs. While current entangled-photon sources are capable of generating entanglement in one or more DOFs, there is currently a lack of practical techniques that can shape and control the entanglement properties in multiple DOFs. Here we show that cascading two or more entangled-photon sources with tunable linear media in between allows us to generate photon-pairs whose entanglement properties can be tailored and shaped in the frequency and polarisation domains. We first develop a quantum mechanical model to study the quantum state generated from the cascade structure with special considerations paid to the effects of pump temporal coherence, linear dispersion, and in-structure polarisation transformation applied between the entangled-photon sources. We then experimentally generate photon-pairs with tunable entanglement properties by manipulating the dispersion and birefringence properties of the linear medium placed in between two entangled-photon sources. This is done in an all-fibre, phase stable, and alignment-free configuration. Our results show that the cascade structure offers a great deal of flexibility in tuning the properties of entangled photons in multiple DOFs, opening up a new avenue in engineering quantum light sources. Copyright © 2019, The Authors. All rights reserved.

关键词： Photons

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pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy

arXiv

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arXiv 2024年

作者： Iyer, Kartheik G. Yunus, Mikaeel O’Neill, Charles Ye, Christine Hyk, Alina McCormick, Kiera Ciucă, Ioana Wu, John F. Accomazzi, Alberto Astarita, Simone Chakrabarty, Rishabh Cranney, Jesse Field, Anjalie Ghosal, Tirthankar Ginolfi, Michele Huertas-Company, Marc Jablońska, Maja Kruk, Sandor Liu, Huiling Marchidan, Gabriel Mistry, Rohit Naiman, J.P. Peek, J.E.G. Polimera, Mugdha Rodríguez Méndez, Sergio J. Schawinski, Kevin Sharma, Sanjib Smith, Michael J. Ting, Yuan-Sen Walmsley, Mike Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Department of Physics and Astronomy Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States School of Computing TheAustralian National University 108 North Rd ActonACT2601 Australia Stanford University 450 Jane Stanford Way StanfordCA94305 United States School of Electrical Engineering and Computer Science Oregon State University 1500 SW Jefferson Way CorvallisOR97331 United States Department of Engineering Loyola University Maryland 4501 North Charles Street BaltimoreMD21210 United States Research School of Astronomy & Astrophysics Australian National University Cotter Rd. WestonACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States Camino Bajo del Castillo s/n Villanueva de la Cañada Madrid28692 Spain Paris France Astralis-AITC - Stromlo RSAA Australian National University Cotter Road WestonACT2600 Australia Department of Computer Science Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Dipartimento di Fisica e Astronomia Universita di Firenze Via G. Sansone 1 Sesto Fiorentino Firenze50019 Italy INAF - Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 FirenzeI-50125 Italy Instituto de Astrofisica de Canarias C. Via Lactea 1 Tenerife La LagunaE-38205 Spain Universidad de la Laguna dept. Astrofisica Tenerife La LagunaE-38206 Spain Universite Paris-Cite LERMA - Observatoire de Paris PSL Paris France SCIPP University of

The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with key-words. Utilizing state-of-the-art large language models (LLMs) and a corpus of 350,000 peer-reviewed papers from the Astrophysics Data System (ADS), pathfinder offers an innovative approach to scientific inquiry and literature exploration. Our framework couples advanced retrieval techniques with LLM-based synthesis to search astronomical literature by semantic context as a complement to currently existing methods that use key-words or citation graphs. It addresses complexities of jargon, named entities, and temporal aspects through time-based and citation-based weighting schemes. We demonstrate the tool’s versatility through case studies, showcasing its application in various research scenarios. The system’s performance is evaluated using custom benchmarks, including single-paper and multi-paper tasks. Beyond literature review, pathfinder offers unique capabilities for reformatting answers in ways that are accessible to various audiences (e.g. in a different language or as simplified text), visualizing research landscapes, and tracking the impact of observatories and methodologies. This tool represents a significant advancement in applying AI to astronomical research, aiding researchers at all career stages in navigating modern astronomy literature. © 2024, CC BY.

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