2.9k citations
- Harvard UniversityUS9 papers
- Harvard University PressUS5 papers
- Millennium Institute of AstrophysicsCL5 papers
- Center for Astrophysics Harvard & SmithsonianUS4 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- George Mason UniversityUS4 papers
- Goddard Space Flight CenterUS4 papers
- Massachusetts Institute of TechnologyUS4 papers
- Princeton UniversityUS4 papers
- Search for Extraterrestrial IntelligenceUS4 papers
- Swarthmore CollegeUS4 papers
- Virtua Voorhees HospitalUS4 papers
6 papers · 1 filter
Multivariate time series transformer embeddings for light curves of periodic variable stars
Gabriel Chiong, Ignacio Becker, Pavlos Protopapas
Astronomical surveys produce time series data by observing stellar objects across multiple photometry bands. Foundational transformer-based models, such as Astromer, encode each ti…
Applying Vision Transformers on Spectral Analysis of Astronomical Objects
Luis Felipe Strano Moraes, Ignacio Becker, Pavlos Protopapas +1
We apply pre-trained Vision Transformers (ViTs), originally developed for image recognition, to the analysis of astronomical spectral data. By converting traditional one-dimensiona…
Purcell-enhanced spin-phonon coupling with a single color center
Graham Joe, Michael Haas, Kazuhiro Kuruma +9
The radiative properties of atoms are inherently linked to their surrounding environment. Placing an electromagnetic resonator around atoms can enhance spontaneous emission, as sho…
Leveraging pre-trained vision Transformers for multi-band photometric light curve classification
Daniel Moreno-Cartagena, Pavlos Protopapas, Guillermo Cabrera-Vives +3
This study investigates the potential of a pre-trained vision Transformer (VT) model, specifically the Swin Transformer V2 (SwinV2), to classify photometric light curves without th…
Two-Point Deterministic Equivalence for Stochastic Gradient Dynamics in Linear Models
Alexander Atanasov, Blake Bordelon, Jacob A. Zavatone-Veth +2
We derive a novel deterministic equivalence for the two-point function of a random matrix resolvent. Using this result, we give a unified derivation of the performance of a wide va…
Astromer 2
Cristobal Donoso-Oliva, Ignacio Becker, Pavlos Protopapas +3
Foundational models have emerged as a powerful paradigm in deep learning field, leveraging their capacity to learn robust representations from large-scale datasets and effectively…